title: OpenCL-based hardware-software co-design methodology for image processing implementation on heterogeneous FPGA platform

abstract: Recently, the OpenCL hardware-software co-design methodology has gained traction in realizing effective parallel architecture designs in heterogeneous FPGA platforms. In fact, the portability of OpenCL on hardware ready platforms such as GPU or multicore CPU enables ease of design verification. This is true especially for parallel algorithms before implementing them using cumbersome HDL-based RTL design. In this paper we employed OpenCL programming platform based on Altera SDK for OpenCL (AOCL) to implement a Sobel filter algorithm as an image processing test case on a Cyclone V FPGA board. Using the portability of this platform, the performance of the kernel code is benchmarked against that of the GPU and multicore CPU implementations for different image and kernel sizes. Different optimization strategies are also applied for each platform. We found that increasing the Sobel filter kernel size from 3×3 to 5×5 results in only 11.3% increase in computation time for FPGA, while the effect was much more significant where the execution time was as high as 23.6% and 85.7% for CPU and GPU, respectively.


B-1 Photogrammetry and Laser Scanning for Archaeological Site 3D Modeling- Some Critical Issues


title: A Newton root-finding algorithm for estimating the regularization parameter for solving ill-conditioned least squares problems

abstract: We discuss the solution of numerically ill-posed overdetermined systems of equations using Tikhonov a priori based regularization. When the noise distribution on the measured data is available to appropriately weight the fidelity term, and the regularization is assumed to be weighted by inverse covariance information on the model parameters, the underlying cost functional becomes a random variable that follows a χ2 distribution. The regularization parameter can then be found so that the optimal cost functional has this property. Under this premise a scalar Newton root-finding algorithm for obtaining the regularization parameter is presented. The algorithm, which uses the singular value decomposition of the system matrix, is found to be very efficient for parameter estimation, requiring on average about 10 Newton steps. Additionally, the theory and algorithm apply for generalized Tikhonov regularization using the generalized singular value decomposition. The performance of the Newton algorithm is contrasted to standard techniques, including the L-curve, generalized cross validation and unbiased predictive risk estimation. This χ2-curve Newton method of parameter estimation is seen to be robust and cost effective in comparison to other methods, when white or colored noise information on the measured data is incorporated.


title: Regularized Cost-Model Oblivious Database Tuning with Reinforcement Learning

abstract: In this paper, we propose a learning approach to adaptive performance tuning of database applications. The objective is to validate the opportunity to devise a tuning strategy that does not need prior knowledge of a cost model. Instead, the cost model is learned through reinforcement learning. We instantiate our approach to the use case of index tuning. We model the execution of queries and updates as a Markov decision process whose states are database configurations, actions are configuration changes, and rewards are functions of the cost of configuration change and query and update evaluation. During the reinforcement learning process, we face two important challenges: the unavailability of a cost model and the size of the state space. To address the former, we iteratively learn the cost model, in a principled manner, using regularization to avoid overfitting. To address the latter, we devise strategies to prune the state space, both in the general case and for the use case of index tuning. We empirically and comparatively evaluate our approach on a standard OLTP dataset. We show that our approach is competitive with state-of-the-art adaptive index tuning, which is dependent on a cost model.


title: RFID Systems: A Survey on Security Threats and Proposed Solutions

abstract: Low-cost Radio Frequency Identification (RFID) tags affixed to consumer items as smart labels are emerging as one of the most pervasive computing technology in history. This can have huge security implications. The present article surveys the most important technical security challenges of RFID systems. We first provide a brief summary of the most relevant standards related to this technology. Next, we present an overview about the state of the art on RFID security, addressing both the functional aspects and the security risks and threats associated to its use. Finally, we analyze the main security solutions proposed until date.


title: MEMS tri-axial force sensor with an integrated mechanical stopper for guidewire applications

abstract: This paper describes the design and characterization of a micro-electro-mechanical systems tri-axial force sensor that can be mounted on the tip of an 1-French guidewire (0.014ź). Piezoresistive silicon nanowires (SiNWs) are embedded into four beams forming a cross-shape to allow the detection of forces in three axes. The electrical resistance changes in the four SiNWs are used to decode arbitrary force applied onto the force sensor. Finite element analysis was used in the structural design of the force sensor. Robustness of the force sensor is improved due to the novel design of incorporating a mechanical stopper on the tip of the stylus. Flip chip bonding, using gold stud bumps, is used to mount the force sensor on a substrate for characterization and to simplify the assembly process. The sensor is robust enough to withstand normal forces higher than 20 gf. The proposed sensor can be used for new medical applications in vascular interventions and robotic surgeries.


title: Improving ATM security via face recognition

abstract: A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source. Proposed paper uses face recognition technique for verification in ATM system. For face recognition, there are two types of comparisons. The first is verification, this is where the system compares the given individual with who that individual says they are and gives a yes or no decision. The next one is identification this is where the system compares the given individual to all the other individuals in the database and gives a ranked list of matches. Face recognition technology analyzes the unique shape, pattern and positioning of the facial features. Face recognition is very complex technology and is largely software based. This Biometric Methodology establishes the analysis framework with PCA algorithms for each type of biometric device. Face recognition starts with a picture, attempting to find a person in the image. This can be accomplished using several methods including movement, skin tones, or blurred human shapes.


Hierarchical Recurrent Neural Network for Story Segmentation


title: Principles of Optimal Page Replacement

abstract: ABSTP~CT. A formal model is presented for paging algorithms under /-order nonstationary assumptions about program behavior. When processing a program under paging in a given memory, a given paging policy generates a certain (expected) number of page calls, i.e., its "cost." Under usual assumptions about memory system organization, minimum cost is always achieved by a demand paging algorithm. The minimum cost for /-order program behavior assumptions is expressed as a dynamic programming problem whose solution yields an optimal replacement algorithm. Solutions are exhibited in several 0-order cases of interest. Paging algorithms that implement and approximate the minimum cost are discussed.


title: Recognition of cursive Roman handwriting: past, present and future

abstract: This paper reviews the state of the art in off-line Roman cursive handwriting recognition. The input provided to an off-line handwriting recognition system is an image of a digit, a word, or - more generally -some text, and the system produces, as output, an ASCII transcription of the input. This task involves a number of processing steps, some of which are quite difficult. Typically, preprocessing, normalization, feature extraction, classification, and postprocessing operations are required. We'll survey the state of the art, analyze recent trends, and try to identify challenges for future research in this field.


title: Why Are Adolescents Addicted to Online Gaming? An Interview Study in Taiwan

abstract: The purpose of this study was twofold: to investigate the conscious and unconscious psychological motivations of online game addicts, and to further discuss the relationship between surface and source motivations. Ten Taiwanese adolescents with online game addiction were selected for in-depth interviews. Through sentence completion test and semi-structured interviews, data were collected and analyzed from the following four realms: (1) surface motivations, (2) source motivations, (3) self-conception, and (4) interpersonal relationships in real life. After content analysis, five categories with distinct themes were formed: (1) addicts' psychological needs and motivations; (2) online games as the everyday focus of the addicts; (3) the interplay of real self and virtual self; (4) online games as the compensatory or extensive satisfaction for addicts' needs; and (5) addicts' self-reflections. The implications of the present study are discussed.


title: Tissue-engineered heart valves.

abstract: Currently-used mechanical and biological heart valve prostheses have several disadvantages. Mechanical prostheses, based on carbon, metallic and polymeric components, require permanent anticoagulation treatment, and their usage often leads to adverse reactions, e.g. thromboembolic complications and endocarditis. Xenogenous and allogenous biological prostheses are associated with immune reaction, thrombosis and degeneration, and thus they have a high rate of reoperation. Biological prostheses of autologous origin, such as pulmonary autografts, often burden the patient with a complicated surgery and the risk of reoperation. Therefore, efforts are being made to prepare bioartificial heart valves with an autologous biological component by methods of tissue engineering. They should be biocompatible, durable, endowed with appropriate mechanical properties and able to grow with a child. For this purpose, scaffolds composed of synthetic materials, such as poly(lactic acid), poly(caprolactone), poly(4-hydroxybutyrate), hydrogels or natural polymers, e.g. collagen, elastin, fibrin or hyaluronic acid, have been seeded with autologous differentiated, progenitor or stem cells. Promising results have been obtained with nanostructured scaffolds, and also with cultivation in special dynamic bioreactors prior to implantation of the bioartificial grafts into an animal organism.


title: Local Anchor Schemes for Seamless and Low-Cost Handover in Coordinated Small Cells

abstract: Cellular systems are rapidly evolving from a homogeneous macrocell deployment to a heterogeneous deployment of macrocells overlaid with many small cells. The striking features of small cells include small coverage area, ad-hoc deployment, and flexible backhaul connectivity. These features call for a profound rethinking of traditional cellular concepts including mobility management and interference management among others. Owing to the unique features, coordinated small cells or commonly referred to as network of small cells promises several benefits including efficient mobility management in a rapid and scalable fashion. The problem of handover in a high-density small cell deployment is studied in this work. A novel local anchor-based architecture for a static cluster of small cells is proposed using which new handover schemes are presented. Such clusters are prevalent in the evolving cellular systems involving high-density small cell deployments in urban, residential, and enterprise environments. A mathematical framework is developed using discrete-time-Markov-models to evaluate the proposed schemes. Using this, closed-form expressions for key handover metrics including handover cost and interruption time are derived. Extensive numerical and simulation studies indicate significant savings of over 50 percent in the handover costs and, more importantly, up to 80 percent in the handover interruption time compared to the existing 3GPP scheme for coordinated small cells.


