title: Using Screen Brightness to Improve Security in Mobile Social Network Access

abstract: In the today's mobile communications scenario, smartphones offer new capabilities to develop sophisticated applications that seem to make daily life easier and more convenient for users. Such applications, which may involve mobile ticketing, identification, access control operations, etc., are often accessible through social network aggregators, that assume a fundamental role in the federated identity management space. While this makes modern smartphones very powerful devices, it also makes them very attractive targets for spyware injection. This kind of malware is able to bypass classic authentication measures and steal user credentials even when a secure element is used, and can, therefore, perform unauthorized mobile access to social network services without the user's consent. Such an event allows stealing sensitive information or even a full identity theft. In this work, we address this issue by introducing BrightPass, a novel authentication mechanism based on screen brightness. BrightPass allows users to authenticate safely with a PIN-based confirmation in the presence of specific operations on sensitive data. We compare BrightPass with existing schemes, in order to show its usability and security within the social network arena. Furthermore, we empirically assess the security of BrightPass through experimentation. Our tests indicate that BrightPass protects the PIN code against automatic submissions carried out by malware while granting fast authentication phases and reduced error rates.


title: Design of multiband sierpinski fractal carpet antenna array for C-band

abstract: Paper presents a design of (1×4) fractal antenna array for the C-band satellite-TV ground station. The microstrip line feeding network of the array is realized on the same board with radiating elements, and combined with the shorting-pin to reduce the antenna elements size. The Rogers RT/duroid 5880 microwave laminate of permittivity e=2.2 and thickness h=1.57mm was used. Antenna operates at two resonant frequencies, f 1 = 4.04 andf 2 =6.17 GHz with return loss S 11 60MHz, for VSWR <2 at 50-Ohm input impedance. Total power gain of antenna array is greater than 12dB. The antenna array was designed and simulated by means of HFSS computer code. The simulated and experimental results agree favorable.


title: Exoskeleton inflatable robotic arm with thin McKibben muscle

abstract: To realize an extremely safe robot, an exoskeleton inflatable robotic arm with thin McKibben muscles and simple driving systems installed inside the arm, except for air-supply devices, was designed and manufactured using soft materials. McKibben muscles, which are considerably thin, lightweight, flexible, and can be mass produced, are suitable for this soft robotic mechanism. The arm is safe and useful for human-friendly robots owing to its softness, low weight, and compliance. The exoskeleton inflatable robotic arm was modeled, theoretical equations were derived for the joint angle and torque, and theoretical and experimental results obtained at various structural stiffness were compared. In the experiments, the developed arm could bend at 90° and 91° on each side. Furthermore, it was proposed that experimental values can be estimated using theoretical expressions with correction factors.


title: XNOR Neural Engine: a Hardware Accelerator IP for 21.6 fJ/op Binary Neural Network Inference

abstract: Binary Neural Networks (BNNs) are promising to deliver accuracy comparable to conventional deep neural networks at a fraction of the cost in terms of memory and energy. In this paper, we introduce the XNOR Neural Engine (XNE), a fully digital configurable hardware accelerator IP for BNNs, integrated within a microcontroller unit (MCU) equipped with an autonomous I/O subsystem and hybrid SRAM / standard cell memory. The XNE is able to fully compute convolutional and dense layers in autonomy or in cooperation with the core in the MCU to realize more complex behaviors. We show post-synthesis results in 65nm and 22nm technology for the XNE IP and post-layout results in 22nm for the full MCU indicating that this system can drop the energy cost per binary operation to 21.6fJ per operation at 0.4V, and at the same time is flexible and performant enough to execute state-of-the-art BNN topologies such as ResNet-34 in less than 2.2mJ per frame at 8.9 fps.


title: 2006): “Sorting and Incentive Effects of Pay-forPerformance: An Experimental Investigation,” Academy of Management Journal, forthcoming

abstract: Agency theory highlights losses in productivity that may occur when the interests of owners and employees are imperfectly aligned. Pay for performance has been proposed as a solution to this problem. Using a real—effort laboratory experiment with salient incentives, we compared pay—for—performance and fixed—salary compensation. The former achieved significantly higher firm productivity through both sorting and incentive effects. In particular, more productive employees selected pay for performance, and employees on average, regardless of their preferred compensation scheme, produced more under it. However, more risk—averse individuals were less likely to select pay for performance and less responsive to its incentives.


Science with the Constellation-X Observatory


title: Personality and Attachment in Transsexual Adults.

abstract: The main aim of this study was to investigate the associations between personality features and attachment patterns in transsexual adults. We explored mental representations of attachment, assessed personality traits, and possible personality disorders. Forty-four individuals diagnosed with gender identity disorder (now gender dysphoria), 28 male-to-female and 16 female-to-male, were evaluated using the Shedler–Westen assessment procedure-200 (SWAP-200) to assess personality traits and disorders; the adult attachment interview was used to evaluate their attachment state-of-mind. With respect to attachment, our sample differed both from normative samples because of the high percentage of disorganized states of mind (50% of the sample), and from clinical samples for the conspicuous percentage of secure states of mind (37%). Furthermore, we found that only 16% of our sample presented a personality disorder, while 50% showed a high level of functioning according to the SWAP-200 scales. In order to find latent subgroups that shared personality characteristics, we performed a Q-factor analysis. Three personality clusters then emerged: Healthy Functioning (54% of the sample); Depressive/Introverted (32%) and Histrionic/Extroverted (14%). These data indicate that in terms of personality and attachment, GD individuals are a heterogeneous sample and show articulate and diverse types with regard to these constructs.


title: Optimizing data permutations for SIMD devices

abstract: The widespread presence of SIMD devices in today's microprocessors has made compiler techniques for these devices tremendously important. One of the most important and difficult issues that must be addressed by these techniques is the generation of the data permutation instructions needed for non-contiguous and misaligned memory references. These instructions are expensive and, therefore, it is of crucial importance to minimize their number to improve performance and, in many cases, enable speedups over scalar code.Although it is often difficult to optimize an isolated data reorganization operation, a collection of related data permutations can often be manipulated to reduce the number of operations. This paper presents a strategy to optimize all forms of data permutations. The strategy is organized into three steps. First, all data permutations in the source program are converted into a generic representation. These permutations can originate from vector accesses to non-contiguous and misaligned memory locations or result from compiler transformations. Second, an optimization algorithm is applied to reduce the number of data permutations in a basic block. By propagating permutations across statements and merging consecutive permutations whenever possible, the algorithm can significantly reduce the number of data permutations. Finally, a code generation algorithm translates generic permutation operations into native permutation instructions for the target platform. Experiments were conducted on various kinds of applications. The results show that up to 77% of the permutation instructions are eliminated and, as a result, the average performance improvement is 48% on VMX and 68% on SSE2. For several applications, near perfect speedups have been achieved on both platforms.


You Can't Make Bricks Without Straw: Designing Systematic Literature Search Systems


title: Optimal Robust Precoders for Tracking the AoD and AoA of a mm-Wave Path

abstract: Due to high penetration losses, millimeter wave channels are formed of few paths. Most channel estimation procedures exploit this property by sounding the channel in multiple directions and then identifying those yielding the largest power. Whether in initial access or tracking mode, the beams for sweeping the channel have maximum gain towards a small range of angles. These beams are heuristic in nature and may not lead the best estimation/tracking performance. In this paper, we investigate what are the optimal precoders for estimating the parameters of a single path, when prior knowledge is available, according to the well known Cram\'er-Rao lower bound. We use orthogonal matching pursuit (OMP) to compute such optimal precoders in a hybrid analog-digital architecture, but contrary to previous works which relied on approximations, we show how to apply OMP exactly for any type of array. To validate the theoretical results, the maximum likelihood estimators of the channel parameters are derived and their accuracy assessed.


title: WEAKLY SUPERVISED SEGMENTATION-AIDED CLASSIFICATION OF URBAN SCENES FROM 3D LIDAR POINT CLOUDS

abstract: Abstract. We consider the problem of the semantic classification of 3D LiDAR point clouds obtained from urban scenes when the training set is limited. We propose a non-parametric segmentation model for urban scenes composed of anthropic objects of simple shapes, partionning the scene into geometrically-homogeneous segments which size is determined by the local complexity. This segmentation can be integrated into a conditional random field classifier (CRF) in order to capture the high-level structure of the scene. For each cluster, this allows us to aggregate the noisy predictions of a weakly-supervised classifier to produce a higher confidence data term. We demonstrate the improvement provided by our method over two publicly-available large-scale data sets.


