title: Extracting query facets from search results

abstract: Web search queries are often ambiguous or multi-faceted, which makes a simple ranked list of results inadequate. To assist information finding for such faceted queries, we explore a technique that explicitly represents interesting facets of a query using groups of semantically related terms extracted from search results. As an example, for the query ``baggage allowance'', these groups might be different airlines, different flight types (domestic, international), or different travel classes (first, business, economy). We name these groups query facets and the terms in these groups facet terms. We develop a supervised approach based on a graphical model to recognize query facets from the noisy candidates found. The graphical model learns how likely a candidate term is to be a facet term as well as how likely two terms are to be grouped together in a query facet, and captures the dependencies between the two factors. We propose two algorithms for approximate inference on the graphical model since exact inference is intractable. Our evaluation combines recall and precision of the facet terms with the grouping quality. Experimental results on a sample of web queries show that the supervised method significantly outperforms existing approaches, which are mostly unsupervised, suggesting that query facet extraction can be effectively learned.


title: Brushless AC interior-permanent magnet motor design: Comparison of slot/pole combinations and distributed vs. concentrated windings

abstract: This paper compares the attributes of 36 slot, 33 slot and 12 slot brushless interior permanent magnet motor designs, each with an identical 10 pole interior magnet rotor. The aim of the paper is to quantify the trade-offs between alternative distributed and concentrated winding configurations taking into account aspects such as thermal performance, field weakening behaviour, acoustic noise, and efficiency. It is found that the concentrated 12 slot design gives the highest theoretical performance however significant rotor losses are found during testing and a large amount of acoustic noise and vibration is generated. The 33 slot design is found to have marginally better performance than the 36 slot but it also generates some unbalanced magnetic pull on the rotor which may lead to mechanical issues at higher speeds.


title: The role of deliberate practice in the acquisition of expert performance

abstract: because observed behavior is the result of interactions between environmental factors and genes during the extended period of development. Therefore, to better understand expert and exceptional performance, we must require that the account specify the different environmental factors that could selectively promote and facilitate the achievement of such performance. In addition, recent research on expert performance and expertise (Chi, Glaser, & Farr, 1988; Ericsson & Smith, 1991a) has shown that important characteristics of experts' superior performance are acquired through experience and that the effect of practice on performance is larger than earlier believed possible. For this reason, an account of exceptional performance must specify the environmental circumstances, such as the duration and structure of activities, and necessary minimal biological attributes that lead to the acquisition of such characteristics and a corresponding level of performance. An account that explains how a majority of individuals can attain a given level of expert performance might seem inherently unable to explain the exceptional performance of only a small number of individuals. However, if such an empirical account could be empirically supported, then the extreme characteristics of experts could be viewed as having been acquired through learning and adaptation, and studies of expert performance could provide unique insights into the possibilities and limits of change in cognitive capacities and bodily functions. In this article we propose a theoretical framework that explains expert performance in terms of acquired characteristics resulting from extended deliberate practice and that limits the role of innate (inherited) characteristics to general levels of activity and emotionality. We provide empirical support from two new studies and from already published evidence on expert performance in many different domains.


title: Machine learning-based run-time anomaly detection in software systems: An industrial evaluation

abstract: Anomalies are an inevitable occurrence while operating enterprise software systems. Traditionally, anomalies are detected by threshold-based alarms for critical metrics, or health probing requests. However, fully automated detection in complex systems is challenging, since it is very difficult to distinguish truly anomalous behavior from normal operation. To this end, the traditional approaches may not be sufficient. Thus, we propose machine learning classifiers to predict the system's health status. We evaluated our approach in an industrial case study, on a large, real-world dataset of 7.5 • 106 data points for 231 features. Our results show that recurrent neural networks with long short-term memory (LSTM) are more effective in detecting anomalies and health issues, as compared to other classifiers. We achieved an area under precision-recall curve of 0.44. At the default threshold, we can automatically detect 70% of the anomalies. Despite the low precision of 31 %, the rate in which false positives occur is only 4 %.


title: Process Mining: Discovering Direct Successors in Process Logs

abstract: Workflow management technology requires the existence of explicit process models, i.e. a completely specified workflow design needs to be developed in order to enact a given workflow process. Such a workflow design is time consuming and often subjective and incomplete. We propose a learning method that uses the workflow log, which contains information about the process as it is actually being executed. In our method we will use a logistic regression model to discover the direct connections between events of a realistic not complete workflow log with noise. Experimental results are used to show the usefulness and limitations of the presented method.


title: A momentum-based balance controller for humanoid robots on non-level and non-stationary ground

abstract: Recent research suggests the importance of controlling rotational dynamics of a humanoid robot in balance maintenance and gait. In this paper, we present a novel balance strategy that controls both linear and angular momentum of the robot. The controller’s objective is defined in terms of the desired momenta, allowing intuitive control of the balancing behavior of the robot. By directly determining the ground reaction force (GRF) and the center of pressure (CoP) at each support foot to realize the desired momenta, this strategy can deal with non-level and non-stationary grounds, as well as different frictional properties at each foot-ground contact. When the robot cannot realize the desired values of linear and angular momenta simultaneously, the controller attributes higher priority to linear momentum at the cost of compromising angular momentum. This creates a large rotation of the upper body, reminiscent of the balancing behavior of humans. We develop a computationally efficient method to optimize GRFs and CoPs at individual foot by sequentially solving two small-scale constrained linear least-squares problems. The balance strategy is demonstrated on a simulated humanoid robot under experiments such as recovery from unknown external pushes and balancing on non-level and moving supports.


title: Social Cognitive Neuroscience: A Review of Core Processes

abstract: Social cognitive neuroscience examines social phenomena and processes using cognitive neuroscience research tools such as neuroimaging and neuropsychology. This review examines four broad areas of research within social cognitive neuroscience: (a) understanding others, (b) understanding oneself, (c) controlling oneself, and (d ) the processes that occur at the interface of self and others. In addition, this review highlights two core-processing distinctions that can be neurocognitively identified across all of these domains. The distinction between automatic versus controlled processes has long been important to social psychological theory and can be dissociated in the neural regions contributing to social cognition. Alternatively, the differentiation between internally-focused processes that focus on one’s own or another’s mental interior and externally-focused processes that focus on one’s own or another’s visible features and actions is a new distinction. This latter distinction emerges from social cognitive neuroscience investigations rather than from existing psychological theories demonstrating that social cognitive neuroscience can both draw on and contribute to social psychological theory.


title: When Is "Nearest Neighbor" Meaningful?

abstract: We explore the effect of dimensionality on the nearest neighbor problem. We show that under a broad set of conditions (much broader than independent and identically distributed dimensions), as dimensionality increases, the distance to the nearest data point approaches the distance to the farthest data point. To provide a practical perspective, we present empirical results on both real and synthetic data sets that demonstrate that this effect can occur for as few as 10-15 dimensions. These results should not be interpreted to mean that high-dimensional indexing is never meaningful; we illustrate this point by identifying some high-dimensional workloads for which this effect does not occur. However, our results do emphasize that the methodology used almost universally in the database literature to evaluate high-dimensional indexing techniques is flawed, and should be modified. In particular, most such techniques proposed in the literature are not evaluated versus simple linear scan, and are evaluated over workloads for which nearest neighbor is not meaningful. Often, even the reported experiments, when analyzed carefully, show that linear scan would outperform the techniques being proposed on the workloads studied in high (10-15) dimensionality!.


title: Camera Self-Calibration: Theory and Experiments

abstract: The problem of finding the internal orientation of a camera (camera calibration) is extremely important for practical applications. In this paper a complete method for calibrating a camera is presented. In contrast with existing methods it does not require a calibration object with a known 3D shape. The new method requires only point matches from image sequences. It is shown, using experiments with noisy data, that it is possible to calibrate a camera just by pointing it at the environment, selecting points of interest and then tracking them in the image as the camera moves. It is not necessary to know the camera motion.


title: Detrital zircons from the Hronicum Carboniferous–Permian sandstones (Western Carpathians, Slovakia): depositional age and provenance

abstract: For the assessment of depositional age and provenance of the Hronicum Unit Pennsylvanian to Permian siliciclastic sediments, SIMS (SHRIMP) U–Pb analyses have been carried out on detrital zircons. To constrain the presumed provenance of the Hronicum Unit sediments five samples have been taken from two lithostratigraphic units, the Nižna Boca and the Malužina formations. The detrital-zircon age spectrum demonstrates two prominent populations, the first, Late Pennsylvanian–Early Cisuralian (288–309 Ma) and the second, Famennian—Tournaisian (345–371 Ma). The probability density age peak at 297 Ma permits to estimate the maximum sedimentation age of the Nižna Boca Fm. to younger than Asselian and the beginning of the Malužina Formation sedimentation has been assessed at least in Sakmarian. The sedimentation persisted, with the exception of a short break in the Wordian/Capitanian, through the Lopingian. Smaller zircon age clusters range within 446–541 Ma, with a dominance of the Cambrian detrital zircons (491–541 Ma). The Precambrian time-span is dominated by the two groups of detrital zircons; Ediacaran in the range of 545–612 Ma and Paleoproterozoic–Neoarchean ranging from 1.8 to 2.8 Ga. The documented zircon ages reflect derivation of the Hronicum sediments from the Variscan Western Carpathian crystalline basement, the Late Devonian/Early Mississippian magmatic arc. These data support close relations of the presumed Hronicum basement with the Armorican terranes and derivation from the Cadomian Belt, associated with the West African Craton during Neoproterozoic and Cambrian time.


title: Multiresolution Tree Networks for 3D Point Cloud Processing

abstract: We present multiresolution tree-structured networks to process point clouds for 3D shape understanding and generation tasks. Our network represents a 3D shape as a set of locality-preserving 1D ordered list of points at multiple resolutions. This allows efficient feed-forward processing through 1D convolutions, coarse-to-fine analysis through a multi-grid architecture, and it leads to faster convergence and small memory footprint during training. The proposed tree-structured encoders can be used to classify shapes and outperform existing point-based architectures on shape classification benchmarks, while tree-structured decoders can be used for generating point clouds directly and they outperform existing approaches for image-to-shape inference tasks learned using the ShapeNet dataset. Our model also allows unsupervised learning of point-cloud based shapes by using a variational autoencoder, leading to higher-quality generated shapes.


