title: [New subjects for exceeding conventional on-pump CABG].

abstract: Coronary artery bypass grafting (CABG) used to be performed under cardiac arrest and cardiopulmonary bypass (CPB). During the last decade, efforts were made to minimize CPB-related complications. The technique of off-pump CABG (OPCAB) has been established during the last 5 years. Elimination of CPB and OPCAB has successfully reduced a number of perioperative complications and has provided early patient recovery. A compression type of coronary stabilizer was used early phase of OPCAB. Off-pump revascularization using the compression device was limited to the anterior wall of the heart. Bypass to the posterior wall under a beating heart was not popular until the suction type of stabilizer had become available. A suction device assisted by the Lima's pericardial suture allowed us to perform bypass grafting any aspects of the heart. Recently, we are skeltonizing the arterial grafts using the Harmonic scalpel. Applying skeltonizing technique to the radial artery or internal thoracic artery, we can successfully perform sequential grafting in selected cases. The number of distal anastomoses has been gradually increased as the device and technique were advanced (2.1 distal anastomoses with a compression device, 2.9 with a suction device, and 3.2 with the skeltonization technique). The frequency of the complete revascularization also increased. On the other hand, the complications associated with the procedure were comparable among these three off-pump methods, but were significantly fewer than on-pump CABG. Currently performed OPCAB can provide almost same number of distal anastomoses as on-pump CABG, with less frequency of postoperative mortality and morbidity, and with early patient recovery. These favorable results were attributed to the progress of the device and technique.


title: Effective and Efficient Global Context Verification for Image Copy Detection

abstract: To detect illegal copies of copyrighted images, recent copy detection methods mostly rely on the bag-of-visual-words (BOW) model, in which local features are quantized into visual words for image matching. However, both the limited discriminability of local features and the BOW quantization errors will lead to many false local matches, which make it hard to distinguish similar images from copies. Geometric consistency verification is a popular technology for reducing the false matches, but it neglects global context information of local features and thus cannot solve this problem well. To address this problem, this paper proposes a global context verification scheme to filter false matches for copy detection. More specifically, after obtaining initial scale invariant feature transform (SIFT) matches between images based on the BOW quantization, the overlapping region-based global context descriptor (OR-GCD) is proposed for the verification of these matches to filter false matches. The OR-GCD not only encodes relatively rich global context information of SIFT features but also has good robustness and efficiency. Thus, it allows an effective and efficient verification. Furthermore, a fast image similarity measurement based on random verification is proposed to efficiently implement copy detection. In addition, we also extend the proposed method for partial-duplicate image detection. Extensive experiments demonstrate that our method achieves higher accuracy than the state-of-the-art methods, and has comparable efficiency to the baseline method based on the BOW quantization.


title: RESP: a robust physical unclonable function retrofitted into embedded SRAM array

abstract: Physical Unclonable Functions (PUFs) have emerged as an attractive primitive to address diverse hardware security issues in Integrated Circuits (ICs). A majority of existing PUFs rely on a dedicated circuit structure for generating chip-specific signatures, which often imposes concerns due to area/power overhead and extra design efforts. Furthermore, existing PUF-based signature generation cannot be employed to authenticate chips already in the market. In this paper, we propose RESP, a novel PUF structure realized in embedded SRAM array, a prevalent component in processors and system-on-chips (SOCs), with virtually no design modification. RESP leverages on voltage-depend memory access failures (during write) to produce large volume of high-quality challenge-response pairs. Since many modern ICs integrate SRAM array of varying size with isolated power grid, RESP can be easily retrofitted into these chips. Circuit-level simulation of 1000 chips using realistic process variation model shows high uniqueness of 49.2% average inter-die Hamming distance and good reproducibility of 2.88% intra-die Hamming distance under temperature <; 85°C. The device aging effect, e.g. bias temperature instability (BTI), results in only 4.95% estimated unstable bits for ten-year usage.


title: An analytical framework to nowcast well-being using mobile phone data

abstract: An intriguing open question is whether measurements derived from Big Data recording human activities can yield high-fidelity proxies of socio-economic development and well-being. Can we monitor and predict the socio-economic development of a territory just by observing the behavior of its inhabitants through the lens of Big Data? In this paper, we design a data-driven analytical framework that uses mobility measures and social measures extracted from mobile phone data to estimate indicators for socio-economic development and well-being. We discover that the diversity of mobility, defined in terms of entropy of the individual users’ trajectories, exhibits (i) significant correlation with two different socio-economic indicators and (ii) the highest importance in predictive models built to predict the socio-economic indicators. Our analytical framework opens an interesting perspective to study human behavior through the lens of Big Data by means of new statistical indicators that quantify and possibly “nowcast” the well-being and the socio-economic development of a territory.


title: Scalability and Yield in Elastomer Stamp Micro-Transfer-Printing

abstract: Elastomer stamp micro-transfer-printing is a highly scalable method for the assembly of microscale components onto non-native substrates. One of the key value propositions of micro-transfer-printing is that the transfer stamp can be scaled to wafer-dimensions and can transfer tens to thousands of micro-devices in a single step, equating to multiple millions of units per hour. Here, we report on the results of systematically scaling the stamp from 12.8 mm × 12.8 mm to a full 150 mm stamp, capable of transferring all the required devices to a 150 mm receiving wafer in one operation. The 150 mm stamp is designed to transfer more than 80,000 chips in one print cycle. This study was carried out using silicon nitride test vehicles that were specially designed for this project. We will discuss how stamp scaling impacts transfer yield and the implications for ultra-high throughput assembly of micro-devices. In addition, we will explore the capability to transfer very small devices down to 3 µm × 3 µm.


title: Early predictors of adolescent aggression and adult violence

abstract: The Cambridge Study in Delinquent Development is a prospective longitudinal survey of 411 London males from ages 8 years old to 32 years old. This article investigates the prediction of adolescent aggression (ages 12-14 years old), teenage violence (ages 16-18 years old), adult violence (age 32 years old), and convictions for violence. Generally, the best predictors were measures of economic deprivation, family criminality, poor child-rearing, school failure, hyperactivity-impulsivity-attention deficit, and antisocial child behavior. Similar predictors applied to all four measures of aggression and violence. It is concluded that aggression and violence are elements of a more general antisocial tendency, and that the predictors of aggression and violence are similar to the predictors of antisocial and criminal behavior in general. VioLit summary: OBJECTIVE: The purpose of this article by Farrington was to explore factors that were thought to predispose young males to violent behavior and examine those factors that were predictive. METHODOLOGY: The author conducted a quasi-experimental prospective longitudinal survey of 411 males aged 8 to 32, to explore predictive variables for adolescent aggression and adult violence. The research covered a span of 24 years. The sample was gathered from a working class area in London. Psychologists tested boys at ages 8, 10, and 14 in their schools. These tests included measures of intelligence, school attainment, personality, and psychomotor impulsiveness. At ages 16, 18, and 21 the boys were interviewed at the project's research office. At approximately ages 25 and 32 the subjects were interviewed in their homes by young male social science graduate students. Interviews gathered information on employment histories, heterosexual relationships, leisure activities, offending behavior, and living circumstances. Female social workers interviewed the subjects' parents at the boys' home once every year from ages 8 until ages 14 and 15. These parental interviews collected information about family income, size of family, employment histories, child rearing practices, boys' temporary or permanent separation from parents, and the degree of parental supervision of boys. Questionnaires were given to the boys' teachers when the boys were approximately ages 8, 10, 12, and 14. These questionnaires asked about the boy's attention deficit, their aggressive and disorderly behavior, school achievements, and their truancy. The authors also obtained measures of the boys daring, dishonesty, propensity for trouble, and popularity from their peers. The Criminal Record Office in London was searched to locate guilty verdicts of the subjects, their parents, their wives and cohabitees. Only the most serious criminal offense on each day was counted. Criminality was also measured by self-reports obtained from the subjects from age 14 and up. At ages 8, 10, 12, and 14, measures of aggression were derived from the teachers' questionnaire. Using this instrument, aggression was defined as those who were difficult to discipline. At ages 16, 18, and 32, aggression measures were derived from self-reports. Aggressive youths referred to those who most frequently admitted carrying and using weapons, getting into fights, and starting fights. Four categories of aggression and violence were examined in this study: adolescent aggression at ages 12-14; teenage violence at ages 16-18; adult violence at age 32; and convictions of violence between ages 10 and 32. The author used 2x2 contingency tables to examine the data and used stepwise multivariate multiple regression to explore the independent relationship between predictors and measures of aggression and violence. FINDINGS/DISCUSSION: There was a significant difference between low income males and the other males in their teenage violence measures. Forty-two percent of low income males were violent as teenagers while only 27% of the remaining group were violent as teenagers. Low income males were more likely to be found to be convicted of violent crimes when compared to the remaining males in the study. Poor housing significantly predicted adolescent aggression and teenage violence. Large family size was found to predict teenage violence and convictions for violence. Low socioeconomic status predicted convictions for violence. Subjects who had convicted parents, delinquent siblings, and siblings with behavior problems had significantly higher rates of convictions for violence. Convicted parents predicted adolescent aggression and teenage violence. Low verbal intelligence, low nonverbal intelligence, low junior high school attainment, and low secondary school tracking placement, significantly predicted adolescent aggression and convictions for violence. All four measures of aggression were significantly predicted by the childhood daring factor. Adolescent violence was predicted by the "daring" measure as determined by peer perceptions. Predictive social background measures at age 14 included poor housing, large family size, and parental disharmony. At ages 8-10, important predictors of aggression were placed by the author into six categories: economic deprivation, family criminality, poor child rearing, school failure, hyperactivity-impulsivity, and antisocial child behavior. AUTHOR'S RECOMMENDATIONS: The author recommended that future research be done to test explanations and prevention techniques of violent behavior. (CSPV Abstract - Copyright © 1992-2007 by the Center for the Study and Prevention of Violence, Institute of Behavioral Science, Regents of the University of Colorado) KW - Longitudinal Studies KW - Violence Predictors KW - England KW - Countries Other Than USA KW - Male Aggression KW - Male Offender KW - Male Violence KW - Aggression Causes KW - Aggression Predictors KW - Aggression Risk Factors KW - Juvenile Aggression KW - Juvenile Male KW - Adult Male KW - Adult Offender KW - Adult Violence KW - Violence Risk Factors KW - Violence Predictors KW - Violence Causes Language: en


