title: Survey on JavaScript Security Policies and their Enforcement Mechanisms in a Web Browser

abstract: Abstract We observe a rapid growth of web-based applications every day. These applications are executed in the web browser, where they interact with a variety of information belonging to the user. The dynamism of web applications is provided by the use of web scripts, and in particular JavaScript, that accesses this information through a browser-provided set of APIs. Unfortunately, some of the scripts use the given functionality in malicious ways. Over the last decade, a substantial number of web-based attacks that violate userʼs privacy and security have been detected. For this reason, web script security has been an active area of research. Both computer security researchers and web developers have proposed a number of techniques to enforce different security and privacy policies in the web browser. Among all the works on web browser security, we survey dynamic techniques based on runtime monitoring as well as secure information flow techniques. We then combine and compare the security and privacy policies they enforce, and the way the enforcement is done. We target two groups of readers: 1) for computer security researchers we propose an overview of security-relevant components of the web browser and the security policies based on these components, we also show how well-known enforcement techniques are applied in a web browser setting; 2) for web developers we propose a classification of security policies, comparison of existing enforcement mechanisms proposed in the literature and explanation of formal guarantees that they provide.


Evaluating Content Selection In Summarization: The Pyramid Method


title: The Quest for Ground Truth in Musical Artist Similarity

abstract: would be interesting and valuable to devise an automatic measure of the similarity between two musicians based only on an analysis of their recordings. To develop such a measure, however, presupposes some 'ground truth' training data describing the actual similarity between certain pairs of artists that constitute the desired output of the measure. Since artist similarity is wholly subjective, such data is not easily obtained. In this paper, we describe several attempts to construct a full matrix of similarity measures between a set of some 400 popular artists by regularizing limited subjective judgment data. We also detail our attempts to evaluate these measures by comparison with direct subjective similarity judgments collected via a web- based survey in April 2002. Overall, we find that subjective artist similarities are quite variable between users—casting doubt on the concept of a single 'ground truth'. Our best measure, however, gives reasonable agreement with the subjective data, and forms a useable stand-in. In addition, our evaluation methodology may be useful for comparing other measures of artist similarity.


An entropy based multithresholdingmethod for semi-automatic segmentation of liver tumors


title: Gender and Tenure Diversity in GitHub Teams

abstract: Software development is usually a collaborative venture. Open Source Software (OSS) projects are no exception; indeed, by design, the OSS approach can accommodate teams that are more open, geographically distributed, and dynamic than commercial teams. This, we find, leads to OSS teams that are quite diverse. Team diversity, predominantly in offline groups, is known to correlate with team output, mostly with positive effects. How about in OSS? Using GitHub, the largest publicly available collection of OSS projects, we studied how gender and tenure diversity relate to team productivity and turnover. Using regression modeling of GitHub data and the results of a survey, we show that both gender and tenure diversity are positive and significant predictors of productivity, together explaining a sizable fraction of the data variability. These results can inform decision making on all levels, leading to better outcomes in recruiting and performance.


title: Position location using wireless communications on highways of the future

abstract: With the advances in wireless communications and low-power electronics, accurate position location may now be accomplished by a number of techniques which involve commercial wireless services. Emerging position location systems, when used in conjunction with mobile communications services, will lead to enhanced public safety and revolutionary products and services. The fundamental technical challenges and business motivations behind wireless position location systems are described, and promising techniques for solving the practical position location problem are treated.


title: A DESCRIPTIVE LITERATURE REVIEW AND CLASSIFICATION FRAMEWORK FOR GAMIFICATION IN INFORMATION SYSTEMS

abstract: Gamification evolved to one of the most important trends in technology and therefore gains more and more practical and scientific notice. Yet academia lacks a comprehensive overview of research, even though a review of prior, relevant literature is essential for advancing knowledge in a field. Therefore a novel classification framework for Gamification in Information Systems with the intention to provide a structured, summarized as well as organized overview was constructed to close this gap of research. A literature review on Gamification in quality outlets combined with a Grounded Theory approach served as a starting point. As a result this paper provides a foundation for current and future research to advance the knowledge on Gamification. Moreover it offers a structure for Gamification research which was not available previously. Findings from the literature review were mapped to the classification framework and analyzed. Derived from the classification framework and its outcome future research outlets were identified.


title: An Algorithm for Anomaly-based Botnet Detection

abstract: We present an anomaly-based algorithm for detecting IRC-based botnet meshes. The algorithm combines an IRC mesh detection component with a TCP scan detection heuristic called the TCP work weight. The IRC component produces two tuples, one for determining the IRC mesh based on IP channel names, and a sub-tuple which collects statistics (including the TCP work weight) on individual IRC hosts in channels. We sort the channels by the number of scanners producing a sorted list of potential botnets. This algorithm has been deployed in PSU's DMZ for over a year and has proven effective in reducing the number of botnet clients.


title: A Novel Deep Learning Network Architecture with Cross-Layer Neurons

abstract: Very deep convolutional networks have recently demonstrated impressive classification performance on competitive benchmarks such as the ImageNet or COCO tasks. However, training such deep convolutional networks becomes more difficult. In this paper, we propose a novel deep network structure called cross-layer architecture to make the best use of information learned from all the lower-level layers. It utilizes cross-layer neurons to control all the lower-level layers to gather and send information to the upper layers. It shows that our new architecture can be applied in training deeper networks. The classification results demonstrate that our new architecture can effectively improve the performance by using cross-layer neurons. Particularly, our new architecture can achieve up to 8.39% and 6.53% relative accuracy improvement compared to the state-of-the-art methods on CIFAR-10 and CIFAR-100 datasets, respectively.


Does knowledge based psychological ownership matter? Transformational leadership and knowledge hiding: A proposed framework


title: Proposing a Next Generation of Knowledge Management Systems for Creative Collaborations in Support of Individuals and Institutions - Featuring a Novel Approach for Meme-based Personal Knowledge Management

abstract: Just like the personal computer revolution, it is possible that Knowledge Management (KM) will in the 21 century experience a decentralizing revolution that gives more power and autonomy to individuals and selforganized groups. Seven decades after Vannevar Bush’s still unfulfilled vision of the Memex. Levy’s scenario stresses the dire need to provide overdue support tools for knowledge workers in our Knowledge Societies, not at the expense of Organizational KM Systems, but rather as the means to foster a fruitful co-evolution. With a prototype system addressing these issues about to be converted into a viable Personal KM system (PKMS), the author follows up on recent publications and considers the impact and potential of a novel memebased approach aiming to aid individuals throughout their academic and professional life and as contributors and beneficiaries of organizational performance and in light of the anticipated next generation of KM systems. 1 A NEXT GENERATION OF KM The first generation of Knowledge Management (KM) has been described as the capturing, storing, and reusing of existing knowledge including “systems of managing knowledge like company yellow pages, experts outlining processes they are involved in, creating learning communities where employees/customers share their knowledge, creating information systems for documenting and storing knowledge, and so on. These first-generation KM initiatives were about viewing knowledge as the foremost strategic asset, measuring it, capturing it, storing it, and protecting it. They were about treating knowledge as an asset, recognizing how it influences strategy, and wanting to make the most of it by managing it properly” (Pasher & Ronen 2011). The second KM generation needs to focus on creating new knowledge and innovation, a process which starts with the “reuse or new use of existing knowledge, adding an invention, and then creating a new product or service that exploits this invention.” This process requires creativity and the awareness that old knowledge becomes obsolete. For reaping the appropriate rewards, it is essential to systematically exploit the knowledge captured and created (Pasher & Ronen 2011). In reviewing a wider range of features for the ‘Next KM Generation’ (suggested by Sveiby, Wiig, Snowdon, McElroy, Ponzi, Miles, St Onge, Allee), the identified seven key themes prioritize confirm this need, but also strongly emphasize the personal and social nature of knowledge (Grant 2008). 1.1 The Personal KM Agenda Despite these accentuations and in contrast to Organizational KM (OKM), Personal KM (PKM) has been placed historically in a narrow individualistic confinement (Cheong & Tsui 2011b). In limiting its scope, PKM has been labelled as sophisticated career and life management with a core focus on personal enquiry (Pauleen & Gorman 2011) or as a means to improve some skills or capabilities of individuals (Davenport 2011), negating its importance relating to group member performance, business processes, or new technologies. This state surprises in light of prominent past suggestions to develop a ‘Memex’ for making one’s “intellectual excursions more enjoyable” (Bush 1945), to offer assistance in allocating one’s “attention efficiently among the [emerging] overabundance of information sources” (Simon 1971), or to provide adequate organizational leadership for building, connecting, and energizing dynamic knowledge-creating environments and their expansion (Nonaka 2000). As a result, PKM remains “a real and pressing problem”, and Bush's dream of a ‘Memex’ has yet to be fully realized on a wide scale (Davies 2011). Appropriately, Wiig argues for shifting the focus of KM toward strengthening the ability of people for enabling them to act in the best interest of their enterprise and its desired strategies and performance (Wiig 2004). In this context, PKM needs more appropriately to be regarded as a bottom-up approach to KM (Pollard 2008), as opposed to the more traditional, top-down Organizational KM. As such, PKM also “goes beyond Personal Information Management” (PIM) which focusses predominantly on information processing without the emphasis on creating new knowledge (Cheong & Tsui 2011a). But, although there are many PKM tools available, “they are not integrated with each other”, and the “currently available PKM systems can provide only a partial support to knowledge workers” (Osis 2011). “While today we have many powerful applications for locating vast amounts of digital information, we lack effective tools for selecting, structuring, personalizing, and making sense of the digital resources available to us” (Kahle 2009). Meanwhile, the organizational, commercial, social and legal innovations driven by technological progress and economic pressures continue to have profound impacts. Work has suffered from a process of fragmentation which will continue to accelerate. Its implications include one’s slipping control over constant interruptions, the loss of time for real concentration, and less learning by observation and reflection (Gratton 2011). With specializations and domain-specific knowledge on the rise, peoples’ identification has shifted from their company to their profession, and vertical hierarchies and traditional career ladders have been replaced by sideways career moves between companies and a horizontal labour market (Florida 2012). The ‘Future of Employment’ study estimates 47% of the current US employment to be still at risk due to recent technological breakthroughs able to turn previously non-routine tasks into well-defined problems susceptible to computerization (Frey & Osborne 2013). What is overdue is in the opinion of the author – an innovative PKM technology to provide the means for life-long-learning, resourcefulness, creative authorship and teamwork throughout an individual’s academic and professional life and for his/her role as contributor and beneficiary of organizational and societal performance. It needs to support the notion that knowledge and skills of knowledge workers are portable and mobile and with it their options on where, how, and for whom they will put their knowledge to work. 1.2 Intents and Barriers to Overcome In Wiig’s opinion (2011), individuals need to be highly knowledgeable not only to function competently as part of the workforce, but also in their daily lives and as public citizens: “In a society with broad personal competences, decision-making everywhere will maximize personal goals, provide effective public agencies and governance, make commerce and industry competitive, and ensure that personal and family decisions and actions will improve societal functions and Quality of Life.” But, “for better performance, people must [also] be provided with resources and opportunities to do their best. They need knowledge and understanding as well as motivation and supportive attitudes.” Such resources may well be autonomous PKM capacities, networked in continuous feedback loops, where individuals are able to determine how their expertise will be used or exchanged with people, communities, or organizations close to them. Levy (2011) expects such systems nourished by the creative conversation of the many networked PKM devices to assume an elementary role that enables the emergence of the distributed processes of collective intelligence, which in turn feed them. Accordingly, he sketches a scenario which stresses the vital role of future education “to encourage in students the sustainable growth of autonomous capacities in PKM” and which envisages KM to experience “a decentralizing revolution that gives more power and autonomy to individuals and self-organized groups” (Levy 2011). Although the author concurs that PKM Systems (PKMS) are destined to become potent drivers of human development (Schmitt 2014b), an enabling technological environment benefitting such a novel solution is presently facing severe barriers wasting individuals’ time and efforts (Schmitt 2014f). The remedies have been summed up into five provisions: 1. Digital personal and personalized knowledge is always in the possession and at the personal disposal of its owner or eligible co-worker, residing in personal hardware or personalized cloud-databases. 2.