Multi-Scale Convolutional Architecture for Semantic Segmentation


title: Measuring information systems service quality: concerns for a complete canvas

abstract: This paper responds to the research note in this issue by Van Dyke et al. concerning the use of SERVQUAL, an instrument to measure service quality, and its use in the IS domain. This paper attempts to balance some of the arguments they raise from the marketing literature on the topic with the well-documented counterarguments of SERVQUAL's developers, as well as our own research evidence and observations in an IS-specific environment. Specifically, evidence is provided to show that the service quality perceptions-expectations subtraction in SERVQUAL is far more rigorously grounded than Van Dyke et al. suggest; that the expectations construct, while potentially ambiguous, is generally a vector in the case of an IS department; and that the dimensions of service quality seem to be as applicable to the IS department as to any other organizational setting. Then, the paper demonstrates that the problems of reliability of difference score calculations in SERVQUAL are not nearly as serious as Van Dyke et al. suggest; that while perceptions-only measurement of service quality might have marginally better predictive and convergent validity, this comes at considerable expense to managerial diagnostics; and reiterate some of the problems of dimensional instability found in our previous research, highlighted by Van Dyke et al. and discussed in many other studies of SERVQUAL across a range of settings. Finally, four areas for further research in this area are identified.


title: Person Attribute Recognition with a Jointly-Trained Holistic CNN Model

abstract: This paper addresses the problem of human visual attribute recognition, i.e., the prediction of a fixed set of semantic attributes given an image of a person. Previous work often considered the different attributes independently from each other, without taking advantage of possible dependencies between them. In contrast, we propose a method to jointly train a CNN model for all attributes that can take advantage of those dependencies, considering as input only the image without additional external pose, part or context information. We report detailed experiments examining the contribution of individual aspects, which yields beneficial insights for other researchers. Our holistic CNN achieves superior performance on two publicly available attribute datasets improving on methods that additionally rely on pose-alignment or context. To support further evaluations, we present a novel dataset, based on realistic outdoor video sequences, that contains more than 27,000 pedestrians annotated with 10 attributes. Finally, we explore design options to embrace the N/A labels inherently present in this task.


title: A decision theory based tool for detection of encrypted WebRTC traffic

abstract: The detection of encrypted streamed traffic (like VoIP or Video) is an increasingly important issue for authorities involved in lawful interception. Aside from well established technologies like Skype, Facetime and MSN Messenger a new one is recently spreading: Web Real-Time Communication (WebRTC), which, with the support of powerful encryption methods as DTLS, offers capabilities for encrypted streaming voice and video without the need of installing a specific application but using a common browser like Chrome, Firefox or Opera. WebRTC traffic cannot be detected through methods of semantic recognition since it does not exhibit a distinguishable sequence of information pieces and hence statistical recognition methods are called for. In this paper we propose and evaluate a decision theory based system allowing to recognize encrypted WebRTC traffic by means of an open-source machine learning environment: Weka.


title: Mersenne twister-based RFID authentication protocol

abstract: This work presents an ultra-lightweight, cryptographic, mutual authentication protocol for radio-frequency identification (RFID) tags. The proposed scheme is more secure than its predecessors. The vulnerabilities of previous schemes based on triangular functions and rotation have been demonstrated in traditional and rotational cryptanalysis. In this paper, we summarize the successful attacks on previous schemes and demonstrate further attacks on 3 recent ultra-lightweight protocols. Next, we present a proposal that resists all of the known passive attacks. The proposal obeys the properties and rules of addition-rotation-XOR with constants systems. The proposed scheme inserts parts of advanced encryption standard S-boxes into the temperings of the Mersenne twister, which is used as a deterministic random number generator. The proposal is supported by extensive performance and security analysis. Apart from previous work, our scheme is compared and contrasted against the results of some popular hashing and encryption algorithms, recommended for RFID tags.


title: Detection of Fragmented Rectangular Enclosures in Very High Resolution Remote Sensing Images

abstract: We develop an approach for the detection of ruins of livestock enclosures (LEs) in alpine areas captured by high-resolution remotely sensed images. These structures are usually of approximately rectangular shape and appear in images as faint fragmented contours in complex background. We address this problem by introducing a rectangularity feature that quantifies the degree of alignment of an optimal subset of extracted linear segments with a contour of rectangular shape. The rectangularity feature has high values not only for perfectly regular enclosures but also for ruined ones with distorted angles, fragmented walls, or even a completely missing wall. Furthermore, it has a zero value for spurious structures with less than three sides of a perceivable rectangle. We show how the detection performance can be improved by learning a linear combination of the rectangularity and size features from just a few available representative examples and a large number of negatives. Our approach allowed detection of enclosures in the Silvretta Alps that were previously unknown. A comparative performance analysis is provided. Among other features, our comparison includes the state-of-the-art features that were generated by pretrained deep convolutional neural networks (CNNs). The deep CNN features, although learned from a very different type of images, provided the basic ability to capture the visual concept of the LEs. However, our handcrafted rectangularity-size features showed considerably higher performance.


title: Torque and Flux Weakening Control with MTPV for Interior Permanent Magnet Synchronous Motor

abstract: This paper proposes an improved stator flux control algorithm based on the torque feedforward control technique for interior permanent magnet synchronous motor (IPMSM). The proposed flux linkage control algorithm can prevent the d and q- axis voltages from saturation and improve the dynamic behavior. A lookup table is used in the torque feedforward control technique, which outputs the desired d and q-axis currents according to the two inputs: torque command and desired stator flux linkage magnitude. The method of constructing lookup table is mentioned. Simulations are carried out. The results prove the effectiveness of the proposed method.


title: Tree Colors: Color Schemes for Tree-Structured Data

abstract: We present a method to map tree structures to colors from the Hue-Chroma-Luminance color model, which is known for its well balanced perceptual properties. The Tree Colors method can be tuned with several parameters, whose effect on the resulting color schemes is discussed in detail. We provide a free and open source implementation with sensible parameter defaults. Categorical data are very common in statistical graphics, and often these categories form a classification tree. We evaluate applying Tree Colors to tree structured data with a survey on a large group of users from a national statistical institute. Our user study suggests that Tree Colors are useful, not only for improving node-link diagrams, but also for unveiling tree structure in non-hierarchical visualizations.


title: Protecting people from phishing: the design and evaluation of an embedded training email system

abstract: Phishing attacks, in which criminals lure Internet users to websites that impersonate legitimate sites, are occurring with increasing frequency and are causing considerable harm to victims. In this paper we describe the design and evaluation of an embedded training email system that teaches people about phishing during their normal use of email. We conducted lab experiments contrasting the effectiveness of standard security notices about phishing with two embedded training designs we developed. We found that embedded training works better than the current practice of sending security notices. We also derived sound design principles for embedded training systems.


title: Fluorescent protein‐mediated colour polymorphism in reef corals: multicopy genes extend the adaptation/acclimatization potential to variable light environments

abstract: The genomic framework that enables corals to adjust to unfavourable conditions is crucial for coral reef survival in a rapidly changing climate. We have explored the striking intraspecific variability in the expression of coral pigments from the green fluorescent protein (GFP) family to elucidate the genomic basis for the plasticity of stress responses among reef corals. We show that multicopy genes can greatly increase the dynamic range over which corals can modulate transcript levels in response to the light environment. Using the red fluorescent protein amilFP597 in the coral Acropora millepora as a model, we demonstrate that its expression increases with light intensity, but both the minimal and maximal gene transcript levels vary markedly among colour morphs. The pigment concentration in the tissue of different morphs is strongly correlated with the number of gene copies with a particular promoter type. These findings indicate that colour polymorphism in reef corals can be caused by the environmentally regulated expression of multicopy genes. High-level expression of amilFP597 is correlated with reduced photodamage of zooxanthellae under acute light stress, supporting a photoprotective function of this pigment. The cluster of light-regulated pigment genes can enable corals to invest either in expensive high-level pigmentation, offering benefits under light stress, or to rely on low tissue pigment concentrations and use the conserved resources for other purposes, which is preferable in less light-exposed environments. The genomic framework described here allows corals to pursue different strategies to succeed in habitats with highly variable light stress levels. In summary, our results suggest that the intraspecific plasticity of reef corals’ stress responses is larger than previously thought.


title: A Mode-Based Design Method for Dual-Band and Self-Diplexing Antennas Using Double T-Stubs Loaded Aperture

abstract: A mode-based design method for dual-band and self-deplexing antennas is presented. By analyzing the E-field distributions and cut-off frequencies of the individual modes in a T-stub loaded aperture, we selected two proper modes for the antenna designed for dual-frequency operations. The desired feature is that at the two different frequencies, the antenna may perform the same or similar radiation characteristics including the polarization, the pattern shape, and the gain level. A rectangular aperture loaded with double T-stubs was employed for the illustration basis. The proposed method was demonstrated to the dual-band antenna and self-diplexing antenna design with promising performances. The presented dual-band antenna performed a wide range of the frequency ratio from 1.3 to 3.0 under a fixed antenna size. The proposed self-diplexing antenna achieved good port isolation better than 26 dB in both operating bands. Both illustrated antenna designs were successfully verified with built prototypes of which the simulation and measurement results were quite consistent.