title: The social behavior of the bees: a comparative study

abstract: Although the honeybee is without doubt man's favorite social insect, and the most studied by him, there are twenty thousand other species of bees, many of which are social. This book is the first to offer a systematic account of social behavior in the entire super family "Apoidea." Of all the social insects, the various species of bees exhibit perhaps the broadest spectrum of social behavior, including intermediate stages which are scarce or totally extinct in other groups; in this respect the bees are particularly appropriate subjects for evolutionary study.With the aid of more than 200 illustrations, Charles Michener characterizes and describes all levels of social organization in the bees from simple aggregations of solitary nests to elaborate, eusocial colonies. He reviews the entire repertoire of social behavior in bees and gives detailed attention to mechanisms of communication, division of labor, determination of sex and caste, maintenance and control of nest conditions, and organization of defense. In a major chapter the evolutionary context of the bee societies is extensively explored; the author examines the selective advantages and disadvantages entailed in evolving nonreproductive castes, the problem of multiple, independent origins of eusociaI behavior, and the question of direction in the evolution of social behavior. The final section is an account of the life history and behavioral attributes of each of the groups of social bees."


title: Vision-based coaching: optimizing resources for leader development

abstract: Leaders develop in the direction of their dreams, not in the direction of their deficits. Yet many coaching interactions intended to promote a leader’s development fail to leverage the benefits of the individual’s personal vision. Drawing on intentional change theory, this article postulates that coaching interactions that emphasize a leader’s personal vision (future aspirations and core identity) evoke a psychophysiological state characterized by positive emotions, cognitive openness, and optimal neurobiological functioning for complex goal pursuit. Vision-based coaching, via this psychophysiological state, generates a host of relational and motivational resources critical to the developmental process. These resources include: formation of a positive coaching relationship, expansion of the leader’s identity, increased vitality, activation of learning goals, and a promotion–orientation. Organizational outcomes as well as limitations to vision-based coaching are discussed.


title: A ${\rm TM}_{11}$ Dual-Mode Dielectric Resonator Filter With Planar Coupling Configuration

abstract: This paper presents a novel dielectric resonator filter exploiting dual TM11 degenerate modes. The dielectric rod resonators are short circuited on the top and bottom surfaces to the metallic cavity. The dual-mode cavities can be conveniently arranged in many practical coupling configurations. Through-holes in height direction are made in each of the dielectric rods for the frequency tuning and coupling screws. All the coupling elements, including inter-cavity coupling elements, are accessible from the top of the filter cavity. This planar coupling configuration is very attractive for composing a diplexer or a parallel multifilter assembly using the proposed filter structure. To demonstrate the new filter technology, two eight-pole filters with cross-couplings for UMTS band are prototyped and tested. It has been experimentally shown that as compared to a coaxial combline filter with a similar unloaded Q, the proposed dual-mode filter can save filter volume by more than 50%. Moreover, a simple method that can effectively suppress the lower band spurious mode is also presented.


title: Perpetual development: A model for the Linux kernel life cycle

abstract: Software evolution is widely recognized as an important and common phenomenon, whereby the system follows an ever-extending development trajectory with intermittent releases. Nevertheless there have been only few lifecycle models that attempt to portray such evolution. We use the evolution of the Linux kernel as the basis for the formulation of such a model, integrating the progress in time with growth of the codebase, and differentiating between development of new functionality and maintenance of production versions. A unique element of the model is the sequence of activities involved in releasing new production versions, and how this has changed with the growth of Linux. In particular, the release follow-up phase before the forking of a new development version, which was prominent in early releases of production versions, has been eliminated in favor of a concurrent merge window in the release of 2.6.x versions. We also show that a piecewise linear model with increasing slopes provides the best description of the growth of Linux. The perpetual development model is used as a framework in which commonly recognized benefits of incremental and evolutionary development may be demonstrated, and to comment on issues such as architecture, conservation of familiarity, and failed projects. We suggest that this model and variants thereof may apply to many other projects in addition to Linux.


title: What Strategies are Effective for Formative Assessment in an E-Learning Environment?

abstract: The web-based formative assessment developed in this research is named Formative Assessment Module of the Web-based Assessment and Test Analysis System (FAM-WATA). FAMWATA is a multiple-choice web-based formative assessment module containing six effective strategies: ‘repeat the test’, ‘correct answers are not given’, ‘query scores’, ‘ask questions’, ‘monitor answering history’, and ‘all pass and then reward’. This research explored the effectiveness of FAM-WATA, cognitive styles and e-learning, and student attitudes towards the six strategies of FAM-WATA. A total of 503 seventh-grade students in central Taiwan were valid in this research. Overall results indicated that students displayed a positive attitude towards the six strategies of FAM-WATA. In addition, results also showed that students in an e-learning environment equipped with FAM-WATA achieved better learning effectiveness, and that field independent students appeared to make better use of FAM-WATA strategies than field dependent students. This research concluded that FAM-WATA benefited student learning in an e-learning environment.


title: Does a Rock Implement Every Finite-State Automaton?

abstract: Hilary Putnam has argued that computational functionalism cannot serve as a foundation for the study of the mind, as every ordinary open physical system implements every finite-state automaton. I argue that Putnam's argument fails, but that it points out the need for a better understanding of the bridge between the theory of computation and the theory of physical systems: the relation of implementation. It also raises questions about the class of automata that can serve as a basis for understanding the mind. I develop an account of implementation, linked to an appropriate class of automata, such that the requirement that a system implement a given automaton places a very strong constraint on the system. This clears the way for computation to play a central role in the analysis of mind.


title: Concepts as Semantic Pointers: A Framework and Computational Model

abstract: The reconciliation of theories of concepts based on prototypes, exemplars, and theory-like structures is a longstanding problem in cognitive science. In response to this problem, researchers have recently tended to adopt either hybrid theories that combine various kinds of representational structure, or eliminative theories that replace concepts with a more finely grained taxonomy of mental representations. In this paper, we describe an alternative approach involving a single class of mental representations called “semantic pointers.” Semantic pointers are symbol-like representations that result from the compression and recursive binding of perceptual, lexical, and motor representations, effectively integrating traditional connectionist and symbolic approaches. We present a computational model using semantic pointers that replicates experimental data from categorization studies involving each prior paradigm. We argue that a framework involving semantic pointers can provide a unified account of conceptual phenomena, and we compare our framework to existing alternatives in accounting for the scope, content, recursive combination, and neural implementation of concepts.


title: Fuzzy modelling and its application to magnetic bearing systems

abstract: Abstract Fuzzy modelling is rule-based. This rule base is described by a certain system of fuzzy equations. In order to obtain an accurate fuzzy model, topics such as sufficient conditions for satisfying the boundary conditions, the behaviour of systems of fuzzy equations, the choice of a suitable t-norm t , and the adjustment of membership functions are discussed intensively in this paper. It is then applied to magnetic bearings without premagnetization.


title: Figure-Ground Separation: A Case Study in Energy Minimization via Evolutionary Computing

abstract: It is known that the problem of figure-ground separation can be modeled as one of energy minimization using the Ising system model from quantum physics. The Ising system model for the figure-ground separation problem makes explicit the definition of shape in terms of attributes such as cocircularity, smoothness, proximity and contrast and is based on the formulation of an energy function that incorporates pairwise interactions between local image features in the form of edgels. This paper explores a class of stochastic optimization techniques based on evolutionary algorithms for the problem of figure-ground separation using the Ising system model. Experimental results on synthetic edgel maps and edgel maps derived from gray scale images are presented. The advantages and shortcomings of evolutionary algorithms in the context of figure-ground separation are discussed.


title: Photocatalytic degradation of trichloroethylene in water using TiO2 pellets

abstract: Abstract A recirculating system of aqueous trichloroethylene (TCE) solutions through the packed bed reactor with TiO 2 pellets has been developed in order to mineralize TCE without difficulties for filtration and recovery of catalyst. The TiO 2 pellets prepared by sol–gel method have photocatalytic activity similar to commercially available PC-101 and PC-102 in the powder form and to ST-B11 pellets. In batch experiments with TiO 2 powders, Degussa P-25 is the most active photocatalyst, which indicates that specific surface area is not an important factor controlling the photocatalytic activity in aqueous solutions. The degradation rates of TCE in the recirculating system with TiO 2 pellets decreased in the presence of H 2 O 2 , while were remarkably accelerated by adding S 2 O 8 2− . The presence of S 2 O 8 2− ions more than 0.01 mol dm −3 completely suppressed hole-electron recombination and mineralized 50 ppm TCE with the 2 h irradiation. In a reactor without TiO 2 photocatalysts, TCE was photodegraded by SO 4 − radicals which produced by photodissociation of S 2 O 8 2− . The degradation rates increased with increase of the initial S 2 O 8 2− concentration. However, TCE was not mineralized but converted to intermediates which were slowly degraded to Cl − by continuing the irradiation.