title: A Survey of Software-Defined Networking: Past, Present, and Future of Programmable Networks

abstract: The idea of programmable networks has recently re-gained considerable momentum due to the emergence of the Software-Defined Networking (SDN) paradigm. SDN, often referred to as a "radical new idea in networking", promises to dramatically simplify network management and enable innovation through network programmability. This paper surveys the state-of-the-art in programmable networks with an emphasis on SDN. We provide a historic perspective of programmable networks from early ideas to recent developments. Then we present the SDN architecture and the OpenFlow standard in particular, discuss current alternatives for implementation and testing of SDN-based protocols and services, examine current and future SDN applications, and explore promising research directions based on the SDN paradigm.


title: Secure Routing Protocols: Theory and Practice*

abstract: Most routing protocols are only designed to deal with simple network failures (e.g., links going up and down, nodes crashing and restarting etc.), and thus can have many vulnerabilities when facing a strategically placed intruder. The paper identifies these threats to routing protocols based on a unified routing framework, with focus on the information flow inside/ outside a router. Real world attacking examples are given to illustrate the argument. Further, we review a few common security techniques and their pros and cons. Finally, we explore the rationales behind securing routing protocols and conclude with our remarks and summary.


title: Master in Education Student Attitudes towards Research: A Comparison between two Public Sector Universities in Punjab

abstract: ABSTRACTIn modern world, attitudes of people are considered more important than their experiences and academic preparation. A positive attitude towards research is a key to success and progress in the knowledge based societies. This study explored the student teacher attitudes towards research. The sample consisted of 194 participants from two public universities of Pakistan and it was taken by using census sampling technique. The participants were Master in Education students in their second semester. The Attitude towards Research scale was used for data collection. The scale was consisted of 30 items which were divided into five factors: research usefulness, research anxiety, positive attitudes, relevance to life, and research difficulties. The data was analyzed using descriptive statistics, t-test and ANOVA. The results showed that student teachers have a negative attitude towards research. A significant difference was found in the attitudes with respect to the type of program and prior areas of specialization. The paper demonstrates a clear need for focus on research into student teacher attitudes towards research. Low student teacher attitudes have negative impact on the pupils. The ability of teacher education programs to alleviate the problem has wide-spread implications. The paper produces empirical evidence about the low student teacher attitudes towards research and raises questions relevant to teacher preparation role of the teacher education programs in developing higher attitudes towards research.KEY WORDS: Research Attitude, Student Teacher, attitudes toward research, knowledge based societies, teacher education.IntroductionTraditionally, teaching has been characterized by the acts that involve various activities that help younger people to learn (Szucs, 2009). It involves planning and delivering lessons, marking class and home work, and examining students' progress. Teachers, traditionally, were not expected to undertake research in order to explore the problems that they would face in the process of teaching and learning. They have been relying on the experts from other fields such as psychologists, philosophers, mathematicians and scientists for the solutions to their problems. This is evident from the fact that there has been a substantial contribution, to the field of teaching and learning, from the people who were not trained as educationists (Polya, Thorndike, 1910).There has been a shiftin the role of teachers (Scheirer, 2000) and now they are expected to explore the solution, by themselves, to their immediate classroom problems through action research. They are also expected to involve in scientific investigations through rigorous research methods (Peterson, Clark & Dickson, 1990). Zeuli (1992) stated that "research of various types forms the bulwark of teachers' professional preparation". He further said that reading research is imperative for learning to teach. It gives future teachers a vision about the practical implications of different approaches, their validity, rationale for decision making, targeting problems and brining improvements, etc. (The importance of research for education's future, 2011).That is why initial teacher training program has been added courses on research methods and trainee teachers are also expected to culminate their program with a research project.In Pakistan, at Master in Education (MEd), which is an advanced teacher preparation level, the trainee teachers are required to write a thesis on a topic of some educational importance. The students in the MEd program are comprised of in-service teachers and also those who do not have any teaching experience. People are inspired to join MEd program due to a variety of reasons that may include rapid progression in the carrier, advancement in the pedagogical research knowledge and skills, and better status in the society. Majority of the MEd students are naive to carry out a research project. …


Detering Dishonest Behaviour in Private Information Retrieval


title: Identification of a novel mutation in a Chinese family with Nance-Horan syndrome by whole exome sequencing

abstract: OBJECTIVE ::: Nance-Horan syndrome (NHS) is a rare X-linked disorder characterized by congenital nuclear cataracts, dental anomalies, and craniofacial dysmorphisms. Mental retardation was present in about 30% of the reported cases. The purpose of this study was to investigate the genetic and clinical features of NHS in a Chinese family. ::: ::: ::: METHODS ::: Whole exome sequencing analysis was performed on DNA from an affected male to scan for candidate mutations on the X-chromosome. Sanger sequencing was used to verify these candidate mutations in the whole family. Clinical and ophthalmological examinations were performed on all members of the family. ::: ::: ::: RESULTS ::: A combination of exome sequencing and Sanger sequencing revealed a nonsense mutation c.322G>T (E108X) in exon 1 of NHS gene, co-segregating with the disease in the family. The nonsense mutation led to the conversion of glutamic acid to a stop codon (E108X), resulting in truncation of the NHS protein. Multiple sequence alignments showed that codon 108, where the mutation (c.322G>T) occurred, was located within a phylogenetically conserved region. The clinical features in all affected males and female carriers are described in detail. ::: ::: ::: CONCLUSIONS ::: We report a nonsense mutation c.322G>T (E108X) in a Chinese family with NHS. Our findings broaden the spectrum of NHS mutations and provide molecular insight into future NHS clinical genetic diagnosis.


title: Multi-region two-stream R-CNN for action detection

abstract: We propose a multi-region two-stream R-CNN model for action detection in realistic videos. We start from frame-level action detection based on faster R-CNN [1], and make three contributions: (1) we show that a motion region proposal network generates high-quality proposals , which are complementary to those of an appearance region proposal network; (2) we show that stacking optical flow over several frames significantly improves frame-level action detection; and (3) we embed a multi-region scheme in the faster R-CNN model, which adds complementary information on body parts. We then link frame-level detections with the Viterbi algorithm, and temporally localize an action with the maximum subarray method. Experimental results on the UCF-Sports, J-HMDB and UCF101 action detection datasets show that our approach outperforms the state of the art with a significant margin in both frame-mAP and video-mAP.


title: B2VDM: Blockchain Based Vehicular Data Management

abstract: Smart interconnected vehicles generate a huge amount of data to be used by a wide range of applications. Although cloud based data management is currently in practice, for many applications serving road safety or traffic regulation, it is utmost important that applications access these data at the site itself for improved quality of service. Road side units (RSUs) play a crucial role in handling these vast amount of vehicular data and serving the running applications in turn. In this current era of edge computing, in-place data access is also proven to be advantageous from cost point of view. As multiple applications from different service providers are interested to access different fragments of these data, a robust access control mechanism is needed to ensure desired level of security as well as reliability for these data. In this paper, we introduce B2VDM, a novel architecture for vehicular data management at RSUs, that provides a seamless access control using Blockchain technology. The proposed B2VDM framework also implements a simple load distribution module, which maintains the reliability by minimizing the number of packet drops at a heavily loaded RSU during peak hours. An extensive evaluation using Etherium Blockchain validates the effectiveness of the proposed architecture.


title: Unsupervised Visual Domain Adaptation Using Subspace Alignment

abstract: In this paper, we introduce a new domain adaptation (DA) algorithm where the source and target domains are represented by subspaces described by eigenvectors. In this context, our method seeks a domain adaptation solution by learning a mapping function which aligns the source subspace with the target one. We show that the solution of the corresponding optimization problem can be obtained in a simple closed form, leading to an extremely fast algorithm. We use a theoretical result to tune the unique hyper parameter corresponding to the size of the subspaces. We run our method on various datasets and show that, despite its intrinsic simplicity, it outperforms state of the art DA methods.


title: What older people want from emergency care: a systematic review

abstract: Objectives To evaluate the expectations and preferred outcomes from emergency care among older people or their caregivers. Methods A review protocol was registered. Medline, Embase, CINAHL, PsychInfo, BNI, AgeInfo and the Cochrane Database of Systematic Reviews were searched in their full date ranges to September 2018. Included articles were hand-searched for further citations. Citations were screened for (1) older people aged over 65 years, (2) ED settings and (3) reporting expectations or preferred outcomes for emergency care (as opposed to experience or satisfaction). Quality appraisal and data extraction of eligible articles were undertaken by two reviewers. Themes were synthesised through content analysis and described narratively. Results Older people wished to have prompt waiting times, efficient care, clear communication and comfortable environments. They had additional and unique expectations for holistic care and support in decision-making. The ED provoked a sense of vulnerability among older people who were likely to have had frailty. Conclusion The lack of dominant themes among included studies suggests that older people should be treated as individuals rather than a homogenous group. Establishing individuals’ preferred outcomes could improve person-centred care. PROSPERO registration number CRD42018107050.