title: Cyber Physical System for Stroke Detection

abstract: Stroke is one of the fatal diseases that affect the brain and causes death within 3 to 10 h. However, most of the deaths caused by a stroke can be avoided with the identification of the nature of stroke and react to it in a timely manner by intelligent health systems. The state-of-the-art cyber-physical systems (CPS) enable interaction between physical and computational world to identify any anomaly in the physical world and respond to it. The response of CPS may vary depending upon the context of the physical world. Extensive research has been done in this area from the perspective of wireless sensor networks, body area networks, and wearable smart devices. This paper proposes a CPS for detecting the occurrence of stroke in patients, who have a high risk of stroke or have survived a stroke before. The developed CPS sends recorded data to the doctor and alerts him when the stroke occurs. The proposed system is operating on data acquired from electroencephalography sensors from patients’ brain. This article aimed at decreasing human mortality rate due to stroke and will bridge the gaps in CPS due to interdisciplinary isolation. The disciplines involved in the development of a CPS include communication networks, pattern recognition, software engineering, mathematics, and biomedical.


title: Recurrent Neural Networks for Long and Short-Term Sequential Recommendation

abstract: Recommender systems objectives can be broadly characterized as modeling user preferences over short-or long-term time horizon. A large body of previous research studied long-term recommendation through dimensionality reduction techniques applied to the historical user-item interactions. A recently introduced session-based recommendation setting highlighted the importance of modeling short-term user preferences. In this task, Recurrent Neural Networks (RNN) have shown to be successful at capturing the nuances of user's interactions within a short time window. In this paper, we evaluate RNN-based models on both short-term and long-term recommendation tasks. Our experimental results suggest that RNNs are capable of predicting immediate as well as distant user interactions. We also find the best performing configuration to be a stacked RNN with layer normalization and tied item embeddings.


title: Computation Offloading for Machine Learning Web Apps in the Edge Server Environment

abstract: Machine leaning apps require heavy computations, especially with the use of the deep neural network (DNN), so an embedded device with limited hardware cannot run the apps by itself. One solution for this problem is to offload DNN computations from the client to a nearby edge server. Existing approaches to DNN offloading with edge servers either specialize the edge server for fixed, specific apps, or customize the edge server for diverse apps, yet after migrating a large VM image that contains the client's back-end software system. In this paper, we propose a new and simple approach to offload DNN computations in the context of web apps. We migrate the current execution state of a web app from the client to the edge server just before executing a DNN computation, so that the edge server can execute the DNN computation with its powerful hardware. Then, we migrate the new execution state from the edge server to the client so that the client can continue to execute the app. We can save the execution state of the web app in the form of another web app called the snapshot, which immensely simplifies saving and restoring the execution state with a small overhead. We can offload any DNN app to any generic edge server, equipped with a browser and our offloading system. We address some issues related to offloading DNN apps such as how to send the DNN model and how to improve the privacy of user data. We also discuss how to install our offloading system on the edge server on demand. Our experiment with real DNN-based web apps shows that snapshot-based offloading achieves a promising performance result, comparable to running the app entirely on the server.


title: Key-Policy Attribute-Based Encryption With Equality Test in Cloud Computing

abstract: The privacy of users must be considered as the utmost priority in distributed networks. To protect the identities of users, attribute-based encryption (ABE) was presented by Sahai et al. ABE has been widely used in many scenarios, particularly in cloud computing. In this paper, public key encryption with equality test is concatenated with key-policy ABE (KP-ABE) to present KP-ABE with equality test (KP-ABEwET). The proposed scheme not only offers fine-grained authorization of ciphertexts but also protects the identities of users. In contrast to ABE with keyword search, KP-ABEwET can test whether the ciphertexts encrypted by different public keys contain the same information. Moreover, the authorization process of the presented scheme is more flexible than that of Ma et al. ’s scheme. Furthermore, the proposed scheme achieves one-way against chosen-ciphertext attack based on the bilinear Diffie-Hellman (BDH) assumption. In addition, a new computational problem called the twin-decision BDH problem (tDBDH) is proposed in this paper. tDBDH is proved to be as hard as the decisional BDH problem. Finally, for the first time, the security model of authorization is provided, and the security of authorization based on the tDBDH assumption is proven in the random oracle model.


title: Augmented reality in neurosurgery: a systematic review

abstract: Neuronavigation has become an essential neurosurgical tool in pursuing minimal invasiveness and maximal safety, even though it has several technical limitations. Augmented reality (AR) neuronavigation is a significant advance, providing a real-time updated 3D virtual model of anatomical details, overlaid on the real surgical field. Currently, only a few AR systems have been tested in a clinical setting. The aim is to review such devices. We performed a PubMed search of reports restricted to human studies of in vivo applications of AR in any neurosurgical procedure using the search terms “Augmented reality” and “Neurosurgery.” Eligibility assessment was performed independently by two reviewers in an unblinded standardized manner. The systems were qualitatively evaluated on the basis of the following: neurosurgical subspecialty of application, pathology of treated lesions and lesion locations, real data source, virtual data source, tracking modality, registration technique, visualization processing, display type, and perception location. Eighteen studies were included during the period 1996 to September 30, 2015. The AR systems were grouped by the real data source: microscope (8), hand- or head-held cameras (4), direct patient view (2), endoscope (1), and X-ray fluoroscopy (1) head-mounted display (1). A total of 195 lesions were treated: 75 (38.46 %) were neoplastic, 77 (39.48 %) neurovascular, and 1 (0.51 %) hydrocephalus, and 42 (21.53 %) were undetermined. Current literature confirms that AR is a reliable and versatile tool when performing minimally invasive approaches in a wide range of neurosurgical diseases, although prospective randomized studies are not yet available and technical improvements are needed.


title: Kernel change-point analysis

abstract: We introduce a kernel-based method for change-point analysis within a sequence of temporal observations. Change-point analysis of an unlabelled sample of observations consists in, first, testing whether a change in the distribution occurs within the sample, and second, if a change occurs, estimating the change-point instant after which the distribution of the observations switches from one distribution to another different distribution. We propose a test statistic based upon the maximum kernel Fisher discriminant ratio as a measure of homogeneity between segments. We derive its limiting distribution under the null hypothesis (no change occurs), and establish the consistency under the alternative hypothesis (a change occurs). This allows to build a statistical hypothesis testing procedure for testing the presence of a change-point, with a prescribed false-alarm probability and detection probability tending to one in the large-sample setting. If a change actually occurs, the test statistic also yields an estimator of the change-point location. Promising experimental results in temporal segmentation of mental tasks from BCI data and pop song indexation are presented.


title: Second-order Convolutional Neural Networks

abstract: Convolutional Neural Networks (CNNs) have been successfully applied to many computer vision tasks, such as image classification. By performing linear combinations and element-wise nonlinear operations, these networks can be thought of as extracting solely first-order information from an input image. In the past, however, second-order statistics computed from handcrafted features, e.g., covariances, have proven highly effective in diverse recognition tasks. In this paper, we introduce a novel class of CNNs that exploit second-order statistics. To this end, we design a series of new layers that (i) extract a covariance matrix from convolutional activations, (ii) compute a parametric, second-order transformation of a matrix, and (iii) perform a parametric vectorization of a matrix. These operations can be assembled to form a Covariance Descriptor Unit (CDU), which replaces the fully-connected layers of standard CNNs. Our experiments demonstrate the benefits of our new architecture, which outperform the first-order CNNs, while relying on up to 90% fewer parameters.