An Object-oriented Workflow Modeling Schema Using Dataflow Analysis for Collaborative E-governance Platform


VR Based Robot Teleoperation Interface for Virtual Tour


title: Knowledge Propagation in Contextualized Knowledge Repositories: an Experimental Evaluation

abstract: As the interest in the representation of context dependent knowledge in the Semantic Web has been recognized, a number of logic based solutions have been proposed in this regard. In our recent works, in response to this need, we presented the description logic-based Contextualized Knowledge Repository (CKR) framework. CKR is not only a theoretical framework, but it has been effectively implemented over state-of-the-art tools for the management of Semantic Web data: inference inside and across contexts has been realized in the form of forward SPARQL-based rules over different RDF named graphs. In this paper we present the first evaluation results for such CKR implementation. In particular, in our first experiment we study its scalability with respect to different reasoning regimes. In a second experiment we analyze the effects of knowledge propagation on the reasoning process. In the last experiment we study the effects of modularization of global knowledge with respect to local reasoning.


title: Screening Adults for Asperger Syndrome Using the AQ: A Preliminary Study of its Diagnostic Validity in Clinical Practice

abstract: The Autism Spectrum Quotient (AQ) has been developed to measure the degree to which an adult with normal intelligence has autistic traits. In this paper it is evaluated for its potential as a screening questionnaire in clinical practice on one hundred consecutive referrals to a diagnostic clinic for adults suspected of having Asperger Syndrome or high functioning autism (AS/HFA). The results indicate that it has good discriminative validity and good screening properties at a threshold score of 26. The implications of these results are discussed.


title: American Neurogastroenterology and Motility Society consensus statement on intraluminal measurement of gastrointestinal and colonic motility in clinical practice

abstract: Tests of gastric, small intestinal and colonic motor function provide relevant physiological information and are useful for diagnosing and guiding the management of dysmotilities. Intraluminal pressure measurements may include concurrent measurements of transit or intraluminal pH. A consensus statement was developed and based on reports in the literature, experience of the authors, and discussions conducted under the auspices of the American Neurogastroenterology and Motility Society in 2008. The article reviews the indications, methods, performance characteristics, and clinical utility of intraluminal measurements of pressure activity and tone in the stomach, small bowel and colon in humans. Gastric and small bowel motor function can be measured by intraluminal manometry, which may identify patterns suggestive of myopathy, neuropathy, or obstruction. Manometry may be most helpful when it is normal. Combined wireless pressure and pH capsules provide information on the amplitude of contractions as they traverse the stomach and small intestine. In the colon, manometry assesses colonic phasic pressure activity while a barostat assesses tone, compliance, and phasic pressure activity. The utility of colonic pressure measurements by a single sensor in wireless pressure/pH capsules is not established. In children with intractable constipation, colonic phasic pressure measurements can identify patterns suggestive of neuropathy and predict success of antegrade enemas via cecostomy. In adults, these assessments may be used to document severe motor dysfunction (colonic inertia) prior to colectomy. Thus, intraluminal pressure measurements may contribute to the management of patients with disorders of gastrointestinal and colonic motility.


title: A report on random testing

abstract: Random testing of programs is usually (but not always) viewed as a worst case of program testing. Test case generation that takes into account the program structure is usually preferred. Path testing is an often proposed ideal for structural testing. Path testing is treated here as an instance of partition testing. (Partition testing is any testing scheme which forces execution of at least one test case from each subset of a partition of the input domain.) Simulation results are presented which treat path and partition testing in a reasonably favorable way, and yet still suggest that random testing may often be more cost effective. Results of actual random testing experiments are presented which tend to confirm the viability of random testing as a useful validation tool.


Xenomai-Implementing a RTOS emulation framework on GNU / Linux


title: Aware and smart member card: RFID and license plate recognition systems integrated applications at parking guidance in shopping mall

abstract: Member card can provide personal identification, authentication, data storage, and application processing. It may provide strong marketing media for customer relationship within business organizations. In this paper, the integrated applications of passive radio frequency identification (RFID) and license plate recognition (LPR) are presented. We applied RFID and LPR techniques integrated, meanwhile, we collected the vehicles self-adhered e-Tag ID data. All of these development to compile on the member card as a linking media, it provided the more premium services for card holder. By the cumulative utilization and analysis data of member card, it has become an essential connection between the customers and the companies. It is not only added card self-valued, but also do grasp customers' preference. This proposed system is composed of three main modules at RFID (3M e-Tag), LPR (Image processing), and RFID (NXP MIFARE), respectively. It is designed to meet the requirements of performance and can be generally applied to the commercial markets (e.g., other malls, marts, department stores) that also operate parking lots which face similar problems.


title: Visible light communications: Challenges and possibilities

abstract: Solid-state lighting is a rapidly developing field. White-light and other visible LEDs are becoming more efficient, have high reliability and can be incorporated into many lighting applications. Recent examples include car head-lights based on white LEDs, and LED illumination as an architectural feature. The prediction that general illumination will use white LEDs in the future has been made, due to the increased energy efficiency that such an approach may have. Such sources can also be modulated at high-speed, offering the possibility of using sources for simultaneous illumination and data communications. Such visible light communications (VLC) was pioneered in Japan, and there is now growing interest worldwide, including within bodies such as the Visible Light Communications Consortium (VLCC) and the Wireless World Research Forum (WWRF). In this paper we outline the basic components in these systems, review the state of the art and discuss some of the challenges and possibilities for this new wireless transmission technique.


title: Algorithm based on taboo search and shifting bottleneck for job shop scheduling

abstract: In this paper, a computational effective heuristic method for solving the minimum makespan problem of job shop scheduling is presented. It is based on taboo search procedure and on the shifting bottleneck procedure used to jump out of the trap of the taboo search procedure. A key point of the algorithm is that in the taboo search procedure two taboo lists are used to forbid two kinds of reversals of arcs, which is a new and effective way in taboo search methods for job shop scheduling. Computational experiments on a set of benchmark problem instances show that, in several cases, the approach, in reasonable time, yields better solutions than the other heuristic procedures discussed in the literature.


title: Techniques, Process, and Enterprise Solutions of Business Intelligence

abstract: Business intelligence (BI) has been viewed as sets of powerful tools and approaches to improving business executive decision-making, business operations, and increasing the value of the enterprise. The technology categories of BI mainly encompass data warehousing, OLAP, and data mining. This article reviews the concept of Business Intelligence and provides a survey, from a comprehensive point of view, on the BI technical framework, process, and enterprise solutions. In addition, the conclusions point out the possible reasons for the difficulties of broad deployment of enterprise BI, and the proposals of constructing a better BI system.


title: A Four-Way Microstrip Filtering Power Divider With Frequency-Dependent Couplings

abstract: A four-way microstrip power divider is designed with bandpass filtering response. The synthesized inline filter has a generalized Chebyshev response, where frequency-dependent couplings are utilized. All of the critical parameters, including the characteristic impedances and electrical lengths, can be determined by our derived closed-form formulas. By extending the inline filter, the configuration of four-way power divider is obtained. Then, three isolation resistors are properly selected according to the even-/odd-mode analysis. The proposed four-way filtering power divider has low in-band insertion loss and high frequency selectivity. It can provide the in-band return loss and isolation between outputs better than 16.7 and 17.5 dB, respectively .


title: Forgiveness in marriage: The role of relationship quality, attributions, and empathy

abstract: Italian husbands (n = 79) and wives (n = 92) from long-term marriages provided data on the role of marital quality, affective reactions, and attributions for hypothetical partner transgressions in promoting forgiveness. Structural equation modeling revealed that, as hypothesized, positive marital quality was predictive of more benign attributions that, in turn, facilitated forgiveness both directly and indirectly via affective reactions and emotional empathy. Unexpectedly, marital quality did not account for unique variance in forgiveness. Compared to husbands, wives’ responsibility attributions were more predictive of forgiveness, whereas empathy was a better predictor of forgiveness in husbands than in wives. The findings are discussed in terms of their implications for the burgeoning therapeutic literature on forgiveness. Intimate relationships satisfy our deepest affiliative needs and are also the source of some of our most poignant hurts. When the hurt occurs, negative feelings (e.g., anger, resentment) are common, creating a potential disruption in the relationship. One means of meeting this challenge is through forgiveness, a concept that has received remarkably little attention in science despite its pervasiveness across cultures and major religions (Worthington & Wade, 1999). Although it is a complex construct without a consensual definition, at the center of various approaches to forgiveness is the idea of a transformation in which motivation to seek revenge and to avoid contact with the transgressor is lessened and prosocial motivation toward the transgressor is increased. According to the psychotherapy literature, forgiveness helps to restore relationships, release bitterness and anger, and heal inner emotional wounds (e.g., DiBlasio &


title: WirelessHART Versus ISA100.11a: The Format War Hits the Factory Floor

abstract: The first decade of the new millennium has been a stage for the rapid development of wireless communication technologies for low-cost, low-power wireless solutions capable of robust and reliable communication [1]. IEEE Standard 802.15.4 for low-rate wireless personal area networks (WPANs) [2] has been the enabling technology for numerous applications within the field of wireless sensor networks (WSNs) [3], and more recently, wireless instrumentation. Although WSNs quickly found their way into a wide variety of applications, the adoption of wireless technology in the process automation and manufacturing industries has been slow. None of the industrial solutions based on standards such as IEEE 802.11 [4], Bluetooth [5], ZigBee [6], and Internet Protocol version 6 (IPv6) over low-power wireless personal area networks (6L0WPAN) [7] have yet to achieve a breakthrough a widely adopted wireless solution for industrial applications. A major reason for this is believed to be the lack of an open, international standard fulfilling the industrial requirements [8]. This changed in September 2007, when the Highway Addressable Remote Transducer (HART) Communication Foundation (HCF) released the HART Field Communication Protocol Specifi cation, Revision 7.0, which included the definition of a wireless interface to field devices, referred to as Wireless HART [9].


title: Empowerment theory, research, and application

abstract: This introduction to the special issue briefly reviews the meaning and significance of the empowerment concept and problems associated with the proliferation of interest in empowerment. We identify some of the topics not included in this issue and relate those to the many broad and diverse areas of psychological empowerment theory and community-based research and intervention that are covered. We present synopses of each article along with some of the themes and lessons cutting across the frameworks, studies, and applications. These include a wide diversity of settings, fairly representative of empowerment interventions, and, at the same time, improved clarity (if not unanimity) of definitions and measurement, which has been a problem in much empowerment research and intervention.