A framework for sensitivity analysis of decision trees


MicroRNA-3646 Contributes to Docetaxel Resistance in Human Breast Cancer Cells by GSK-3β/β-Catenin Signaling Pathway


title: Low-operable and Low-ppm H 2 S Gas Sensing Performance of Nanocrystalline WO 3 Thin Films

abstract: Nanocrystalline WO 3 thin films were prepared by spray pyrolysis technique onto heated glass substrates with different thickness by varying spray deposition time of the solution. The structural, surface morphology, microstructural, electrical properties and gas sensing performance of the WO 3 thin films were studied on exposure of various conventional gases. As prepared thin films were characterized by employing XRD, FE-SEM, TEM and EDAX to know crystal structure, surface morphology, microstructure properties and elemental composition respectively. The crystallographic structure of the films was studied by X-ray diffraction (XRD) with crystallite size found to be 16 nm. It is found that the films are hexagonal with (110) orientation. The film was observed to be most sensitive (S = 789) to H 2 S at 50 °C. Furthermore, the H 2 S sensor reported is cost-effective, user friendly and easy to fabricate. The quick response (6 s) and fast recovery (13 s) are the main features of this sensor.


title: Social anxiety and technology: Face-to-face communication versus technological communication among teens

abstract: This study examined teens' use of socially interactive technologies (SITs), such as online social sites, cell phones/text messaging, and instant messaging (IM), and the role that social anxiety plays on how teens communicate with others (technologically or face-to-face). Participants included 280 high school students from a large western city. On average, 35-40% of teens reported using cell phones/text messaging and online social sites between 1 and 4h daily, 24% reported using IMs 1-4h daily and only 8% reported using email between 1 and 4h daily. Females tended to use cell phones/text messaging and online social sites more so than did males. In assessing social anxiety, analyses revealed a positive relationship between social anxiety (not comfortable talking with others face-to-face) and (1) talking with others online and (2) talking with others via text messaging. In contrast, there was a positive relationship between the lack of social anxiety (feeling ''comfortable'' talking with others) and making friends online. Assessing gender differences and social anxiety also revealed significant differences. Results revealed females reported more social anxiety (not comfortable talking with others in person) than did males. In addition, females, more than males, reported feeling more comfortable using SITs (text messaging and online social sites only) rather than talking with others face-to-face.


title: Lumbar Stabilization A Review of Core Concepts and Current Literature , Part 2

abstract: Lumbar-stabilization exercise programs have become increasingly popular as a treatment for low-back pain. In this article, we outline an evidence-based medicine approach to evaluating patients for a lumbar-stabilization program. We also discuss typical clinical components of this type of program and the rationale for including these particular features based on the medical literature.


title: High efficiency X-band class-E GaN MMIC high-power amplifiers

abstract: We have demonstrated 8.5–11.5 GHz class-E MMIC high-power amplifiers (HPAs) with a peak power-added-efficiency (PAE) of 61% and drain efficiency (DE) of 70% with an output power of 3.7 W in a continuous-mode operation. At 5 W output power, PAE and DE of 58% and 67% are measured, respectively, which implies MMIC power density of 5 W/mm at Vds = 30 V. The peak gain is 11 dB, with an associated gain of 9 dB at the peak PAE. At an output power of 9 W, DE and PAE of 59% and 51 % were measured, respectively. In order to improve the linearity, we have designed and simulated X-band class-E MMIC PAs similar to a Doherty configuration. The Doherty-based class-E amplifiers show an excellent cancellation of a third-order intermodulation product (IM3), which improved the simulated two-tone linearity C/IM3 to > 50 dBc.


title: Approximate capacity of a class of partially connected interference channels

abstract: We derive inner and outer bounds on the capacity region for a class of three-user partially connected interference channels. We focus on the impact of topology, interference alignment, and interplay between interference and noise. The representative channels we consider are the ones that have clear interference alignment gain. For these channels, Z-channel type outer bounds are tight to within a constant gap from capacity. We present near-optimal achievable schemes based on rate-splitting and lattice alignment.


title: Conceptual design of a novel variable stiffness actuator for use in lower limb exoskeletons

abstract: A novel modular variable stiffness actuator (VSA), for use in the knee joint of lower limb exoskeletons, is presented. The actuator consists of a combination of a spindle-driven MACCEPA (Mechanically Adjustable Compliance and Controllable Equilibrium Position Actuator) and a spring acting in parallel, (dis)engaged by means of a simple on/off mechanism depending on the phase of the gait cycle. Such design approach is inspired by two clearly distinctive gait phases of a knee joint, one with a high velocity and low torque, and another one with low velocity and high torque profiles. By tackling each of these two phases separately, energy consumption and torque requirements of an active part of the actuator have been decreased, while keeping the size and the weight of the actuator at a reasonable size for use in wearable robots (WR).


title: Deficiency of Asparagine Synthetase Causes Congenital Microcephaly and a Progressive Form of Encephalopathy

abstract: Summary We analyzed four families that presented with a similar condition characterized by congenital microcephaly, intellectual disability, progressive cerebral atrophy, and intractable seizures. We show that recessive mutations in the ASNS gene are responsible for this syndrome. Two of the identified missense mutations dramatically reduce ASNS protein abundance, suggesting that the mutations cause loss of function. Hypomorphic Asns mutant mice have structural brain abnormalities, including enlarged ventricles and reduced cortical thickness, and show deficits in learning and memory mimicking aspects of the patient phenotype. ASNS encodes asparagine synthetase, which catalyzes the synthesis of asparagine from glutamine and aspartate. The neurological impairment resulting from ASNS deficiency may be explained by asparagine depletion in the brain or by accumulation of aspartate/glutamate leading to enhanced excitability and neuronal damage. Our study thus indicates that asparagine synthesis is essential for the development and function of the brain but not for that of other organs.


title: A Wideband Transmitarray Using Dual-Resonant Double Square Rings

abstract: A four-layer transmitarray operating at 30 GHz is designed using a dual-resonant double square ring as the unit cell element. The two resonances of the double ring are used to increase the per-layer phase variation while maintaining a wide transmission magnitude bandwidth of the unit cell. The design procedure for both the single-layer unit cell and the cascaded connection of four layers is described and it leads to a 50% increase in the -1 dB gain bandwidth over that of previous transmitarrays. Results of a 7.5% -1 dB gain bandwidth and 47% radiation efficiency are reported.


title: Combining strengths, emotions and polarities for boosting Twitter sentiment analysis

abstract: Twitter sentiment analysis or the task of automatically retrieving opinions from tweets has received an increasing interest from the web mining community. This is due to its importance in a wide range of fields such as business and politics. People express sentiments about specific topics or entities with different strengths and intensities, where these sentiments are strongly related to their personal feelings and emotions. A number of methods and lexical resources have been proposed to analyze sentiment from natural language texts, addressing different opinion dimensions. In this article, we propose an approach for boosting Twitter sentiment classification using different sentiment dimensions as meta-level features. We combine aspects such as opinion strength, emotion and polarity indicators, generated by existing sentiment analysis methods and resources. Our research shows that the combination of sentiment dimensions provides significant improvement in Twitter sentiment classification tasks such as polarity and subjectivity.


title: A realistic mechatronic system applied on the detection of optical information for CMOS-MEMS reflective micro grating

abstract: The study proposed a realistic mechatronic system to detect the optical information for CMOS-MEMS reflective micro grating. The different diffraction patterns with the various angles for the micro grating loaded on the stepping motor were exploited. Further the relationships between the diffraction patterns and resolving power with various elevation angles were investigated. For improving the image resolving power, the micro grating loaded on the shaft of stepping motor can be elevated to produce a different diffraction at the smallest stepping angle 3'23”. Through the comparison with theory and experimental results, NI LabVIEW and Vision Builder AI control an automation measurement system which is reliable and powerful for the micro grating optical information detection. A mechatronic system realistically demonstrated the high precision motion control performance for the micro device.


title: SWARD: System for weapon allocation research & development

abstract: The allocation of firing units to hostile targets is an important process within the air defense domain. Many algorithms have been proposed for solving various weapon allocation problems, but evaluation of the performance of such algorithms is problematic, since it does not exist any standard scenarios on which to test the algorithms. It is to a large extent unknown how weapon allocation algorithms compare to each other when it comes to solution quality. We have developed the testbed SWARD, making it possible to systematically compare algorithm performance, and to support the development of new weapon allocation algorithms.


title: A model of noise reduction using Gabor Kuwahara filter

abstract: Noise analysis of the image is the most important part in image processing. A filter is designed to improve the Kuwahara filter to reducing the noise. The Proposed Gabor Kuwahara filter is efficient to reduce the noise without losing the information on edges, before the preparation of the images for segmentation and other image processing techniques. This proposed noise reduction model is automated algorithm incorporated with Gabor transformation. The proposed model results the filtered image without blurring the edges and provides fine quality of images by reducing noise. The experimental results of MSE (Mean Square Error) and SSIM (Structural Similarity Index Measure) using the proposed model is compared with other state-of-art noise reduction method and provides many promising results.


title: Resistance of herpes simplex viruses to acyclovir: an update from a ten-year survey in France.

abstract: The widespread use of acyclovir (ACV) and the increasing number of immunocompromised patients have raised concern about an increase in ACV-resistant herpes simplex virus (HSV). ACV resistance has traditionally been a major concern for immunocompromised patients with a frequency reported between 2.5% and 10%. The aim of this study was to reassess the status of HSV resistance to ACV in immunocompetent and immunocompromised patients over a ten year period, between 2002 and 2011. This was done by retrospectively following 1425 patients. In immunocompetent patients, prevalence of resistance did not exceed 0.5% during the study period; whereas in immunocompromised patients, a significant increase was observed, rising from 3.8% between 2002 and 2006 (7/182 patients) to 15.7% between 2007 and 2011 (28/178) (p = 0.0001). This sharp rise in resistance may largely be represented by allogeneic hematopoietic stem cell transplant patients, in which the prevalence of ACV resistance rose similarly from 14.3% (4/28) between 2002 and 2006 to 46.5% (26/56) between 2007 and 2011 (p = 0.005). No increase in ACV resistance was detected in association with other types of immune deficiencies. Genotypic characterization of HSV UL23 thymidine kinase and UL30 DNA polymerase genes revealed 11 and 7 previously unreported substitutions, respectively. These substitutions may be related to potential polymorphisms, drug resistance, or other mutations of unclear significance.