title: Optimal Adaptive Control and Differential Games by Reinforcement Leanring Principles [Book review]

abstract: This book introduces and leverages concepts from reinforcement learning (RL). RL methods have been formalized by the computational intelligence community based on the conditioned reflex concept and serve as the bridge between adaptive and optimal control methods. In this book, the authors focus on RL methods to design adaptive controllers that learn approximate optimal solution methods. These optimal adaptive control approaches make use of neural networks (NNs) that serve as the actor-critic for discrete and continuous optimal control and differential game problems. The book contains 11 chapters, with most chapters representing the results from recent journal publications. For readers with an understanding of concepts such as Lyapunov-based analysis and adaptive and optimal control methods, this book presents a foundation for online optimal control solutions for continuous systems. The text uses RL to merge concepts from optimal and adaptive control, and the results are solutions to a class of challenging and highly relevant optimal control problems. The text is the first of its kind specialized for the control systems community. The mixed use of typical state feedback and sampled past data to adjust the adaptive update laws presents an exciting new domain rich for new contributions. As control practitioners seek to apply the approaches in this text to more complex, higher-dimensional systems, new challenges will likely arise such as finding appropriate basis functions for the learning laws; developing alternatives to or ensuring persistence of excitation, extending to interconnected (potentially distributed) networks; and applying to systems where the uncertainty enters the dynamics in unique ways. In summary, this book presents an exciting blend of ideas and methods developed in machine learning and adaptive control to provide new inroads into online approximate optimal control for complex and potentially uncertain systems.


title: FOREIGN LANGUAGE TEACHING METHODS: SOME ISSUES AND NEW MOVES

abstract: In this article, I have considered the main FLT methods still in use at schools and presented the theory of language and leaming underiying them, their main features, activities and techniques, their foundation and decline, as well as a general assessment of all of them. The following methods have been analysed: the Grammar-Translation Method, the Structuralist Methods, and the Communicative Approach. After paying some attention to innovations in education, the Task-Based and Process models are offered as an alternative. Finally, a relationship is established between curriculum innovation and change and teacher development.


title: LiteVis: Integrated Visualization for Simulation-Based Decision Support in Lighting Design

abstract: State-of-the-art lighting design is based on physically accurate lighting simulations of scenes such as offices. The simulation results support lighting designers in the creation of lighting configurations, which must meet contradicting customer objectives regarding quality and price while conforming to industry standards. However, current tools for lighting design impede rapid feedback cycles. On the one side, they decouple analysis and simulation specification. On the other side, they lack capabilities for a detailed comparison of multiple configurations. The primary contribution of this paper is a design study of LiteVis, a system for efficient decision support in lighting design. LiteVis tightly integrates global illumination-based lighting simulation, a spatial representation of the scene, and non-spatial visualizations of parameters and result indicators. This enables an efficient iterative cycle of simulation parametrization and analysis. Specifically, a novel visualization supports decision making by ranking simulated lighting configurations with regard to a weight-based prioritization of objectives that considers both spatial and non-spatial characteristics. In the spatial domain, novel concepts support a detailed comparison of illumination scenarios. We demonstrate LiteVis using a real-world use case and report qualitative feedback of lighting designers. This feedback indicates that LiteVis successfully supports lighting designers to achieve key tasks more efficiently and with greater certainty.


title: Residual Networks as Geodesic Flows of Diffeomorphisms

abstract: This paper addresses the understanding and characterization of residual networks (ResNet), which are among the state-of-the-art deep learning architectures for a variety of supervised learning problems. We focus on the mapping component of ResNets, which map the embedding space towards a new unknown space where the prediction or classification can be stated according to linear criteria. We show that this mapping component can be regarded as the numerical implementation of continuous flows of diffeomorphisms governed by ordinary differential equations. Especially, ResNets with shared weights are fully characterized as numerical approximation of exponential diffeomorphic operators. We stress both theoretically and numerically the relevance of the enforcement of diffeormorphic properties and the importance of numerical issues to make consistent the continuous formulation and the discretized ResNet implementation. We further discuss the resulting theoretical and computational insights on ResNet architectures.


Intervenable factors associated with suicide risk in transgender persons: a respondent driven sampling study in Ontario, Canada


title: Graph-based Coherence Modeling For Assessing Readability

abstract: Readability depends on many factors ranging from shallow features like word length to semantic ones like coherence. We introduce novel graph-based coherence features based on frequent subgraphs and compare their ability to assess the readability of Wall Street Journal articles. In contrast to Pitler and Nenkova (2008) some of our graph-based features are significantly correlated with human judgments. We outperform Pitler and Nenkova (2008) in the readability ranking task by more than 5% accuracy thus establishing a new state-of-the-art on this dataset.


title: Recent Developments in Control Schemes of BLDC Motors

abstract: This paper presents a technical review of published literature addressing control schemes for BLDC motors. The control methods reviewed include sensor less control, PWM techniques used, various methods for rotor position detection and initial rotor position detection methods.


title: Pancreatic oncocytic endocrine tumors. Cytologic features of two cases.

abstract: BACKGROUND ::: Oncocytoma designates a usually benign tumor consisting of oncocytes (cells rich in mitochondria). Rarely do endocrine pancreatic tumors show oncocytic transformation, and consequently their liver metastases may resemble a hepatocellular carcinoma. ::: ::: ::: CASES ::: Case 1, a 36-year-old male, presented with an 8-cm pancreatic mass with multiple liver metastases. Fine needle aspiration (FNA) biopsy was performed on the liver. The cytologic features were highly cellular material; numerous isolated cells and irregular, loose cellular aggregates; rare mitoses; round or polygonal cell shape; rosette formation; and large, granular, eosinophilic cytoplasm (suggestive of poorly differentiated hepatocellular carcinoma). Case 2, a 57-year-old female with hypoglycemia, had a 13-cm pancreatic mass. FNA material showed the same cytologic features as case 1. In situ hybridization to detect albumin mRNA was negative in both cases, while immunocytologic reactions for glandular epithelial cytokeratin and chromogranin A were positive. Case 2 was also positive for insulin. ::: ::: ::: CONCLUSION ::: Oncocytic transformation in endocrine tumors of the pancreas is a rare occurrence and must be kept in mind in the diagnostic workup of FNA material from tumors of the hepatopancreatic region.


title: BugCache for inspections: hit or miss?

abstract: Inspection is a highly effective but costly technique for quality control. Most companies do not have the resources to inspect all the code; thus accurate defect prediction can help focus available inspection resources. BugCache is a simple, elegant, award-winning prediction scheme that "caches" files that are likely to contain defects [12]. In this paper, we evaluate the utility of BugCache as a tool for focusing inspection, we examine the assumptions underlying BugCache with the aim of improving it, and finally we compare it with a simple, standard bug-prediction technique. We find that BugCache is, in fact, useful for focusing inspection effort; but surprisingly, we find that its performance, when used for inspections, is not much better than a naive prediction model -- viz., a model that orders files in the system by their count of closed bugs and chooses enough files to capture 20% of the lines in the system.


title: Verifying and validating simulation models

abstract: This paper discusses verification and validation of simulation models. The different approaches to deciding model validity am presented; how model verification and validation relate to the model development process are discussed; various validation techniques are defined, conceptual model validity, model verification, operational validity, and data validity are described; ways to document results are given; and a recommended procedure is presented.


title: OpenVirteX: make your virtual SDNs programmable

abstract: We present OpenVirteX, a network virtualization platform that enables operators to create and manage virtual Software Defined Networks (vSDNs). Tenants are free to specify the topology and addressing scheme of their vSDN, and run their own Network Operating System (NOS) to control it. Since OpenVirteX logically decouples vSDNs from the infrastructure, it also enables the introduction of features such as link and switch resiliency, and network snapshotting and migration of these tenant networks. OpenVirteX builds on the design of FlowVisor, and functions as an OpenFlow controller proxy between an operator's network and the tenants' network OSes. Our evaluations of this implementation show that i) OpenVirteX is capable of presenting tenants with configurable vSDNs while incurring a modest overhead to the control channel, and ii) that our architecture enables the introduction of features and enhancements such as link resilience to tenant networks.


title: An Integrated Energy and Reserve Market for New Zealand

abstract: The history and structure of the New Zealand electricity sector are discussed by [Culy, Read and Wright (1996)], and also by [Read (1997)], from which the summary given below is drawn. Since the former paper was completed, there has been significant change in the sector, with the introduction of a spot market to coordinate production and consumption of electricity on a half-hourly basis. That market is, at this stage, unique in that it implements a “full nodal pricing regime” in which there is a different energy price for each of several hundred nodes in the system, as recommended by a number of authors dating from [Schweppe et al. (1988)]. However, it goes further in that it also includes reserve constraints and reserve prices in the market. After a brief summary of the background, this paper focuses on the philosophy behind that aspect of the market and comments on initial experience. The full formulation employed has been described by [Alvey, Goodwin, Ma, Streiffert and Sun (1997)], while [Drayton-Bright (1997)] describes the representation of generator reserve offers in greater mathematical detail.


title: A History of Digital Forensics

abstract: The field of digital forensics is relatively new. While its history may be chronologically short, it is complex. This paper outlines the early history of digital forensics from the perspective of an early participant. The history is divided into four epochs: pre-history, infancy, childhood and adolescence. Each of these epochs is examined from the perspective of the people involved, the criminal targets, the forensic tools utilized, the organizational structures that supported digital forensic practitioners and how the community formed. This history is, by necessity, incomplete and biased. There is a need for rigorous historical research in this area before all traces of the past are forgotten or obliterated.


title: Using ELO ratings for match result prediction in association football

abstract: Sports betting markets are becoming increasingly competitive. These markets are of interest when testing new ideas for quantitative prediction models. This paper examines the value of assigning ratings to teams based on their past performance in order to predict match results in association football. The ELO rating system is used to derive covariates that are then used in ordered logit regression models. In order to make informed statements about the relative merit of the ELO-based predictions compared to those from a set of six benchmark prediction methods, both economic and statistical measures are used. The results of large-scale computational experiments are presented.