title: Microblog Sentiment Analysis with Emoticon Space Model

abstract: Emoticons have been widely employed to express different types of moods, emotions, and feelings in microblog environments. They are therefore regarded as one of the most important signals for microblog sentiment analysis. Most existing studies use several emoticons that convey clear emotional meanings as noisy sentiment labels or similar sentiment indicators. However, in practical microblog environments, tens or even hundreds of emoticons are frequently adopted and all emoticons have their own unique emotional meanings. Besides, a considerable number of emoticons do not have clear emotional meanings. An improved sentiment analysis model should not overlook these phenomena. Instead of manually assigning sentiment labels to several emoticons that convey relatively clear meanings, we propose the emoticon space model (ESM) that leverages more emoticons to construct word representations from a massive amount of unlabeled data. By projecting words and microblog posts into an emoticon space, the proposed model helps identify subjectivity, polarity, and emotion in microblog environments. The experimental results for a public microblog benchmark corpus (NLP&CC 2013) indicate that ESM effectively leverages emoticon signals and outperforms previous state-of-the-art strategies and benchmark best runs.


title: Interactive and experiential design in smart textile products and applications

abstract: The technical textiles industry in the USA and the EU is growing. As we advance into the knowledge age, objects and material technology will disappear into our material environment, turning unintelligent objects into active and intelligent participants in our lives. As much of our environment is made up from textile materials, they will be the targets of smart engineering. The future of smart textiles will rely on the convergence of electrochemistry and textiles in order to process electronic polymers into fibres and fabrics. The integration of smart functionality into clothing and other textile products will radically change the culture surrounding these products, fundamentally altering people’s relationships with them and the way they use them. Smart functionality will also have an impact on the way products are designed and the materials developed.


title: Adaptive Bitrate Selection: A Survey

abstract: HTTP adaptive streaming (HAS) is the most recent attempt regarding video quality adaptation. It enables cheap and easy to implement streaming technology without the need for a dedicated infrastructure. By using a combination of TCP and HTTP it has the advantage of reusing all the existing technologies designed for ordinary web. Equally important is that HAS traffic passes through firewalls and works well when NAT is deployed. The rate adaptation controller of HAS, commonly called adaptive bitrate selection (ABR), is currently receiving a lot of attention from both industry and academia. However, most of the research efforts concentrate on a specific aspect or a particular methodology without considering the overall context. This paper presents a comprehensive survey of the most significant research activities in the area of client-side HTTP-based adaptive video streaming. It starts by decomposing the ABR module into three subcomponents, namely: resource estimation function, chunk request scheduling, and adaptation module. Each subcomponent encapsulates a particular function that is vital to the operation of an ABR scheme. A review of each of the subcomponents and how they interact with each other is presented. Furthermore, those external factors that are known to have a direct impact on the performance of an ABR module, such as content nature, CDN, and context, are discussed. In conclusion, this paper provides an extensive reference for further research in the field.


title: A smile biases the recognition of eye expressions: Configural projection from a salient mouth

abstract: A smile is visually highly salient and grabs attention automatically. We investigated how extrafoveally seen smiles influence the viewers' perception of non-happy eyes in a face. A smiling mouth appeared in composite faces with incongruent non-happy (fearful, neutral, etc.) eyes, thus producing blended expressions, or it appeared in intact faces with genuine expressions. Attention to the eye region was spatially cued while foveal vision of the mouth was blocked by gaze-contingent masking. Participants judged whether the eyes were happy or not. Results indicated that the smile biased the evaluation of the eye expression: The same non-happy eyes were more likely to be judged as happy and categorized more slowly as not happy in a face with a smiling mouth than in a face with a non-smiling mouth or with no mouth. This bias occurred when the mouth and the eyes appeared simultaneously and aligned, but also to some extent when they were misaligned and when the mouth appeared after the eyes. We conclude that the ...


1. Ontological Engineering: Principles, Methods, Tools and Languages


title: STUDENT ROLE ADJUSTMENT IN ONLINE COMMUNITIES OF INQUIRY : MODEL AND INSTRUMENT VALIDATION

abstract: The purpose of this study is to validate an instrument to study role adjustment of students new to an online community of inquiry. The community of inquiry conceptual model for online learning was used to shape this research and identify the core elements and conditions associated with role adjustment to online learning (Garrison, Anderson and Archer, 2000). Through a factor analytic process it is shown that the instrument did reflect the theoretical model. It was also useful in refining the items for the questionnaire. The instrument is for use in future research designed to measure and understand student role adjustment in online learning.


title: The role of strong and weak ties in Facebook : a community structure perspective

abstract: Pervasive socio-technical networks bring new conceptual and technological challenges to developers and users alike. A central research theme is evaluation of the intensity of relations linking users and how they facilitate communication and the spread of information. These aspects of human relationships have been studied extensively in the social sciences under the framework of the"strength of weak ties"theory proposed by Mark Granovetter.13 Some research has considered whether that theory can be extended to online social networks like Facebook, suggesting interaction data can be used to predict the strength of ties. The approaches being used require handling user-generated data that is often not publicly available due to privacy concerns. Here, we propose an alternative definition of weak and strong ties that requires knowledge of only the topology of the social network (such as who is a friend of whom on Facebook), relying on the fact that online social networks, or OSNs, tend to fragment into communities. We thus suggest classifying as weak ties those edges linking individuals belonging to different communities and strong ties as those connecting users in the same community. We tested this definition on a large network representing part of the Facebook social graph and studied how weak and strong ties affect the information-diffusion process. Our findings suggest individuals in OSNs self-organize to create well-connected communities, while weak ties yield cohesion and optimize the coverage of information spread.


title: Rational Choice Theory: Toward a Psychological, Social, and Material Contextualization of Human Choice Behavior

abstract: The main purpose of this paper is to provide a brief overview of the rational choice approach, followed by an identification of several of the major criticisms of RCT and its conceptual and empirical limitations. It goes on to present a few key initiatives to develop alternative, more realistic approaches which transcend some of the limitations of Rational Choice Theory (RCT). Finally, the article presents a few concluding reflections and a table comparing similarities and differences between the mainstream RCT and some of the initial components of an emerging choice theory. Our method has been to conduct a brief selective review of rational choice theoretical formulations and applications as well as a review of diverse critical literature in the social sciences where rational choice has been systematically criticized. We have focused on a number of leading contributors (among others, several Nobel Prize Recipients in economics, who have addressed rational choice issues). So this article makes no claim for completeness. The review maps a few key concepts and assumptions underpinning the conceptual model and empirical applications of RCT. It reviews also a range of critical arguments and evidence of limitations. It identifies selected emerging concepts and theoretical revisions and adaptations to choice theory and what they entail. The results obtained, based on our literature reviews and analyses, are the identification of several major limitations of RCT as well as selected modifications and adaptations of choice theory which overcome or promise to overcome some of the RCT limitations. Thus, the article with Table 1 in hand provides a point of departure for follow-up systematic reviews and more precise questions for future theory development. The criticisms and adaptations of RCT have contributed to greater realism, empirical relevance, and increased moral considerations. The developments entail, among other things: the now well-known cognitive limitations (“bounded rationality”) and, for instance, the role of satisficing rather than maximizing in decision-making to deal with cognitive complexity and the uncertainties of multiple values; choice situations are re-contextualized with psychology, sociology, economic, and material conditions and factors which are taken into account explicitly and insightfully in empirical and theoretical work. Part of the contextualization concerns the place of multiple values, role and norm contradictions, and moral dilemmas in much choice behavior. In conclusion, the article suggests that the adaptations and modifications made in choice theory have led to substantial fragmentation of choice theory and as of yet no integrated approach has appeared to simply displace RCT.


title: Adoption of open government data among government agencies

abstract: Abstract With an emerging interest in open government data (OGD) around the world, there has been an increasing need for research on the determinants of OGD adoption. This study examines factors influencing the adoption of OGD among government agencies in Taiwan to fill the existing knowledge gap. Accordingly, based on previous research on innovation adoption, we develop a research model that integrates the technology–organization–environment (TOE) framework and the following four factors that are central to adoption decisions: perceived benefits, perceived barriers, organizational readiness, and external pressures. We examined this model through survey data from 342 government agencies of the Executive Yuan in Taiwan. The results show a significant positive relationship among perceived benefits, organizational readiness, and external pressures and the adoption of OGD by government agencies. This study creates a valuable reference for other countries in the early stages of OGD initiatives and has significant implications for governmental policy practitioners.