title: A COMPARATIVE STUDY OF PROBLEMATIC INTERNET USE AND LONELINESS AMONG TURKISH AND KOREAN PROSPECTIVE TEACHERS

abstract: The main aim of this study is to compare the problematic internet use and its relation to loneliness among two nations’ prospective teachers, Turkey and South Korea. Five hundred and ninety five prospective teachers from three universities, two from Turkey and one from South Korea participated in the study. Generalized Problematic Internet Use Scale 2 and UCLA Loneliness Scale were used to collect data. Some of the major findings are as follows: a) No differences were found between the problematic Internet use of Turkish and Korean prospective teachers; b) Male Turkish prospective teachers found to have more problematic use of internet than female counterparts on the other hand no differences were found among South Korean prospective teachers by means of sex; c) Positive but low correlations between problematic Internet use and loneliness levels of prospective teachers of both nations; d) There is a significant difference between Turkish and Korean prospective teachers. South Korean prospective teachers were found to be in higher levels of loneliness than Turkish counterparts.


title: STEM Education

abstract: Improving science, technology, engineering, and mathematics (STEM) education, especially for traditionally disadvantaged groups, is widely recognized as pivotal to the U.S.'s long-term economic growth and security. In this article, we review and discuss current research on STEM education in the U.S., drawing on recent research in sociology and related fields. The reviewed literature shows that different social factors affect the two major components of STEM education attainment: (1) attainment of education in general, and (2) attainment of STEM education relative to non-STEM education conditional on educational attainment. Cognitive and social psychological characteristics matter for both major components, as do structural influences at the neighborhood, school, and broader cultural levels. However, while commonly used measures of socioeconomic status (SES) predict the attainment of general education, social psychological factors are more important influences on participation and achievement in STEM versus non-STEM education. Domestically, disparities by family SES, race, and gender persist in STEM education. Internationally, American students lag behind those in some countries with less economic resources. Explanations for group disparities within the U.S. and the mediocre international ranking of US student performance require more research, a task that is best accomplished through interdisciplinary approaches.


title: Toward millions of file system IOPS on low-cost, commodity hardware

abstract: We describe a storage system that removes I/O bottlenecks to achieve more than one million IOPS based on a user-space file abstraction for arrays of commodity SSDs. The file abstraction refactors I/O scheduling and placement for extreme parallelism and non-uniform memory and I/O. The system includes a set-associative, parallel page cache in the user space. We redesign page caching to eliminate CPU overhead and lock-contention in non-uniform memory architecture machines. We evaluate our design on a 32 core NUMA machine with four, eight-core processors. Experiments show that our design delivers 1.23 million 512-byte read IOPS. The page cache realizes the scalable IOPS of Linux asynchronous I/O (AIO) and increases user-perceived I/O performance linearly with cache hit rates. The parallel, set-associative cache matches the cache hit rates of the global Linux page cache under real workloads.


title: Improving Relation Extraction by Pre-trained Language Representations

abstract: Current state-of-the-art relation extraction methods typically rely on a set of lexical, syntactic, and semantic features, explicitly computed in a pre-processing step. Training feature extraction models requires additional annotated language resources, which severely restricts the applicability and portability of relation extraction to novel languages. Similarly, pre-processing introduces an additional source of error. To address these limitations, we introduce TRE, a Transformer for Relation Extraction, extending the OpenAI Generative Pre-trained Transformer [Radford et al., 2018]. Unlike previous relation extraction models, TRE uses pre-trained deep language representations instead of explicit linguistic features to inform the relation classification and combines it with the self-attentive Transformer architecture to effectively model long-range dependencies between entity mentions. TRE allows us to learn implicit linguistic features solely from plain text corpora by unsupervised pre-training, before fine-tuning the learned language representations on the relation extraction task. TRE obtains a new state-of-the-art result on the TACRED and SemEval 2010 Task 8 datasets, achieving a test F1 of 67.4 and 87.1, respectively. Furthermore, we observe a significant increase in sample efficiency. With only 20% of the training examples, TRE matches the performance of our baselines and our model trained from scratch on 100% of the TACRED dataset. We open-source our trained models, experiments, and source code.


title: Effect of changing slag composition on spinel inclusion dissolution

abstract: AbstractThe rate of MgAl2O4 spinel inclusion dissolution in CaO–SiO2–Al2O3 slags at 1504°C has been measured using a laser scanning confocal microscope. It was found that the mechanism of spinel inclusion dissolution was at least in part controlled by mass transfer in the slag phase for the slag compositions used. Evidence in support of this finding was that the calculated diffusion coefficient was inversely proportional to the slag viscosity and that the diffusion coefficients were in reasonable agreement with those obtained in a separate study on alumina dissolution. The diffusion coefficients obtained were in the range of 0·76–2·2 × 10−10 m2 s−1.


title: Tone recognition for Chinese speech: a comparative study of Mandarin and Cantonese

abstract: The paper presents a comparative study on automatic continuous tone recognition for Mandarin and Cantonese. Compared with Mandarin, Cantonese has a much more complex tone system. The effects of F/sub 0/ normalization on the tone recognition of Mandarin and Cantonese are studied. Furthermore, the two tone systems are compared from an engineering point of view. Tone recognition accuracies of 71.50% and 83.06% have been obtained for Cantonese and Mandarin respectively. These results compare favorably with results reported for other tone recognition experiments on the same (for Cantonese) and similar (for Mandarin) databases.


title: Dynamic trajectory planning of a two-DOF cable-suspended parallel robot

abstract: This paper presents a trajectory planning approach for cable-suspended parallel mechanisms. A planar two-degree-of-freedom parallel mechanism is used for the analysis. Based on the dynamic model of the suspended robot, a set of algebraic inequalities is obtained that represents the constraints on the cable tensions. Parametric Cartesian trajectories are then defined and substituted into the constraints in order to obtain global conditions on the trajectory parameters which ensure that the trajectories are feasible. Special frequencies arise from the equations that are akin to natural frequencies of pendulum-type systems. An experimental validation is also presented using a two-dof prototype. The proposed trajectory planning approach can be used to plan dynamic trajectories that go beyond the static workspace of the mechanism, thereby opening novel applications and possibilities for cable-suspended robots.


Self-Crowdsourcing Training for Relation Extraction


title: Many-objective optimization algorithm applied to history matching

abstract: Reservoir model calibration, called history matching in the petroleum industry, is an important task to make more accurate predictions for better reservoir management. Providing an ensemble of good matched reservoir models from history matching is essential to reproduce the observed production data from a field and to forecast reservoir performance. The nature of history matching is multi-objective because there are multiple match criteria or misfit from different production data, wells and regions in the field. In many cases, these criteria are conflicting and can be handled by the multi-objective approach. Moreover, multi-objective provides faster misfit convergence and more robust towards stochastic nature of optimization algorithms. However, reservoir history matching may feature far too many objectives that can be efficiently handled by conventional multi-objective algorithms, such as multi-objective particle swarm optimizer (MOPSO) and non-dominated sorting genetic algorithm II (NSGA II). Under an increasing number of objectives, the performance of multi-objective history matching by these algorithms deteriorates (lower match quality and slower misfit convergence). In this work, we introduce a recently proposed algorithm for many-objective optimization problem, known as reference vector-guided evolutionary algorithm (RVEA), to history matching. We apply the algorithm to history matching a synthetic reservoir model and a real field case study with more than three objectives. The paper demonstrates the superiority of the proposed RVEA to the state of the art multi-objective history matching algorithms, namely MOPSO and NSGA II.


title: From Ice to Music: The challenges of translating the sights and sounds of Antarctica into music

abstract: In January 2004 I journeyed to Antarctica as an Antarctica New Zealand Honorary Artist Fellow. My proposed study was entitled Sounds of Antarctica and entailed producing a portfolio of original compositions. The attraction of the planet’s last great wilderness for me was to a large degree the challenge of how one translates such a limited visual palette into sound. In this paper I will explore how an environment of sensory deprivation can influence and shape one’s work and how a creative artist can find a productive solution to the issue of transcribing such diverse elements as landscape, history, colour (or absence thereof ) and natural phenomena (such as wind) into a satisfying musical and poetic form. I conclude that through the study of this distant, frozen, inhospitable land, my creativity has paradoxically moved into a very fertile stage. It was not, as I first thought, the wide, majestic vistas that later fuelled my compositions but the play of light and the effects of a limited colour palette. Nevertheless, it is perhaps because of the wide horizons that I have been thinking horizontally in a linear fashion rather than vertically. The vastness of the panorama is also the reason for focusing on the small details close at hand.


title: Combining Facial Dynamics With Appearance for Age Estimation

abstract: Estimating the age of a human from the captured images of his/her face is a challenging problem. In general, the existing approaches to this problem use appearance features only. In this paper, we show that in addition to appearance information, facial dynamics can be leveraged in age estimation. We propose a method to extract and use dynamic features for age estimation, using a person's smile. Our approach is tested on a large, gender-balanced database with 400 subjects, with an age range between 8 and 76. In addition, we introduce a new database on posed disgust expressions with 324 subjects in the same age range, and evaluate the reliability of the proposed approach when used with another expression. State-of-the-art appearance-based age estimation methods from the literature are implemented as baseline. We demonstrate that for each of these methods, the addition of the proposed dynamic features results in statistically significant improvement. We further propose a novel hierarchical age estimation architecture based on adaptive age grouping. We test our approach extensively, including an exploration of spontaneous versus posed smile dynamics, and gender-specific age estimation. We show that using spontaneity information reduces the mean absolute error by up to 21%, advancing the state of the art for facial age estimation.


title: An End-of-Year Oral Examination for Internal Medicine Residents: An Assessment Tool for the Clinical Competency Committee.