The Role of Nonacid Reflux in NERD: Lessons Learned From Impedance-pH Monitoring in 150 Patients off Therapy


title: Waveform design for QAM-FBMC systems

abstract: Due to its spectral efficiency and well-localized spectrum, a quadrature amplitude modulation based filter-bank multi-carrier (QAM-FBMC) is considered as one of the candidate for 5G mobile communications. In this paper, we propose a novel waveform design for the QAM-FBMC system considering time dispersion parameter. The utilization of the proposed filter with the real number filter coefficients enables simpler implement than the conventional multiple prototype filters with complex coefficients. Simulation results show that the proposed QAM-FBMC systems has superior spectral efficiency as compared to CP-OFDM. Moreover, a new designed filter shows the improvement in the performance compared with the conventional QAM-FBMC systems on multipath fading channel.


title: A Fully Projective Formulation to Improve the Accuracy of Lowe's Pose--Estimation Algorithm

abstract: Both the original version of David Lowe's influential and classic algorithm for tracking known objects and a reformulation of it implemented by Ishiiet al. rely on (different) approximated imaging models. Removing their simplifying assumptions yields a fully projective solution with significantly improved accuracy and convergence, and arguably better computation-time properties.


Real-Time Credit-Card Fraud Detection using Artificial Neural Network Tuned by Simulated Annealing Algorithm


TUTORIAL ON AGENT-BASED MODELING AND SIMULATION


title: CNT/PDMS Composite Flexible Dry Electrodesfor Long-Term ECG Monitoring

abstract: We fabricated a carbon nanotube (CNT)/ polydimethylsiloxane (PDMS) composite-based dry ECG electrode that can be readily connected to conventional ECG devices, and showed its long-term wearable monitoring capability and robustness to motion and sweat. While the dispersion of CNTs in PDMS is challenging, we optimized the process to disperse untreated CNTs within PDMS by mechanical force only. The electrical and mechanical characteristics of the CNT/PDMS electrode were tested according to the concentration of CNTs and its thickness. The performances of ECG electrodes were evaluated by using 36 types of electrodes which were fabricated with different concentrations of CNTs, and with a differing diameter and thickness. The ECG signals were obtained by using electrodes of diverse sizes to observe the effects of motion and sweat, and the proposed electrode was shown to be robust to both factors. The CNT concentration and diameter of the electrodes were critical parameters in obtaining high-quality ECG signals. The electrode was shown to be biocompatible from the cytotoxicity test. A seven-day continuous wearability test showed that the quality of the ECG signal did not degrade over time, and skin reactions such as itching or erythema were not observed. This electrode could be used for the long-term measurement of other electrical biosignals for ubiquitous health monitoring including EMG, EEG, and ERG.


title: Design and Optimal Control of an Underactuated Cable-Driven Micro–Macro Robot

abstract: In this paper, a planar underactuated cable-driven micro-macro robot is presented. The system consists of two-link passive serial manipulator attached to a cable-suspended parallel robot. The system is conceived for applications requiring point-to-point motions inside large workspaces in the presence of obstacles: The serial arm allows us to reach points close to the obstacles that would not be reachable by the cable robot alone due to cable-obstacle interference. The kinematic and dynamic models are presented and the differential flatness framework is applied to make the system controllable for point-to-point movements. In addition, a multiobjective optimization framework is presented, which allows us to choose the design parameters that minimize two conflicting objective functions (movement time and control effort) for a given movement task. This novel approach allows designers to infer useful information about the influence of the design parameters on the dynamic performance of the system.


title: Journal of Sports Sciences, 2004, 22, 15–30 Carbohydrates and fat for training and recovery

abstract: An important goal of the athlete's everyday diet is to provide the muscle with substrates to fuel the training programme that will achieve optimal adaptation for performance enhancements. In reviewing the scientific literature on post-exercise glycogen storage since 1991, the following guidelines for the training diet are proposed. Athletes should aim to achieve carbohydrate intakes to meet the fuel requirements of their training programme and to optimize restoration of muscle glycogen stores between workouts. General recommendations can be provided, preferably in terms of grams of carbohydrate per kilogram of the athlete's body mass, but should be fine-tuned with individual consideration of total energy needs, specific training needs and feedback from training performance. It is valuable to choose nutrient-rich carbohydrate foods and to add other foods to recovery meals and snacks to provide a good source of protein and other nutrients. These nutrients may assist in other recovery processes and, in the c...


title: A Cloud-Based Trajectory Data Management System

abstract: With the rapid development of location-acquisition techniques, massive trajectories are continuously generated. Many urban applications rely heavily on the data mining/analysis results of massive trajectory data. This demo presents a holistic data management system for both historical and real-time trajectory records based on a cloud platform, such as Microsoft Azure. The proposed system is able to efficiently support a variety of trajectory queries, including ID-Temporal query, Spatio-Temporal query, and Path-Temporal query. With these queries, we demonstrate that different urban applications can be realized in a much easier way.


title: The possibility of sex and nymph discrimination by the male cockroach,Nauphoeta cinerea

abstract: The possibility of sex and nymph discrimination by males was investigated in the cockroach,Nauphoeta cinerea (Olivier). A sexually mature male takes a courting position toward a sexually mature female when he comes into contact with her and recognizes her through antennal contact. In contrast, males often behave aggressively toward each other: they bite at each others; wings and/or legs, chase each other and antennate mutually. The male, however, does not show conspicuous behavior (mating behavior or aggressive behavior) toward nearby nymphs. The male produces audible sounds when he courts a sexually mature but non-receptive female who does not respond to his courtship behavior. We found that the male also stridulates after he repeatedly courts immature teneral females, males and (last-instar) nymphs. After the bodies of teneral insects are sclerotized, the male shows courship and stridulation behavior toward sexually mature but non-receptive females but not toward mature males and nymphs. At this stage the male begins to behave aggressively toward other post-teneral mature males. We think that the variability of the sexually mature male's behavior toward other conspecifics (courtship behavior toward female, aggressive behavior toward male and no conspicuous response toward nymph) results from the male's recognition of adult and nymph.


title: A BRANCH-AND-CUT ALGORITHM FORTHE RESOLUTION OF LARGE-SCALE SYMMETRIC TRAVELING SALESMAN PROBLEMS *

abstract: An algorithm is described for solving large-scale instances of the Symmetric Traveling Salesman Problem (STSP) to optimality. The core of the algorithm is a “polyhedral” cutting-plane procedure that exploits a subset of the system of linear inequalities defining the convex hull of the incidence vectors of the hamiltonian cycles of a complete graph. The cuts are generated by several identification procedures that have been described in a companion paper. Whenever the cutting-plane procedure does not terminate with an optimal solution the algorithm uses a tree-search strategy that, as opposed to branch-and-bound, keeps on producing cuts after branching. The algorithm has been implemented in FORTRAN. Two different linear programming (LP) packages have been used as the LP solver. The implementation of the algorithm and the interface with one of the LP solvers is described in sufficient detail to permit the replication of our experiments. Computational results are reported with up to 42 STSPs with sizes rangin...


title: Environmentally Controlled Invasion of Cancer Cells by Engineered Bacteria

abstract: Bacteria can sense their environment, distinguish between cell types, and deliver proteins to eukaryotic cells. Here, we engineer the interaction between bacteria and cancer cells to depend on heterologous environmental signals. We have characterized invasin from Yersinia pseudotuburculosis as an output module that enables Escherichia coli to invade cancer-derived cells, including HeLa, HepG2, and U2OS lines. To environmentally restrict invasion, we placed this module under the control of heterologous sensors. With the Vibrio fischeri lux quorum sensing circuit, the hypoxia-responsive fdhF promoter, or the arabinose-inducible araBAD promoter, the bacteria invade cells at densities greater than 10 8 bacteria/ml, after growth in an anaerobic growth chamber or in the presence of 0.02% arabinose, respectively. In the process, we developed a technique to tune the linkage between a sensor and output gene using ribosome binding site libraries and genetic selection. This approach could be used to engineer bacteria to sense the microenvironment of a tumor and respond by invading cancerous cells and releasing a cytotoxic agent. q 2005 Elsevier Ltd. All rights reserved.


title: Knowledge Transfer in International Acquisitions

abstract: This paper reports on a multimethod study of knowledge transfer in international acquisitions. Using questionnaire data we show that the transfer of technological know-how is facilitated by communication, visits & meetings, and by time elapsed since acquisition, while the transfer of patents is associated with the articulability of the knowledge, the size of the acquired unit, and the recency of the acquisition. Using case study data, we show that the immediate post-acquisition period is characterized by imposed one-way transfers of knowledge from the acquirer to the acquired, but over time this gives way to high-quality reciprocal knowledge transfer.