title: Taurocholate induces preferential release of phosphatidylcholine from rat liver canalicular vesicles

abstract: AIMS/BACKGROUND: Biliary phospholipid secretion involves predominant segregation of canalicular phosphatidylcholine into bile. We tested the hypothesis that micellar concentrations of the major physiologic bile salt taurocholate can preferentially solubilize phosphatidylcholine from the canalicular rat liver plasma membrane. METHODS: Subcellular fractions from rat liver and kidney were isolated with standardized procedures, incubated in vitro with taurocholate or 3-[(3-cholamidopropyl)dimethylammonio]-propane-1-sulphonate (CHAPS) and released phospholipids determined after centrifugation. RESULTS: After incubation of canalicular (cLPM) and basolateral (blLPM) rat liver plasma membrane vesicles with 6 and 8 mM taurocholate, the proportion of phosphatidylcholine released was about two-fold higher as compared with its relative contribution to the overall lipid composition of the membranes. Quantitatively, this taurocholate-induced preferential phosphatidylcholine release was about four-fold higher in cLPM (117 nmol) as compared with blLPM (28 nmol). Comparison of membranes from different organs showed that increased sphingomyelin content reduced taurocholate-induced phosphatidylcholine release. Furthermore, phosphatidylcholine release from cLPM did not fit an inverse exponential relationship between membrane sphingomyelin content and phosphatidylcholine release from different starting material, indicating that cLPM is especially prone to taurocholate-induced phosphatidylcholine release. In contrast, in rat liver microsomes and kidney brush border membranes, taurocholate released phospholipids in proportion of their membrane contents, indicating an unspecific membrane solubilizing effect only. Similarly, CHAPS had an unselective lipid solubilizing effects in cLPM and blLPM. CONCLUSION: These results support the concept that the very last step of canalicular phospholipid secretion is mediated in vivo by bile salt-induced vesiculation of phosphatidylcholine-enriched microdomains from the outer leaflet of cLPM.


title: Building a question answering test collection

abstract: The TREC-8 Question Answering (QA) Track was the first large-scale evaluation of domain-independent question answering systems. In addition to fostering research on the QA task, the track was used to investigate whether the evaluation methodology used for document retrieval is appropriate for a different natural language processing task. As with document relevance judging, assessors had legitimate differences of opinions as to whether a response actually answers a question, but comparative evaluation of QA systems was stable despite these differences. Creating a reusable QA test collection is fundamentally more difficult than creating a document retrieval test collection since the QA task has no equivalent to document identifiers.


title: Same titanium glycolate precursor but different products: successful synthesis of twinned anatase TiO2 nanocrystals with excellent solar photocatalytic hydrogen evolution capability

abstract: Exploiting a synthesis protocol to tailor TiO2 with a unique morphology and crystal phase has received considerable interest in the energy and environmental fields. We here describe the use of a titanium glycolate precursor in a hydrothermal hydrolysis reaction to engineer TiO2 nanocrystals with different crystal phases and structures. Anatase TiO2 nanocrystals with twinned structures were obtained by using a lower amount of NaOH in the hydrolysis system, while brookite TiO2 nanocrystals were formed when higher amounts of NaOH were employed. The as-synthesized different TiO2 nanocrystals have a suitable bandgap to harvest photons and a more negative bottom level of the conduction band than the redox potential of H+/H2 indicating their potential as hydrogen-evolution semiconductor photocatalysts. However, the TiO2 nanotwins show promoted charge separation efficiency, and thus result in superior photocatalytic H2 generation activity compared to the anatase and brookite TiO2 nanocrystals. Our findings provide an effective and versatile solution for the fabrication of TiO2-based nanostructures with different phases and morphologies through chemical conversion of powder precursor nanoparticles, which could pave the way to the design of other functional nano-oxides with unique structures.


title: Deep Submodular Functions

abstract: We start with an overview of a class of submodular functions called SCMMs (sums of concave composed with non-negative modular functions plus a final arbitrary modular). We then define a new class of submodular functions we call {\em deep submodular functions} or DSFs. We show that DSFs are a flexible parametric family of submodular functions that share many of the properties and advantages of deep neural networks (DNNs). DSFs can be motivated by considering a hierarchy of descriptive concepts over ground elements and where one wishes to allow submodular interaction throughout this hierarchy. Results in this paper show that DSFs constitute a strictly larger class of submodular functions than SCMMs. We show that, for any integer $k>0$, there are $k$-layer DSFs that cannot be represented by a $k'$-layer DSF for any $k'<k$. This implies that, like DNNs, there is a utility to depth, but unlike DNNs, the family of DSFs strictly increase with depth. Despite this, we show (using a "backpropagation" like method) that DSFs, even with arbitrarily large $k$, do not comprise all submodular functions. In offering the above results, we also define the notion of an antitone superdifferential of a concave function and show how this relates to submodular functions (in general), DSFs (in particular), negative second-order partial derivatives, continuous submodularity, and concave extensions. To further motivate our analysis, we provide various special case results from matroid theory, comparing DSFs with forms of matroid rank, in particular the laminar matroid. Lastly, we discuss strategies to learn DSFs, and define the classes of deep supermodular functions, deep difference of submodular functions, and deep multivariate submodular functions, and discuss where these can be useful in applications.


Dermatomyofibroma on the Nape of the Neck: A Report of 2 Pediatric Cases


title: Electric vehicle differential system based on co-simulation of Carsim/Simulink

abstract: A simple exposition was carried out for the power train's structure of the electric vehicle. Based on this, another simple exposition was designing the electronic differential which was based on various control theories. And detailed exposition was made upon the structure, the object and the control strategy of the electronic differential. Then, the combined simulation of distributed driving electric vehicle with Carsim/Simulink is determined. Detailed exposition was interface settings of the distributed electric drive system and the properly configured vehicle, the setting of key parameters for modeling. The effectiveness of the electronic differential system is verified by the test results and the simulation platform for the study of electronic differential system of electric vehicle.


title: Direct GPU/FPGA communication Via PCI express

abstract: We describe a mechanism for connecting GPU and FPGA devices directly via the PCI Express bus, enabling the transfer of data between these heterogeneous computing units without the intermediate use of system memory. We evaluate the performance benefits of this approach over a range of transfer sizes, and demonstrate its utility in a computer vision application. We find that bypassing system memory yields improvements as high as 2.2× in data transfer speed, and 1.9× in application performance.


title: Ship motion prediction for launch and recovery of air vehicles

abstract: Due to the random nature of the ship's motion in an open water environment, the deployment and the landing of air vehicles from a ship can often be difficult and even dangerous. The ability to reliably predict the motion will allow improvements in safety on board ships and facilitate more accurate deployment of vehicles off ships. This paper presents an investigation into the application of artificial neural network methods trained using singular value decomposition and genetic algorithms for the prediction of ship motion. It is shown that the artificial neural network produces excellent predictions and is able to predict the ship motion satisfactorily for up to 7 seconds.


title: CANNA: Neural network acceleration using configurable approximation on GPGPU

abstract: Neural networks have been successfully used in many applications. Due to their computational complexity, it is difficult to implement them on embedded devices. Neural networks are inherently approximate and thus can be simplified. In this paper, CANNA proposes a gradual training approximation which adaptively sets the level of hardware approximation depending on the neural network's internal error, instead of apply uniform hardware approximation. To accelerate inference, CANNA's layer-based approximation approach selectively relaxes the computation in each layer of neural network, as a function its sensitivity to approximation. For hardware support, we use a configurable floating point unit in Hardware that dynamically identifies inputs which produce the largest approximation error and process them instead in precise mode. We evaluate the accuracy and efficiency of our design by integrating configurable FPUs into AMD's Southern Island GPU architecture. Our experimental evaluation shows that CANNA achieves up to 4.84× (7.13×) energy savings and 3.22× (4.64×) speedup when training four different neural network applications with 0% (2%) quality loss as compared to the implementation on baseline GPU. During the inference phase, our layer-based approach improves the energy efficiency by 4.42× (6.06×) and results in 2.96× (3.98×) speedup while ensuring 0% (2%) quality loss.


title: Range and coexistence analysis of long range unlicensed communication

abstract: A broad range of emerging applications require very low power, very long range yet low throughput communication. Different standards are being proposed to meet these novel requirements. In this paper, the technical differences between a wideband spread spectrum (LoRa-like) and an ultra narrowband (Sigfox-like) network will be explained and evaluated. On the physical layer, simulation results show that an ultra narrowband network has a larger coverage, while wideband spread spectrum networks are less sensitive to interference. When considering the contention between nodes and interference between different networks, simulations show that adaptation of frequency and modulation is imperative for efficiently dealing with varying contention and interference in long range unlicensed networks. Depending on network load, size and distance, a device in a wideband network can send 6 times more packets to the base station when there is active rate and frequency management and an intra-technology control plane.


title: Multi-stack ensemble for job recommendation

abstract: This paper describes the approach that team PumpkinPie adopted in the 2016 Recsys Challenge. The task of the competition organized by XING is to predict which job postings the user has interacted with. The team's approach mainly consists in generating a set of models using different techniques, and then combining them in a multi-stack ensemble. This strategy granted the fourth position in the final leader-board to the team, with an overall score of 1.86M.


title: A Video Fingerprint Based on Visual Digest and Local Fingerprints

abstract: A fingerprinting design extracts discriminating features, called fingerprints. The extracted features are unique and specific to each image/video. The visual hash is usually a global fingerprinting technique with crypto-system constraints. In this paper, we propose an innovative video content identification process which combines a visual hash function and a local fingerprinting. Thanks to a visual hash function, we observe the video content variation and we detect key frames. A local image fingerprint technique characterizes the detected key frames. The set of local fingerprints for the whole video summarizes the video or fragments of the video. The video fingerprinting algorithm identifies an unknown video or a fragment of video within a video fingerprint database. It compares the local fingerprints of the candidate video with all local fingerprints of a database even if strong distortions are applied to an original content.