abstract: Abstract Background Comprehensive evaluations of clinical competency consume a large amount of time and resources. An oral examination is a unique evaluation tool that can augment a global performa...


title: Treating Image Loss by using the Vision/Motion Link: A Generic Framework

abstract: Visual servoing techniques aim at controlling the robot motion using vision data provided by a camera to reach a desired goal defined in the image (Chaumette & Hutchinson, 2006). Therefore, if the considered features are lost because of an occlusion or any other unexpected event, the desired task cannot be realized anymore. The literature provides many works dealing with this problem. A first common solution is to use methods allowing to preserve the visual features visibility during the whole mission. Most of them are dedicated to manipulator arms, and propose to treat this kind of problem by using redundancy (Marchand & Hager, 1998; Mansard & Chaumette, 2005), path-planning (Mezouar & Chaumette, 2002), specific degrees of freedom (DOF) (Corke & Hutchinson, 2001; Kyrki et al., 2004), zoom (Benhimane & Malis, 2003) or even by making a tradeoff with the nominal vision-based task (Remazeilles et al., 2006). In a mobile robotics context, the realization of a vision-based navigation task in a given environment requires to preserve not only the image data visibility, but also the robot safety. In that case, techniques allowing to avoid simultaneously collisions and visual data losses such as (Folio & Cadenat, 2005a; Folio & Cadenat, 2005b) appear to be limited, because they are restricted to missions where an avoidance motion exists without leading to local minima (Folio, 2007). As many robotic tasks cannot be performed if the visual data loss is not tolerated, a true extension of these works would be to provide methods that accept that occlusions may effectively occur without leading to a task failure. A first step towards this objective is to let some of the features appear and disappear temporarily from the image as done in (Garcia-Aracil et al., 2005). However, this approach is limited to partial losses and does not entirely solve the problem. Therefore, in this work, our main goal is to propose a generic framework allowing to reconstruct the visual data when they suddenly become unavailable during the task execution (camera or image processing failure, landmark loss, and so on). Thus, this work relies on the following central assumption: the whole image is considered temporarily entirely unavailable. This problem can be addressed using different methods such as tracking or signal processing techniques. However, we have chosen here to develop another approach for several reasons, which will be detailed in the chapter. The proposed technique allows to reconstruct the visual features using the history of the camera motion and the last available features. It relies on the vision-motion link that is on the relation between the camera motion and the visual data evolution in the image. O pe n A cc es s D at ab as e w w w .ite ch on lin e. co m


title: A Differential Microstrip Antenna With Filtering Response

abstract: This letter presents a vertically integrated differential filtering antenna. This antenna consists of a differential-fed microstrip patch, a U-shaped differential resonator, and two pairs of quarter-wavelength J-inverters. All the elements are vertically integrated without increasing the dimensions. The traditional synthesis procedure of bandpass filters can be followed to design such a filtering antenna. One example with a second-order 0.2-dB equal-ripple response and the fractional bandwidth of 2.5% is designed and measured. The fabricated antenna exhibits a filter-like frequency response for both antenna gain and input return loss. It achieves an impedance bandwidth of 5% with the return loss better than 15 dB, and a gain of 6.85 dBi.


Self-Esteem and Academic Performance of freshmen at Karunya University


Expression of oestrogen receptor α and β in cultured human ovarian surface epithelial cells


The OWL-S Java API


title: Critical Realist HCI

abstract: Against the backdrop of the current debate about HCI's relationship with science and its ways to produce and argue for knowledge, this paper seeks to develop a novel philosophical foundation that rests on the central ideas put forward in critical realism. While it affords many of the features of the post-modern theories that shaped modern HCI, critical realism avoids the danger of slipping into extreme relativism, in which knowledge construction becomes arbitrary and isolated in its context. Moreover, critical realism is inherently multi-faceted and provides a basis on which scientific enquiries of very different natures can be treated complementary rather than as competing with each other. This allows us to develop a non-reductionist view on interaction with technology that accommodates and potentially reconciles the variety of approaches, practices and stances that we see in current HCI.


The Platformer Experience Dataset CONFERENCE


Language Modeling Teaches You More than Translation Does : Lessons Learned Through Auxiliary Task Analysis


title: Mobile crowdsensing with mobile agents

abstract: We introduce mobile agents for mobile crowdsensing. Crowdsensing campaigns are designed through different roles that are implemented as mobile agents. The role-based tasks of mobile agents include collecting data, analyzing data and sharing data in the campaign. Mobile agents execute and control the campaign autonomously as a multi-agent system and migrate in the opportunistic network of participants' devices. Mobile agents take into account the available resources in the devices and match participants' privacy requirements to the campaign requirements. Sharing of task results in real-time facilitates cooperation towards the campaign goal while maintaining a selected global measure, such as energy efficiency. We discuss current challenges in crowdsensing and propose mobile agent based solutions for campaign execution and monitoring, addressing data collection and participant-related issues. We present a software framework for mobile agents-based crowdsensing that is seamlessly integrated into the Web. A set of simulations are conducted to compare mobile agent-based campaigns with existing crowdsensing approaches. We implemented and evaluated a small-scale real-world mobile agent based campaign for pedestrian flock detection. The simulation and evaluation results show that mobile agent based campaigns produce comparable results with less energy consumption when the number of agents is relatively small and enables in-network data processing with sharing of data and task results with insignificant overhead.


title: Exception beyond Exception: Crashing Android System by Trapping in "Uncaught Exception"

abstract: Android is characterized as a complicated open source software stack created for a wide array of devices with different form of factors, whose latest release has over one hundred million lines of code. Such code is mainly developed with the Java language, which builds complicated logic and brings implicit information flows among components and the inner framework. By studying the source code of system service interfaces, we discovered an unknown type of code flaw, which is named uncaughtException flaw, caused by un-well implemented exceptions that could crash the system and be further vulnerable to system level Denial-of-Service (DoS) attacks. We found that exceptions are used to handle the errors and other exceptional events but sometimes they would kill some critical system services exceptionally. We designed and implemented ExHunter, a new tool for automatic detection of this uncaughtException flaw by dynamically reflecting service interfaces, continuously fuzzing parameters and verifying the running logs. On 11 new popular Android devices, ExHunter extracted 1045 system services, reflected 758 suspicious functions, discovered 132 uncaughtException flaws which are 0-day vulnerabilities that have never been known before and generated 275 system DoS attack exploitations. The results showed that: (1) almost every type of Android phone suffers from this flaw, (2) the flaws are different from phone by phone, and (3) all the vulnerabilities can be exploited by direct/indirect trapping. To mitigate uncaughtException flaws, we further developed ExCatcher to re-catch the exceptions. Finally, we informed four internationally renowned manufacturers and provided secure improvements in their commercial phones.


title: Total ADS: Automated Software Anomaly Detection System

abstract: When a software system starts behaving abnormally during normal operations, system administrators resort to the use of logs, execution traces, and system scanners (e.g., anti-malwares, intrusion detectors, etc.) to diagnose the cause of the anomaly. However, the unpredictable context in which the system runs and daily emergence of new software threats makes it extremely challenging to diagnose anomalies using current tools. Host-based anomaly detection techniques can facilitate the diagnosis of unknown anomalies but there is no common platform with the implementation of such techniques. In this paper, we propose an automated anomaly detection framework (Total ADS) that automatically trains different anomaly detection techniques on a normal trace stream from a software system, raise anomalous alarms on suspicious behaviour in streams of trace data, and uses visualization to facilitate the analysis of the cause of the anomalies. Total ADS is an extensible Eclipse-based open source framework that employs a common trace format to use different types of traces, a common interface to adapt to a variety of anomaly detection techniques (e.g., HMM, sequence matching, etc.). Our case study on a modern Linux server shows that Total ADS automatically detects attacks on the server, shows anomalous paths in traces, and provides forensic insights.


title: Two-Stage Pattern Recognition of Load Curves for Classification of Electricity Customers

abstract: This paper describes a two-stage methodology that was developed for the classification of electricity customers. It is based on pattern recognition methods, such as k-means, Kohonen adaptive vector quantization, fuzzy k-means, and hierarchical clustering, which are theoretically described and properly adapted. In the first stage, typical chronological load curves of various customers are estimated using pattern recognition methods, and their results are compared using six adequacy measures. In the second stage, classification of customers is performed by the same methods and measures, together with the representative load patterns of customers being obtained from the first stage. The results of the first stage can be used for load forecasting of customers and determination of tariffs. The results of the second stage provide valuable information for electricity suppliers in competitive energy markets. The developed methodology is applied on a set of medium voltage customers of the Greek power system, and the obtained results are presented and discussed.


title: A novel variable width PWM switching based buck converter to control power factor correction phenomenon for an efficacious grid integrated electric vehicle battery charger

abstract: This paper proposes an innovative approach to utilizing Buck converter as an ideal Power Factor Correction (PFC) controller where variable width Pulse Width Modulation (PWM) switching signals are generated and implemented to reliably control the voltage and current conversion phenomena. The developed converter topology is tactically utilized to design an efficacious grid-connected electric vehicle charger with substantially ameliorated line Power Factor so that the system loss can be averted in the case of AC-DC charging circuits. In order to ensure the sustainability of the proposed method, PSIM simulation software has been used to emulate a simulation model of a Battery charging system for Electric vehicles. The simulated output and evaluated performance parameters provide almost unity Power Factor (PF) with a Total Harmonic Distortion (THD) rate of 4.62% which is lower than the maximum allowable value recommended by IEEE519. The simulation outcome corroborates the efficiency and validity of the proposed framework.