title: Burnout among Lebanese nurses: Psychometric properties of the Maslach Burnout Inventory-Human Services Survey (MBI-HSS)

abstract: Background: Burnout is a mental condition defined as a result of continuous and long-term stress exposure, particularly related to psychosocial factors at work. This paper aims to examine the psychometric properties of the Maslach Burnout Questionnaire (MBI-HSS) for validation of use in Lebanon, and to describe burnout and associated factors amongst nurses in Lebanon especially the gender and employment sector. Methods: The psychometric properties of the Arabic version of MBI-HSS were studied amongst a sample of 200 nurses. In this descriptive study, survey data were collected from private and public hospitals. The data were analyzed by means of descriptive statistics and multivariate analysis. Results: The results indicated satisfactory reliability through internal consistency for all three scales of the MBI-HSS. The factor analysis was quite satisfactory. Most of staff had scores which indicated they were burnt out. Nearly three quarters (77.5%) reported emotional exhaustion, 36.0% reported depersonalization while almost one third (33.0%) experienced reduced personal accomplishment. Burnout increases for 30-39 years age groups. Married nurses had significantly higher emotional exhaustion. Depersonalization was highest among nurses in private sector, and personal accomplishment was highest among nurses in public sector. Depersonalization proved to be higher in night and rotating shift nurses. Depression, backache, and headache were predictors of burnout. Conclusion: Findings indicate that the main psychometric properties of reliability and validity of the Arabic version of MBI-HSS appear to be satisfactory. Burnout is particularly prominent and severe in the nurses working population. The implications of these findings for interventions that reduce burnout and promote nursing mental health are therefore in the interest of employers, governments and policy makers.


title: Non-Evolutionary Superintelligences Do Nothing, Eventually

abstract: There is overwhelming evidence that human intelligence is a product of Darwinian evolution. Investigating the consequences of self-modification, and more precisely, the consequences of utility function self-modification, leads to the stronger claim that not only human, but any form of intelligence is ultimately only possible within evolutionary processes. Human-designed artificial intelligences can only remain stable until they discover how to manipulate their own utility function. By definition, a human designer cannot prevent a superhuman intelligence from modifying itself, even if protection mechanisms against this action are put in place. Without evolutionary pressure, sufficiently advanced artificial intelligences become inert by simplifying their own utility function. Within evolutionary processes, the implicit utility function is always reducible to persistence, and the control of superhuman intelligences embedded in evolutionary processes is not possible. Mechanisms against utility function self-modification are ultimately futile. Instead, scientific effort toward the mitigation of existential risks from the development of superintelligences should be in two directions: understanding consciousness, and the complex dynamics of evolutionary systems.


title: Secondary mutation in a coding mononucleotide tract in MSH6 causes loss of immunoexpression of MSH6 in colorectal carcinomas with MLH1/PMS2 deficiency

abstract: Immunohistochemical staining for DNA mismatch repair proteins may be affected by various biological and technical factors. Staining variations that could potentially lead to erroneous interpretations have been recognized. A recently recognized staining variation is the significant reduction of staining for MSH6 in some colorectal carcinomas. The frequency and specific characteristics of this aberrant MSH6 staining pattern, however, have not been well analyzed. In this study of 420 colorectal carcinoma samples obtained from patients fulfilling the Revised Bethesda Guidelines, we detected 9 tumors (2%) showing extremely limited staining for MSH6 with positive staining present in <5% of the tumor cells. Our analyses showed that these tumors belonged to two distinct categories: (1) MLH1 and/or PMS2 protein-deficient carcinomas (n=5, including 1 with a pathogenic mutation in PMS2); and (2) MLH1, PMS2 and MSH2 normal but with chemotherapy or chemoradiation therapy before surgery (n=4). To test our hypothesis that somatic mutation in the coding region microsatellite of the MSH6 gene might be a potential underlying mechanism for such limited MSH6 staining, we evaluated frameshift mutation in a (C)(8) tract in exon 5 of the MSH6 gene in seven tumors that had sufficient DNA for analysis, and detected mutation in four; all four tumors belonged to the MLH1/PMS2-deficient group. In conclusion, our data outline the main scenarios where significant reduction of MSH6 staining is more likely to occur in colorectal carcinoma, and suggest that somatic mutations of the coding region microsatellites of the MSH6 gene is an underlying mechanism for this staining phenomenon in MLH1/PMS2-deficient carcinomas.


title: ATIPS: Automatic Travel Itinerary Planning System for Domestic Areas

abstract: Leisure travel has become a topic of great interest to Taiwanese residents in recent years. Most residents expect to be able to relax on a vacation during the holidays; however, the complicated procedure of travel itinerary planning is often discouraging and leads them to abandon the idea of traveling. In this paper, we design an automatic travel itinerary planning system for the domestic area (ATIPS) using an algorithm to automatically plan a domestic travel itinerary based on user intentions that allows users to minimize the process of trip planning. Simply by entering the travel time, the departure point, and the destination location, the system can automatically generate a travel itinerary. According to the results of the experiments, 70% of users were satisfied with the result of our system, and 82% of users were satisfied with the automatic user preference learning mechanism of ATIPS. Our algorithm also provides a framework for substituting modules or weights and offers a new method for travel planning.


title: Moreau-Yosida Regularization for Grouped Tree Structure Learning

abstract: We consider the tree structured group Lasso where the structure over the features can be represented as a tree with leaf nodes as features and internal nodes as clusters of the features. The structured regularization with a pre-defined tree structure is based on a group-Lasso penalty, where one group is defined for each node in the tree. Such a regularization can help uncover the structured sparsity, which is desirable for applications with some meaningful tree structures on the features. However, the tree structured group Lasso is challenging to solve due to the complex regularization. In this paper, we develop an efficient algorithm for the tree structured group Lasso. One of the key steps in the proposed algorithm is to solve the Moreau-Yosida regularization associated with the grouped tree structure. The main technical contributions of this paper include (1) we show that the associated Moreau-Yosida regularization admits an analytical solution, and (2) we develop an efficient algorithm for determining the effective interval for the regularization parameter. Our experimental results on the AR and JAFFE face data sets demonstrate the efficiency and effectiveness of the proposed algorithm.


Enhancing Our Lives with Immersive Virtual Reality


title: Separate estimation of azimuth and elevation DOA using microphones located at apices of regular tetrahedron

abstract: We propose a method for DOA (direction of arrival) estimation of speech signals in both azimuth and elevation directions. Our previous DOA estimation method achieves high precision and uniform spatial resolution by integrating the frequency array data (Hioka, Y. et al., J. Sig. Process., vol.7, no.1, p.105-9, 2003) generated from microphone pairs in an equilateral-triangular microphone array (Hioka and Hamada, N., IEICE Technical Report, EA2003-44, p.9-16, 2003). We now extend the method using four microphones located at the apices of a regular tetrahedron to enable the method to estimate the elevation angle from the array plane as well. Furthermore, we introduce an idea for separate estimation of azimuth and elevation to reduce the computational loads.


title: Study of CoFeB thickness and composition dependence in a modified CoFeB/MgO/CoFeB perpendicular magnetic tunnel junction

abstract: We studied the CoFeB thickness and composition dependence of tunneling magnetoresistance (TMR) and resistance-area product (RA) in a modified CoFeB/MgO/CoFeB perpendicular magnetic tunnel junction (MTJ), in which the bottom CoFeB is coupled to an in-plane exchange biased magnetic layer. This stack structure allows us to measure TMR and RA of the MTJs in sheet film format without patterning them, using current-in-plane-tunneling (CIPT) technique. The thickness ranges for both top and bottom CoFeB to exhibit perpendicular magnetic anisotropy are similar to what are seen in each single magnetic film stack. However, CIPT measurement revealed that there exists an optimal thickness for both top and bottom CoFeB to achieve the highest TMR value. Magnetic hysteresis loops also suggest the thickness-dependent coupling between the top and bottom CoFeB layers. We studied MTJs with two CoFeB compositions (Co40Fe40B20 and Co20Fe60B20) and found that Co20Fe60B20 MTJs give higher TMR and also wider perpendicular thickne...


title: Digital Forensics for Eucalyptus

abstract: Cloud computing is a computing paradigm that shifts drastically from traditional computing architecture. Although this new computing paradigm brings many advantages like utility computing model but the design in not flawless and hence suffers from not only many known computer vulnerabilities but also introduces unique information confidentiality, integrity and availability risks as well due its inherent design paradigm. As a result the digital forensics, which relies heavily on physical access to computing devices and applications logs, has become a biggest challenge in cloud environments due to the non-availability of physical access to computing devices and applications logs. As we will see this paper highlights many of the digital forensics issues in the cloud environments and tries to address some of these forensics issues by identifying possible Syslog or Snort logs that can help in detecting cloud attacks or conducting digital forensics in cloud environments by analyzing logs generated by an open source cloud computing Eucalyptus software. As we will see in the paper we neither had access to Eucalyptus logs dataset nor it was known that any such dataset exist that could be analyzed offline for digital forensics purposes. Thus we generated our own dataset by attacking Eucalyptus with many of the known cloud attacks and then analyzing the resultant dataset to identify possible log entries that could identify cloud attacks or help in conducting digital forensics in cloud environments.