title: Ultrasonic RAdar System (URAS): Arduino and Virtual Reality for a Light-Free Mapping of Indoor Environments

abstract: Recently, academia and industry have focused on the creation of new systems for mapping and exploration of unknown spaces in order to create advanced guide systems for robots and people affected by disabilities. In particular, the most common applications are related to the exploration of unknown and/or dangerous spaces that are not accessible to people by exploiting the advantages offered by ultrasonic technology. This work aims at designing a new low-cost system, namely, ultrasonic radar system, to blindly map environments by using ultrasonic sensors, then displaying the acquired information through an Android-based device.


title: CLASSIFICATION OF EEG SIGNALS FOR DETECTION OF EPILEPTIC SEIZURES BASED ON WAVELETS AND STATISTICAL PATTERN RECOGNITION

abstract: The electroencephalogram (EEG) signal is very important in the diagnosis of epilepsy. Long-term EEG recordings of an epileptic patient contain a huge amount of EEG data. The detection of epileptic activity is, therefore, a very demanding process that requires a detailed analysis of the entire length of the EEG data, usually performed by an expert. This paper describes an automated classification of EEG signals for the detection of epileptic seizures using wavelet transform and statistical pattern recognition. The decision making process is comprised of three main stages: (a) feature extraction based on wavelet transform, (b) feature space dimension reduction using scatter matrices and (c) classification by quadratic classifiers. The proposed methodology was applied on EEG data sets that belong to three subject groups: (a) healthy subjects, (b) epileptic subjects during a seizure-free interval and (c) epileptic subjects during a seizure. An overall classification accuracy of 99% was achieved. The results confirmed that the proposed algorithm has a potential in the classification of EEG signals and detection of epileptic seizures, and could thus further improve the diagnosis of epilepsy.


HEXA-BAND INTERNAL ANTENNA FOR MOBILE PHONE


title: RIPE: runtime intrusion prevention evaluator

abstract: Despite the plethora of research done in code injection countermeasures, buffer overflows still plague modern software. In 2003, Wilander and Kamkar published a comparative evaluation on runtime buffer overflow prevention technologies using a testbed of 20 attack forms and demonstrated that the best prevention tool missed 50% of the attack forms. Since then, many new prevention tools have been presented using that testbed to show that they performed better, not missing any of the attack forms. At the same time though, there have been major developments in the ways of buffer overflow exploitation. In this paper we present RIPE, an extension of Wilander's and Kamkar's testbed which covers 850 attack forms. The main purpose of RIPE is to provide a standard way of testing the coverage of a defense mechanism against buffer overflows. In order to test RIPE we use it to empirically evaluate some of the newer prevention techniques. Our results show that the most popular, publicly available countermeasures cannot prevent all of RIPE's buffer overflow attack forms. ProPolice misses 60%, LibsafePlus+TIED misses 23%, CRED misses 21%, and Ubuntu 9.10 with nonexecutable memory and stack protection misses 11%.


The Cognitive Neuroscience of Video Games


title: Model satellite design for CanSat Competition

abstract: Objective of this work is to design and manufacture a model satellite named Vecihi that is able to perform some of the basic tasks that artificial satellites perform. The satellite is developed under the rules of CanSat Competition 2013, which aims to promote innovative space solutions and to improve the current systems. The Vecihi satellite designed around budgetary, dimensional, and mass requirements as set in the competition guidelines, while carrying and landing its payload successfully.


title: Military-Based Vehicle-to-Grid and Vehicle-to-Vehicle Microgrid—System Architecture and Implementation

abstract: A real-life military application of vehicle-to-grid/vehicle-to-vehicle (V2G–V2V)-based microgrid system is described in this paper. The system provides a plug-and-play, very fast forming, smart, aggregated, and efficient power solution for a contingency military base that can be setup in less than 20 min and is ready to generate up to 240 kW of 208-Y/120-VAC three-phase ( $3~\Phi )$ power. The system uses vehicle transmission-integrated generators (TIGs) to produce 600-VDC power for use by vehicle hotel loads (i.e., electrification of nonpropulsion and auxiliary loads) and off-board loads (tents/shelters, communications centers, or other electrical loads). This effort involves four tactical military vehicles—two M1152 high-mobility multipurpose wheeled vehicles equipped with 30 kW of on-board vehicle power and two MaxxPro dash mine resistant ambush protected vehicles equipped with 120-kW 3000 TIGs with V2G and V2V capabilities, four 60-kW dc-to-3 $\Phi $ ac power converters with 600-VDC bus distribution systems and four 22.8-kWh energy storage units. Discussion of the methodology for power management for maximizing fuel economy is included at the end. This paper also includes some test results of subsystems and some results from modeling and simulation of the system. Our study demonstrates significant fuel economy benefits of using V2V-based system.


title: Resonant-free PDN design®

abstract: The design of power distribution networks (PDNs) on printed circuit board (PCB) structures, or even on interconnect structures inside IC packages, typically results, with or without decoupling capacitors added, in a network full of impedance resonances. These resonances functionally hamper fast digital and RF designs from several MHz up to the GHz-range onwards and are the root cause for many EMC issues. These resonances are caused both by the physical size and geometry of the PCB and the decoupling as well as the loading components added to that PCB. Utilizing the characteristic impedance of the adjacent supply and ground layers correctly, results in a resonant free supply PDN with an impedance which can be made very low over an extremely broad frequency range. This, in combination with ‘Kelvin contact’ decoupled ICs, assures that the low impedance of the PDN can be maintained and multiple decoupling capacitors are no longer needed near to the IC pins. This offers great advantages for PCB space allocation and opens opportunities to more efficient routing. This extended concept has been verified by simulations. Additional measurements were taken to validate the concept.


title: Characterizing Large-Scale Click Fraud in ZeroAccess

abstract: Click fraud is a scam that hits a criminal sweet spot by both tapping into the vast wealth of online advertising and exploiting that ecosystem's complex structure to obfuscate the flow of money to its perpetrators. In this work, we illuminate the intricate nature of this activity through the lens of ZeroAccess--one of the largest click fraud botnets in operation. Using a broad range of data sources, including peer-to-peer measurements, command-and-control telemetry, and contemporaneous click data from one of the top ad networks, we construct a view into the scale and complexity of modern click fraud operations. By leveraging the dynamics associated with Microsoft's attempted takedown of ZeroAccess in December 2013, we employ this coordinated view to identify "ad units" whose traffic (and hence revenue) primarily derived from ZeroAccess. While it proves highly challenging to extrapolate from our direct observations to a truly global view, by anchoring our analysis in the data for these ad units we estimate that the botnet's fraudulent activities plausibly induced advertising losses on the order of $100,000 per day.


title: Extending knowledge-driven activity models through data-driven learning techniques

abstract: We combine knowledge- and data-driven approaches for activity modeling.We develop a novel clustering algorithm that uses prior domain expert knowledge.A new learning algorithm to model activities from extracted clusters.We model a pervasive home environment with real users' inputs for experiments.Automatically learn 100% of activity variations performed by users. Knowledge-driven activity recognition is an emerging and promising research area which has already shown very interesting features and advantages. However, there are also some drawbacks, such as the usage of generic and static activity models. This paper presents an approach to using data-driven techniques to evolve knowledge-driven activity models with a user's behavioral data. The approach includes a novel clustering process where initial incomplete models developed through knowledge engineering are used to detect action clusters which represent activities and aggregate new actions. Based on those action clusters, a learning process is then designed to learn and model varying ways of performing activities in order to acquire complete and specialized activity models. The approach has been tested with real users' inputs, noisy sensors and demanding activity sequences. Initial results have shown that complete and specialized activity models are properly learned with success rates of 100% at the expense of learning some false positive models.


title: PAGE 516 A corpus-based analysis of transfer effects and connected speech processes in Vietnamese English

abstract: This paper presents a corpus-based descriptive analysis of the most prevalent transfer effects and connected speech processes observed in a comparison of 11 Vietnamese English speakers (6 females, 5 males) and 12 Australian English speakers (6 males, 6 females) over 24 grammatical paraphrase items. The phonetic processes are segmentally labelled in terms of IPA diacritic features using the EMU speech database system with the aim of labelling departures from native-speaker pronunciation. An analysis of prosodic features was made using ToBI framework. The results show many phonetic and prosodic processes which make non-native speakers’ speech distinct from native ones. The corpusbased methodology of analysing foreign accent may have implications for the evaluation of non-native accent, accented speech recognition and computer assisted pronunciation- learning.


title: Pop-up assembly of 3D structures actuated by heat shrinkable polymers

abstract: Folding 2D sheets into desired 3D structures is a promising fabrication technique that can find a wide range of applications. Compressive buckling provides an attractive strategy to actuate the folding and can be applied to a broad range of materials. Here a new and simple method is reported to achieve controlled compressive buckling, which is actuated by a heat shrinkable polymer sheet. The buckling deformation is localized at the pre-defined creases in the 2D sheet, resulting in sharp folding. Two approaches are developed to actuate the transformation, which follow similar geometric rules. In the first approach, the 2D precursor is pushed from outside, which leads to a 3D structure surrounded by the shrunk polymer sheet. Assembled 3D structures include prisms/pyramids with different base shapes, house roof, partial soccer ball, Miura-ori structure and insect wing. In the second approach, the 2D precursor is pulled from inside, which leads to a 3D structure enclosing the shrunk polymer sheet. Prisms/pyramids with different base shapes are assembled. The assembled structures are further tessellated to fabricate cellular structures that can be used as thermal insulator and crash energy absorber. They are also stacked vertically to fabricate complex multilayer structures.