Design of a Monitor for Detecting Money Laundering and Terrorist Financing


title: Data mining in manufacturing: a review based on the kind of knowledge

abstract: In modern manufacturing environments, vast amounts of data are collected in database management systems and data warehouses from all involved areas, including product and process design, assembly, materials planning, quality control, scheduling, maintenance, fault detection etc. Data mining has emerged as an important tool for knowledge acquisition from the manufacturing databases. This paper reviews the literature dealing with knowledge discovery and data mining applications in the broad domain of manufacturing with a special emphasis on the type of functions to be performed on the data. The major data mining functions to be performed include characterization and description, association, classification, prediction, clustering and evolution analysis. The papers reviewed have therefore been categorized in these five categories. It has been shown that there is a rapid growth in the application of data mining in the context of manufacturing processes and enterprises in the last 3 years. This review reveals the progressive applications and existing gaps identified in the context of data mining in manufacturing. A novel text mining approach has also been used on the abstracts and keywords of 150 papers to identify the research gaps and find the linkages between knowledge area, knowledge type and the applied data mining tools and techniques.


title: Exploring Online Game Players' Flow Experiences and Positive Affect.

abstract: The authors conducted two studies to explore online game players’ flow experiences and positive affect. Our findings indicated that online game are capable of evoking flow experiences and positive affect, and games of violent or nonviolent type may not arouse players’ aggression. The players could be placed into four flow conditions: flow, boredom, anxiety, and apathy, as determined by level of perceived challenges and skills. The majority of players entered the flow condition when playing violent or non-violent online game. The path analysis results suggested that violent online games may have a significant but indirect effect on positive affect via flow experience mediation.


Integration of Decision Support Systems and Data Mining for Improved Decision Making


title: Stress and Emotion Classification using Jitter and Shimmer Features

abstract: In this paper, we evaluate the use of appended jitter and shimmer speech features for the classification of human speaking styles and of animal vocalization arousal levels. Jitter and shimmer features are extracted from the fundamental frequency contour and added to baseline spectral features, specifically Mel-frequency cepstral coefficients (MFCCs) for human speech and Greenwood function cepstral coefficients (GFCCs) for animal vocalizations. Hidden Markov models (HMMs) with Gaussian mixture models (GMMs) state distributions are used for classification. The appended jitter and shimmer features result in an increase in classification accuracy for several illustrative datasets, including the SUSAS dataset for human speaking styles as well as vocalizations labeled by arousal level for African elephant and Rhesus monkey species.


title: An Open-Source Natural Language Generator for OWL Ontologies and its Use in Protege and Second Life

abstract: We demonstrate an open-source natural language generation engine that produces descriptions of entities and classes in English and Greek from OWL ontologies that have been annotated with linguistic and user modeling information expressed in RDF. We also demonstrate an accompanying plug-in for the Protege ontology editor, which can be used to create the ontology's annotations and generate previews of the resulting texts by invoking the generation engine. The engine has been embedded in robots acting as museum tour guides in the physical world and in Second Life; here we demonstrate the latter application.


title: Multilingual Open Information Extraction

abstract: Open Information Extraction (OIE) is a recent unsupervised strategy to extract great amounts of basic propositions (verb-based triples) from massive text corpora which scales to Web-size document collections. We propose a multilingual rule-based OIE method that takes as input dependency parses in the CoNLL-X format, identifies argument structures within the dependency parses, and extracts a set of basic propositions from each argument structure. Our method requires no training data and, according to experimental studies, obtains higher recall and higher precision than existing approaches relying on training data. Experiments were performed in three languages: English, Portuguese, and Spanish.


title: Analysis and simulation of a fair queueing algorithm

abstract: We discuss gateway queueing algorithms and their role in controlling congestion in datagram networks. A fair queueing algorithm, based on an earlier suggestion by Nagle, is proposed. Analysis and simulations are used to compare this algorithm to other congestion control schemes. We find that fair queueing provides several important advantages over the usual first-come-first-serve queueing algorithm: fair allocation of bandwidth, lower delay for sources using less than their full share of bandwidth, and protection from ill-behaved sources.


title: The Impact of Product Quality on Perceived Value, Trust and Students’ Intention to Purchase Electronic Gadgets

abstract: Increasing attention on the role played by product quality on desirable customer behavioural outcomes has been empirically examined over the past decades. Nevertheless, there are significant issues yet to be addressed and resolved, one of which relates to the influences of the quality of electronic gadgets on students’ perceived value, trust and their intention to purchase. In view of this research gap, five posited hypotheses are empirically tested using a sample of 151 in South Africa. The results supports all the posited hypotheses except hypothesis four which although positive as postulated, is insignificant. Managerial implications of the findings are discussed and limitations and future research directions are indicated. DOI: 10.5901/mjss.2013.v4n14p463


title: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93673 Medical Image Processing on the GPU Past, Present and Future

abstract: Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, histogram estimation and distance transforms), the most commonly used algorithms in medical imaging (image registration, image segmentation and image denoising) and algorithms that are specific to individual modalities (CT, PET, SPECT, MRI, fMRI, DTI, ultrasound, optical imaging and microscopy). The review ends by highlighting some future possibilities and challenges.


title: And the winner is …: Bayesian Twitter-based prediction on 2016 U.S. presidential election

abstract: This paper describes a Naive Bayesian predictive model for 2016 U.S. Presidential Election based on Twitter data. We use 33,708 tweets gathered since December 16, 2015 until February 29, 2016. We propose a simple way for data preprocessing which can still achieve 95.8% accuracy on predicting sentiments. The predicted sentiments are used to forecast the U.S. Republican and Democratic parties candidacies. The forecast is compared to the poll collected from RealClearPolitics.com with 26.7% accuracy. However, the true forecasting capacity of the method still have to be observed after the election process come to conclusion.


Distributed Relational Database Performance In Cloud Computing: An Investigative Study


title: Link-based Classification

abstract: A key challenge for machine learning is tackling the problem of mining richly structured data sets, where the objects are linked in some way due to either an explicit or implicit relationship that exists between the objects. Links among the objects demonstrate certain patterns, which can be helpful for many machine learning tasks and are usually hard to capture with traditional statistical models. Recently there has been a surge of interest in this area, fueled largely by interest in web and hypertext mining, but also by interest in mining social networks, bibliographic citation data, epidemiological data and other domains best described using a linked or graph structure. In this paper we propose a framework for modeling link distributions, a link-based model that supports discriminative models describing both the link distributions and the attributes of linked objects. We use a structured logistic regression model, capturing both content and links. We systematically evaluate several variants of our link-based model on a range of data sets including both web and citation collections. In all cases, the use of the link distribution improves classification accuracy.


title: Towards a Neurocognitive Model of Turntaking in Multimodal Dialog

abstract: © Oxford University Press, 2008. All rights reserved. This chapter discusses hierarchically organised actions in communication. One essential, but often overlooked, feature of natural dialogue is turn taking. More recently, turn taking has become an issue in robot and virtual human research as researchers aim to make these systems more fluent and dynamic when interacting naturally with humans. The most promising way to understand turn taking is to develop a model, preferably in ways that it can be tested in interaction with real humans. This chapter describes a hybrid model that integrates features of the Ymir Turn Taking Model and Augmented Competitive Queuing by expanding key cognitive components of the former with neural mechanisms from the latter. The model is able to learn turn taking with little or no overlap in speech and to learn social turn taking cues.


title: Functional neuroimaging and episodic memory: a perspective.

abstract: One area of research that has significantly benefited from the recent development of functional neuroimaging techniques is the study of memory. In this review we explore what has been learned about the neural basis of normal memory function using these techniques. We focus on episodic memory, which is characterized by the ability to consciously recollect memories for facts or events. We highlight three neuroanatomical regions that have been linked to episodic memory: The hippocampal complex, the prefrontal cortex and the amygdala. For each of these regions, we discuss the behavioral methods of assessment and specific episodic memory processes, particularly encoding and retrieval. Finally, we briefly comment on the potential clinical applications for this research and other memory systems.


title: Quality and reliability of oxide by low thermal budget rapid thermal oxidation

abstract: In order to meet increasing requirement for low thermal budget oxidation in memory and logic applications, RadOx™, previously known as in-situ steam generation (ISSG) oxidation, processes of low thermal budgets were developed. In this paper, oxides obtained by 700°C soak and 900–1050°C spike RadOx™ processes are presented. Sidewall growth behavior in STI-type structures were characterized and showed no bird’s beak encroachment by the developed oxidation processes. Basic bulk oxide (40A) integrity and reliability characteristics were compared to the 1050°C soak RadOx™ reference. Using planar metal-on-semiconductor (MOS) capacitors as the test vehicles, flat-band voltage (V fb ), interface trap density (D it ), leakage current, and stress-induced leakage current (SILC) were measured. V fb shift of less than 20mV and D it less than 2×1011/cm2 were observed from the low temperature soak and spike oxides. Leakage currents from fresh devices and after high current stressing (0.1A/cm2) were comparable to the reference oxide.


title: Wideband and low-profile end-fire antennas mountable on metallic platforms

abstract: This paper introduces three types of wideband and low-profile end-fire antennas, which include an H-plane ridged substrate integrated waveguide (SIW) horn antenna, a surface wave antenna, and a log-periodic top-hat monopole antenna. They can achieve the bandwidths of 93%, 100%, and 125% while retaining the antenna thicknesses of 0.13λ0, 0.12λ0, and 0.127λ0 at the center frequency, respectively. These wideband and low-profile antennas are conductor-backed, and can obtain nearly end-fire radiation beams over the entire bandwidths, which are potentially useful to be surface-mounted in airborne communication systems.