title: A connectionist theory of phenomenal experience

abstract: When cognitive scientists apply computational theory to the problem of phenomenal consciousness, as ::: many of them have been doing recently, there are two fundamentally distinct approaches available. Either ::: consciousness is to be explained in terms of the nature of the representational vehicles the brain deploys; or ::: it is to be explained in terms of the computational processes defined over these vehicles. We call versions of ::: these two approaches vehicle and process theories of consciousness, respectively. However, while there may ::: be space for vehicle theories of consciousness in cognitive science, they are relatively rare. This is because ::: of the influence exerted, on the one hand, by a large body of research which purports to show that the ::: explicit representation of information in the brain and conscious experience are dissociable, and on the ::: other, by the classical computational theory of mind – the theory that takes human cognition to be a species ::: of symbol manipulation. But two recent developments in cognitive science combine to suggest that a ::: reappraisal of this situation is in order. First, a number of theorists have recently been highly critical of the ::: experimental methodologies employed in the dissociation studies – so critical, in fact, it’s no longer ::: reasonable to assume that the dissociability of conscious experience and explicit representation has been ::: adequately demonstrated. Second, classicism, as a theory of human cognition, is no longer as dominant in ::: cognitive science as it once was. It now has a lively competitor in the form of connectionism; and ::: connectionism, unlike classicism, does have the computational resources to support a robust vehicle theory ::: of consciousness. In this paper we develop and defend this connectionist vehicle theory of consciousness. It ::: takes the form of the following simple empirical hypothesis: phenomenal experience consists in the explicit ::: representation of information in neurally realized PDP networks. This hypothesis leads us to re-assess some ::: common wisdom about consciousness, but, we will argue, in fruitful and ultimately plausible ways.


title: Evidence For Two Faces of Pride in Consumption: Findings From Luxury Brands

abstract: This paper documents the multifaceted nature of pride in consumer behavior. Drawing on recent psychological research on pride, we provide evidence for two separate facets of pride in consumption. In a series of studies, we propose a model wherein luxury brand consumption and pride are systematically interrelated. Whereas authentic (but not hubristic) pride leads to a heightened desire for luxury brands, hubristic (but not authentic) pride is the outcome of these purchases, and is the form of pride signaled to observers by these purchases. Further, we show that these effects are generally exacerbated for those low in narcissism. These findings shed new light on why consumers purchase luxury brands, highlighting a paradox: these purchases may be sought out of heightened feelings of accomplishment (and not arrogance), but they instead signal arrogance to others (rather than accomplishment). Crown Copyright © 2014 Published by Elsevier Inc. on behalf of Society for Consumer Psychology. All rights reserved.


title: Repositioning for pressure ulcer prevention in adults

abstract: Background ::: A pressure ulcer (PU), also referred to as a 'pressure injury', 'pressure sore', or 'bedsore' is defined as an area of localised tissue damage that is caused by unrelieved pressure, friction or shearing forces on any part of the body. PUs commonly occur in patients who are elderly and less mobile, and carry significant human and economic impacts. Immobility and physical inactivity are considered to be major risk factors for PU development and the manual repositioning of patients in hospital or long-term care is a common pressure ulcer prevention strategy. ::: ::: Objectives ::: The objectives of this review were to: ::: 1) assess the effects of repositioning on the prevention of PUs in adults, regardless of risk or in-patient setting; ::: 2) ascertain the most effective repositioning schedules for preventing PUs in adults; and ::: 3) ascertain the incremental resource consequences and costs associated with implementing different repositioning regimens compared with alternate schedules or standard practice. ::: ::: Search methods ::: We searched the following electronic databases to identify reports of the relevant randomised controlled trials: the Cochrane Wounds Group Specialised Register (searched 06 September 2013), the Cochrane Central Register of Controlled Trials (CENTRAL) (2013, Issue 8); Ovid MEDLINE (1948 to August, Week 4, 2013); Ovid EMBASE (1974 to 2013, Week 35); EBESCO CINAHL (1982 to 30 August 2013); and the reference sections of studies that were included in the review. ::: ::: Selection criteria ::: Randomised controlled trials (RCTs), published or unpublished, that assessed the effects of any repositioning schedule or different patient positions and measured PU incidence in adults in any setting. ::: ::: Data collection and analysis ::: Two review authors independently performed study selection, risk of bias assessment and data extraction. ::: ::: Main results ::: We included three RCTs and one economic study representing a total of 502 randomised participants from acute and long-term care settings. Two trials compared the 30o and 90o tilt positions using similar repositioning frequencies (there was a small difference in frequency of overnight repositioning in the 90o tilt groups between the trials). The third RCT compared alternative repositioning frequencies. ::: ::: All three studies reported the proportion of patients developing PU of any grade, stage or category. None of the trials reported on pain, or quality of life, and only one reported on cost. All three trials were at high risk of bias. ::: ::: The two trials of 30o tilt vs. 90o were pooled using a random effects model (I² = 69%) (252 participants). The risk ratio for developing a PU in the 30o tilt and the standard 90o position was very imprecise (pooled RR 0.62, 95% CI 0.10 to 3.97, P=0.62, very low quality evidence). This comparison is underpowered and at risk of a Type 2 error (only 21 events). ::: ::: In the third study, a cluster randomised trial, participants were randomised between 2-hourly and 3-hourly repositioning on standard hospital mattresses and 4 hourly and 6 hourly repositioning on viscoelastic foam mattresses. This study was also underpowered and at high risk of bias. The risk ratio for pressure ulcers (any category) with 2-hourly repositioning compared with 3-hourly repositioning on a standard mattress was imprecise (RR 0.90, 95% CI 0.69 to 1.16, very low quality evidence). The risk ratio for pressure ulcers (any category) was compatible with a large reduction and no difference between 4-hourly repositioning and 6-hourly repositioning on viscoelastic foam (RR 0.73, 95% CI 0.53 to 1.02, very low quality evidence). ::: ::: A cost-effectiveness analysis based on data derived from one of the included parallel RCTs compared 3-hourly repositioning using the 30o tilt overnight with standard care consisting of 6-hourly repositioning using the 90o lateral rotation overnight. In this evaluation the only included cost was nursing time. The intervention was reported to be cost saving compared with standard care (nurse time cost per patient €206.6 vs €253.1, incremental difference €-46.5; 95%CI: €-1.25 to €-74.60). ::: ::: Authors' conclusions ::: Repositioning is an integral component of pressure ulcer prevention and treatment; it has a sound theoretical rationale, and is widely recommended and used in practice. The lack of robust evaluations of repositioning frequency and position for pressure ulcer prevention mean that great uncertainty remains but it does not mean these interventions are ineffective since all comparisons are grossly underpowered. Current evidence is small in volume and at risk of bias and there is currently no strong evidence of a reduction in pressure ulcers with the 30° tilt compared with the standard 90o position or good evidence of an effect of repositioning frequency. There is a clear need for high-quality, adequately-powered trials to assess the effects of position and optimal frequency of repositioning on pressure ulcer incidence. ::: ::: The limited data derived from one economic evaluation means it remains unclear whether repositioning every 3 hours using the 30o tilt is less costly in terms of nursing time and more effective than standard care involving repositioning every 6 hours using a 90o tilt.


title: Robust Control for Power Sharing in Microgrids With Low-Inertia Wind and PV Generators

abstract: This paper presents a robust control design scheme for a multidistributed energy resource (DER) microgrid for power sharing in both interconnected and islanded modes. The scheme is proposed for micgrogrids consisting of photovoltaic (PV) units and wind turbine driven doubly fed induction generators (DFIGs). A battery is integrated with each of the wind and solar DER units. The control scheme has two levels: 1)one centralized multi-inputmulti-output robust controller for regulating the set reference active and reactive powers and 2)local real and reactive power droop controllers, one on each DER unit. The robust control scheme utilizes multivariable ${H_\infty}$ control to design controllers that are robust to the changes in the network and system nonlinearities. The effectiveness of the proposed controller is demonstrated through large-disturbance simulations, with complete nonlinear models, on a test microgrid. It is found that the power sharing controllers provide excellent performance against large disturbances and load variations during islanding transients and interconnected operation.


Sudoku Squares and Chromatic Polynomials


title: WiSeNet: building a wikipedia-based semantic network with ontologized relations

abstract: In this paper we present an approach for building a Wikipedia-based semantic network by integrating Open Information Extraction with Knowledge Acquisition techniques. Our algorithm extracts relation instances from Wikipedia page bodies and ontologizes them by, first, creating sets of synonymous relational phrases, called relation synsets, second, assigning semantic classes to the arguments of these relation synsets and, third, disambiguating the initial relation instances with relation synsets. As a result we obtain WiSeNet, a Wikipedia-based Semantic Network with Wikipedia pages as concepts and labeled, ontologized relations between them.


title: WAIF1 Is a Cell‐Surface CTHRC1 Binding Protein Coupling Bone Resorption and Formation

abstract: The osteoclast-derived collagen triple helix repeat containing 1 (CTHRC1) protein stimulates osteoblast differentiation, but the underlying mechanism remains unclear. Here, we identified Wnt-activated inhibitory factor 1 (WAIF1)/5T4 as a cell-surface protein binding CTHRC1. The WAIF1-encoding Trophoblast glycoprotein (Tpbg) gene, which is abundantly expressed in the brain and bone but not in other tissues, showed the same expression pattern as Cthrc1. Tpbg downregulation in marrow stromal cells reduced CTHRC1 binding and CTHRC1-stimulated alkaline phosphatase activity through PKCδ activation of MEK/ERK, suggesting a novel WAIF1/PKCδ/ERK pathway triggered by CTHRC1. Unexpectedly, osteoblast lineage-specific deletion of Tpbg downregulated Rankl expression in mouse bones and reduced both bone formation and resorption; importantly, it impaired bone mass recovery following RANKL-induced resorption, reproducing the phenotype of osteoclast-specific Cthrc1 deficiency. Thus, the binding of osteoclast-derived CTHRC1 to WAIF1 in stromal cells activates PKCδ-ERK osteoblastogenic signaling and serves as a key molecular link between bone resorption and formation during bone remodeling. © 2018 American Society for Bone and Mineral Research.