title: White-Box Traceable Ciphertext-Policy Attribute-Based Encryption Supporting Flexible Attributes

abstract: Ciphertext-policy attribute-based encryption (CP-ABE) enables fine-grained access control to the encrypted data for commercial applications. There has been significant progress in CP-ABE over the recent years because of two properties called traceability and large universe, greatly enriching the commercial applications of CP-ABE. Traceability is the ability of ABE to trace the malicious users or traitors who intentionally leak the partial or modified decryption keys for profits. Nevertheless, due to the nature of CP-ABE, it is difficult to identify the original key owner from an exposed key since the decryption privilege is shared by multiple users who have the same attributes. On the other hand, the property of large universe in ABE enlarges the practical applications by supporting flexible number of attributes. Several systems have been proposed to obtain either of the above properties. However, none of them achieve the two properties simultaneously in practice, which limits the commercial applications of CP-ABE to a certain extent. In this paper, we propose two practical large universe CP-ABE systems supporting white-box traceability. Compared with existing systems, both the two proposed systems have two advantages: 1) the number of attributes is not polynomially bounded and 2) malicious users who leak their decryption keys could be traced. Moreover, another remarkable advantage of the second proposed system is that the storage overhead for traitor tracing is constant, which are suitable for commercial applications.


title: A Survey of Visualization Systems for Network Security

abstract: Security Visualization is a very young term. It expresses the idea that common visualization techniques have been designed for use cases that are not supportive of security-related data, demanding novel techniques fine tuned for the purpose of thorough analysis. Significant amount of work has been published in this area, but little work has been done to study this emerging visualization discipline. We offer a comprehensive review of network security visualization and provide a taxonomy in the form of five use-case classes encompassing nearly all recent works in this area. We outline the incorporated visualization techniques and data sources and provide an informative table to display our findings. From the analysis of these systems, we examine issues and concerns regarding network security visualization and provide guidelines and directions for future researchers and visual system developers.


title: Multi-Imager Compatible, MR Safe, Remote Center of Motion Needle-Guide Robot

abstract: We report the development of a new robotic system for direct image-guided interventions (DIGI; images acquired at the time of the intervention). The manipulator uses our previously reported pneumatic step motors and is entirely made of electrically nonconductive, nonmetallic, and nonmagnetic materials. It orients a needle-guide with two degrees of freedom (DoF) about a fulcrum point located below the guide using an innovative remote center of motion parallelogram type mechanism. The depth of manual needle insertion is preset with a third DoF, located remotely of the manipulator. Special consideration was given to the kinematic accuracy and the structural stiffness. The manipulator includes registration markers for image-to-robot registration. Based on the images, it may guide needles, drills, or other slender instruments to a target (OD in vitro were 1.71 mm and 0.51 mm, at an average target depth of ∼38 mm, with no adjustments. The system may be suitable for DIGI where ${\text{1.07 + 0.0031}} \cdot \boldsymbol{d}$ [mm] accuracy lateral to the needle (2D) or ${\text{1.59 + 0.0031}} \cdot \boldsymbol{d}$ [mm] in 3D is acceptable. The system is also multi-imager compatible and could be used with other imaging modalities.


title: Discovering outlier filtering rules from unlabeled data: combining a supervised learner with an unsupervised learner

abstract: This paper is concerned with the problem of detecting outliers from unlabeled data. In prior work we have developed SmartSifter, which is an on-line outlier detection algorithm based on unsupervised learning from data. On the basis of SmartSifter this paper yields a new framework for outlier filtering using both supervised and unsupervised learning techniques iteratively in order to make the detection process more effective and more understandable. The outline of the framework is as follows: In the first round, for an initial dataset, we run SmartSifter to give each data a score, with a high score indicating a high possibility of being an outlier. Next, giving positive labels to a number of higher scored data and negative labels to a number of lower scored data, we create labeled examples. Then we construct an outlier filtering rule by supervised learning from them. Here the rule is generated based on the principle of minimizing extended stochastic complexity. In the second round, for a new dataset, we filter the data using the constructed rule, then among the filtered data, we run SmartSifter again to evaluate the data in order to update the filtering rule. Applying of our framework to the network intrusion detection, we demonstrate that 1) it can significantly improve the accuracy of SmartSifter, and 2) outlier filtering rules can help the user to discover a general pattern of an outlier group.


title: Long Text Generation via Adversarial Training with Leaked Information

abstract: Automatically generating coherent and semantically meaningful text has many applications in machine translation, dialogue systems, image captioning, etc. Recently, by combining with policy gradient, Generative Adversarial Nets (GAN) that use a discriminative model to guide the training of the generative model as a reinforcement learning policy has shown promising results in text generation. However, the scalar guiding signal is only available after the entire text has been generated and lacks intermediate information about text structure during the generative process. As such, it limits its success when the length of the generated text samples is long (more than 20 words). In this paper, we propose a new framework, called LeakGAN, to address the problem for long text generation. We allow the discriminative net to leak its own high-level extracted features to the generative net to further help the guidance. The generator incorporates such informative signals into all generation steps through an additional Manager module, which takes the extracted features of current generated words and outputs a latent vector to guide the Worker module for next-word generation. Our extensive experiments on synthetic data and various real-world tasks with Turing test demonstrate that LeakGAN is highly effective in long text generation and also improves the performance in short text generation scenarios. More importantly, without any supervision, LeakGAN would be able to implicitly learn sentence structures only through the interaction between Manager and Worker.


title: Reliability and validity of the Advanced Basal Cell Carcinoma Index (aBCCdex).

abstract: BACKGROUND ::: Patient-reported outcome (PRO) questionnaires were recently developed specifically for use with patients with advanced basal cell carcinoma (aBCC) and basal cell carcinoma naevus syndrome (BCCNS). ::: ::: ::: OBJECTIVES ::: To evaluate the measurement properties of PRO questionnaires for use in patients with aBCC or BCCNS. ::: ::: ::: METHODS ::: In total 129 patients from 10 clinical sites in the U.S.A. and the BCCNS Support Network completed the two newly developed questionnaires multiple times over 3 months. Patients also completed the Skindex-16 and the 12-Item Short-Form Health Survey as collateral measures. Psychometric properties of the questionnaires were evaluated, including internal consistency and test-retest reliability, construct and known-groups validity, and responsiveness. ::: ::: ::: RESULTS ::: Based on the results of exploratory factor analysis and clinical input, the two newly developed questionnaires were combined into a single questionnaire, called the aBCCdex, which is relevant for patients with both aBCC and BCCNS. The internal consistency reliability was acceptable, and all aBCCdex scale scores correlated significantly with conceptually similar scales. When divided into groups that differed based on scores from collateral measures, aBCCdex scale scores differentiated between groups (known-groups validity) and were responsive to change. ::: ::: ::: CONCLUSIONS ::: The aBCCdex is a brief and comprehensive questionnaire appropriate for use with patients with aBCC and BCCNS. Its reliability and validity have been confirmed. Further research is necessary to estimate the minimally important difference in a larger patient population.


title: Stanford’s Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task

abstract: This paper details the coreference resolution system submitted by Stanford at the CoNLL-2011 shared task. Our system is a collection of deterministic coreference resolution models that incorporate lexical, syntactic, semantic, and discourse information. All these models use global document-level information by sharing mention attributes, such as gender and number, across mentions in the same cluster. We participated in both the open and closed tracks and submitted results using both predicted and gold mentions. Our system was ranked first in both tracks, with a score of 57.8 in the closed track and 58.3 in the open track.


title: Bar graphs depicting averages are perceptually misinterpreted: The within-the-bar bias

abstract: Perhaps the most common method of depicting data, in both scientific communication and popular media, is the bar graph. Bar graphs often depict measures of central tendency, but they do so asymmetrically: A mean, for example, is depicted not by a point, but by the edge of a bar that originates from a single axis. Here we show that this graphical asymmetry gives rise to a corresponding cognitive asymmetry. When viewers are shown a bar depicting a mean value and are then asked to judge the likelihood of a particular data point being part of its underlying distribution, viewers judge points that fall within the bar as being more likely than points equidistant from the mean, but outside the bar—as if the bar somehow “contained” the relevant data. This “within-the-bar bias” occurred (a) for graphs with and without error bars, (b) for bars that originated from both lower and upper axes, (c) for test points with equally extreme numeric labels, (d) both from memory (when the bar was no longer visible) and in online perception (while the bar was visible during the judgment), (e) both within and between subjects, and (f) in populations including college students, adults from the broader community, and online samples. We posit that this bias may arise due to principles of object perception, and we show how it has downstream implications for decision making.


title: Long-Term Follow-Up of Transsexual Persons Undergoing Sex Reassignment Surgery: Cohort Study in Sweden

abstract: CONTEXT ::: The treatment for transsexualism is sex reassignment, including hormonal treatment and surgery aimed at making the person's body as congruent with the opposite sex as possible. There is a dearth of long term, follow-up studies after sex reassignment. ::: ::: ::: OBJECTIVE ::: To estimate mortality, morbidity, and criminal rate after surgical sex reassignment of transsexual persons. ::: ::: ::: DESIGN ::: A population-based matched cohort study. ::: ::: ::: SETTING ::: Sweden, 1973-2003. ::: ::: ::: PARTICIPANTS ::: All 324 sex-reassigned persons (191 male-to-females, 133 female-to-males) in Sweden, 1973-2003. Random population controls (10:1) were matched by birth year and birth sex or reassigned (final) sex, respectively. ::: ::: ::: MAIN OUTCOME MEASURES ::: Hazard ratios (HR) with 95% confidence intervals (CI) for mortality and psychiatric morbidity were obtained with Cox regression models, which were adjusted for immigrant status and psychiatric morbidity prior to sex reassignment (adjusted HR [aHR]). ::: ::: ::: RESULTS ::: The overall mortality for sex-reassigned persons was higher during follow-up (aHR 2.8; 95% CI 1.8-4.3) than for controls of the same birth sex, particularly death from suicide (aHR 19.1; 95% CI 5.8-62.9). Sex-reassigned persons also had an increased risk for suicide attempts (aHR 4.9; 95% CI 2.9-8.5) and psychiatric inpatient care (aHR 2.8; 95% CI 2.0-3.9). Comparisons with controls matched on reassigned sex yielded similar results. Female-to-males, but not male-to-females, had a higher risk for criminal convictions than their respective birth sex controls. ::: ::: ::: CONCLUSIONS ::: Persons with transsexualism, after sex reassignment, have considerably higher risks for mortality, suicidal behaviour, and psychiatric morbidity than the general population. Our findings suggest that sex reassignment, although alleviating gender dysphoria, may not suffice as treatment for transsexualism, and should inspire improved psychiatric and somatic care after sex reassignment for this patient group.