title: Grounded Theory, Mixed Methods, and Action Research

abstract: These commonly used methods are appropriate for particular research questions and contexts ::: ::: Qualitative research includes a variety of methodological approaches with different disciplinary origins and tools. This article discusses three commonly used approaches: grounded theory, mixed methods, and action research. It provides background for those who will encounter these methodologies in their reading rather than instructions for carrying out such research. We describe the appropriate uses, key characteristics, and features of rigour of each approach. ::: ::: Grounded theory was developed by Glaser and Strauss.[1] Its main thrust is to generate theories regarding social phenomena: that is, to develop higher level understanding that is “grounded” in, or derived from, a systematic analysis of data. Grounded theory is appropriate when the study of social interactions or experiences aims to explain a process, not to test or verify an existing theory. Researchers approach the question with disciplinary interests, background assumptions (sometimes called “sensitising concepts”[2]) and an acquaintance with the literature in the domain, but they neither develop nor test hypotheses. Rather, the theory emerges through a close and careful analysis of the data. ::: ::: Key features of grounded theory are its iterative study design, theoretical (purposive) sampling, and system of analysis.[3] An iterative study design entails cycles of simultaneous data collection and analysis, where analysis informs the next cycle of data collection. In a study of the experience of caring for a dying family member, for instance, preliminary analysis of interviews with family care providers may suggesta theme of “care burdens,” and this theme could be refined by interviewing participants who are at variouspoints in the care trajectory, who might offer different perspectives. Analysis of the subsequent phase of data collection will lead to further adaptations of the data collection process to refine and complicate the emerging theory of care burdens. In keeping with this …


title: Content Based Image Retrieval using Color and Texture

abstract: The increased need of content based image retrieval technique can be found in a number of different domains such as Data Mining, Education, Medical Imaging, Crime Prevention, Weather forecasting, Remote Sensing and Management of Earth Resources. This paper presents the content based image retrieval, using features like texture and color, called WBCHIR (Wavelet Based Color Histogram Image Retrieval).The texture and color features are extracted through wavelet transformation and color histogram and the combination of these features is robust to scaling and translation of objects in an image. The proposed system has demonstrated a promising and faster retrieval method on a WANG image database containing 1000 general-purpose color images. The performance has been evaluated by comparing with the existing systems in the literature.


title: Convolutional Decision Trees for Feature Learning and Segmentation

abstract: Most computer vision and especially segmentation tasks require to extract features that represent local appearance of patches. Relevant features can be further processed by learning algorithms to infer posterior probabilities that pixels belong to an object of interest. Deep Convolutional Neural Networks (CNN) define a particularly successful class of learning algorithms for semantic segmentation, although they proved to be very slow to train even when employing special purpose hardware. We propose, for the first time, a general purpose segmentation algorithm to extract the most informative and interpretable features as convolution kernels while simultaneously building a multivariate decision tree. The algorithm trains several orders of magnitude faster than regular CNNs and achieves state of the art results in processing quality on benchmark datasets.


title: Differentiable Genetic Programming

abstract: We introduce the use of high order automatic differentiation, implemented via the algebra of truncated Taylor polynomials, in genetic programming. Using the Cartesian Genetic Programming encoding we obtain a high-order Taylor representation of the program output that is then used to back-propagate errors during learning. The resulting machine learning framework is called differentiable Cartesian Genetic Programming (dCGP). In the context of symbolic regression, dCGP offers a new approach to the long unsolved problem of constant representation in GP expressions. On several problems of increasing complexity we find that dCGP is able to find the exact form of the symbolic expression as well as the constants values. We also demonstrate the use of dCGP to solve a large class of differential equations and to find prime integrals of dynamical systems, presenting, in both cases, results that confirm the efficacy of our approach.


title: Activity matters:investigating the influence of Facebook on life satisfaction of teenage users

abstract: As Facebook has become an integral part of a daily routine for many, the impact of its participation on users’ lives is of growing interest. Nonetheless, extant research does not offer a clear answer on the directionality of the link between Facebook use and markers of subjective well-being. These issues are particularly critical for the vulnerable segment of teenage users. Suggesting both negative and positive outcomes, existing studies are plagued by recall bias, with available findings often undermined by the reliance on aggregated measures of Facebook use. To close these gaps and address unique dynamics of the teen segment, in this study we adopt a diary approach to reliably capture different indicators of FB participation by young adolescents. This method allows us to arrive at more concrete conclusions regarding the counter-acting forces at work when it comes to the influence of Facebook. Based on our analysis, we show that the type of activity matters. Specifically, while such active uses of FB as posting and chatting are positively associated with life satisfaction in young adolescents, passive following has an adverse effect. Theoretically, our findings help getting a more holistic picture of the consequences of SNS use by teens.


Three Models for the Description of Language


title: A Taxonomy of Domain-Generation Algorithms

abstract: Domain-generation algorithms (DGAs) allow attackers to manage infection-spreading websites and command-and-control (CaC) deployments by altering domain names on a timely basis. DGAs have made the infection and CaC architecture more robust and supportive for attackers. This detailed taxonomy of DGAs highlights the problem and offers solutions to combat DGAs through detection of drive-by download and CaC activity from the compromised machine.


title: A systematic approach to determine the fouling index for a RO/NF membrane process.

abstract: A membrane fouling index such as the silt density index (SDI) and modified fouling index (MFI) is an important parameter in design and operation of reverse osmosis (RO) and nanofiltration (NF) membrane processes for desalination. Nevertheless, SDI and MFI often fail to predict actual membrane fouling due to their limited capability to measure fouling potential by colloidal deposition and organic adsorption. In this study, a novel method to determine fouling index was attempted using a set of different membrane filters for better prediction of RO/NF fouling potential. Three MF/UF membranes were used for MFI tests in order to increase sensitivity to fouling potential of particles, hydrophobic organics, and sub-micron colloids. The fouling indices determined using different membrane filters were compared with RO filtration results. Experimental results indicated that fouling indices using different test membranes showed variable results for untreated and pretreated waters. Nevertheless, no single method was sufficient for accurate measurement of fouling potential. Accordingly, a new fouling index (CFI: combined fouling index) was developed by combining various fouling indices. The CFI exhibited good agreement with experimental data compared with other fouling indices such as SDI, MFI, and MFI–UF.


title: Embedded wafer level ball grid array (eWLB)

abstract: The main challenges of today's device packaging are miniaturization, continuously increasing operating frequencies/high data rates, high number of I/Os, reliability, and thermal requirements. One of the major package trends driven by mobile-phone applications is the Wafer Level Ball Grid Array (WLB). Drivers for the implementation of WLB technology are cost reduction, smaller form factor and better electrical performance with respect to high frequency applications. Thin-film WLB technology consists in realizing additional redistribution layers above the passivation of a semiconductor chip using standard thin-film techniques to rearrange peripheral pads on the wafer in an array pattern. A hard limit will be reached with this technology, when the number of I/Os reaches a larger number dian can be fitted on the silicon chip at a given pitch. We introduce Infineon's embedded Wafer Level Ball Grid Array technology, which allows fitting interconnects onto a so-called fan-out area extending the chip area. The core process of this emerging technology is the encapsulation of silicon dice by compression molding. The eWLB technology is a forward-looking development of the WLB technology, upholding the known benefits such as small package dimensions, excellent electrical and thermal performance, and maximum connection density. However, this technology significantly increases the functionality and application spread. Due to eWLB. complex semiconductor chips such as modem and processor chips for applications in mobile communications require a high number of solder connections with standardized contact spacing to be produced with a minimal footprint. At the same time, the packages can be provided with as many solder contacts as needed. The possibility of additional wiring area around the chip proper means that the wafer-level packaging technology also lends itself to new. space-sensitive applications. We demonstrate the capabilities of Infineon's molded embedded Wafer Level Package Technology and show how we extended it towards a Platform Technology. The qualified Platform we introduce here covers currently a range of package sizes up to 8×8mm2 at a ball pitch of 0.5mm. The Qualification Criteria we have applied follow the tests described in JEDEC Standard Number 26-A.


title: A Low-ppm Digitally Controlled Crystal Oscillator Compensated by a New 0.19-mm2 Time-Domain Temperature Sensor

abstract: A low-ppm digitally controlled crystal oscillator (DCXO) in a Pierce readout topology with a new 0.19-mm2 CMOS time-domain temperature sensor (TDTS) circuit for temperature compensation is designed and fabricated in this paper. The Pierce readout circuit is designed to output a 16-MHz oscillating signal as an important base clock for mobile devices. To cope with inevitable imprecision caused by environmental temperature variation, the readout should be compensated based on crystal’s frequency-temperature curve via a temperature sensor. To this end, a new low-power, small-sized, CMOS on-chip temperature sensor circuit is successfully synthesized by 20-stages of newly designed delay cells. Each delay cell is compensated by a CMOS-process-compatible varactor, enabling a TDTS consisting of only a low number of delay cells to generate long enough delay that is proportional to temperature and in required precisions. In addition to Pierce and TDTS circuits, the DCXO consists of the logics to compute capacitance correction, a switched-capacitor array to adjust Pierce capacitances, and regulators for DCXO and TDTS. The proposed circuits are fabricated by TSMC 0.18- $\mu \text{m}$ CMOS process, where the active area is 0.516 mm2 for the whole chip, while 0.19 mm2 for the TDTS. With temperature compensation enabled, the best measured frequency deviations of a calibrated TCXO is within ±0.2 ppm from −40 °C to 85 °C. The temperature resolution of the developed TDTS is successfully designed to reach 0.18 °C/LSB with an accuracy of ±1 °C validated by one of the tape-out chips.


title: Selfish Decentralized Computation Offloading for Mobile Cloud Computing in Dense Wireless Networks

abstract: Offloading computation to a mobile cloud is a promising solution to augment the computation capabilities of mobile devices. In this paper, we consider selfish mobile devices in a dense wireless network, in which individual mobile devices can offload computations through multiple access points or through the base station to a mobile cloud so as to minimize their computation costs. We provide a game theoretical analysis of the problem, prove the existence of pure strategy Nash equilibria, and provide an efficient decentralized algorithm for computing an equilibrium. For the case when the cloud computing resources scale with the number of mobile devices, we show that all improvement paths are finite. Furthermore, we provide an upper bound on the price of anarchy of the game, which serves as an upper bound on the approximation ratio of the proposed decentralized algorithms. We use simulations to evaluate the time complexity of computing Nash equilibria and to provide insights into the price of anarchy of the game under realistic scenarios. Our results show that the equilibrium cost may be close to optimal, and the convergence time is almost linear in the number of mobile devices.