title: Case consistency: a necessary data quality property for software engineering data sets

abstract: Data quality is an essential aspect in any empirical study, because the validity of models and/or analysis results derived from an empirical data is inherently influenced by its quality. In this empirical study, we focus on data consistency as a critical factor influencing the accuracy of prediction models in software engineering. We propose a software metric called Cases Inconsistency Level (CIL) for analyzing conflicts within software engineering data sets by leveraging probability statistics on project cases and counting the number of conflicting pairs. The result demonstrated that CIL is able to be used as a metric to identify either consistent data sets or inconsistent data sets, which are valuable for building robust prediction models. In addition to measuring the level of consistency, CIL is proved to be applicable to predict whether or not an effort model built from data set can achieve higher accuracy, an important indicator for empirical experiments in software engineering.


title: Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition

abstract: Motion representation plays a vital role in human action recognition in videos. In this study, we introduce a novel compact motion representation for video action recognition, named Optical Flow guided Feature (OFF), which enables the network to distill temporal information through a fast and robust approach. The OFF is derived from the definition of optical flow and is orthogonal to the optical flow. The derivation also provides theoretical support for using the difference between two frames. By directly calculating pixel-wise spatiotemporal gradients of the deep feature maps, the OFF could be embedded in any existing CNN based video action recognition framework with only a slight additional cost. It enables the CNN to extract spatiotemporal information, especially the temporal information between frames simultaneously. This simple but powerful idea is validated by experimental results. The network with OFF fed only by RGB inputs achieves a competitive accuracy of 93.3% on UCF-101, which is comparable with the result obtained by two streams (RGB and optical flow), but is 15 times faster in speed. Experimental results also show that OFF is complementary to other motion modalities such as optical flow. When the proposed method is plugged into the state-of-the-art video action recognition framework, it has 96:0% and 74:2% accuracy on UCF-101 and HMDB-51 respectively. The code for this project is available at this https URL.


title: Motivation and Work Behavior

abstract: Part One: Initial Considerations Chapter 1: Motivation in Organizations Mitchell, Terence R., and Daniels, Denise. Observation and Commentary on Recent Research in Work Motivation. Chapter 2: Conceptual Approaches to Motivation at Work Ryan, Richard M., and Deci, Edward L. 2000. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1): 68-78. Mowday, Richard, and Colwell, Kenneth A. Employee reactions to unfair outcomes in the workplace: The contributions of Adams' equity theory to understanding work motivation. Cropanzano, Russell, and Rupp, Deborah. An overview of organizational justice: Implications for work motivation. Komaki, Judith. Reinforcement theory at work: Enhancing and explaining what employees do. Locke, Edwin A. 1996. Motivation through conscious goal setting. Applied and Preventive Psychology, 5: 117-124. Stajkovic, Alexander D., and Luthans, Fred. Social cognitive theory and self-efficacy: Implications for motivation theory and practice. Part Two: Central Issues in Motivation at Work Chapter 3: The Role of Cognitions, Beliefs, and Attitudes in Motivation Staw, Barry M. 1986. Organizational psychology and the pursuit of the happy/productive worker. California Management Review, 28(4): 40-53. Rousseau, Denise M., and Tijoriwala, Snehal A. 1999. What's a good reason to change? Motivated reasoning and social accounts in promoting organizational change. Journal of Applied Psychology, 84(4): 514-528. Luthans, Fred. Positive Organizational Behavior: Implications for Leadership and HR Development and Motivation. Chapter 4: The Role of Goals and Intentions in Motivation Klein, Howard J., Wesson, Michael J., Hollenbeck, John R., and Alge, Bradley J. 1999. Goal commitment and the goal-setting process: Conceptual clarification and empirical synthesis. Journal of Applied Psychology, 6: 885-896. O'Leary-Kelly, Anne M., Martocchio, Joseph J., and Frink, Dwight D. 1994. A review of the influence of group goals on group performance. Academy of Management Journal, 37(5): 1285-1301. Crown, Deborah F., and Rosse, Joseph G. 1995. Yours, mine, and ours: Facilitating group productivity through the integration of individual and group goals. Organizational Behavior and Human Decision Processes, 64(2): 138-150. Chapter 5: The Role of Affect in Motivation Raghunathan, Rajagopal, and Pham, Michel T. 1999. All negative moods are not equal: Motivational influences of anxiety and sadness on decision-making. Organizational Behavior and Human Decision Processes, 79(1): 56-77. Venkatesh, Viswanath, and Speier, Cheri. 1999. Computer technology training in the workplace: A longitudinal investigation of the effect of mood. Organizational Behavior and Human Decision Processes, 79(1): 1-28. Chapter 6: The Role of Social Influences in Motivation Porter, Lyman W., Lawler, Edward E. III, and Hackman, J. Richard. 1975. Ways groups influence individual effectiveness. (Holdover from previous edition) Vardi, Yoav and Wiener, Yoash. 1996. Misbehavior in organizations: A motivational framework. Organization Science, 7(2): 151-165. Whyte, Glen. 1998. Recasting Janis's groupthink model: The key role of collective efficacy in decision fiascoes. Organizational Behavior and Human Decision Processes, 73(2/3): 185-209. Chapter 7: The Role of Cross-Cultural Influences in Work Motivation Hofstede, G. 1993. Cultural constraints in management theories. Academy of Management Executive, 7(1): 81-94. Sanchez-Runde, Carlos J., and Steers, Richard M. Cultural influences on work motivation and performance. Frese, Michael, Kring, Wolfgang, Soos, Andrea, Zempel, Jeannette. 1996. Personal initiative at work: Differences between east and west Germany. Academy of Management Journal, 39(1): 37-63. Meek, Christopher B. 1999. Ganbatte: Understanding the Japanese employee. Business Horizons, January-February, 27-36. Chapter 8: The Role of Individual Differences in Motivation O'Reilly, Charles A. III and Chatman, Jennifer A. 1994. Working smarter and harder: A longitudinal study of managerial success. Administrative Science Quarterly, 39: 603-627. Pilegge, Anthony J. and Holtz, Rolf. 1997. The effects of social identity on the self-set goals and task performance of high and low self-esteem individuals. Organizational Behavior and Human Decision Processes, 70(1): 17-26. Part Three: Applications of Motivational Approaches Chapter 9: Rewards Lawler, Edward L. 1987. The design of effective reward systems. In J. W. Lorsch (ed.), Handbook of Organizational Behavior. Englewood Cliffs, NJ: Prentice Hall, pp, 25-271. Kerr, Steven. 1995. On the folly of rewarding A, while hoping for B. Academy of Management Executive, 9(1): 7-14. Pearce, Jone L. 1987. Why merit pay doesn't work: Implications from organizational theory. In D. B. Balkin and L. R. Gomez-Mejia (eds.), New Perspectives on Compensation, pp. 169-178. Pfeffer, Jeffrey. 1998. Six dangerous myths about pay. Harvard Business Review, May-June, 109-119. Duncan, W. Jack. 2001. Stock ownership and work motivation. Organizational Dynamics, 30(1): 1-11. Chapter 10: Punishment George, Jennifer M. 1995. Asymmetrical effects of rewards and punishments: the case of social loafing. Journal of Occupational and Organizational Psychology, 68: 327-338. Butterfield, Kenneth D., Trevino, Linda K., and Ball, Gail A. 1996. Punishment from the manager's perspective: A grounded investigation and inductive model. Academy of Management Journal, 39(6): 1479-1512. Chapter 11: Motivating Creativity aand Innovation Amabile, Teresa. 1997. Motivating creativity in organizations: On doing what you love and loving what you do. California Management Review, 40(1): 39-58. Cummings, Anne and Oldham, Greg R. 1997. Enhancing creativity: Managing work contexts for the high potential employee. 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title: Differentiation of citrus bacterial canker strains in Korea by host range, rep-PCR fingerprinting and 16S rDNA analysis

abstract: New Xanthomonas isolates causing citrus bacterial canker in Korea were differentiated primarily on the basis of host range by comparison with reference strains. The new isolates were pathogenic to Citrus sinensis, C. paradisi, C. limon and C. unshiu and formed crater-like canker on the plants; this indicated that they were X. axonopodis (X.a.) pv. citri A types. Molecular characterization using rep-PCR fingerprinting and 16S rDNA sequence analysis was also performed. Cluster analysis by combining the band patterns of ERIC-, BOX- and REP-PCR clearly separated one group including only X. a. pv. citrumelo and the other group including X. a. pv. citri and X. a. pv. aurantifolii strains. There was a clear separation between X. a. pv. citri Asiatic types and X. a. pv. aurantifolii B, C types in the second group. Partial sequence analysis of 16S rDNA revealed that all strains of X. a. pv. aurantifolii B and C type, and X. a. pv. citrumelo formed a distinct cluster with a similarity of 99%. Our results indicate that the isolates causing citrus canker in Korea belong to the A type of X. a. pv. citri.


title: Toward Highly Available and Scalable Software Defined Networks for Service Providers

abstract: Software-defined networking is moving from its initial deployment in small-scale data center networks to large-scale carrier-grade networks. In such environments, high availability and scalability are two of the most prominent issues, and thus extensive work is ongoing. In this article, we first review the state of the art on high availability and scalability issues in SDN and investigate relevant open source activities. In particular, two well-known open source projects, OpenDaylight (ODL) and Open Network Operating System (ONOS), are analyzed in terms of high availability (i.e., network state database replication/synchronization and controller failover mechanisms) and scalability (i.e., network state database partition/ distribution and controller assignment mechanisms) issues. We also present experimental results on the flow rule installation/read throughput and the failover time upon a controller failure in ONOS and ODL, and identify open research challenges.