title: Wafer bonding of different III–V compound semiconductors by atomic hydrogen surface cleaning

abstract: Large-area wafer bonding of different III–V compound semiconductors in an ultrahigh vacuum background is demonstrated. The bonding procedure, the microstructure, and the mechanical strength of the bonded GaAs/InP and GaAs/GaP interfaces were studied. The cleaning procedure and the bonding were separated in order to avoid undesired artifacts and thermal stress at the interface. First, thermally generated atomic hydrogen was employed to clean the surfaces. Then, the wafers were brought into contact below 150 °C. At contact, the interface formed spontaneously over the whole wafer area without application of a mechanical load. Transmission electron microscopy showed the formation of atomically direct interfaces and misfit dislocation networks. The fracture surface energy was measured as being comparable to that of respective bulk materials. Heat treatments of the bonded GaAs/InP samples led to relaxation of the interfaces but also to the formation of nanoscopic voids in the interface plane and volume dislocat...


YOLOv 3 : An Incremental Improvement


title: Review On Expectancy Disconfirmation Theory (EDT) Model In B2C E-Commerce

abstract: This study focuses on a review of “Expectancy Disconfirmation Theory” (EDT) as a famous theory in measuring customer’s satisfaction. In today’s competitive e-marketplace, e-businesses that determine an efficient strategic think behind their e-commerce activities involve designing a qualified website and presenting good quality of products and services will be more successful in attracting customer satisfaction. These points emphasize on the importance of attracting customer’s satisfaction for the vita of e-businesses. That’s why measuring customer’s satisfaction by an empowerment tool that has ability to cover and make relationship among all concepts that are explained above is imperative. “Expectancy Disconfirmation Theory” (EDT) which is defined as an theory for measuring customer satisfaction from perceived quality of products or services is reviewed in this research for measuring customers satisfaction. Evolution of “EDT” shown this theory is able to measure quality of services and information which provided by B2C E-commerce from customer’s point of view. Moreover, review on EDT measurement methods and their strengths and weaknesses in accuracy of the results shown that Additive Difference Model (ADM) and Direct Effects Model (DEM) worked well across both standards involve customer‘s expectation and desire. Between DEM and ADM methods, when managers need information about desires and expectations DEM appears to be a good choice but it does not provide a distinct measure of the disconfirmation of customer‘s expectation and desire. In versus ADM provide a distinct measure of the disconfirmation of customer‘s expectation and desire. That’s why it is concerned by managerial issues.


title: Cost-Sensitive Learning with Neural Networks

abstract: In the usual setting of Machine Learning, classifiers are typically evaluated by estimating their error rate (or equi valently, the classification accuracy) on the test data. However, this mak es sense only if all errors have equal (uniform) costs. When the costs of er- rors differ between each other, the classifiers should be eva luated by comparing the total costs of the errors. Classifiers are typically designed to minimize the number of errors (incorrect classifications) made. When misclassification c osts vary between classes, this approach is not suitable. In this case the total misclassification cost should be minimized. In Machine Learning, only little work for dealing with non- uniform misclassification costs has been done. This paper pr esents a few different approaches for cost-sensitive modifications of the back- propagation learning algorithm for multilayered feedforw ard neural networks . The described approaches are thoroughly tested and eval- uated on several standard benchmark domains.


title: A Digital Watermarking Approach Based on DCT Domain Combining QR Code and Chaotic Theory

abstract: This paper proposes a robust watermarking approach based on Discrete Cosine Transform (DCT) domain that combines Quick Response (QR) Code and chaotic system. When embed the watermark, the high error correction performance and the strong decoding capability of QR Code are utilized to decode the text watermark information which improves the robustness of the watermarking algorithm. Then the QR Code image is encrypted with chaotic system to enhance the security of this approach. Finally the encrypted image is embedded to the carrier image's DCT blocks after they underwent block-based Arnold scrambling transformation. During the extraction process, as long as the QR Code image can be decoded, the completeness and accuracy of the text watermarking information can be guaranteed. The results of simulation experiment show that this approach has high robustness and security and has, therefore, some practical value in the copyright protection.


title: Bagging gradient-boosted trees for high precision, low variance ranking models

abstract: Recent studies have shown that boosting provides excellent predictive performance across a wide variety of tasks. In Learning-to-rank, boosted models such as RankBoost and LambdaMART have been shown to be among the best performing learning methods based on evaluations on public data sets. In this paper, we show how the combination of bagging as a variance reduction technique and boosting as a bias reduction technique can result in very high precision and low variance ranking models. We perform thousands of parameter tuning experiments for LambdaMART to achieve a high precision boosting model. Then we show that a bagged ensemble of such LambdaMART boosted models results in higher accuracy ranking models while also reducing variance as much as 50%. We report our results on three public learning-to-rank data sets using four metrics. Bagged LamdbaMART outperforms all previously reported results on ten of the twelve comparisons, and bagged LambdaMART outperforms non-bagged LambdaMART on all twelve comparisons. For example, wrapping bagging around LambdaMART increases NDCG@1 from 0.4137 to 0.4200 on the MQ2007 data set; the best prior results in the literature for this data set is 0.4134 by RankBoost.


title: Practical Very Large Scale CRFs

abstract: Conditional Random Fields (CRFs) are a widely-used approach for supervised sequence labelling, notably due to their ability to handle large description spaces and to integrate structural dependency between labels. Even for the simple linear-chain model, taking structure into account implies a number of parameters and a computational effort that grows quadratically with the cardinality of the label set. In this paper, we address the issue of training very large CRFs, containing up to hundreds output labels and several billion features. Efficiency stems here from the sparsity induced by the use of a l penalty term. Based on our own implementation, we compare three recent proposals for implementing this regularization strategy. Our experiments demonstrate that very large CRFs can be trained efficiently and that very large models are able to improve the accuracy, while delivering compact parameter sets.


title: Metabolic demands of match performance in young soccer players.

abstract: The aim of the present study was to determine metabolic responses, movement patterns and distance covered at running speeds corresponding to fixed blood lactate concentrations (FBLs) in young soccer players during a match play. A further aim of the study was to evaluate the relationships between FBLs, maximal oxygen consumption (VO2max) and distance covered during a game. A multistage field test was administered to 32 players to determine FBLs and VO2max. Blood lactate (LA), heart rate (HR) and rate of perceived exertion (RPE) responses were obtained from 36 players during tournament matches filmed using six fixed cameras. Images were transferred to a computer, for calibration and synchronization. In all players, values for LA and HR were higher and RPE lower during the 1(st) half compared to the 2(nd) half of the matches (p < 0.01). Players in forward positions had higher LA levels than defenders, but HR and RPE values were similar between playing positions. Total distance and distance covered in jogging, low-moderate-high intensity running and low intensity sprint were higher during the 1(st) half (p < 0.01). In the 1(st) half, players also ran longer distances at FBLs [p<0.01; average running speed at 2mmol·L(-1) (FBL2): 3.32 ± 0.31m·s(-1) and average running speed at 4mmol·L(-1) (FBL4): 3.91 ± 0.25m·s(-1)]. There was a significant difference between playing positions in distance covered at different running speeds (p < 0.05). However, when distance covered was expressed as FBLs, the players ran similar distances. In addition, relationships between FBLs and total distance covered were significant (r = 0.482 to 0.570; p < 0.01). In conclusion, these findings demonstrated that young soccer players experienced higher internal load during the 1(st) half of a game compared to the 2(nd) half. Furthermore, although movement patterns of players differed between playing positions, all players experienced a similar physiological stress throughout the game. Finally, total distance covered was associated to fixed blood lactate concentrations during play. Key pointsBased on LA, HR and RPE responses, young top soccer players experienced a higher physiological stress during the 1(st) half of the matches compared to the 2(nd) half.Movement patterns differed in accordance with the players' positions but that all players experienced a similar physiological stress during match play.Approximately one quarter of total distance was covered at speeds that exceeded the 4 mmol·L(-1) fixed LA threshold.Total distance covered was influenced by running speeds at fixed lactate concentrations in young soccer players during match play.


title: A Data-Level Fusion Model for Developing Composite Health Indices for Degradation Modeling and Prognostic Analysis

abstract: Prognostics involves the effective utilization of condition or performance-based sensor signals to accurately estimate the remaining lifetime of partially degraded systems and components. The rapid development of sensor technology, has led to the use of multiple sensors to monitor the condition of an engineering system. It is therefore important to develop methodologies capable of integrating data from multiple sensors with the goal of improving the accuracy of predicting remaining lifetime. Although numerous efforts have focused on developing feature-level and decision-level fusion methodologies for prognostics, little research has targeted the development of “data-level” fusion models. In this paper, we present a methodology for constructing a composite health index for characterizing the performance of a system through the fusion of multiple degradation-based sensor data. This methodology includes data selection, data processing, and data fusion steps that lead to an improved degradation-based prognostic model. Our goal is that the composite health index provides a much better characterization of the condition of a system compared to relying solely on data from an individual sensor. Our methodology was evaluated through a case study involving a degradation dataset of an aircraft gas turbine engine that was generated by the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS).