Attention Based Auto Image Cropping


title: Effects of watermarking on iris recognition performance

abstract: Protection of biometric data and templates is a crucial issue for the security of biometric systems, and biometric watermarking is introduced for this purpose. However, watermarking introduces extra information into the biometric data (biometric images or biometric feature templates) which leads to certain distortion. In addition, watermarked images are always subject to the risk of being attacked. Hence, whether and how biometric recognition performance will be affected by biometric watermarking deserves investigation. In this paper, we make a first attempt in such investigations by studying two application scenarios in the context of iris recognition, namely protection of iris templates by hiding them in cover images as watermarks (iris watermarks), and protection of iris images by watermarking them. Experimental results suggest that watermark embedding in iris images does not introduce detectable decreases on iris recognition performance whereas recognition performance drops significantly if iris watermarks suffer from severe attacks.


title: Efficient analysis of event processing applications

abstract: Complex event processing (CEP) middleware systems are increasingly adopted to implement distributed applications: they not only dispatch events across components, but also embed part of the application logic into declarative rules that detect situations of interest from the occurrence of specific pattern of events. While this approach simplifies the development of large scale event processing applications, writing the rules that correctly capture the application domain arguably remains a difficult and error prone task, which fundamentally lacks consolidated tool support. Moving from these premises, this paper introduces CAVE, an efficient approach and tool to support developers in analyzing the behavior of an event processing application. CAVE verifies properties based on the adopted CEP ruleset and on the environmental conditions, and outputs sequences of events that prove the satisfiability or unsatisfiability of each property. The key idea that contributes to the efficiency of CAVE is the translation of the property checking task into a set of constraint solving problems. The paper presents the CAVE approach in detail, describes its prototype implementation and evaluates its performance in a wide range of scenarios.


title: Factors Affecting Perceived Persuasiveness of a Behavior Change Support System

abstract: Despite the popularity of the technology acceptance and adoption studies, adoption of persuasive systems has not been investigated from a theoretical perspective. In the present study, we put forward a novel approach for investigating behavior change support systems (BCSS) through a theoretical model. We constructed and tested (two measurement points; 172 subjects) a model predicting perceived persuasiveness and actual usage of a behavior change support system. Results from a rigorous PLS-SEM analysis support most of our hypotheses about factors affecting persuasiveness and actual usage. The proffered model can be considered as a meta-model, i.e. it may be utilized in a multitude of domains, such as health behaviors (as in the present study), safety and education. The present study extends the extant (rather limited) body of knowledge regarding the factors contributing to engagement with behavior change support systems.


Learning the Language of the Genome using RNNs


Extubation after Anaesthesia : A Systematic Review


title: Hierarchical data-driven vehicle dispatch and ride-sharing

abstract: Modern transportation system suffers from increasing passenger demand, limited vehicle supply and inefficient mobility service. Towards building an intelligent transportation system to address these issues, we propose a hierarchical framework to implement strategies that is capable of allocating vehicles to serve passengers in different locations based on limited supply. In the higher hierarchy, we optimize idle mileage induced by rebalancing vehicles across regions using receding horizon control towards current and predicted future requests. In addition, we design a dispatch strategy that is robust against passenger demand and vehicle mobility pattern uncertainties. In the lower hierarchy, within each region, pick-up and drop-off schedules for real-time requests are obtained for each vehicle by solving mixed-integer linear programs (MILP). The objective of the MILP is to minimize total mileage delay due to ride-sharing while serving as many requests as possible. We illustrate the validity of our framework via numerical simulations on taxi trip data from New York City.


title: Blood-brain barrier permeability precedes senile plaque formation in an Alzheimer disease model, Microcirculation 10

abstract: OBJECTIVE ::: To establish the generality of cerebrovascular pathology frequently observed with Alzheimer disease, we have assessed blood-brain barrier (BBB) integrity using the Alzheimer disease model Tg2576 mice in which cognitive deficits and neuritic plaque formation develop around 10-12 months of age. ::: ::: ::: METHODS ::: We assessed BBB integrity using well-established methods involving albumin and Evans blue uptake and introduce the use of a novel perfusion protocol using succinimidyl ester of carboxyfluorescein diacetate. ::: ::: ::: RESULTS ::: BBB permeability is increased in the cerebral cortex of 10-month-old Tg2576 mice preceding Alzheimer disease pathology presentation. Furthermore, when compared with their nontransgenic littermates, 4-month-old Tg2576 mice exhibit compromised BBB integrity in some areas of the cerebral cortex. An age-related increase in albumin uptake by the brains of Tg2576 mice, compared with nontransgenic mice, was also observed. These findings were supported by quantitative Evans blue analysis (p = 0.07, two-way analysis of variance). ::: ::: ::: CONCLUSION ::: A breakdown of BBB was evident in young 4- to 10-month-old Tg2576 mice. Compromised barrier function could explain the mechanisms of Abeta entry into the brain observed in experimental Alzheimer disease vaccination models. Such structural changes to the BBB caused by elevated Abeta could play a central role in Alzheimer disease development and might define an early point of intervention for designing effective therapy against the disease.


title: FPGA-based design and implementation of a phase detector to correct the I/Q imbalance

abstract: This paper describes the design and implementation of a system to evaluate the I/Q modulation when phase and amplitude imperfections are added. This system allows observing the signal behavior in the presence of phase and amplitude imbalance. An approach to correct I/Q imbalances using a power detector is proposed, by means calculating peak impairments in the interest signal and phase shifting is detected. Phase shift stability is introduced for correcting (I or Q) branches respectively to guarantee amplitude and phase balancing condition in the modulator output. Experimental results are implemented employing an FPGA by using DSP-Builder to bit true VHDL hardware description of proposed model. The modulated signal with the constellation and measurements in the oscilloscope is compared.


title: A webpage similarity measure for web sessions clustering using sequence alignment

abstract: Web sessions clustering is a process of web usage mining task that aims to group web sessions with similar trends and usage patterns into clusters. This process is crucial for effective website management, web personalization and developing web recommender systems. Accurate clustering of web sessions is highly dependent to the similarity measure defined to compare web sessions. In this paper, we propose a similarity measure for comparing web sessions. The sequential order of web navigations in sessions is considered using sequence alignment method. Furthermore, we propose to consider the usage similarity of two web sessions based on the time a user spends on a webpage, and also the frequency of visit of each page within the session. The proposed method is validated by clustering a collection of web sessions using an agglomerative clustering technique and comparing the results with available methods. The experimental results show effectiveness of the proposed method to capture the properties of web session data.


title: Imaging diagnosis of early rheumatoid arthritis.

abstract: Early diagnosis of rheumatoid arthritis is essential for its proper management. Currently, the initial phase of rheumatoid arthritis is known to provide a window of therapeutic opportunity. Although the diagnosis is primarily clinical, the development and improvement of laboratory and imaging methods have contributed to earlier diagnosis and determination of procedures in early rheumatoid arthritis. In this article, the authors review the role of the major imaging methods used for assessing early rheumatoid arthritis, especially conventional radiography, ultrasonography, and magnetic resonance imaging.


title: Translating Neuralese

abstract: Several approaches have recently been proposed for learning decentralized deep multiagent policies that coordinate via a differentiable communication channel. While these policies are effective for many tasks, interpretation of their induced communication strategies has remained a challenge. Here we propose to interpret agents' messages by translating them. Unlike in typical machine translation problems, we have no parallel data to learn from. Instead we develop a translation model based on the insight that agent messages and natural language strings mean the same thing if they induce the same belief about the world in a listener. We present theoretical guarantees and empirical evidence that our approach preserves both the semantics and pragmatics of messages by ensuring that players communicating through a translation layer do not suffer a substantial loss in reward relative to players with a common language.


title: Semi-supervised CCG Lexicon Extension

abstract: This paper introduces Chart Inference (CI), an algorithm for deriving a CCG category for an unknown word from a partial parse chart. It is shown to be faster and more precise than a baseline brute-force method, and to achieve wider coverage than a rule-based system. In addition, we show the application of CI to a domain adaptation task for question words, which are largely missing in the Penn Treebank. When used in combination with self-training, CI increases the precision of the baseline StatCCG parser over subject-extraction questions by 50%. An error analysis shows that CI contributes to the increase by expanding the number of category types available to the parser, while self-training adjusts the counts.


title: A novel compliant orthogonal displacement amplification mechanism and its application in micro-grasping

abstract: In the compact micro-grasping system, the combination of precisely orthogonal movement transformation, displacement amplification and simple structure is important. The typical solution of the combination issue requires bidirectional symmetric input forces/displacements. However, under a certain driving condition, numerous actuators used in micro-manipulation only supply unidirectional input froce/displacement for the driven mechanism, which makes the typical solution infeasible. In this study, a novel compliant orthogonal displacement amplification mechanism (DAM) is proposed to solve the combination issue for most of the actuators used in micro-grasping. The proposed mechanism is a triangulation amplification-based mechanism with undetermined structural parameters. The number of the undetermined parameters is analyzed. The equations satisfying the displacement boundary conditions and the equilibrium equations of the orthogonal movement transformation are derived to solve the undetermined parameters. Finite element analysis (FEA) of four design examples is used to verify the design method. The FEA results show that, for the design examples, the errors evaluating the orthogonal movement transformation are smaller than 0.56% and 0.15% respectively, and the displacement amplification ratios are larger than 4.6. The orthogonal displacement amplification is realized. Furthermore, a microgripper utilizing the proposed orthogonal DAM is presented. The performances of the gripper, including the displacement amplification and the parallel movement of the jaws, are verified by FEA.