title: Region Growing for Segmenting Green Microalgae Images

abstract: We describe a specialized methodology for segmenting 2D microscopy digital images of freshwater green microalgae. The goal is to obtain representative algae shapes to extract morphological features to be employed in a posterior step of taxonomical classification of the species. The proposed methodology relies on the seeded region growing principle and on a fine-tuned filtering preprocessing stage to smooth the input image. A contrast enhancement process then takes place to highlight algae regions on a binary pre-segmentation image. This binary image is also employed to determine where to place the seed points and to estimate the statistical probability distributions that characterize the target regions, i.e., the algae areas and the background, respectively. These preliminary stages produce the required information to set the homogeneity criterion for region growing. We evaluate the proposed methodology by comparing its resulting segmentations with a set of corresponding ground-truth segmentations (provided by an expert biologist) and also with segmentations obtained with existing strategies. The experimental results show that our solution achieves highly accurate segmentation rates with greater efficiency, as compared with the performance of standard segmentation approaches and with an alternative previous solution, based on level-sets, also specialized to handle this particular problem.


title: Steering the Beam of Medium-to-High Gain Antennas Using Near-Field Phase Transformation

abstract: A method to steer the beam of aperture-type antennas is presented in this paper. Beam steering is achieved by transforming phase of the antenna near field using a pair of totally passive metasurfaces, which are located just above and parallel to the antenna. They are rotated independently or synchronously around the antenna axis. A prototype, with a peak gain of 19.4 dBi, demonstrated experimentally that the beam of a resonant cavity antenna can be steered to any direction within a large conical region (with an apex angle of 102°), with less than 3-dB gain variation, by simply turning the two metasurfaces without moving the antenna at all. Measured gain variation within a 92° cone is only 1.9 dBi. Contrary to conventional mechanical steering methods, such as moving reflector antennas with multiaxis rotary joints, the 3-D volume occupied by this antenna system does not change during beam steering. This advantage, together with its low profile, makes it a strong contender for space-limited applications where beam steering with active devices is not desirable due to cost, nonlinear distortion, limited power handling, sensitivity to temperature variations, radio frequency losses, or associated heating. This beam steering method using near-field phase transformation can also be applied to other aperture-type antennas and arrays with medium-to-high gains.


title: The HermiT OWL Reasoner

abstract: HermiT is the only reasoner we know of that fully supports the OWL 2 standard, and that correctly reasons about properties as well as classes. It is based on a novel "hypertableau" calculus that addresses performance problems due to nondeterminism and model size-the primary sources of complexity in state-of-the-art OWL reasoners. HermiT also incorporates a number of novel optimizations, including an optimized ontology classification procedure. Our tests show that HermiT performs well compared to existing tableau reasoners and is often much faster when classifying complex ontologies.


title: VNF Placement and Chaining in Distributed Cloud

abstract: This paper presents a model for Virtual Network Function (VNF) placement and chaining across Cloud environments. We propose a new analytical approach for joint VNFs placement and traffic steering for complex service chains and different VNF types. A custom greedy algorithm is also proposed to compare with our solution. Performance evaluation results show that our approach is fast and stable and has a execution time that essentially depends only on the NFV infrastructure size.


title: Fast Min-Sum Algorithms for Decoding of LDPC over GF(q)

abstract: In this paper, we present a fast min-sum algorithm for decoding LDPC codes over GF(q). Our algorithm is different from the one presented by David Declercq and Marc Fossorier in [1] only at the way of speeding up the horizontal scan in the min-sum algorithm. The Declercq and Fossorier's algorithm speeds up the computation by reducing the number of configurations, while our algorithm uses the dynamic programming instead. Compared with the configuration reduction algorithm, the dynamic programming one is simpler at the design stage because it has less parameters to tune. Furthermore, it does not have the performance degradation problem caused by the configuration reduction because it searches the whole configuration space efficiently through dynamic programming. Both algorithms have the same level of complexity and use simple operations which are suitable for hardware implementations.


title: User feedback in the appstore: An empirical study

abstract: Application distribution platforms - or app stores - such as Google Play or Apple AppStore allow users to submit feedback in form of ratings and reviews to downloaded applications. In the last few years, these platforms have become very popular to both application developers and users. However, their real potential for and impact on requirements engineering processes are not yet well understood. This paper reports on an exploratory study, which analyzes over one million reviews from the Apple AppStore. We investigated how and when users provide feedback, inspected the feedback content, and analyzed its impact on the user community. We found that most of the feedback is provided shortly after new releases, with a quickly decreasing frequency over time. Reviews typically contain multiple topics, such as user experience, bug reports, and feature requests. The quality and constructiveness vary widely, from helpful advices and innovative ideas to insulting offenses. Feedback content has an impact on download numbers: positive messages usually lead to better ratings and vice versa. Negative feedback such as shortcomings is typically destructive and misses context details and user experience. We discuss our findings and their impact on software and requirements engineering teams.


title: Onychomatricoma masquerading as candidal onychomycosis and paronychia.

abstract: Onychomatricoma is a benign slow-growing fibroepithelial tumor arising from the nail matrix. The tumor was described as a new entity almost two decades ago. Although the clinical appearance is typical, most cases are probably misdiagnosed by physicians because of unfamiliarity with the condition. Herein we describe a case of onychomatricoma masquerading as candidal onychomycosis and paronychia and treated erroneously as such.


title: Effective erasure codes for reliable computer communication protocols

abstract: Reliable communication protocols require that all the intended recipients of a message receive the message intact. Automatic Repeat reQuest (ARQ) techniques are used in unicast protocols, but they do not scale well to multicast protocols with large groups of receivers, since segment losses tend to become uncorrelated thus greatly reducing the effectiveness of retransmissions. In such cases, Forward Error Correction (FEC) techniques can be used, consisting in the transmission of redundant packets (based on error correcting codes) to allow the receivers to recover from independent packet losses.Despite the widespread use of error correcting codes in many fields of information processing, and a general consensus on the usefulness of FEC techniques within some of the Internet protocols, very few actual implementations exist of the latter. This probably derives from the different types of applications, and from concerns related to the complexity of implementing such codes in software. To fill this gap, in this paper we provide a very basic description of erasure codes, describe an implementation of a simple but very flexible erasure code to be used in network protocols, and discuss its performance and possible applications. Our code is based on Vandermonde matrices computed over GF(pr), can be implemented very efficiently on common microprocessors, and is suited to a number of different applications, which are briefly discussed in the paper. An implementation of the erasure code shown in this paper is available from the author, and is able to encode/decode data at speeds up to several MB/s running on a Pentium 133.


title: Transition control of tilt rotor unmanned aerial vehicle based on multi-model adaptive method

abstract: Tilt rotor unmanned aerial vehicle (TRUAV) with ability of hovering and high-speed cruise has attached much attention, but its transition control is still a difficult point because of varying dynamics. This paper proposes a multi-model adaptive control (MMAC) method for a quad-TRUAV, and the stability in the transition procedure could be ensured by considering corresponding dynamics. For safe transition, tilt corridor is considered firstly, and actual flight status should locate within it. Then, the MMAC controller is constructed according to mode probabilities, which are calculated by solving a quadratic programming problem based on a set of input- output plant models. Compared with typical gain scheduling control, this method could ensure transition stability more effectively.


title: DWS: Demand-aware Work-Stealing in Multi-programmed Multi-core Architectures

abstract: Traditional work-stealing schedulers perform poorly in multi-programmed multi-core architectures, because all the programs tend to use all the cores and thus incur serious core contention. To relieve this problem, this paper proposes a Demand-aware Work-Stealing (DWS) task scheduler, with which a work-stealing program uses cores according to its realtime demand on the cores. If multiple programs scheduled by DWS run in a multi-core architecture concurrently, the cores are first evenly allocated to the co-running programs. At runtime, if a program cannot fully utilize its cores, it releases some of its allocated cores. Otherwise, if a program demands more cores, it tries to use the free cores released by its co-running programs. Experimental results show that DWS can achieve up to 32.3% performance gain for co-running programs compared to traditional work-stealing schedulers with the ABP yielding mechanism.