Advanced Framework for Simulation, Integration and Modeling (AFSIM) (Case Number: 88ABW-2015-2258)


title: An IoT based home automation using android application

abstract: Now a day's technology becomes ever more invasive, the design challenges in home automation are increasingly apparent. Seamless controlling home, monitoring and programming by the end user have yet to enter the mainstream. This could be legitimate to the challenge of developing a fully independent and extensible home system that can support devices and technologies of differing functionalities and protocols. This paper describes how to control and monitor home appliances using android application over internet. There are number of commercial home automation systems available in market. However, these are designed for limited use. Therefore, home appliances can individually be controlled both from within the home and remotely. This is very helpful to physically challenged people. The practical goal of this paper has been to create a virtual, but practically usable, android home automation system. The android mobile is used to send the commands to the Arduino to control all the home appliances. The main feature of this system is to control the voltage levels of home appliance in home like speed of fan based on temperature, intensity of light based on light intensity etc. and another feature is we may get the status of our home appliances from our android mobile phone. In this system we use different sensors like temperature, rain sensor and LDR for different applications.


title: Phase control through Huygens' metasurfaces

abstract: We describe a dielectric Huygens' metasurface, operating in the visible spectrum, that can manipulate the phase of the transmitted light over a full 2π with high transmission efficiency. The metasurface is comprised of dielectric cylindrical nanoparticles embedded in a glass-like medium. The size of the nanoparticles and their separation are much smaller than the wavelength of visible light. From the metasurface, we construct a lens that focuses light to a diffraction limited spot size with high efficiency.


title: DFScala: High Level Dataflow Support for Scala

abstract: In this paper we present DFScala, a library for constructing and executing dataflow graphs in the Scala language. Through the use of Scala this library allows the programmer to construct coarse grained dataflow graphs that take advantage of functional semantics for the dataflow graph and both functional and imperative semantics within the dataflow nodes. This combination allows for very clean code which exhibits the properties of dataflow programs, but we believe is more accessible to imperative programmers. We first describe DFScala in detail, before using a number of benchmarks to evaluate both its scalability and its absolute performance relative to existing codes. DFScala has been constructed as part of the Teraflux project and is being used extensively as a basis for further research into dataflow programming.


title: Multidimensional Assessment of Emotion Regulation and Dysregulation: Development, Factor Structure, and Initial Validation of the Difficulties in Emotion Regulation Scale

abstract: Given recent attention to emotion regulation as a potentially unifying function of diverse symptom presentations, there is a need for comprehensive measures that adequately assess difficulties in emotion regulation among adults. This paper (a) proposes an integrative conceptualization of emotion regulation as involving not just the modulation of emotional arousal, but also the awareness, understanding, and acceptance of emotions, and the ability to act in desired ways regardless of emotional state; and (b) begins to explore the factor structure and psychometric properties of a new measure, the Difficulties in Emotion Regulation Scale (DERS). Two samples of undergraduate students completed questionnaire packets. Preliminary findings suggest that the DERS has high internal consistency, good test–retest reliability, and adequate construct and predictive validity.


title: A high speed power efficient dynamic comparator designed in 90nm CMOS technology

abstract: A fully dynamic latched comparator has been designed to meet the requirement of high speed and low power consumption. Such comparators are used in high speed data converters. In this work, dynamic comparators are designed in two different technologies and compared on the basis of delay, offset voltage and power consumption. These comparators work on the concept of charge sharing. Main focus is given towards reduction of both propagation delay and the power dissipation, which will be beneficial in improving performance of the comparator. 90nm CMOS technology is used to simulate the design with 1 V supply voltage. Hspice is used for designing and functional verification.


title: A Survey of Anti-Tamper Technologies The

abstract: This article surveys the various anti-tamper (AT) technologies used to protect software. The primary objective of AT tech- niques is to protect critical program information by preventing unauthorized modification and use of software. This protec- tion goal applies to any program that requires protection from unauthorized disclosure or inadvertent transfer of leading- edge technologies and sensitive data or systems. In this article, we review the various approaches to AT techniques, their strengths and weaknesses, their advantages and disadvantages, and briefly discuss a process for developing program protec- tion plans. We also survey the tools that are typically used to circumvent AT protections, and techniques that are commonly used to make these protections more resilient against such attack.


title: Skating motion by a leg-wheeled robot with passive wheels

abstract: This paper presents a new type of mobile robot that was developed based on the idea of developing a robot with reduced number of Degree of Freedom (DOF). The higher the number of DOF implies that more actuators are being fixed onto the robot. This eventually results in a complicated control system, as well as influencing the energy efficiency of the robot. Besides that, more DOF will only add up the total weight of the robot, which is a disadvantage because lightweight robot is more likely to be applicable. In this study where a closed link mobile robot was made, number of active joints was lessened, while passive wheels were used for mobility to meet the objective of reducing the number of DOF. In this paper, we will discuss on the reasons behind the development of a reduced DOF robot, the mechanism of trajectory that allows the robot to move by skating, and finally the results to the experiments conducted.


title: Penile Septoplasty for Congenital Ventral Penile Curvature: Results in 51 Patients

abstract: PURPOSE ::: The technique most widely used to correct congenital ventral penile curvature is still corporoplasty as originally described by Nesbit. We present results in patients treated with a variation of Nesbit corporoplasty used specifically for congenital ventral penile curvature. ::: ::: ::: MATERIALS AND METHODS ::: From June 2000 to June 2007 we treated 51 patients with congenital ventral penile curvature using modified corporoplasty (septoplasty), consisting of accessing the bed of the penile dorsal vein and excising 1 or more diamonds of tunica albuginea from it, extending in wedge-like formation 4 to 5 mm deep into the septum, until the penis is completely straightened. Patient history, clinical findings, self-photography results and the International Index of Erectile Function score were assessed. Curvature grade is expressed using the equation, 180 degrees - X, where X represents the deviation in degrees from the penis axis. Mean preoperative ventral curvature was 131.4 degrees (median 135, range 145 to 110). Of the patients 13 also had erectile dysfunction. ::: ::: ::: RESULTS ::: At followup postoperative mean ventral curvature was 178.3 degrees (median 179.1, range 180 to 175). A total of 49 stated that they were completely satisfied. Penile shortening was 5 to 15 mm. Compared to preoperative values there were marked improvements in the International Index of Erectile Function score in the various groups. No major postoperative complications developed. In 4 patients wound healing occurred by secondary intent. ::: ::: ::: CONCLUSIONS ::: This technique provides excellent straightening of the curved penis. By avoiding isolation of the whole dorsal neurovascular bundle there is no risk of neurovascular lesions. Suture perception is minimized.


title: POTENTIALITIES OF USRP-BASED SOFTWARE DEFINED RADAR SYSTEMS

abstract: Software Deflned Radar is the latest trend in radar development. To handle enhanced radar signal processing techniques, advanced radars need to be able of generating various types of waveforms, such as frequency modulated or phase coded, and to perform multiple functions. The adoption of a Software Deflned Radio system makes easier all these abilities. In this work, the implementation of a Software Deflned Radar system for target tracking using the Universal Software Radio Peripheral platform is discussed. For the flrst time, an experimental characterization in terms of radar application is performed on the latest Universal Software Radio Peripheral NI2920, demonstrating a strongly improved target resolution with respect to the flrst generation platform.


title: Human factors study on the usage of BCI headset for 3D CAD modeling

abstract: Since its inception, computer aided 3D modeling has primarily relied on the Windows, Icons, Menus, Pointer (WIMP) interface in which user input is in the form of keystrokes and pointer movements. The brain-computer interface (BCI) is a novel modality that uses the brain signals of a user to enable natural and intuitive interaction with an external device. In this paper we present a human factors study on the use of an Emotiv EEG BCI headset for 3D CAD modeling. The study focuses on substituting the conventional computer mouse- and keyboard-based inputs with inputs from the Emotiv EEG headset. The main steps include (1) training the headset to recognize user-specific EEG/EMG signals and (2) assigning the classified signals to emulate keystrokes which are used to activate/control different commands of a CAD package. To assess the performance of the new system, we compared the time taken by the users to create the 3D CAD models using both the conventional and BCI-based interfaces. In addition, to exhibit the adaptability of the new system, we carried out the study for a set of CAD models of varying complexity. We present a novel BCI based user interface for conceptual 3D modeling.The BCI performs CAD functions such as 3D shape creation and manipulation.Video abstract: https://www.youtube.com/watch?v=GATQUVgLLYY.A human factors study to assess intuitiveness of BCI in 3D modeling is presented.


title: Scheduling in multiprogrammed parallel systems

abstract: Processor scheduling on multiprocessor systems that simultaneously run concurrent applications is currently not well-understood. This paper reports a preliminary investigation of a number of fundamental issues which are important in the context of scheduling concurrent jobs on multiprogrammed parallel systems. The major motivation for this research is to gain insight into system behaviour and understand the basic principles underlying the performance of scheduling strategies in such parallel systems. Based on abstract models of systems and scheduling disciplines, several high level issues that are important in this context have been analysed.