A Systematic Mapping Study on Current Research Topics in Smart Contracts


title: Privacy Loss in Apple's Implementation of Differential Privacy on MacOS 10.12

abstract: In June 2016, Apple announced that it will deploy differential privacy for some user data collection in order to ensure privacy of user data, even from Apple. The details of Apple's approach remained sparse. Although several patents have since appeared hinting at the algorithms that may be used to achieve differential privacy, they did not include a precise explanation of the approach taken to privacy parameter choice. Such choice and the overall approach to privacy budget use and management are key questions for understanding the privacy protections provided by any deployment of differential privacy. ::: In this work, through a combination of experiments, static and dynamic code analysis of macOS Sierra (Version 10.12) implementation, we shed light on the choices Apple made for privacy budget management. We discover and describe Apple's set-up for differentially private data processing, including the overall data pipeline, the parameters used for differentially private perturbation of each piece of data, and the frequency with which such data is sent to Apple's servers. ::: We find that although Apple's deployment ensures that the (differential) privacy loss per each datum submitted to its servers is $1$ or $2$, the overall privacy loss permitted by the system is significantly higher, as high as $16$ per day for the four initially announced applications of Emojis, New words, Deeplinks and Lookup Hints. Furthermore, Apple renews the privacy budget available every day, which leads to a possible privacy loss of 16 times the number of days since user opt-in to differentially private data collection for those four applications. ::: We advocate that in order to claim the full benefits of differentially private data collection, Apple must give full transparency of its implementation, enable user choice in areas related to privacy loss, and set meaningful defaults on the privacy loss permitted.


title: A High-Resolution Enhancer Atlas of the Developing Telencephalon

abstract: The mammalian telencephalon plays critical roles in cognition, motor function, and emotion. Though many of the genes required for its development have been identified, the distant-acting regulatory sequences orchestrating their in vivo expression are mostly unknown. Here, we describe a digital atlas of in vivo enhancers active in subregions of the developing telencephalon. We identified more than 4,600 candidate embryonic forebrain enhancers and studied the in vivo activity of 329 of these sequences in transgenic mouse embryos. We generated serial sets of histological brain sections for 145 reproducible forebrain enhancers, resulting in a publicly accessible web-based data collection comprising more than 32,000 sections. We also used epigenomic analysis of human and mouse cortex tissue to directly compare the genome-wide enhancer architecture in these species. These data provide a primary resource for investigating gene regulatory mechanisms of telencephalon development and enable studies of the role of distant-acting enhancers in neurodevelopmental disorders.


title: Thematic relations as links between nominal reference and temporal constitution

abstract: This paper treats the correspondence between the reference type of NPs (i.e., mass nouns, count nouns, measure constructions, plurals) and the temporal constitution of verbal predicates (i.e., activities, accomplishments). A theory will be developed that handles the well known influence of the reference type of NPs in argument positions on the temporal constitution of the verbal expressions, assuming an event semantics with lattice structures and thematic roles as primitive relations between events and objects. Some consequences for the theory of thematic roles will be discussed, and the effect of partitive case marking on the verbal aspect, as in Finnish, and of aspectual marking on the definiteness of NPs, like in Slavic, will be explained.


title: Momentum control of humanoid robots with series elastic actuators

abstract: Humanoid robots may require a degree of compliance at the joint level for improving efficiency, shock tolerance, and safe interaction with humans. The presence of joint elasticity, however, complexifies the design of balancing and walking controllers. This paper proposes a control framework for extending momentum based controllers developed for stiff actuators to the case of series elastic actuators. The key point is to consider the motor velocities as an intermediate control input, and then apply high-gain control to stabilise the desired motor velocities achieving momentum control. Simulations carried out on a model of the robot iCub verify the soundness of the proposed approach.


title: A NOVEL SWITCHED-CURRENT SUCCESSIVE APPROXIMATION ADC

abstract: A novel switched-current successive approximation ADC is presented in this paper with high speed and low power consumption. The proposed ADC contains a new high-accuracy and power-efficient switched-current S/H circuit and a speed-improved current comparator. Designed and simulated in a 0.18-μm CMOS process, this 8-bit ADC achieves 46.23 dB SNDR at 1.23 MS/s consuming 73.19 μW under 1.2 V voltage supply, resulting in an ENOB of 7.38-bit and an FOM of 0.357 pJ/Conv.-step.


title: Temporally Consistent Depth Estimation in Videos with Recurrent Architectures

abstract: Convolutional networks trained on large RGB-D datasets have enabled depth estimation from a single image. Many works on automotive applications rely on such approaches. However, all existing methods work on a frame-by-frame manner when applied to videos, which leads to inconsistent depth estimates over time. In this paper, we introduce for the first time an approach that yields temporally consistent depth estimates over multiple frames of a video. This is done by a dedicated architecture based on convolutional LSTM units and layer normalization. Our approach achieves superior performance on several error metrics when compared to independent frame processing. This also shows in an improved quality of the reconstructed multi-view point clouds.


title: ASPIER: An Automated Framework for Verifying Security Protocol Implementations

abstract: We present ASPIER -- the first framework that combines software model checking with a standard protocol security model to automatically analyze authentication and secrecy properties of protocol implementations in C. The technical approach extends the iterative abstraction-refinement methodology for software model checking with a domain-specific protocol and symbolic attacker model. We have implemented the ASPIER tool and used it to verify authentication and secrecy properties of a part of an industrial strength protocol implementation -- the handshake in OpenSSL -- for configurations consisting of up to 3 servers and 3 clients. We have also implemented two distinct methods for reasoning about attacker message derivations, and evaluated them in the context of OpenSSL verification. ASPIER detected the "version-rollback" vulnerability in OpenSSL 0.9.6c source code and successfully verified the implementation when clients and servers are only willing to run SSL 3.0.


title: Human brain white matter atlas: Identification and assignment of common anatomical structures in superficial white matter

abstract: Structural delineation and assignment are the fundamental steps in understanding the anatomy of the human brain. The white matter has been structurally defined in the past only at its core regions (deep white matter). However, the most peripheral white matter areas, which are interleaved between the cortex and the deep white matter, have lacked clear anatomical definitions and parcellations. We used axonal fiber alignment information from diffusion tensor imaging (DTI) to delineate the peripheral white matter, and investigated its relationship with the cortex and the deep white matter. Using DTI data from 81 healthy subjects, we identified nine common, blade-like anatomical regions, which were further parcellated into 21 subregions based on the cortical anatomy. Four short association fiber tracts connecting adjacent gyri (U-fibers) were also identified reproducibly among the healthy population. We anticipate that this atlas will be useful resource for atlas-based white matter anatomical studies.


title: Socially Guided Intrinsic Motivation for Robot Learning of Motor Skills

abstract: This paper presents a technical approach to robot learning of motor skills which combines active intrinsically motivated learning with imitation learning. Our algorithmic architecture, called SGIM-D, allows efficient learning of high-dimensional continuous sensorimotor inverse models in robots, and in particular learns distributions of parameterised motor policies that solve a corresponding distribution of parameterised goals/tasks. This is made possible by the technical integration of imitation learning techniques within an algorithm for learning inverse models that relies on active goal babbling. After reviewing social learning and intrinsic motivation approaches to action learning, we describe the general framework of our algorithm, before detailing its architecture. In an experiment where a robot arm has to learn to use a flexible fishing line, we illustrate that SGIM-D efficiently combines the advantages of social learning and intrinsic motivation and benefits from human demonstration properties to learn how to produce varied outcomes in the environment, while developing more precise control policies in large spaces.


title: HADM: Hybrid Analysis for Detection of Malware

abstract: Android is the most popular mobile operating system with a market share of over 80% [1]. Due to its popularity and also its open source nature, Android is now the platform most targeted by malware, creating an urgent need for effective defense mechanisms to protect Android-enabled devices.


title: Bike sharing station placement leveraging heterogeneous urban open data

abstract: Bike sharing systems have been deployed in many cities to promote green transportation and a healthy lifestyle. One of the key factors for maximizing the utility of such systems is placing bike stations at locations that can best meet users' trip demand. Traditionally, urban planners rely on dedicated surveys to understand the local bike trip demand, which is costly in time and labor, especially when they need to compare many possible places. In this paper, we formulate the bike station placement issue as a bike trip demand prediction problem. We propose a semi-supervised feature selection method to extract customized features from the highly variant, heterogeneous urban open data to predict bike trip demand. Evaluation using real-world open data from Washington, D.C. and Hangzhou shows that our method can be applied to different cities to effectively recommend places with higher potential bike trip demand for placing future bike stations.