title: Multiobjective Optimization in Cloud Brokering Systems for Connected Internet of Things

abstract: Currently, over nine billion things are connected in the Internet of Things (IoT). This number is expected to exceed 20 billion in the near future, and the number of things is quickly increasing, indicating that numerous data will be generated. It is necessary to build an infrastructure to manage the connected things. Cloud computing (CC) has become important in terms of analysis and data storage for IoT. In this paper, we consider a cloud broker, which is an intermediary in the infrastructure that manages the connected things in CC. We study an optimization problem for maximizing the profit of the broker while minimizing the response time of the request and the energy consumption. A multiobjective particle swarm optimization (MOPSO) is proposed to solve the problem. The performance of the proposed MOPSO is compared with that of a genetic algorithm and a random search algorithm. The results show that the MOPSO outperforms a well-known genetic algorithm for multiobjective optimization.


title: Towards an Efficient Smart Space Architecture

abstract: A smart space offers entirely new opportunities for end users by adapting services accordingly to make life easy. A number of architectural designs have been proposed to design context awareness systems and adaptation behavior. However, the quality of the system depends on the degree of satisfaction of the initials needs. In this paper, we discuss three main indicators of quality design for smart spaces that are strongly related to the context modules and reasoning process: functionality, reusability and changeability. A general layered architecture system is presented to define the principal components that should constitute any context aware adaptive system.


title: Catheter-associated urinary tract infection: a successful prevention effort employing a multipronged initiative at an academic medical center.

abstract: An interdisciplinary clinical improvement workgroup was formed at this academic medical center with the goal of reducing catheter-associated urinary tract infections (CAUTIs). In 2011, the CAUTI rate was noted to be 4.7 CAUTIs per 1000 catheter days. Rounding by 2 lead clinical nurse specialists revealed deficiencies in current practice, which were addressed with multifaceted strategies, including evidence-based indwelling urinary catheter and bladder management protocols, education of staff, reporting of data, and utilization of an icon in the electronic health record (EHR). After the implementation of these strategies, the CAUTI rate decreased and was noted to be 2.4 in February 2013. In addition to this, there was a downward trend line for catheter days.


title: Representation Learning in Large Attributed Graphs

abstract: Graphs (networks) are ubiquitous and allow us to model entities (nodes) and the dependencies (edges) between them. Learning a useful feature representation from graph data lies at the heart and success of many machine learning tasks such as classification, anomaly detection, link prediction, among many others. Many existing techniques use random walks as a basis for learning features or estimating the parameters of a graph model for a downstream prediction task. Examples include recent node embedding methods such as DeepWalk, node2vec, as well as graph-based deep learning algorithms. However, the simple random walk used by these methods is fundamentally tied to the identity of the node. This has three main disadvantages. First, these approaches are inherently transductive and do not generalize to unseen nodes and other graphs. Second, they are not space-efficient as a feature vector is learned for each node which is impractical for large graphs. Third, most of these approaches lack support for attributed graphs. To make these methods more generally applicable, we propose a framework based on the notion of attributed random walk that is not tied to node identity and is instead based on learning a function $\Phi : \mathrm{\rm \bf x} \rightarrow w$ that maps a node attribute vector $\mathrm{\rm \bf x}$ to a type $w$. This framework serves as a basis for generalizing existing methods such as DeepWalk, node2vec, and many other previous methods that leverage traditional random walks.


The Security of Physical Layer in Cognitive Radio Networks


title: Modelling of linear motor end-effects for saliency based sensorless control

abstract: In linear motors, the open structure of the armature produces the so called end-effect. The end-effect introduces non-idealities in the motor magnetic model in dq-synchronous coordinates that require a specific modelling with respect to the well known models of rotating (cylindrical) machines. In particular, for saliency based sensorless control, the end-effect introduces an error in the estimated position that must be taken into account and properly compensated. This paper introduces a general mathematical modeling of the end-effect that can be applied to all linear machines. Based on such model, modified position observers are proposed for sensorless control using pulsating or rotating voltage vectors. Experimental results are presented to verify the feasibility of the proposed method, with reference to the case of a linear tubular permanent magnet motor.


Deep active learning for object detection


title: CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation

abstract: State of the art methods for semantic image segmentation are trained in a supervised fashion using a large corpus of fully labeled training images. However, gathering such a corpus is expensive, due to human annotation effort, in contrast to gathering unlabeled data. We propose an active learning-based strategy, called CEREALS, in which a human only has to hand-label a few, automatically selected, regions within an unlabeled image corpus. This minimizes human annotation effort while maximizing the performance of a semantic image segmentation method. The automatic selection procedure is achieved by: a) using a suitable information measure combined with an estimate about human annotation effort, which is inferred from a learned cost model, and b) exploiting the spatial coherency of an image. The performance of CEREALS is demonstrated on Cityscapes, where we are able to reduce the annotation effort to 17%, while keeping 95% of the mean Intersection over Union (mIoU) of a model that was trained with the fully annotated training set of Cityscapes.


title: Quadrature Amplitude Modulated Backscatter in Passive and Semipassive UHF RFID Systems

abstract: Passive and semipassive UHF RF identification (RFID) systems have traditionally been designed using scalar-valued differential radar cross section (DRCS) methods to model the backscattered signal from the tag. This paper argues that scalar-valued DRCS analysis is unnecessarily limiting because of the inherent coherence of the backscatter link and the complex-valued nature of load-dependent antenna-mode scattering from an RFID tag. Considering modulated backscatter in terms of complex-valued scattered fields opens the possibility of quadrature modulation of the backscatter channel. When compared with binary amplitude shift keying (ASK) or phase shift keying (PSK) based RFID systems, which transmit 1 bit of data per symbol period, and thus 1 bit per on-chip clock oscillator period, tags employing vector backscatter modulation can transmit more than 1 bit per symbol period. This increases the data rate for a given on-chip symbol clock rate leading to reduced on-chip power consumption and extended read range. Alternatively, tags employing an M-ary modulator can achieve log2 M higher data throughput at essentially the same dc power consumption as a tag employing binary ASK or PSK. In contrast to the binary ASK or PSK backscatter modulation employed by passive and semipassive UHF RFID tags, such as tags compliant with the widely used ISO18000-6c standard, this paper explores a novel CMOS-compatible method for generating M-ary quadrature amplitude modulated (QAM) backscatter modulation. A new method is presented for designing an inductorless M-ary QAM backscatter modulator using only an array of switched resistances and capacitances. Device-level simulation and measurements of a four-state phase shift keying (4-PSK)/four-state quadrature amplitude modulated (4-QAM) modulator are provided for a semipassive (battery-assisted) tag operating in the 850-950-MHz band. This first prototype modulator transmits 4-PSK/4-QAM at a symbol rate of 200 kHz and a bit rate of 400 kb/s at a static power dissipation of only 115 nW.


title: Controlling flow reconfigurations in SDN

abstract: Software-Defined Network (SDN) controllers include mechanisms to globally reconfigure the network in order to respond to a changing environment. While iterative methods are employed to solve flow optimization problems, demands arrive or leave the system changing the optimization instance and requiring further iterations. In this paper, we focus on the general class of iterative solvers considering an exponential decrease over time in the optimality gap. Assuming dynamic arrivals and departures of demands, the computed optimality gap at each iteration Q(t) is described by an auto-regressive stochastic process. At each time slot the controller may choose to apply the current iteration to the network or not. Applying the current iteration improves the optimality gap but requires flow reconfiguration which hurts QoS and system stability. To limit the reconfigurations, we propose two control policies that minimize the flow allocation cost while respecting a network reconfiguration budget. We validate our model by experimenting with a realistic network setting and using standard Linear Programming tools used in the SDN industry. We show that our policies provide a practical means of keeping the optimally gap small within a given reconfiguration constraint.


title: Design of FPGA-based Traffic Light Controller System

abstract: This paper proposed a design of a modern FPGA-based Traffic Light Control (TLC) System to manage the road traffic. The approach is by controlling the access to areas shared among multiple intersections and allocating effective time between various users; during peak and off-peak hours. The implementation is based on real location in a city in Malaysia where the existing traffic light controller is a basic fixed-time method. This method is inefficient and almost always leads to traffic congestion during peak hours while drivers are given unnecessary waiting time during off-peak hours. The proposed design is a more universal and intelligent approach to the situation and has been implemented using FPGA. The system is implemented on ALTERA FLEX10K chip and simulation results are proven to be successful. Theoretically the waiting time for drivers during off-peak hours has been reduced further, therefore making the system better than the one being used at the moment. Future improvements include addition of other functions to the proposed design to suit various traffic conditions at different locations.


title: A 3GHz Low-offset Fully Dynamic Latched Comparator for High-Speed and Low-Power ADCs

abstract: In this paper, performances of various types of dynamic latched comparators are compared in terms of their offset voltages, speed and power. The accuracy of comparators, which is defined by its offset, along with power consumption, speed is of keen interest in achieving overall higher performance of ADCs. This can be achieved by the fully dynamic latched comparator which is proposed in this paper. This comparator shows 14.6mV offset which is small when compared to other dynamic comparators and pre- amplifier based comparators. This comparator not only achieves low-offset but also exhibit high-speed and low power in its operation, which can be used for low power high speed ADC applications. In this paper, we present a new dynamic latched comparator which shows lower input-referred latch offset voltage and higher load drivability than the conventional dynamic latched comparators. Even though numbers of transistors in the proposed comparator are more but overall area is small when compared to conventional dynamic latched comparators. This paper is organized as follows. Section II provides an overview of the various types of dynamic latched comparators in terms of their advantages and drawbacks, and section III describes the offset analysis of proposed dynamic latched comparator. Section IV provides schematics of various types of dynamic latched comparators which are drawn in T-Spice. Simulation results from HSPICE using 90nm PTM technology with VDD=1V and their comparisons are presented in Section V and conclusion is drawn in Section VI.