Privacy-Preserving Multibiometric Authentication in Cloud with Untrusted Database Providers


title: A comparative study of open source deep learning frameworks

abstract: Deep Learning (DL) is one of the hottest trends in machine learning as DL approaches produced results superior to the state-of-the-art in problematic areas such as image processing and natural language processing (NLP). To foster the growth of the DL community, several open source frameworks appeared providing implementations of the most common DL algorithms. These frameworks vary in the algorithms they support and in the quality of their implementations. The purpose of this work is to provide a qualitative and quantitative comparison among three of the most popular and most comprehensive DL frameworks (namely Google's TensorFlow, University of Montreal's Theano, and Microsoft's CNTK). The ultimate goal of this work is to help end users make an informed decision about the best DL framework that suits their needs and resources. To ensure that our study is as comprehensive as possible, we conduct several experiments using multiple benchmark datasets and measure the performance of the frameworks' implementation of different DL algorithms. For most of our experiments, we find out that CNTK's implementations are superior to the other ones under consideration.


A Latent Concept Topic Model for Robust Topic Inference Using Word Embeddings


title: Deep Unsupervised Clustering with Gaussian Mixture Variational Autoencoders

abstract: We study a variant of the variational autoencoder model (VAE) with a Gaussian mixture as a prior distribution, with the goal of performing unsupervised clustering through deep generative models. We observe that the known problem of over-regularisation that has been shown to arise in regular VAEs also manifests itself in our model and leads to cluster degeneracy. We show that a heuristic called minimum information constraint that has been shown to mitigate this effect in VAEs can also be applied to improve unsupervised clustering performance with our model. Furthermore we analyse the effect of this heuristic and provide an intuition of the various processes with the help of visualizations. Finally, we demonstrate the performance of our model on synthetic data, MNIST and SVHN, showing that the obtained clusters are distinct, interpretable and result in achieving competitive performance on unsupervised clustering to the state-of-the-art results.


title: Scars, marks and tattoos (SMT): Soft biometric for suspect and victim identification

abstract: Scars, marks and tattoos (SMT) are being increasingly used for suspect and victim identification in forensics and law enforcement agencies. Tattoos, in particular, are getting serious attention because of their visual and demographic characteristics as well as their increasing prevalence. However, current tattoo matching procedure requires human-assigned class labels in the ANSI/NIST ITL 1-2000 standard which makes it time consuming and subjective with limited retrieval performance. Further, tattoo images are complex and often contain multiple objects with large intra-class variability, making it very difficult to assign a single category in the ANSI/NIST standard. We describe a content-based image retrieval (CBIR) system for matching and retrieving tattoo images. Based on scale invariant feature transform (SIFT) features extracted from tattoo images and optional accompanying demographical information, our system computes feature-based similarity between the query tattoo image and tattoos in the criminal database. Experimental results on two different tattoo databases show encouraging results.


title: PEG Hydrogels for the Controlled Release of Biomolecules in Regenerative Medicine

abstract: Polyethylene glycol (PEG) hydrogels are widely used in a variety of biomedical applications, including matrices for controlled release of biomolecules and scaffolds for regenerative medicine. The design, fabrication, and characterization of PEG hydrogels rely on the understanding of fundamental gelation kinetics as well as the purpose of the application. This review article will focus on different polymerization mechanisms of PEG-based hydrogels and the importance of these biocompatible hydrogels in regenerative medicine applications. Furthermore, the design criteria that are important in maintaining the availability and stability of the biomolecules as well as the mechanisms for loading of biomolecules within PEG hydrogels will also be discussed. Finally, we overview and provide a perspective on some of the emerging novel design and applications of PEG hydrogel systems, including the spatiotemporal-controlled delivery of biomolecules, hybrid hydrogels, and PEG hydrogels designed for controlled stem cell differentiation.


title: A secure steganography for privacy protection in healthcare system

abstract: Private data in healthcare system require confidentiality protection while transmitting. Steganography is the art of concealing data into a cover media for conveying messages confidentially. In this paper, we propose a steganographic method which can provide private data in medical system with very secure protection. In our method, a cover image is first mapped into a 1D pixels sequence by Hilbert filling curve and then divided into non-overlapping embedding units with three consecutive pixels. We use adaptive pixel pair match (APPM) method to embed digits in the pixel value differences (PVD) of the three pixels and the base of embedded digits is dependent on the differences among the three pixels. By solving an optimization problem, minimal distortion of the pixel ternaries caused by data embedding can be obtained. The experimental results show our method is more suitable to privacy protection of healthcare system than prior steganographic works.


title: Structural Brain Alterations following 5 Days of Intervention: Dynamic Aspects of Neuroplasticity

abstract: Activation-dependent brain plasticity in humans on a structural level has been demonstrated in adults after 3 months of training a visiomotor skill. The exact timescale of usage-dependent structural changes, whether days, months, or years, is, however, still debated. A better understanding of the temporal parameters may help elucidate to what extent this type of cortical plasticity contributes to fast adapting cortical processes that may be relevant to learning and effects of treatments. Using voxel-based morphometry, we are able to show that repetitive transcranial magnetic stimulation delivered to the superior temporal cortex causes macroscopic cortical changes in gray matter (GM) in the auditory cortex as early as within 5 days of continuous intervention. These structural alterations are mirrored by changes in cortical evoked potentials attributed to the GM changes and demonstrate the rapid dynamics of these processes, which occur within a time range characteristic for the onset of behavioral effects induced by a variety of treatment methods for neuropsychiatric diseases. Our finding suggests that cortical plasticity on a structural level in adult humans is already detectable after 1 week, which provides support for fast adjusting neuronal systems, such as spine and synapse turnover, and contradicts slow evolving mechanisms, such as neuronal or glial cell genesis.


title: Increasing trend of wearables and multimodal interface for human activity monitoring: A review.

abstract: Abstract Activity recognition technology is one of the most important technologies for life-logging and for the care of elderly persons. Elderly people prefer to live in their own houses, within their own locality. If, they are capable to do so, several benefits can follow in terms of society and economy. However, living alone may have high risks. Wearable sensors have been developed to overcome these risks and these sensors are supposed to be ready for medical uses. It can help in monitoring the wellness of elderly persons living alone by unobtrusively monitoring their daily activities. The study aims to review the increasing trends of wearable devices and need of multimodal recognition for continuous or discontinuous monitoring of human activity, biological signals such as Electroencephalogram (EEG), Electrooculogram (EOG), Electromyogram (EMG), Electrocardiogram (ECG) and parameters along with other symptoms. This can provide necessary assistance in times of ominous need, which is crucial for the advancement of disease-diagnosis and treatment. Shared control architecture with multimodal interface can be used for application in more complex environment where more number of commands is to be used to control with better results in terms of controlling.


There's no 'Count or Predict' but task-based \\selection for distributional models.


title: Pinching at Fingertips for Humanoid Robot Hand

abstract: It is difficult to generate the action of stably pinching paper or needle, etc. with the finger tips, which is one of the important functions to be realized by humanoid robot hands. In this paper, therefore, the authors firstly propose a small-sized and light-weight robotic hand designed according to the concept of extracting required minimum motor functions and implementing them to the robot, and secondly propose a new robot hand capable of properly realizing a pinching motion with finger tips, by adding the minimum required degree of supplementary freedom which can be realized only with a machine. In the new robot hand, the authors mainly focus on additions of the degrees of freedom of independent motion to the terminal fingers and the degree of freedom of twisting motion to the thumb. Experiments were carried out to investigate force control characteristics of the finger tip joint. The results showed that providing the finger tip with rich force control performance even with weak force is effective for securing delicate control characteristics in a humanoid robot hand. Key words— humanoid robot hand, pinching and grasping, addition of degree of freedom to finger tip, twisting mechanism of


title: Learning Optimal Bayesian Networks: A Shortest Path Perspective

abstract: In this paper, learning a Bayesian network structure that optimizes a scoring function for a given dataset is viewed as a shortest path problem in an implicit state-space search graph. This perspective highlights the importance of two research issues: the development of search strategies for solving the shortest path problem, and the design of heuristic functions for guiding the search. This paper introduces several techniques for addressing the issues. One is an A* search algorithm that learns an optimal Bayesian network structure by only searching the most promising part of the solution space. The others are mainly two heuristic functions. The first heuristic function represents a simple relaxation of the acyclicity constraint of a Bayesian network. Although admissible and consistent, the heuristic may introduce too much relaxation and result in a loose bound. The second heuristic function reduces the amount of relaxation by avoiding directed cycles within some groups of variables. Empirical results show that these methods constitute a promising approach to learning optimal Bayesian network structures.


title: Data Flow and Validation in Workflow Modelling

abstract: A complete workflow specification requires careful integration of many different process characteristics. Decisions must be made as to the definitions of individual activities, their scope, the order of execution that maintains the overall business process logic, the rules governing the discipline of work list scheduling to performers, identification of time constraints and more. The goal of this paper is to address an important issue in workflows modelling and specification, which is data flow, its modelling, specification and validation. Researchers have neglected this dimension of process analysis for some time, mainly focussing on structural considerations with limited verification checks. In this paper, we identify and justify the importance of data modelling in overall workflows specification and verification. We illustrate and define several potential data flow problems that, if not detected prior to workflow deployment may prevent the process from correct execution, execute process on inconsistent data or even lead to process suspension. A discussion on essential requirements of the workflow data model in order to support data validation is also given.