Airport operations management


title: Interface agents as social models: the impact of appearance on females' attitude toward engineering

abstract: This experimental study investigated the impact of interface agent appearance (age, gender, "coolness") on enhancing undergraduate females' attitudes toward engineering. Results revealed that participants reported more positive stereotypes of engineers after interacting with a female agent. In contrast, participants interacting with a male agent reported that engineering was more useful and engaging. An interaction of "coolness" and age indicated that agents who were young and "cool" (i.e., peer-like; similar to participants) and agents who were old and "uncool" (stereotypical engineers) were both most effective on enhancing self-efficacy toward engineering.


title: DARPA-funded efforts in the development of novel brain–computer interface technologies

abstract: The Defense Advanced Research Projects Agency (DARPA) has funded innovative scientific research and technology developments in the field of brain-computer interfaces (BCI) since the 1970s. This review highlights some of DARPA's major advances in the field of BCI, particularly those made in recent years. Two broad categories of DARPA programs are presented with respect to the ultimate goals of supporting the nation's warfighters: (1) BCI efforts aimed at restoring neural and/or behavioral function, and (2) BCI efforts aimed at improving human training and performance. The programs discussed are synergistic and complementary to one another, and, moreover, promote interdisciplinary collaborations among researchers, engineers, and clinicians. Finally, this review includes a summary of some of the remaining challenges for the field of BCI, as well as the goals of new DARPA efforts in this domain.


title: A new hand exoskeleton device for rehabilitation using a three-layered sliding spring mechanism

abstract: In this paper, a new hand exoskeleton device using a three-layered sliding spring mechanism is presented. In contrast to state of the art hand exoskeleton mechanisms (typically link, wire or pneumatically driven), the proposed mechanism is driven through large deformations of the compliant mechanism body. The mechanism can be made compact and lightweight by adequately positioning the compliant elements. In addition, the mechanism is designed to distribute 1-DOF actuated linear motion into three rotational motions of the finger joints, which translate into natural finger flexion/extension. The primary application of the proposed mechanism is to provide robotic support during physical therapy at the hospital (e.g. Continuous Passive Motion). However, thanks to its light and wearable structure, the proposed device could also be used at home as an assistive/therapeutic device to support activities of daily living. We introduce the mechanical structure of the three-layered sliding spring mechanism, present a prototype implementation as a hand exoskeleton device, and provide a preliminary evaluation.


title: Comparative Study on Vision Based Rice Seed Varieties Identification

abstract: This paper presents a system for automated classification of rice variety for rice seed production using computer vision and image processing techniques. Rice seeds of different varieties are visually very similar in color, shape and texture that make the classification of rice seed varieties at high accuracy challenging. We investigated various feature extraction techniques for efficient rice seed image representation. We analyzed the performance of powerful classifiers on the extracted features for finding the robust one. Images of six different rice seed varieties in northern Vietnam were acquired and analyzed. Our experiments have demonstrated that the average accuracy of our classification system can reach 90.54% using Random Forest method with a simple feature extraction technique. This result can be used for developing a computer-aided machine vision system for automated assessment of rice seeds purity.


title: Trends in Obesity Among Adults in the United States, 2005 to 2014

abstract: IMPORTANCE ::: Between 1980 and 2000, the prevalence of obesity increased significantly among adult men and women in the United States; further significant increases were observed through 2003-2004 for men but not women. Subsequent comparisons of data from 2003-2004 with data through 2011-2012 showed no significant increases for men or women. ::: ::: ::: OBJECTIVE ::: To examine obesity prevalence for 2013-2014 and trends over the decade from 2005 through 2014 adjusting for sex, age, race/Hispanic origin, smoking status, and education. ::: ::: ::: DESIGN, SETTING, AND PARTICIPANTS ::: Analysis of data obtained from the National Health and Nutrition Examination Survey (NHANES), a cross-sectional, nationally representative health examination survey of the US civilian noninstitutionalized population that includes measured weight and height. ::: ::: ::: EXPOSURES ::: Survey period. ::: ::: ::: MAIN OUTCOMES AND MEASURES ::: Prevalence of obesity (body mass index ≥30) and class 3 obesity (body mass index ≥40). ::: ::: ::: RESULTS ::: This report is based on data from 2638 adult men (mean age, 46.8 years) and 2817 women (mean age, 48.4 years) from the most recent 2 years (2013-2014) of NHANES and data from 21,013 participants in previous NHANES surveys from 2005 through 2012. For the years 2013-2014, the overall age-adjusted prevalence of obesity was 37.7% (95% CI, 35.8%-39.7%); among men, it was 35.0% (95% CI, 32.8%-37.3%); and among women, it was 40.4% (95% CI, 37.6%-43.3%). The corresponding prevalence of class 3 obesity overall was 7.7% (95% CI, 6.2%-9.3%); among men, it was 5.5% (95% CI, 4.0%-7.2%); and among women, it was 9.9% (95% CI, 7.5%-12.3%). Analyses of changes over the decade from 2005 through 2014, adjusted for age, race/Hispanic origin, smoking status, and education, showed significant increasing linear trends among women for overall obesity (P = .004) and for class 3 obesity (P = .01) but not among men (P = .30 for overall obesity; P = .14 for class 3 obesity). ::: ::: ::: CONCLUSIONS AND RELEVANCE ::: In this nationally representative survey of adults in the United States, the age-adjusted prevalence of obesity in 2013-2014 was 35.0% among men and 40.4% among women. The corresponding values for class 3 obesity were 5.5% for men and 9.9% for women. For women, the prevalence of overall obesity and of class 3 obesity showed significant linear trends for increase between 2005 and 2014; there were no significant trends for men. Other studies are needed to determine the reasons for these trends.


title: Control Strategy for Dispatchable Distributed Energy Resources in Islanded Microgrids

abstract: This paper proposes a multi-input muti-output control strategy for dispatchable power electronic based distributed energy resources (DERs) in islanded mode operation of microgrids. The controller is designed based on the $dq$ model of the DER unit. Cascade, feedforward, and internal model control principle, incorporating the theory of integral control and repetitive controller, are used. The proposed controller regulates the voltage at the output of DERs under any load (balanced, unbalanced, and harmonic) variation and/or fault condition. The stability of the closed-loop system has been investigated. Enhanced phase-locked loop (EPLL) is used to determine the system variables in the $dq$ frame under unbalanced (and balanced) operating conditions. The structure of the EPLL is further modified to regulate the microgrid frequency and a stability analysis of proposed frequency control loop is presented. The performance of the proposed controller is verified through test case studies, carried out on an autonomous microgrid with single and multiple DER units.


title: QoS Support in Wireless Sensor Networks : A Survey

abstract: In this paper, we assess the state of the art of Quality of Services (QoS) support in wireless sensor networks (WSNs). Unlike traditional end-to-end multimedia applications, many non-end-to-end mission-critical applications envisioned for WSNs have brought forward new QoS requirements on the network. Further, unique characteristics of WSNs, such as extremely resource-constrained sensors, large-scale random deployment, and novel data-centric communication protocols, pose unprecedented challenges in the area of QoS support in WSNs. Thus, we first review the techniques for QoS support in traditional networks, analyze new QoS requirements in WSNs from a wide variety of applications classified by data delivery models, and propose some non-end-to-end collective QoS parameters. Next, the challenges of QoS support in this new paradigm are presented. Finally, we comment on current research efforts and identify many exciting open issues in order to stimulate more research interest in this largely unexplored area. Keywords— Wireless networks, wireless sensor networks, QoS, collective QoS


title: Deep learning for tactile understanding from visual and haptic data

abstract: Robots which interact with the physical world will benefit from a fine-grained tactile understanding of objects and surfaces. Additionally, for certain tasks, robots may need to know the haptic properties of an object before touching it. To enable better tactile understanding for robots, we propose a method of classifying surfaces with haptic adjectives (e.g., compressible or smooth) from both visual and physical interaction data. Humans typically combine visual predictions and feedback from physical interactions to accurately predict haptic properties and interact with the world. Inspired by this cognitive pattern, we propose and explore a purely visual haptic prediction model. Purely visual models enable a robot to "feel" without physical interaction. Furthermore, we demonstrate that using both visual and physical interaction signals together yields more accurate haptic classification. Our models take advantage of recent advances in deep neural networks by employing a unified approach to learning features for physical interaction and visual observations. Even though we employ little domain specific knowledge, our model still achieves better results than methods based on hand-designed features.


title: Modelling individual routines and spatio-temporal trajectories in human mobility.

abstract: Human mobility modelling is of fundamental importance in a wide range of applications, such as the developing of protocols for mobile ad hoc networks or for what-if analysis and simulation in urban ecosystems. Current generative models generally fail in accurately reproducing the individuals' recurrent daily schedules and at the same time in accounting for the possibility that individuals may break the routine and modify their habits during periods of unpredictability of variable duration. In this article we present DITRAS (DIary-based TRAjectory Simulator), a framework to simulate the spatio-temporal patterns of human mobility in a realistic way. DITRAS operates in two steps: the generation of a mobility diary and the translation of the mobility diary into a mobility trajectory. The mobility diary is constructed by a Markov model which captures the tendency of individuals to follow or break their routine. The mobility trajectory is produced by a model based on the concept of preferential exploration and preferential return. We compare DITRAS with real mobility data and synthetic data produced by other spatio-temporal mobility models and show that it reproduces the statistical properties of real trajectories in an accurate way.


title: Measuring and comparing QoE and simulator sickness of omnidirectional videos in different head mounted displays

abstract: In this paper, we evaluated and compared the integral quality of different omnidirectional contents for two head mounted displays (HMDs), namely HTC Vive and Oculus Rift. We also investigated motion sickness and head-movements. To this aim, we categorized omnidirectional contents into three categories based on the degree of motion: high, medium and low motion. For assessing simulator sickness, we used the Simulator Sickness Questionnaire for each of the contents in both HMDs. The viewing direction for subjects while watching the contents were recorded in terms of the three coordinates yaw, roll and pitch. Experimental results show that HTC Vive offers better integral quality compared to Oculus Rift. We also compared simulator sickness scores along with the behavioral data for different contents and HMDs and discussed the results in the paper.


title: Computer security and ethics awareness among IIUM students: An empirical study

abstract: People's perception and attitude towards computer ethics and information security significantly affect the way they use information technology. This is especially the case among university students who are generally regarded as major violators of computer ethics and computer security. This paper follows previous work on computer security and ethics. The paper intend to examine the level of ethical and security awareness among IT and education students. The findings of this study reveals that there are satisfactory levels of awareness among the students surveyed with slightly higher level of awareness among IT students, most likely due to security and ethics courses they offered. Also, the findings indicate that gender-wise male students reported higher level of computer security and ethics violations than their female counterparts. The paper concludes that female students are more conscious of security and ethics while using computer (e.g. Internet) than the male students. Furthermore, IT students were found to be more aware of internet security & ethics, but largely ignore this knowledge and are more engaged in unethical activities and illegal internet practices when compared with Education students.