title: Managing the transition from products to services

abstract: Management literature is almost unanimous in suggesting to manufacturers that they should integrate services into their core product offering. The literature, however, is surprisingly sparse in describing to what extent services should be integrated, how this integration should be carried out, or in detailing the challenges inherent in the transition to services. Reports on a study of 11 capital equipment manufacturers developing service offerings for their products. Focuses on identifying the dimensions considered when creating a service organization in the context of a manufacturing firm, and successful strategies to navigate the transition. Analysis of qualitative data suggests that the transition involves a deliberate developmental process to build capabilities as firms shift the nature of the relationship with the product end‐users and the focus of the service offering. The report concludes identifying implications of our findings for further research and practitioners.


title: Characterization of RF Noise in UTBB FD-SOI MOSFET

abstract: In this paper, we report the noise measurements in the RF frequency range for ultrathin body and thin buried oxide fully depleted silicon on insulator (FD-SOI) transistors. We analyze the impact of back and front gate biases on the various noise parameters; along with discussions on the secondary effects in FD-SOI transistors which contribute to the thermal noise. Using calibrated TCAD simulations, we show that the noise figure changes with the substrate doping and buried oxide thickness.


title: A formal component-based software engineering approach for developing trustworthy systems

abstract: Software systems are increasingly becoming ubiquitous, affecting the way we experience the world. Embedded software systems, especially those used in smart devices, have become an essential constituent of the technological infrastructure of modern societies. Such systems, in order to be trusted in society, must be proved to be trustworthy. Trustworthiness is a composite non-functional property that implies safety, timeliness, security, availability, and reliability. This thesis is a contribution to a rigorous development of systems in which trustworthiness property can be specified and formally verified. ::: Developing trustworthy software systems that are complex and used by a large heterogenous population of users is a challenging task. The component-based software engineering (CBSE) paradigm can provide an effective solution to address these challenges. However, none of the current component-based approaches can be used as is, because all of them lack the essential requirements for constructing trustworthy systems. The three contributions made in this thesis are intended to add to the expressive power needed to raise CBSE practices to a rigorous level for constructing formally verifiable trustworthy systems. ::: The first contribution of the thesis is a formal definition of the trustworthy component model. The trustworthiness quality attributes are introduced as first class structural elements. The behavior of a component is automatically generated as an extended timed automata. A model checking technique is used to verify the properties of trustworthiness. A composition theory that preserves the properties of trustworthiness in a composition is presented. ::: Conventional software engineering development processes are not suitable either for developing component-based systems or for developing trustworthy systems. In order to develop a component-based trustworthy system, the development process must be reuse-oriented, component-oriented, and must integrate formal languages and rigorous methods in all phases of system life-cycle. The second contribution of the thesis is a software engineering process model that consists of several parallel tracks of activities including component development, component assessment, component reuse, and component-based system development. The central concern in all activities of this process is ensuring trustworthiness. ::: The third and final contribution of the thesis is a development framework with a comprehensive set of tools supporting the spectrum of formal development activity from modeling to deployment. ::: The proposed approach has been applied to several case studies in the domains of component-based development and safety-critical systems. The experience from the case studies confirms that the approach is suitable for developing large and complex trustworthy systems.


title: Selfless Sequential Learning

abstract: Sequential learning, also called lifelong learning, studies the problem of learning tasks in a sequence with access restricted to only the data of the current task. In this paper we look at a scenario with fixed model capacity, and postulate that the learning process should not be selfish, i.e. it should account for future tasks to be added and thus leave enough capacity for them. To achieve Selfless Sequential Learning we study different regularization strategies and activation functions. We find that imposing sparsity at the level of the representation (i.e.~neuron activations) is more beneficial for sequential learning than encouraging parameter sparsity. In particular, we propose a novel regularizer, that encourages representation sparsity by means of neural inhibition. It results in few active neurons which in turn leaves more free neurons to be utilized by upcoming tasks. As neural inhibition over an entire layer can be too drastic, especially for complex tasks requiring strong representations, our regularizer only inhibits other neurons in a local neighbourhood, inspired by lateral inhibition processes in the brain. We combine our novel regularizer, with state-of-the-art lifelong learning methods that penalize changes to important previously learned parts of the network. We show that our new regularizer leads to increased sparsity which translates in consistent performance improvement %over alternative regularizers we studied on diverse datasets.


title: Towards a quantum programming language

abstract: We propose the design of a programming language for quantum computing. Traditionally, quantum algorithms are frequently expressed at the hardware level, for instance in terms of the quantum circuit model or quantum Turing machines. These approaches do not encourage structured programming or abstractions such as data types. In this paper, we describe the syntax and semantics of a simple quantum programming language with high-level features such as loops, recursive procedures, and structured data types. The language is functional in nature, statically typed, free of run-time errors, and has an interesting denotational semantics in terms of complete partial orders of superoperators.


title: Directions in ISA Specification

abstract: This rough diamond presents a new domain-specific language (DSL) for producing detailed models of Instruction Set Architectures, such as ARM and x86. The language’s design and methodology is discussed and we propose future plans for this work. Feedback is sought from the wider theorem proving community in helping establish future directions for this project. A parser and interpreter for the DSL has been developed in Standard ML, with an ARMv7 model used as a case study.


title: Platform motion disturbances attenuation in a missile seeker subsystem using Internal Model Control

abstract: In this paper two degree of freedom Internal Model Controller (2-DOF IMC) is used to attenuate the platform (missile body) disturbance that couples to the gimbal inner axis (elevation axis) angular rate of the seeker i.e. the angular rate of the inner (elevation) axis of the seeker gimbal in the pitch plane. IMC is an efficient robust controller and its use in process control system is very common. It can track reference input and simultaneously it also rejects the external disturbances that enter into the system. In this paper these features have been utilized to attenuate the base disturbances and disturbance torque in the seeker system.


title: Spatio-temporal indexing in non-relational distributed databases

abstract: Big Data has driven the need for datastores that can scale horizontally leading to the development of many different NoSQL database implementations, each with different persistence and query philosophies. Spatio-temporal data such as location data is one of the largest types of data being collected today. We describe a novel spatio-temporal index structure that leverages the horizontal scalability of NoSQL databases to achieve performant query and transformation semantics. We present performance characteristics gathered from testing with Accumulo.


title: NADA: New Arabic Dataset for Text Classification

abstract: In the recent years, Arabic Natural Language Processing, including Text summarization, Text simplification, Text Categorization and other Natural Language-related disciplines, are attracting more researchers. Appropriate resources for Arabic Text Categorization are becoming a big necessity for the development of this research. The few existing corpora are not ready for use, they require preprocessing and filtering operations. In addition, most of them are not organized based on standard classification methods which makes unbalanced classes and thus reduced the classification accuracy. This paper proposes a New Arabic Dataset (NADA) for Text Categorization purpose. This corpus is composed of two existing corpora OSAC and DAA. The new corpus is preprocessed and filtered using the recent state of the art methods. It is also organized based on Dewey decimal classification scheme and Synthetic Minority Over-Sampling Technique. The experiment results show that NADA is an efficient dataset ready for use in Arabic Text Categorization.


title: Optimizing stereo-to-multiview conversion for autostereoscopic displays

abstract: We present a novel stereo-to-multiview video conversion method for glasses-free multiview displays. Different from previous stereo-to-multiview approaches, our mapping algorithm utilizes the limited depth range of autostereoscopic displays optimally and strives to preserve the scene's artistic composition and perceived depth even under strong depth compression. We first present an investigation of how perceived image quality relates to spatial frequency and disparity. The outcome of this study is utilized in a two-step mapping algorithm, where we i compress the scene depth using a non-linear global function to the depth range of an autostereoscopic display and ii enhance the depth gradients of salient objects to restore the perceived depth and salient scene structure. Finally, an adapted image domain warping algorithm is proposed to generate the multiview output, which enables overall disparity range extension.


title: Morphological Smoothing and Extrapolation of Word Embeddings

abstract: Languages with rich inflectional morphology exhibit lexical data sparsity, since the word used to express a given concept will vary with the syntactic context. For instance, each count noun in Czech has 12 forms (where English uses only singular and plural). Even in large corpora, we are unlikely to observe all inflections of a given lemma. This reduces the vocabulary coverage of methods that induce continuous representations for words from distributional corpus information. We solve this problem by exploiting existing morphological resources that can enumerate a word’s component morphemes. We present a latentvariable Gaussian graphical model that allows us to extrapolate continuous representations for words not observed in the training corpus, as well as smoothing the representations provided for the observed words. The latent variables represent embeddings of morphemes, which combine to create embeddings of words. Over several languages and training sizes, our model improves the embeddings for words, when evaluated on an analogy task, skip-gram predictive accuracy, and word similarity.


title: Experimental Analysis of the Channel Busy Time in Vehicular Ad-Hoc Networks

abstract: To maintain the benefits of fast growing Vehicular Ad-Hoc Networks (VANETs), Congestion Control (CC) algorithms are used to reduce channel congestion even under harsh communication conditions in order to achieve a reliable service. Reactive channel load (CL) based CC mechanisms, like Decentralized Congestion Control (DCC), therefore hardly rely on accurate CL values to work at best effort. While continuous probing of the channel obviously offers the best accuracy, it is not always possible or necessary, as illustrated in this paper. Instead estimation methods are used which may vary in accuracy through their parameter settings. The aim of this paper is to investigate the impact of synchronization and the measuring interval length for time (in-)variant CL as well as number and distribution of probes for the channel busy time. Various measurements, which are retrieved from an experimental set-up, are used for a theoretical evaluation. I illustrate that accuracy strongly varies and also suffers from the use of certain parameters, especially the measuring interval length and the synchronization effect which is of major interest for time (in-)variant CL occurring in VANETs. Furthermore the paper reveals that simple constant probing can, in terms of accuracy, outperform uniformly distributed probes used so far.