title: Identifying Behaviors in Crowd Scenes Using Stability Analysis for Dynamical Systems

abstract: A method is proposed for identifying five crowd behaviors (bottlenecks, fountainheads, lanes, arches, and blocking) in visual scenes. In the algorithm, a scene is overlaid by a grid of particles initializing a dynamical system defined by the optical flow. Time integration of the dynamical system provides particle trajectories that represent the motion in the scene; these trajectories are used to locate regions of interest in the scene. Linear approximation of the dynamical system provides behavior classification through the Jacobian matrix; the eigenvalues determine the dynamic stability of points in the flow and each type of stability corresponds to one of the five crowd behaviors. The eigenvalues are only considered in the regions of interest, consistent with the linear approximation and the implicated behaviors. The algorithm is repeated over sequential clips of a video in order to record changes in eigenvalues, which may imply changes in behavior. The method was tested on over 60 crowd and traffic videos.


title: Medium access control with coordinated adaptive sleeping for wireless sensor networks

abstract: This paper proposes S-MAC, a medium access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect sensor networks to be deployed in an ad hoc fashion, with nodes remaining largely inactive for long time, but becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in several ways: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important. S-MAC uses a few novel techniques to reduce energy consumption and support self-configuration. It enables low-duty-cycle operation in a multihop network. Nodes form virtual clusters based on common sleep schedules to reduce control overhead and enable traffic-adaptive wake-up. S-MAC uses in-channel signaling to avoid overhearing unnecessary traffic. Finally, S-MAC applies message passing to reduce contention latency for applications that require in-network data processing. The paper presents measurement results of S-MAC performance on a sample sensor node, the UC Berkeley Mote, and reveals fundamental tradeoffs on energy, latency and throughput. Results show that S-MAC obtains significant energy savings compared with an 802.11-like MAC without sleeping.


title: Method for Determining Kinematic Parameters of the In Vivo Thumb Carpometacarpal Joint

abstract: The mobility of the thumb carpometacarpal (CMC) joint is critical for functional grasping and manipulation tasks. We present an optimization technique for determining from surface marker measurements a subject-specific kinematic model of the in vivo CMC joint that is suitable for measuring mobility. Our anatomy-based cost metric scores a candidate joint model by the plausibility of the corresponding joint angle values and kinematic parameters rather than only the marker trajectory reconstruction error. The proposed method repeatably determines CMC joint models with anatomically-plausible directions for the two dominant rotational axes and a lesser range of motion (RoM) for the third rotational axis. We formulate a low-dimensional parameterization of the optimization domain by first solving for joint axis orientation variables that then constrain the search for the joint axis location variables. Individual CMC joint models were determined for 24 subjects. The directions of the flexion-extension (FE) axis and adduction-abduction (AA) axis deviated on average by 9deg and 22deg, respectively, from the mean axis direction. The average RoM for FE, AA, and pronation-supination (PS) joint angles were 76deg, 43deg, and 23deg for active CMC movement. The mean separation distance between the FE and AA axes was 4.6 mm, and the mean skew angle was 87deg from the positive flexion axis to the positive abduction axis.


title: Relationships Matter: Linking Teacher Support to Student Engagement and Achievement

abstract: A frequency multiplier includes a ring oscillator having a number of logic gates arranged in a plurality of rings. Control inputs enable the selection of individual gates so as to connect them into the ring or, conversely, remove them from the ring. As additional gates are removed, the combined delay imposed by the gates remaining in the ring is reduced and the frequency of the oscillator increases. A variable delay element, preferably a group of tri-state inverters connected in parallel, is connected between two of the gates. The oscillator is fine tuned by controlling the delay inserted by the variable delay element. The frequency multiplier also includes a frequency comparator. A reference frequency is passed through a divide-by-K unit and the output of the ring oscillator is passed through a divide-by-N unit, N being greater than K. The frequency multiplier is coarse-tuned by progressively removing additional gates from the ring oscillator, and then fine-tuned by increasing the delay imposed by the variable delay element. At the conclusion of coarse and fine tuning, the frequency multiplier is locked at a frequency which closely approximates a reference frequency multiplied by N/K. An accuracy of 1% or less may be achieved. When the frequency multiplier ceases to be hooked on a frequency, it enters an idle state in which it consumes no power.


title: Detection and Tracking of Eyes for Gaze-camera Control

abstract: Abstract A head-off gaze-camera needs eye location information for head-free usage. For this purpose, we propose new algorithms to extract and track the positions of eyes in a real-time video stream. For extraction of eye positions, we detect blinks based on the differences between successive images. However, eyelid regions are fairly small. To distinguish them from dominant head movement, we elaborate a head movement cancellation process. For eye-position tracking, we use a template of ‘Between-the-Eyes,’ which is updated frame-by-frame, instead of the eyes themselves. Eyes are searched based on the current position of ‘Between-the-Eyes’ and their geometrical relations to the position in the previous frame. The ‘Between-the-Eyes’ pattern is easier to locate accurately than eye patterns. We implemented the system on a PC with a Pentium III 866-MHz CPU. The system runs at 30 frames/s and robustly detects and tracks the eyes.


title: NCR: A Scalable Network-Based Approach to Co-Ranking in Question-and-Answer Sites

abstract: Question-and-answer (QA b) The large-scale Q&A data makes extracting supervised information very expensive. In order to address these issues, we propose an unsupervised Network-based Co-Ranking framework (NCR) to rank multiple objects in Q&A sites. Empirical studies on real-world Yahoo! Answers datasets demonstrate the effectiveness and the efficiency of the proposed NCR method.


title: Effects of R&D expenditure on employment growth : a dynamic panel analysis.

abstract: This paper estimates the effects of research and development (R&D) expenditure on the employment growth in ::: Malaysian manufacturing sector during the period 2000 to 2008. Theoretical literatures devote the link between ::: R&D and employment structure tends to suggest technological change has positive effects on job. Using dynamic ::: panel GMM system estimation and 3 digit industry levels from manufacturing survey over the period 2000 to ::: 2008, this paper find there is negative and significant relationship between R&D expenditure and employment ::: growth. This is true when we consider with the second lag of the variable. Employment growth in Malaysian ::: labour market however still favour to labour oriented and the absorption of the new technology is considered low.


title: Gastric rupture with necrosis following acute gastric dilatation: report of a case

abstract: Gastric rupture with necrosis following acute gastric dilatation (AGD) is a rare and potentially fatal event; usually seen in patients with eating disorders such as anorexia nervosa or bulimia. A 12-year-old lean boy with no remarkable medical history was brought to our Emergency Department suffering acute abdominal symptoms. Emergency laparotomy revealed massive gastric dilatation and partial necrosis, with rupture of the anterior wall of the fundus of the stomach. We performed partial gastrectomy and the patient recovered uneventfully. We report this case to demonstrate that AGD and subsequent gastric rupture can occur in patients without any underlying disorders and that just a low body mass index is a risk factor for this potentially fatal condition.


title: Probing for semantic evidence of composition by means of simple classification tasks

abstract: We propose a diagnostic method for probing specific information captured in vector representations of sentence meaning, via simple classification tasks with strategically constructed sentence sets. We identify some key types of semantic information that we might expect to be captured in sentence composition, and illustrate example classification tasks for targeting this information.


Video Denoising Algorithm : A Review


title: Sentence Reduction For Automatic Text Summarization

abstract: We present a novel sentence reduction system for automatically removing extraneous phrases from sentences that are extracted from a document for summarization purpose. The system uses multiple sources of knowledge to decide which phrases in an extracted sentence can be removed, including syntactic knowledge, context information, and statistics computed from a corpus which consists of examples written by human professionals. Reduction can significantly improve the conciseness of automatic summaries.


1 An Introduction to Conditional Random Fields for Relational Learning


X CLAIM : Interoperability with Cryptocurrency-Backed Tokens ?