title: A Novel Differential-Fed Patch Antenna on Stepped-Impedance Resonator With Enhanced Bandwidth Under Dual-Resonance

abstract: A novel design concept to enhance the bandwidth of a differential-fed patch antenna using the dual-resonant radiation of a stepped-impedance resonator (SIR) is proposed. The SIR is composed of two distinctive portions: the radiating patch and a pair of open stubs. Initially, based on the transmission line model, the first and second odd-order radiative resonant modes, i.e., TM10 and TM30, of this SIR-typed patch antenna are extensively investigated. It is demonstrated that the frequency ratio between the dual-resonant modes can be fully controlled by the electrical length and the impedance ratios between the open stub and radiating patch. After that, the SIR-typed patch antenna is reshaped with stepped ground plane in order to increase the impedance ratio as highly required for wideband radiation. With this arrangement, these two radiative modes are merged with each other, resulting in a wide impedance bandwidth with a stable radiation pattern under dual-resonant radiation. Finally, the proposed antenna is designed, fabricated, and measured. It is verified in experiment that the impedance bandwidth ( $\vert S_{\mathrm{ dd11}}\vert dB) of the proposed antenna has gained tremendous increment up to 10% (0.85–0.94 GHz) with two attenuation poles. Most importantly, the antenna has achieved a stable gain varying from 7.4 to 8.5 dB within the whole operating band, while keeping low-cross polarization.


title: Cross-Platform Emoji Interpretation: Analysis, a Solution, and Applications

abstract: Most social media platforms are largely based on text, and users often write posts to describe where they are, what they are seeing, and how they are feeling. Because written text lacks the emotional cues of spoken and face-to-face dialogue, ambiguities are common in written language. This problem is exacerbated in the short, informal nature of many social media posts. To bypass this issue, a suite of special characters called "emojis," which are small pictograms, are embedded within the text. Many emojis are small depictions of facial expressions designed to help disambiguate the emotional meaning of the text. However, a new ambiguity arises in the way that emojis are rendered. Every platform (Windows, Mac, and Android, to name a few) renders emojis according to their own style. In fact, it has been shown that some emojis can be rendered so differently that they look "happy" on some platforms, and "sad" on others. In this work, we use real-world data to verify the existence of this problem. We verify that the usage of the same emoji can be significantly different across platforms, with some emojis exhibiting different sentiment polarities on different platforms. We propose a solution to identify the intended emoji based on the platform-specific nature of the emoji used by the author of a social media post. We apply our solution to sentiment analysis, a task that can benefit from the emoji calibration technique we use in this work. We conduct experiments to evaluate the effectiveness of the mapping in this task.


title: Interaction of extravillous trophoblast galectin-1 and mucin(s)—Is there a functional relevance?

abstract: ABSTRACTIn the course of embryo implantation extensive interaction of the trophoblast with uterine tissue is crucial for adequate trophoblast invasion. This interaction is highly controlled, and it has been pointed out that a specific glycocode and changes in glycosylation may be important for successful implantation and maintenance of pregnancy. Both uterine and trophoblast cells have been shown to express cell surface glycoconjugates and sugar binding proteins, such as mucins (MUC) and galectins (gals). An increasing number of studies have investigated potential candidates interacting in this process. However, knowledge about the biochemical nature of the interactions and their importance for trophoblast cell function, and, consequently, for pregnancy outcome are still lacking. This review is aimed at deliberating the possibility that mucins, as heavily glycosylated proteins, might be among the functionally relevant galectin ligands in human trophoblast, based on both published data and our original res...


title: LIFT: Learned Invariant Feature Transform

abstract: We introduce a novel Deep Network architecture that implements the full feature point handling pipeline, that is, detection, orientation estimation, and feature description. While previous works have successfully tackled each one of these problems individually, we show how to learn to do all three in a unified manner while preserving end-to-end differentiability. We then demonstrate that our Deep pipeline outperforms state-of-the-art methods on a number of benchmark datasets, without the need of retraining.


title: Survey: interpolation methods in medical image processing

abstract: Image interpolation techniques often are required in medical imaging for image generation (e.g., discrete back projection for inverse Radon transform) and processing such as compression or resampling. Since the ideal interpolation function spatially is unlimited, several interpolation kernels of finite size have been introduced. This paper compares 1) truncated and windowed sine; 2) nearest neighbor; 3) linear; 4) quadratic; 5) cubic B-spline; 6) cubic; g) Lagrange; and 7) Gaussian interpolation and approximation techniques with kernel sizes from 1/spl times/1 up to 8/spl times/8. The comparison is done by: 1) spatial and Fourier analyses; 2) computational complexity as well as runtime evaluations; and 3) qualitative and quantitative interpolation error determinations for particular interpolation tasks which were taken from common situations in medical image processing. For local and Fourier analyses, a standardized notation is introduced and fundamental properties of interpolators are derived. Successful methods should be direct current (DC)-constant and interpolators rather than DC-inconstant or approximators. Each method's parameters are tuned with respect to those properties. This results in three novel kernels, which are introduced in this paper and proven to be within the best choices for medical image interpolation: the 6/spl times/6 Blackman-Harris windowed sinc interpolator, and the C2-continuous cubic kernels with N=6 and N=8 supporting points. For quantitative error evaluations, a set of 50 direct digital X-rays was used. They have been selected arbitrarily from clinical routine. In general, large kernel sizes were found to be superior to small interpolation masks. Except for truncated sine interpolators, all kernels with N=6 or larger sizes perform significantly better than N=2 or N=3 point methods (p/spl Lt/0.005). However, the differences within the group of large-sized kernels were not significant. Summarizing the results, the cubic 6/spl times/6 interpolator with continuous second derivatives, as defined in (24), can be recommended for most common interpolation tasks. It appears to be the fastest six-point kernel to implement computationally. It provides eminent local and Fourier properties, is easy to implement, and has only small errors. The same characteristics apply to B-spline interpolation, but the 6/spl times/6 cubic avoids the intrinsic border effects produced by the B-spline technique. However, the goal of this study was not to determine an overall best method, but to present a comprehensive catalogue of methods in a uniform terminology, to define general properties and requirements of local techniques, and to enable the reader to select that method which is optimal for his specific application in medical imaging.


title: Systematically Evaluating Security and Privacy for Consumer IoT Devices

abstract: Internet-of-Things (IoT) devices such as smart bulbs, cameras, and health monitors are being enthusiastically adopted by consumers, with numbers projected to rise to the billions. However, such devices are also easily attacked, or used for launching attacks, at large scale and at increasing frequency. This paper is an attempt at developing a systematic method to identify the security and privacy shortcomings of various IoT devices, with a view towards alerting consumers, manufacturers, and regulators to the associated risks. We categorize the threats along four dimensions: confidentiality of private data sent to/from the IoT device; integrity of data from the IoT device to internal/external entities; access control of the IoT device; and reflective attacks that can be launched from an IoT device. We develop scripts to automate the security testing along each of these dimensions, subject twenty market-ready consumer IoT devices to our test suite, and reveal findings that give a fairly comprehensive picture of the security/privacy posture of these devices. Our methodology can be used as a basis for a star-based security ratings system for IoT devices being brought to market.


title: Lifting and wound closure with barbed sutures.

abstract: The advent of barbed sutures has been a novel and useful adjunct for the aesthetic plastic surgeon in properly selected patients. The deployment of a barbed suture minimizes the risks of cheese wiring and stress relaxation, facilitating the minimally invasive repositioning of soft tissue in the head and neck, as well as optimizing and enhancing traditionally long and potentially tedious procedures in body contouring. This article highlights the advances, advantages, and efficacy associated with the use of barbed sutures in lifting and wound closure.


title: Design and development of a compressor-embedded pneumatic-driven musculoskeletal humanoid

abstract: Although pneumatic robots are expected to be physically friendly to humans and human-environments, large and heavy air sources and reservoir tanks are a problem to build a self-contained pneumatic robot. This paper proposes a compressor-embedded pneumatic-driven humanoid system consisting of a very small distributed compressors and hollow bones as air reservoir tanks as well as the structural parts. Musculoskeletal systems have possibility of doing dynamic motions using physical elasticity of muscles and tendons, coupled-driven systems of multi-articular muscles, and so on. We suppose a pneumatic driven flexible spine will be contribute to dynamic motions as well as physical adaptivity to environments. This paper presents the concept, design, and implementation of the compressor-embedded pneumatic-driven musculoskeletal humanoid robot named “buEnwa.” We have developed the pneumatic robot which embeds very small compressors and reservoir tanks, and has a multi-joint spine in which physically elastic elements such as rubber bands are attached, and the coupled-driving system of the spine and the shoulder. This paper also shows preliminary experiments of the real robot.


Effect of visual realism on cybersickness in virtual reality


title: Privacy-Preserving Multiple Linear Regression of Vertically Partitioned Real Medical Datasets

abstract: This paper studies the feasibility of privacy-preservingdata mining in epidemiological study. As for the data-miningalgorithm, we focus to a linear multiple regression thatcan be used to identify the most significant factorsamong many possible variables, such as the historyof many diseases. We try to identify the linear model to estimate a lengthof hospital stay from distributed dataset related tothe patient and the disease information. In this paper, we have done experiment usingthe real medical dataset related to stroke andattempt to apply multiple regression with sixpredictors of age, sex, the medical scales, e.g., Japan Coma Scale, and the modified Rankin Scale. Our contributions of this paper include(1) to propose a practical privacy-preserving protocols for linear multiple regressionwith vertically partitioned datasets, and(2) to show the feasibility of the proposed system usingthe real medical dataset distributed into two parties, the hospital who knows the technical details of diseasesduring the patients are in the hospital, and the local government who knows the residence even afterthe patients left hospital. (3) to show the accuracy and the performance of thePPDM system which allows us to estimate the expectedprocessing time with arbitrary number of predictors.