title: AnswerBus Question Answering System

abstract: AnswerBus is an open-domain question answering system based on sentence level Web information retrieval. It accepts users' natural-language questions in English, German, French, Spanish, Italian and Portuguese and provides answers in English. Five search engines and directories are used to retrieve Web pages that are relevant to user questions. From the Web pages, AnswerBus extracts sentences that are determined to contain answers. Its current rate of correct answers to TREC-8's 200 questions is 70.5% with the average response time to the questions being seven seconds. The performance of AnswerBus in terms of accuracy and response time is better than other similar systems.


title: Planning the sports training sessions with the bat algorithm

abstract: Planning proper sports training has always been a very challenging task for coaches. In line with this, they need to have almost two special abilities: firstly, to have a lot of earlier experiences with sports training and secondly, to know the capability of their athletes very well. New ways in planning sports training have emerged with development of pervasive and mobile technologies. Recently, a GPS receiver is one of the most useful parts of each standard sports watch that enables athletes to track the duration of their sports activities and analyze them later on digital computers using GPS viewers. Most sport's watches are also capable of measuring an athlete's heart rate during activities. Both measures represent reliable data sources that can be used for planning the sports trainings by coaches. In this paper, we introduce a novel intelligent planning method for sports training sessions, where the training plans are generated on digital computers using the bat algorithm according to reliable data obtained from sports watches. Real-world experiments showed promising results that encouraged us to proceed with this research also in the future.


SciTaiL: A Textual Entailment Dataset from Science Question Answering


title: Multispectral Object Detection for Autonomous Vehicles

abstract: Recently, researchers have actively conducted studies on mobile robot technologies that involve autonomous driving. To implement an automatic mobile robot (e.g., an automated driving vehicle) in traffic, robustly detecting various types of objects such as cars, people, and bicycles in various conditions such as daytime and nighttime is necessary. In this paper, we propose the use of multispectral images as input information for object detection in traffic. Multispectral images are composed of RGB images, near-infrared images, middle-infrared images, and far-infrared images and have multilateral information as a whole. For example, some objects that cannot be visually recognized in the RGB image can be detected in the far-infrared image. To train our multispectral object detection system, we need a multispectral dataset for object detection in traffic. Since such a dataset does not currently exist, in this study we generated our own multispectral dataset. In addition, we propose a multispectral ensemble detection pipeline to fully use the features of multispectral images. The pipeline is divided into two parts: the single-spectral detection model and the ensemble part. We conducted two experiments in this work. In the first experiment, we evaluate our single-spectral object detection model. Our results show that each component in the multispectral image was individually useful for the task of object detection when applied to different types of objects. In the second experiment, we evaluate the entire multispectral object detection system and show that the mean average precision (mAP) of multispectral object detection is 13% higher than that of RGB-only object detection.


Simulation Service System with Cloud Manufacturing for Industrial Robot


title: Objective Reduction in Evolutionary Multiobjective Optimization: Theory and Applications

abstract: Many-objective problems represent a major challenge in the field of evolutionary multiobjective optimization---in terms of search efficiency, computational cost, decision making, visualization, and so on. This leads to various research questions, in particular whether certain objectives can be omitted in order to overcome or at least diminish the difficulties that arise when many, that is, more than three, objective functions are involved. This study addresses this question from different perspectives. ::: ::: First, we investigate how adding or omitting objectives affects the problem characteristics and propose a general notion of conflict between objective sets as a theoretical foundation for objective reduction. Second, we present both exact and heuristic algorithms to systematically reduce the number of objectives, while preserving as much as possible of the dominance structure of the underlying optimization problem. Third, we demonstrate the usefulness of the proposed objective reduction method in the context of both decision making and search for a radar waveform application as well as for well-known test functions.


title: Improving northbound interface communication in SDWSN

abstract: Software-Defined Wireless Sensor Networking (SDWSN) is an emerging paradigm that seeks to alleviate the inherent resource constraint issues present in Wireless Sensor Networks (WSN) by adopting a Software-Defined Networking (SDN) approach to the management of WSN. This SDWSN paradigm is said to play a crucial role in both the developing Internet of Things (IoT) paradigm and the development of smart city grids. The northbound and southbound SDWSN interfaces are important for realizing efficient network understanding and programmability, however there has been a lack of attention towards the northbound interface as most work done has been surrounding the southbound interface. Therefore some work is needed to improve the northbound interface so that it may allow for a better degree of network programmability. In order to achieve network programmability and automation, there is a need for a metadata based Application Programing Interface (API). The work done in this paper seeks to improve the northbound interface communications by addressing the issue of a metadata in REST as well as identifying potential platforms for the development of a metadata framework.


title: Autonomous Vehicle Navigation and MappingSystem

abstract: Autonomous vehicle navigation gains increasing importance in various growing application areas. In this paper we described a system it navigates the vehicle autonomously to its destination. This system provides a communication between vehicle and internet using GPRS modem. This system interfaced with OSRM open source map through internet. So we can decide the robot path from internet. In non-urban Domains such as deserts the problem of successful GPS-based navigation appears to be almost solved, navigation in urban domains particularly in the close vicinity of buildings is still a challenging problem. In such situations GPS accuracy significantly drops down due to unavailability of GPS signal. This project also improves the efficiency in navigation. This system not only relay on GPS. To improve the efficiency it uses location information from inertial sensors also. This system uses rotatable laser range finder for obstacle sensing. This is also designed in such a way that It can be monitored from anywhere through internet.


title: Kynoid: Real-time enforcement of fine-grained, user-defined, and data-centric security policies for Android

abstract: We introduce Kynoid, a real-time monitoring and enforcement framework for Android. Kynoid is based on user-defined security policies which are defined for data-items. This allows users to define temporal, spatial, and destination constraints which have to hold for single items. We introduce an innovative approach to allow for the real-time tracking and enforcement of such policies. In this way, Kynoid is the first extension for Android which enables the enforcement of security policies of data-items stored in shared resources. We outline Kynoid's architecture, present its operation and discuss it in terms of applicability, and performance. By providing a proof-of-concept implementation we further show the feasibility of our framework.


title: MPVisor: A Modular Programmable Data Plane Hypervisor

abstract: P4 is a domain-specific language designed to define the behavior of a data plane. It facilitates offloading simple Network Functions (NFs) onto a programmable data plane in order to reduce latency and improve device efficiency. However, these NFs enforced by different operators may be contradicted. Besides, dynamic management of NFs without interrupting the operation of a data plane is almost impossible. And operation expenditure (Opex) inevitably increases due to the need of expressing richer polices and resolving policy inconsistencies. Therefore, in this poster we propose MPVisor, a high performance hypervisor of P4 specific data plane with modular programmability, to enable isolation and dynamic management of NF instances without data plane interruption. We implement MPVisor and evaluate several benchmarks by comparing with equivalent baseline applications implemented in Hyper4 and native P4 switch.


title: Rescue of the Appropriative "Thought-Action-Mood" Space: Anatomy and Mast Cells Generate "Mixable" Dimensions in Language and Statistics.

abstract: BACKGROUND ::: The orthogonal axes of Thought (T), Action (A), and Mood (M) span a phase space which corresponds e.g. to the three medial thalamic areas related to three resonating cortico-subcortico-thalamo-cortical loops. The above three of several loops constitute an "appropriative engine", since within that space, as hinted to via Fig. 228 by Emil Kraepelin to illustrate bipolar mixed states, circular waves of appropriative functioning - from need via action to e.g. satisfaction - reflect a spectrum of temperamental to anxio-affective signatures of sequential appropriation waves. This neo-classical "dyn4TAM"-model also posits that a prime (thalamic) motivating system of Uncertainty-orientation (R. M. Sorrentino) regulates the temperamental balance between only 4-dimensional (D)-"Thought" (G. Halford) about effort-sparing models and high-D-"Action" (G. Rizzolatti) meaningfully related to movement. In fact the exchange across this "complexity divide" - between "grasping" action-related high-D-modules and "calculating" 4D-modules of brains - even concerns the grounding of symbolic relational "concepts. " It thus expands on the Franco-Kraepelinian "TAM"-System (FKS) which suffered a distortion by Kraepelin and the eliminative eugenicist Wilhelm Weygandt, unfortunately carried on in the "bipolar spectrum" current. Because the above loops are independently segregated they generate true dimensions. Furthermore the phenomena they jointly create become patterns, i.e. independently filled slots. Now these are irremediably destroyed at acquisition by Galtonian statistics which is detrimental to conceiving dimensional topics. ::: ::: ::: HYPOTHESIS ::: Here we posit that preponderantly "uncertainty-oriented", calculating academics unless depressed, are attracted by 4D-Thought and repulsed by intuition. They thus avoid bio-psychologically the " comprehension" of patterns. ::: ::: ::: METHOD & RESULT ::: New research initiated by dyn4TAM confirmed, that the homologous rodent sign-tracking depends on mast cells modulating the ACC-loop for "Action." ::: ::: ::: CONCLUSION ::: The "complexity divide" warrants more attention in clinical and pure cognitive sciences and should include a "psychology of statistics".