Research Statement


title: Visual Field Maps in Human Cortex

abstract: Much of the visual cortex is organized into visual field maps: nearby neurons have receptive fields at nearby locations in the image. Mammalian species generally have multiple visual field maps with each species having similar, but not identical, maps. The introduction of functional magnetic resonance imaging made it possible to identify visual field maps in human cortex, including several near (1) medial occipital (V1,V2,V3), (2) lateral occipital (LO-1,LO-2, hMT+), (3) ventral occipital (hV4, VO-1, VO-2), (4) dorsal occipital (V3A, V3B), and (5) posterior parietal cortex (IPS-0 to IPS-4). Evidence is accumulating for additional maps, including some in the frontal lobe. Cortical maps are arranged into clusters in which several maps have parallel eccentricity representations, while the angular representations within a cluster alternate in visual field sign. Visual field maps have been linked to functional and perceptual properties of the visual system at various spatial scales, ranging from the level of individual maps to map clusters to dorsal-ventral streams. We survey recent measurements of human visual field maps, describe hypotheses about the function and relationships between maps, and consider methods to improve map measurements and characterize the response properties of neurons comprising these maps.


title: Parsing R-CNN for Instance-Level Human Analysis

abstract: Instance-level human analysis is common in real-life scenarios and has multiple manifestations, such as human part segmentation, dense pose estimation, human-object interactions, etc. Models need to distinguish different human instances in the image panel and learn rich features to represent the details of each instance. In this paper, we present an end-to-end pipeline for solving the instance-level human analysis, named Parsing R-CNN. It processes a set of human instances simultaneously through comprehensive considering the characteristics of region-based approach and the appearance of a human, thus allowing representing the details of instances. Parsing R-CNN is very flexible and efficient, which is applicable to many issues in human instance analysis. Our approach outperforms all state-of-the-art methods on CIHP (Crowd Instance-level Human Parsing), MHP v2.0 (Multi-Human Parsing) and DensePose-COCO datasets. Based on the proposed Parsing R-CNN, we reach the 1st place in the COCO 2018 Challenge DensePose Estimation task. Code and models are publicly available.


title: Local Obfuscation Mechanisms for Hiding Probability Distributions

abstract: We introduce a formal model for the information leakage of probability distributions and define a notion called distribution privacy as the local differential privacy for probability distributions. Roughly, the distribution privacy of a local obfuscation mechanism means that the attacker cannot significantly gain any information on the distribution of the mechanism’s input by observing its output. Then we show that existing local mechanisms can hide input distributions in terms of distribution privacy, while deteriorating the utility by adding too much noise. For example, we prove that the Laplace mechanism needs to add a large amount of noise proportionally to the infinite Wasserstein distance between the two distributions we want to make indistinguishable. To improve the tradeoff between distribution privacy and utility, we introduce a local obfuscation mechanism, called a tupling mechanism, that adds random dummy data to the output. Then we apply this mechanism to the protection of user attributes in location based services. By experiments, we demonstrate that the tupling mechanism outperforms popular local mechanisms in terms of attribute obfuscation and service quality.


title: Stripe boundary codes for real-time structured-light range scanning of moving objects

abstract: We present a novel approach to real-time structured light range scanning. After an analysis of the underlying assumptions of existing structured light techniques, we derive a new set of illumination patterns based on coding the boundaries between projected stripes. These stripe boundary codes allow range scanning of moving objects, with only modest assumptions about scene continuity and reflectance. We describe an implementation that integrates these new codes with real-time algorithms for tracking stripe boundaries and determining depths. Our system uses a standard video camera and DLP projector, and produces dense range images at 60 Hz with 100 /spl mu/m accuracy over a 10 cm working volume. As an application, we demonstrate the creation of complete models of rigid objects: the objects are rotated in front of the scanner by hand, and successive range images are automatically aligned.


title: Designing emotionally evocative homepages: an empirical study of the quantitative relations between design factors and emotional dimensions

abstract: Emotional aspects of homepages are becoming more important as people spend more time in cyberspace. This research aims to identify quantitative relationships between key design factors and generic dimensions of secondary emotions so that we may develop homepages which target emotions more effectively. In order to achieve this goal, we conducted three related studies. In the first study, we identified 13 generic dimensions of secondary emotions that people usually feel when viewing diverse homepages. In the second study, we identified key design factors that professional designers frequently use in their attempts to develop emotionally evocative homepages. Finally, in the third study, we identified quantitative relationships between the key design factors and the 13 emotional dimensions. This paper describes these three studies and concludes with the implications and limitations of the study results.


title: Using Belief Theory to Diagnose Control Knowledge Quality. Application to cartographic generalisation

abstract: Both humans and artificial systems frequently use trial and error methods to problem solving. In order to be effective, this type of strategy implies having high quality control knowledge to guide the quest for the optimal solution. Unfortunately, this control knowledge is rarely perfect. Moreover, in artificial systems--as in humans--self-evaluation of one's own knowledge is often difficult. Yet, this self-evaluation can be very useful to manage knowledge and to determine when to revise it. The objective of our work is to propose an automated approach to evaluate the quality of control knowledge in artificial systems based on a specific trial and error strategy, namely the informed tree search strategy. Our revision approach consists in analysing the system's execution logs, and in using the belief theory to evaluate the global quality of the knowledge. We present a real-world industrial application in the form of an experiment using this approach in the domain of cartographic generalisation. Thus far, the results of using our approach have been encouraging. This paper deals with the problem of the automatic evaluation of the control knowledge quality. To face this problem, we propose an approach based on the analysis of the execution logs and on the belief theory. In Section II, we introduce the general context in which our work takes place and the difficulties we must face. Section III is devoted to the presentation of our approach. Section IV describes an application of our approach to the cartographic generalisation domain. In this context, we present a real case study that we carried out as well as its results. Section V concludes and presents perspectives of this work.


title: A time series approach for profiling attack

abstract: The goal of a profiling attack is to challenge the security of a cryptographic device in the worst case scenario. Though template attack is reputed as the strongest power analysis attack, they effectiveness is strongly dependent on the validity of the Gaussian assumption. This led recently to the appearance of nonparametric approaches, often based on machine learning strategies. Though these approaches outperform template attack, they tend to neglect the potential source of information available in the temporal dependencies between power values. In this paper, we propose an original multi-class profiling attack that takes into account the temporal dependence of power traces. The experimental study shows that the time series analysis approach is competitive and often better than static classification alternatives.


title: Relationships Between Bullying and Violence Among US Youth

abstract: Objective To determine the extent to which bullying and being bullied, both in and away from school, is associated with involvement in violent behavior. Design, Setting, and Participants A US representative cross-sectional sample of 15 686 students in grades 6 through 10 in public and private schools completed the World Health Organization's Health Behaviour in School-aged Children survey in 1998. Main Outcome Measures Self-report of weapon carrying, weapon carrying in school, physical fighting, and being injured in a physical fight. Results Involvement in each of the violence-related behaviors ranged from 13% to 23% of boys and 4% to 11% of girls. Bullying others and being bullied were consistently related to each violence-related behavior for both boys and girls. Greater odds of involvement occurred with bullying others than being bullied, and greater odds of involvement occurred with bullying that took place away from school than that occurring in school. For example, the adjusted odds ratio for weapon carrying associated with being bullied in school weekly was 1.5, for bullying others in school 2.6, for being bullied away from school 4.1, and for bullying others away from school 5.9. Conclusion Bullying should not be considered a normative aspect of youth development, but rather a marker for more serious violent behaviors, including weapon carrying, frequent fighting, and fighting-related injury.


title: Robust visual domain adaptation with low-rank reconstruction

abstract: Visual domain adaptation addresses the problem of adapting the sample distribution of the source domain to the target domain, where the recognition task is intended but the data distributions are different. In this paper, we present a low-rank reconstruction method to reduce the domain distribution disparity. Specifically, we transform the visual samples in the source domain into an intermediate representation such that each transformed source sample can be linearly reconstructed by the samples of the target domain. Unlike the existing work, our method captures the intrinsic relatedness of the source samples during the adaptation process while uncovering the noises and outliers in the source domain that cannot be adapted, making it more robust than previous methods. We formulate our problem as a constrained nuclear norm and l 2, 1 norm minimization objective and then adopt the Augmented Lagrange Multiplier (ALM) method for the optimization. Extensive experiments on various visual adaptation tasks show that the proposed method consistently and significantly beats the state-of-the-art domain adaptation methods.


title: A multi-view intelligent editor for digital video libraries

abstract: Silver is an authoring tool that aims to allow novice users to edit di gital video. The goal is to make editing of digital video as easy as text editing. Silver provides multiple coordinated views, including project, source, outline, subject, storyboard, textual transcript and timeline views. Selections and edits in any view are synchronized with all other views. A variety of recognition algorithms are applied to the video and audio content and then are used to aid in the editing tasks. The Informedia Digital Library supplies the recognition algorithms and metadata used to support intelligent editing, and Informedia also provides search and a repository. The metadata includes shot boundaries and a time-synchronized transcript, which are used to support intelligent selection and intelligent cut/copy/paste.


title: Single actuator wave-like robot (SAW): design, modeling, and experiments.

abstract: In this paper, we present a single actuator wave-like robot, a novel bioinspired robot which can move forward or backward by producing a continuously advancing wave. The robot has a unique minimalistic mechanical design and produces an advancing sine wave, with a large amplitude, using only a single motor but with no internal straight spine. Over horizontal surfaces, the robot does not slide relative to the surface and its direction of locomotion is determined by the direction of rotation of the motor. We developed a kinematic model of the robot that accounts for the two-dimensional mechanics of motion and yields the speed of the links relative to the motor. Based on the optimization of the kinematic model, and accounting for the mechanical constraints, we have designed and built multiple versions of the robot with different sizes and experimentally tested them (see movie). The experimental results were within a few percentages of the expectations. The larger version attained a top speed of 57 cm s−1 over a horizontal surface and is capable of climbing vertically when placed between two walls. By optimizing the parameters, we succeeded in making the robot travel by 13% faster than its own wave speed.