WebChild 2.0: Fine-Grained Commonsense Knowledge Distillation


title: Spectral properties of the Laplacian of multiplex networks

abstract: One of the more challenging tasks in the understanding of dynamical properties of models on top of complex networks is to capture the precise role of multiplex topologies. In a recent paper, Gomez et al. [Phys. Rev. Lett. 101, 028701 (2013)] proposed a framework for the study of diffusion processes in such networks. Here, we extend the previous framework to deal with general configurations in several layers of networks, and analyze the behavior of the spectrum of the Laplacian of the full multiplex. We derive an interesting decoupling of the problem that allow us to unravel the role played by the interconnections of the multiplex in the dynamical processes on top of them. Capitalizing on this decoupling we perform an asymptotic analysis that allow us to derive analytical expressions for the full spectrum of eigenvalues. This spectrum is used to gain insight into physical phenomena on top of multiplex, specifically, diffusion processes and synchronizability.


title: A Structure-Synthesis Image Inpainting Algorithm Based on Morphological Erosion Operation

abstract: Image inpainting provides a means to restore damaged region of an image, such that the image looks complete and natural after the inpainting process. This paper presents a new inpainting algorithm, which implements the filling of damaged region based on morphological erosion and structure feature replication. The method, which is based on a structure/texture feature matching algorithm, can retain isophote continuity by propagating both texture and structure characteristics information of the known patch into the damaged region, and output a complete, natural-looking and non-blurred image. By implementing region-filling through morphological erosion, several pixels instead of one can be restored at every inpainting step, making the method faster than many traditional texture synthesis inpainting algorithms. We demonstrate through several examples the effectiveness of the algorithm in removing large occluding objects as well as thin scratches.


title: Protecting Your Right: Verifiable Attribute-Based Keyword Search with Fine-Grained Owner-Enforced Search Authorization in the Cloud

abstract: Search over encrypted data is a critically important enabling technique in cloud computing, where encryption-before-outsourcing is a fundamental solution to protecting user data privacy in the untrusted cloud server environment. Many secure search schemes have been focusing on the single-contributor scenario, where the outsourced dataset or the secure searchable index of the dataset are encrypted and managed by a single owner, typically based on symmetric cryptography. In this paper, we focus on a different yet more challenging scenario where the outsourced dataset can be contributed from multiple owners and are searchable by multiple users, i.e., multi-user multi-contributor case. Inspired by attribute-based encryption (ABE), we present the first attribute-based keyword search scheme with efficient user revocation (ABKS-UR) that enables scalable fine-grained (i.e., file-level) search authorization. Our scheme allows multiple owners to encrypt and outsource their data to the cloud server independently. Users can generate their own search capabilities without relying on an always online trusted authority. Fine-grained search authorization is also implemented by the owner-enforced access policy on the index of each file. Further, by incorporating proxy re-encryption and lazy re-encryption techniques, we are able to delegate heavy system update workload during user revocation to the resourceful semi-trusted cloud server. We formalize the security definition and prove the proposed ABKS-UR scheme selectively secure against chosen-keyword attack. To build confidence of data user in the proposed secure search system, we also design a search result verification scheme. Finally, performance evaluation shows the efficiency of our scheme.


title: Application Performance Monitoring: Trade-Off between Overhead Reduction and Maintainability

abstract: Monitoring of a software system provides insights into its runtime behavior, improving system analysis and comprehension. System-level monitoring approaches focus, e.g., on network monitoring, providing information on externally visible system behavior. Application-level performance monitoring frameworks, such as Kieker or Dapper, allow to observe the internal application behavior, but introduce runtime overhead depending on the number of instrumentation probes. ::: ::: We report on how we were able to significantly reduce the runtime overhead of the Kieker monitoring framework. For achieving this optimization, we employed micro-benchmarks with a structured performance engineering approach. During optimization, we kept track of the impact on maintainability of the framework. In this paper, we discuss the emerged trade-off between performance and maintainability in this context. ::: ::: To the best of our knowledge, publications on monitoring frameworks provide none or only weak performance evaluations, making comparisons cumbersome. However, our micro-benchmark, presented in this paper, provides a basis for such comparisons. Our experiment code and data are available as open source software such that interested researchers may repeat or extend our experiments for comparison on other hardware platforms or with other monitoring frameworks.


title: Bayesian online clustering of eye movement data

abstract: The task of automatically tracking the visual attention in dynamic visual scenes is highly challenging. To approach it, we propose a Bayesian online learning algorithm. As the visual scene changes and new objects appear, based on a mixture model, the algorithm can identify and tell visual saccades (transitions) from visual fixation clusters (regions of interest). The approach is evaluated on real-world data, collected from eye-tracking experiments in driving sessions.


Naive Bayes Spam Filtering Using Word-Position-Based Attributes


title: Attacking NTP's Authenticated Broadcast Mode

abstract: We identify two attacks on the Network Time Protocol (NTP)'s cryptographically-authenticated broadcast mode. First, we present a replay attack that allows an on-path attacker to indefinitely stick a broadcast client to a specific time. Second, we present a denial-of-service (DoS) attack that allows an off-path attacker to prevent a broadcast client from ever updating its system clock; to do this, the attacker sends the client a single malformed broadcast packet per query interval. Our DoS attack also applies to all other NTP modes that are `ephemeral' or `preemptable' (including manycast, pool, etc). We then use network measurements to give evidence that NTP's broadcast and other ephemeral/preemptable modes are being used in the wild. We conclude by discussing why NTP's current implementation of symmetric-key cryptographic authentication does not provide security in broadcast mode, and make some recommendations to improve the current state of affairs.


title: Coverage and Its Discontents

abstract: Everyone wants to know one thing about a test suite: will it detect enough bugs? Unfortunately, in most settings that matter, answering this question directly is impractical or impossible. Software engineers and researchers therefore tend to rely on various measures of code coverage (where mutation testing is considered a form of syntactic coverage). A long line of academic research efforts have attempted to determine whether relying on coverage as a substitute for fault detection is a reasonable solution to the problems of test suite evaluation. This essay argues that the profusion of coverage-related literature is in part a sign of an underlying uncertainty as to what exactly it is that measuring coverage should achieve, as well as how we would know if it can, in fact, achieve it. We propose some solutions and mitigations, but the primary focus of this essay is to clarify the state of current confusions regarding this key problem for effective software testing.


title: Active learning based news veracity detection with feature weighting and deep-shallow fusion

abstract: The objective of a news veracity detection system is to identify various types of potentially misleading or false information, typically in a digital platform. A critical challenge in this scenario is that there are large volumes of data available online. However, obtaining samples with annotations (i.e. ground-truth labels) is difficult and a known limiting factor for many data analytic tasks including the current problem of news veracity detection. In this paper, we propose a human-machine collaborative learning system to evaluate the veracity of a news content, with a limited amount of annotated data samples. In a semi-supervised scenario, an initial classifier is learnt on a small, limited amount of the annotated data followed by an interactive approach to gradually update the model by shortlisting only relevant samples from the large pool of unlabeled data that are most likely to improve the classifier performance. Our prioritized active learning solution achieves faster convergence in terms of the classification performance, while requiring about 1–2 orders of magnitude fewer annotated samples compared to fully supervised solutions to attain a reasonably acceptable accuracy of nearly 80%. Unlike traditional deep learning architecture, the proposed active learning based deep model designed with a smaller number of more localized filters per layer can efficiently learn from small relevant sample batches that can effectively improve performance in the weakly-supervised learning environment and thus is more suitable for several practical applications. An effective dynamic domain adaptive feature weighting scheme can adjust the relative importance of feature dimensions iteratively. Insightful initial feedback gathered from two independent learning modules (a NLP shallow feature based classifier and a deep classifier), modeled to capture complementary information about data characteristics are finally fused together to achieve an impressive 25% average gain in the detection performance.


title: Comparative genomic analysis of mitogen activated protein kinase gene family in grapevine

abstract: Mitogen activated protein kinases (MAPKs) are important proteins involved in the signal transduction of extracellular information to intracellular targets, and play a crucial role in the response to biotic and abiotic stresses. Although Arabidopsis MAPKs are used for identification of the putative MAPKs in higher plants, no grapevine MAPK gene nomenclature has yet been appeared in the literature. In this study, we have identified 12 members of grapevine MAPK gene (VvMPK) family via In-silico analysis of current grapevine genome database. The structural comparison of 12 VvMPKs through the analysis of chromosome locations, sequence annotation and paralogous gene pair indicated that VvMPKs have evolved by segmental duplication, rather than by tandem amplification. Although further functional analysis of VvMPKs through in vivo and in vivo experiments will be required, our study provides the basis for future research on the diverse signaling pathways medicated by MAPKs in grapevine.


title: Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

abstract: This paper proposes a two-phase scheme for removing salt-and-pepper impulse noise. In the first phase, an adaptive median filter is used to identify pixels which are likely to be contaminated by noise (noise candidates). In the second phase, the image is restored using a specialized regularization method that applies only to those selected noise candidates. In terms of edge preservation and noise suppression, our restored images show a significant improvement compared to those restored by using just nonlinear filters or regularization methods only. Our scheme can remove salt-and-pepper-noise with a noise level as high as 90%.


title: A novel approach to on-line handwriting recognition based on bidirectional long short-term memory networks

abstract: In this paper we introduce a new connectionist approach to on-line handwriting recognition and address in particular the problem of recognizing handwritten whiteboard notes. The approach uses a bidirectional recurrent neural network with the long short-term memory architecture. We use a recently introduced objective function, known as Connectionist Temporal Classification (CTC), that directly trains the network to label unsegmented sequence data. Our new system achieves a word recognition rate of 74.0%, compared with 65.4% using a previously developed HMMbased recognition system.


title: People Tracking with Mobile Robots Using Sample-Based Joint Probabilistic Data Association Filters

abstract: One of the goals in the field of mobile robotics is the development of mobile platforms which operate in populated environments. For many tasks it is therefore highly desirable that a robot can track the positions of the humans in its surrounding. In this paper we introduce sample-based joint probabilistic data association filters as a new algorithm to track multiple moving objects. Our method applies Bayesian filtering to adapt the tracking process to the number of objects in the perceptual range of the robot. The approach has been implemented and tested on a real robot using laser-range data. We present experiments illustrating that our algorithm is able to robustly keep track of multiple people. The experiments furthermore show that the approach outperforms other techniques developed so far.


title: Artificial Neural Networks Improve the Accuracy of Cancer Survival Prediction

abstract: BACKGROUND ::: ::: The TNM staging system originated as a response to the need for an accurate, consistent, universal cancer outcome prediction system. Since the TNM staging system was introduced in the 1950s, new prognostic factors have been identified and new methods for integrating prognostic factors have been developed. This study compares the prediction accuracy of the TNM staging system with that of artificial neural network statistical models. ::: ::: ::: ::: METHODS ::: ::: For 5-year survival of patients with breast or colorectal carcinoma, the authors compared the TNM staging system's predictive accuracy with that of artificial neural networks (ANN). The area under the receiver operating characteristic curve, as applied to an independent validation data set, was the measure of accuracy. ::: ::: ::: ::: RESULTS ::: ::: For the American College of Surgeons' Patient Care Evaluation (PCE) data set, using only the TNM variables (tumor size, number of positive regional lymph nodes, and distant metastasis), the artificial neural network's predictions of the 5-year survival of patients with breast carcinoma were significantly more accurate than those of the TNM staging system (TNM, 0.720; ANN, 0.770; P < 0.001). For the National Cancer Institute's Surveillance, Epidemiology, and End Results breast carcinoma data set, using only the TNM variables, the artificial neural network's predictions of 10-year survival were significantly more accurate than those of the TNM staging system (TNM, 0.692; ANN, 0.730; P < 0.01). For the PCE colorectal data set, using only the TNM variables, the artificial neural network's predictions of the 5-year survival of patients with colorectal carcinoma were significantly more accurate than those of the TNM staging system (TNM, 0.737; ANN, 0.815; P < 0.001). Adding commonly collected demographic and anatomic variables to the TNM variables further increased the accuracy of the artificial neural network's predictions of breast carcinoma survival (0.784) and colorectal carcinoma survival (0.869). ::: ::: ::: ::: CONCLUSIONS ::: ::: Artificial neural networks are significantly more accurate than the TNM staging system when both use the TNM prognostic factors alone. New prognostic factors can be added to artificial neural networks to increase prognostic accuracy further. These results are robust across different data sets and cancer sites. Cancer 1997; 79:857-62. © 1997 American Cancer Society.


title: Siddhi: a second look at complex event processing architectures

abstract: Today there are so much data being available from sources like sensors (RFIDs, Near Field Communication), web activities, transactions, social networks, etc. Making sense of this avalanche of data requires efficient and fast processing. Processing of high volume of events to derive higher-level information is a vital part of taking critical decisions, and Complex Event Processing (CEP) has become one of the most rapidly emerging fields in data processing. e-Science use-cases, business applications, financial trading applications, operational analytics applications and business activity monitoring applications are some use-cases that directly use CEP. This paper discusses different design decisions associated with CEP Engines, and proposes some approaches to improve CEP performance by using more stream processing style pipelines. Furthermore, the paper will discuss Siddhi, a CEP Engine that implements those suggestions. We present a performance study that exhibits that the resulting CEP Engine--Siddhi--has significantly improved performance. Primary contributions of this paper are performing a critical analysis of the CEP Engine design and identifying suggestions for improvements, implementing those improvements through Siddhi, and demonstrating the soundness of those suggestions through empirical evidence.


title: Carrageenans from the Red Seaweed Sarconema filiforme Attenuate Symptoms of Diet-Induced Metabolic Syndrome in Rats

abstract: Carrageenans are thickening and gelling agents that may provide health benefits. Iota (ι)-carrageenan, a linear sulfated polysaccharide, is produced by the red seaweed, Sarconema filiforme. This study investigated the potential of this seaweed as a functional food for the reversal of metabolic syndrome and possible mechanisms. Male Wistar rats were divided into four groups in a 16-week protocol: corn starch diet-fed rats (C); C rats supplemented with 5% S. filiforme for the last 8 weeks (CSF); high-carbohydrate, high-fat diet-fed rats (H); and H rats supplemented with 5% S. filiforme for the last 8 weeks (HSF). S. filiforme was produced in tank-based aquaculture yielding 27 g dry weight/day/m2 of culture area. H rats developed obesity, hypertension, dyslipidaemia, glucose intolerance, fatty liver and increased left ventricular collagen deposition. S. filiforme supplementation decreased body weight, abdominal and liver fat, systolic blood pressure, plasma total cholesterol concentrations, and plasma activities of alanine transaminase and aspartate transaminase. S. filiforme supplementation modulated gut microbiota without changing the Firmicutes to Bacteroidetes ratio. S. filiforme improved symptoms of high-carbohydrate, high-fat diet-induced metabolic syndrome in rats. Possible mechanisms include a reduced infiltration of inflammatory cells into organs as well as prebiotic actions in the gastrointestinal tract.


title: Flow in games (and everything else)

abstract: A well-designed game transports its players to their personal Flow Zones, delivering genuine feelings of pleasure and happiness.


Merging virtual objects with the real world: seeing ultrasound imagery within the patient


title: Inductively-Loaded Yagi-Uda Antenna With Cylindrical Cover for Size Reduction at VHF-UHF Bands

abstract: A new technique is employed to reduce the size of Yagi-Uda antennas. The technique consists of adding short circuited cylindrical covers to the structure, making the elements be inductively loaded, and as a result, increase the electric length. A prototype resonating at 660 MHz is developed, and compared to a conventional Yagi-Uda antenna. An effective area reduction of 35% is achieved without decreasing, considerably, the gain, preserving the bandwidth, and front to back lobe ratio.


UnibucKernel: An Approach for Arabic Dialect Identification Based on Multiple String Kernels.


title: Mathematical Modeling and Nonlinear Controller Design for a Novel Electrohydraulic Power-Steering System

abstract: This paper is concerned with the mathematical modeling and nonlinear controller design of a novel electrohydraulic closed-center power-steering system. After a short introduction to the requirements of modern power-steering systems, the construction of the power-steering system under consideration will be described. The main advantage of this construction is the enhancement of the overall energetic efficiency of the steering system and the possibility of a variable steering assistance while keeping the good steering feeling of traditional hydraulic steering systems. Based on a detailed mathematical model of the essential components of the system, it is shown how some of the parameters of the system can be chosen to achieve an optimal dynamic behavior of the closed-loop system. The controller design proceeds in two steps: first, a nonlinear controller for the assistance force based on the differential flatness property of the system is designed, and afterwards, a steering torque controller using an impedance matching design is derived. Finally, measurement results of a test stand show the good performance and the robust behavior of the proposed control strategy


title: Online and incremental machine learning approaches for IC yield improvement

abstract: In the competitive semiconductor manufacturing industry where large amounts of data are generated, data driven quality control technologies are gaining increasing importance. In this work, we build machine learning models for high yield and time varying semiconductor manufacturing processes. Challenges include class imbalance and concept drift. Batch, online and incremental learning frameworks are developed to overcome these challenges. We study the packaging and testing process in chip stack flash memory as an application, and show the possibility of yield improvement with machine learning based classifiers detecting bad dies before packaging. Experimental results demonstrate significant yield improvement potential using real data from industry. Without concept drift, for stacks of 8 dies, an approximately 9% yield improvement can be achieved. In a longer period of time with realistic concept drift, our incremental learning approach achieves approximately 1.4% yield improvement in the 8 die stack case and 3.4% in the 16 die stack case.


title: Deep learning and its application to medical image segmentation

abstract: One of the most common tasks in medical imaging is semantic segmentation. Achieving this segmentation automatically has been an active area of research, but the task has been proven very challenging due to the large variation of anatomy across different patients. However, recent advances in deep learning have made it possible to significantly improve the performance of image recognition and semantic segmentation methods in the field of computer vision. Due to the data driven approaches of hierarchical feature learning in deep learning frameworks, these advances can be translated to medical images without much difficulty. Several variations of deep convolutional neural networks have been successfully applied to medical images. Especially fully convolutional architectures have been proven efficient for segmentation of 3D medical images. In this article, we describe how to build a 3D fully convolutional network (FCN) that can process 3D images in order to produce automatic semantic segmentations. The model is trained and evaluated on a clinical computed tomography (CT) dataset and shows state-of-the-art performance in multi-organ segmentation.


title: Face Sketch Synthesis Style Similarity:A New Structure Co-occurrence Texture Measure

abstract: Existing face sketch synthesis (FSS) similarity measures are sensitive to slight image degradation (e.g., noise, blur). However, human perception of the similarity of two sketches will consider both structure and texture as essential factors and is not sensitive to slight ("pixel-level") mismatches. Consequently, the use of existing similarity measures can lead to better algorithms receiving a lower score than worse algorithms. This unreliable evaluation has significantly hindered the development of the FSS field. To solve this problem, we propose a novel and robust style similarity measure called Scoot-measure (Structure CO-Occurrence Texture Measure), which simultaneously evaluates"block-level"spatial structure and co-occurrence texture statistics. In addition, we further propose 4 new meta-measures and create 2 new datasets to perform a comprehensive evaluation of several widely-used FSS measures on two large databases. Experimental results demonstrate that our measure not only provides a reliable evaluation but also achieves significantly improved performance. Specifically, the study indicated a higher degree (78.8%) of correlation between our measure and human judgment than the best prior measure (58.6%). Our code will be made available.