Fabrickeyboard: multimodal textile sensate media as an expressive and deformable musical interface


title: Proofs of ownership in remote storage systems

abstract: Cloud storage systems are becoming increasingly popular. A promising technology that keeps their cost down is deduplication, which stores only a single copy of repeating data. Client-side deduplication attempts to identify deduplication opportunities already at the client and save the bandwidth of uploading copies of existing files to the server. In this work we identify attacks that exploit client-side deduplication, allowing an attacker to gain access to arbitrary-size files of other users based on a very small hash signatures of these files. More specifically, an attacker who knows the hash signature of a file can convince the storage service that it owns that file, hence the server lets the attacker download the entire file. (In parallel to our work, a subset of these attacks were recently introduced in the wild with respect to the Dropbox file synchronization service.) To overcome such attacks, we introduce the notion of proofs-of-ownership (PoWs), which lets a client efficiently prove to a server that that the client holds a file, rather than just some short information about it. We formalize the concept of proof-of-ownership, under rigorous security definitions, and rigorous efficiency requirements of Petabyte scale storage systems. We then present solutions based on Merkle trees and specific encodings, and analyze their security. We implemented one variant of the scheme. Our performance measurements indicate that the scheme incurs only a small overhead compared to naive client-side deduplication.


title: Knowledge, attitudes, and practices surrounding breast cancer and screening in female teachers of buraidah, saudi arabia.

abstract: Background : Breast cancer is by far the most frequent cancer of women. However the preventive measures for such problem are probably less than expected. The objectives of this study are to assess breast cancer knowledge and attitudes and factors associated with the practice of breast self examination (BSE) among female teachers of Saudi Arabia. Patients and Methods: We conducted a cross-sectional survey of teachers working in female schools in Buraidah, Saudi Arabia using a self-administered questionnaire to investigate participants' knowledge about the risk factors of breast cancer, their attitudes and screening behaviors. A sample of 376 female teachers was randomly selected. Participants lived in urban areas, and had an average age of 34.7 ±5.4 years. Results: More than half of the women showed a limited knowledge level. Among participants, the most frequently reported risk factors were non-breast feeding and the use of female sex hormones. The printed media was the most common source of knowledge. Logistic regression analysis revealed that high income was the most significant predictor of better knowledge level. Knowing a non-relative case with breast cancer and having a high knowledge level were identified as the significant predictors for practicing BSE. Conclusions: The study points to the insufficient knowledge of female teachers about breast cancer and identified the negative influence of low knowledge on the practice of BSE. Accordingly, relevant educational programs to improve the knowledge level of women regarding breast cancer are needed.


CONTEXT-CONDITIONAL GENERATIVE ADVERSARIAL NETWORKS


title: Spoken and Written Language Resources for Vietnamese

abstract: This paper presents an overview of our activities for spoken and written language resources for Vietnamese implemented at CLIPSIMAG Laboratory and International Research Center MICA. A new methodology for fast text corpora acquisition for minority languages which has been applied to Vietnamese is proposed. The first results of a process of building a large Vietnamese speech database (VNSpeechCorpus) and a phonetic dictionary, which is used for automatic alignment process, are also presented.


title: Fast Domain Adaptation for Neural Machine Translation

abstract: Neural Machine Translation (NMT) is a new approach for automatic translation of text from one human language into another. The basic concept in NMT is to train a large Neural Network that maximizes the translation performance on a given parallel corpus. NMT is gaining popularity in the research community because it outperformed traditional SMT approaches in several translation tasks at WMT and other evaluation tasks/benchmarks at least for some language pairs. However, many of the enhancements in SMT over the years have not been incorporated into the NMT framework. In this paper, we focus on one such enhancement namely domain adaptation. We propose an approach for adapting a NMT system to a new domain. The main idea behind domain adaptation is that the availability of large out-of-domain training data and a small in-domain training data. We report significant gains with our proposed method in both automatic metrics and a human subjective evaluation metric on two language pairs. With our adaptation method, we show large improvement on the new domain while the performance of our general domain only degrades slightly. In addition, our approach is fast enough to adapt an already trained system to a new domain within few hours without the need to retrain the NMT model on the combined data which usually takes several days/weeks depending on the volume of the data.


title: SiteLens: situated visualization techniques for urban site visits

abstract: Urban designers and urban planners often conduct site visits prior to a design activity to search for patterns or better understand existing conditions. We introduce SiteLens, an experimental system and set of techniques for supporting site visits by visualizing relevant virtual data directly in the context of the physical site, which we call situated visualization. We address alternative visualization representations and techniques for data collection, curation, discovery, comparison, manipulation, and provenance. A real use scenario is presented and two iterations of evaluation with faculty and students from the Columbia University Graduate School of Architecture, Planning and Preservation provide directions and insight for further investigation.


title: CoolStreaming/DONet: a data-driven overlay network for peer-to-peer live media streaming

abstract: This paper presents DONet, a data-driven overlay network for live media streaming. The core operations in DONet are very simple: every node periodically exchanges data availability information with a set of partners, and retrieves unavailable data from one or more partners, or supplies available data to partners. We emphasize three salient features of this data-driven design: 1) easy to implement, as it does not have to construct and maintain a complex global structure; 2) efficient, as data forwarding is dynamically determined according to data availability while not restricted by specific directions; and 3) robust and resilient, as the partnerships enable adaptive and quick switching among multi-suppliers. We show through analysis that DONet is scalable with bounded delay. We also address a set of practical challenges for realizing DONet, and propose an efficient member and partnership management algorithm, together with an intelligent scheduling algorithm that achieves real-time and continuous distribution of streaming contents. We have extensively evaluated the performance of DONet over the PlanetLab. Our experiments, involving almost all the active PlanetLab nodes, demonstrate that DONet achieves quite good streaming quality even under formidable network conditions. Moreover, its control overhead and transmission delay are both kept at low levels. An Internet-based DONet implementation, called CoolStreaming v.0.9, was released on May 30, 2004, which has attracted over 30000 distinct users with more than 4000 simultaneously being online at some peak times. We discuss the key issues toward designing CoolStreaming in this paper, and present several interesting observations from these large-scale tests; in particular, the larger the overlay size, the better the streaming quality it can deliver.


title: Efficient salient foreground detection for images and video using Fiedler vectors

abstract: Automatic detection of salient image regions is a useful tool with applications in intelligent camera control, virtual cinematography, video summarization and editing, evaluation of viewer preferences, and many others. This paper presents an effective method for detecting potentially salient foreground regions. Salient regions are identified by eigenvalue analysis of a graph Laplacian that is defined over the color similarity of image superpixels, under the assumption that the majority of pixels on the image boundary show non-salient background. In contrast to previous methods based on graph-cuts or graph partitioning, our method provides continuously-valued saliency estimates with complementary properties to recently proposed color contrast-based approaches. Moreover, exploiting discriminative properties of the Fiedler vector, we devise an SVM-based classifier that allows us to determine whether an image contains any salient objects at all, a problem that has been largely neglected in previous works. We also describe how the per-frame saliency detection can be extended to improve its spatiotemporal coherence when computed on video sequences. Extensive evaluation on several datasets demonstrates and validates the state-of-the-art performance of the proposed method.


title: Too interconnected to fail ’ financial network of US CDS market : opological fragility and systemic risk

abstract: A small segment of credit default swaps (CDS) on residential mortgage backed securities (RMBS) stand implicated in the 2007 financial crisis. The dominance of a few big players in the chains of insurance and reinsurance for CDS credit risk mitigation for banks’ assets has led to the idea of too interconnected to fail (TITF) resulting, as in the case of AIG, of a tax payer bailout. We provide an empirical reconstruction of the US CDS network based on the FDIC Call Reports for off balance sheet bank data for the 4th quarter in 2007 and 2008. The propagation of financial contagion in networks with dense clustering which reflects high concentration or localization of exposures between few participants will be identified as one that is TITF. Those that dominate in terms of network centrality and connectivity are called ‘super-spreaders’. Management of systemic risk from bank failure in uncorrelated random networks is different to those with clustering. As systemic risk of highly connected financial firms in the CDS (or any other) financial markets is not priced into their holding of capital and collateral, we design a super-spreader tax based on eigenvector centrality of the banks which can mitigate potential socialized losses.


title: 3D Reconstruction from Accidental Motion

abstract: We have discovered that 3D reconstruction can be achieved from asingle still photographic capture due to accidental motions of thephotographer, even while attempting to hold the camera still. Although these motions result in little baseline and therefore high depth uncertainty, in theory, we can combine many such measurements over the duration of the capture process (a few seconds) to achieve usable depth estimates. Wepresent a novel 3D reconstruction system tailored for this problemthat produces depth maps from short video sequences from standard cameraswithout the need for multi-lens optics, active sensors, or intentionalmotions by the photographer. This result leads to the possibilitythat depth maps of sufficient quality for RGB-D photography applications likeperspective change, simulated aperture, and object segmentation, cancome "for free" for a significant fraction of still photographsunder reasonable conditions.


title: Relaxation-based harmonic balance technique for semiconductor device simulation

abstract: Harmonic and intermodulation distortion effects play an important role in numerous analog applications, particularly in such areas as wireless communication systems. In this paper, we present a two-dimensional harmonic balance semiconductor device simulator which accurately models these nonlinear effects at the physical (drift-diffusion) level. The simulator is based on Stanford University's PISCES code, and supports the full range of physical models and features present in the time-domain version of the program. A modified block Gauss-Seidel-Newton nonlinear relaxation scheme is developed to efficiently handle the extremely large size of two-dimensional harmonic balance semiconductor device simulation problems.


title: Developing and validating an instrument for measuring user-perceived web quality

abstract: Many of the instruments to measure information and system quality were developed in the context of mainframe and PC-based technologies of yesteryears. With the proliferation of the Internet and World Wide Web applications, users are increasingly interfacing and interacting with web-based applications. It is, therefore, important to develop new instruments and scales, which are directly targeted to these new interfaces and applications. In this article, we report on the development of an instrument that captures key characteristics of web site quality from the user's perspective. The 25-item instrument measures four dimensions of web quality: specific content, content quality, appearance and technical adequacy. While improvements are possible, the instrument exhibits excellent psychometric properties. The instrument would be useful to organizations and web designers as it provides an aggregate measure of web quality, and to researchers in related web research.