title: Is Verbal Irony Special?

text: The way we speak can reveal much about what we intend to communicate, but the words we use often only indirectly relate to the meanings we wish to convey. Verbal irony is a commonly studied form of indirect speech in which a speaker produces an explicit evaluative utterance that implicates an unstated, opposing evaluation. Producing and understanding ironic language, as well as many other types of indirect speech, requires the ability to recognize mental states in others, sometimes described as a capacity for metarepresentation. This article aims to connect common elements between the major theoretical approaches to verbal irony to recent psycholinguistic, developmental, and neuropsychological research demonstrating the necessity for metarepresentation in the effective use of verbal irony in social interaction. Here I will argue that verbal irony is one emergent, strategic possibility given the interface between people’s ability to infer mental states, and use language. Rather than think of ironic communication as a specialized cognitive ability, I will claim that it arises from the same set of abilities that underlie a wide range of inferential communicative behaviors. Language interaction involves a complex interplay of many cognitive abilities. Theorists across many disciplines struggle with questions of how to carve up these abilities, and whether they can be carved up in the first place (e.g., Christiansen and Chater 2008). Among the most difficult questions to address are those that involve how people recognize intentions in others’ behavior, and how that is achieved through language in the context of many other sources of information. The way we speak can reveal much about what we intend to communicate, but the words we use are often quite different from the meanings we wish to convey. People often speak indirectly for a variety of strategic reasons, and these strategies rely intrinsically on social cognition. One well-researched example of this is the phenomenon of verbal irony – a type of indirect speech in which a speaker produces an explicit evaluative utterance that implicates an unstated, opposing evaluation. As described below, this trope has been traditionally defined in rather vague terms, but has generated a great deal of research as a phenomenon in need of special theoretical explanation. Here I will argue that verbal irony is one emergent, strategic possibility given the interface between people’s ability to infer the mental states of others, and use language. Rather than think of ironic communication as a unique skill or specialized cognitive ability, I suggest that it arises from the same set of abilities that underlie a wide range of inferential communicative behaviors. The study of verbal irony production and comprehension has been a multidisciplinary effort lacking extensive interdisciplinary exchange. There have been various taxonomies and definitions of what constitutes irony, both verbal and situational – a struggling enterprise to say the least (Colston and Gibbs 2007). The traditional notion of verbal irony dates back at least to the Roman rhetorician Quintilian, who described irony as a kind of allegory expressing the opposite of what one means, often for mocking Language and Linguistics Compass 6/11 (2012): 673–685, 10.1002/lnc3.364 a 2012 The Author Language and Linguistics Compass a 2012 Blackwell Publishing Ltd communicative effects. Some of the assumptions of this early categorization have carried over into modern psycholinguistic research without proper consideration of underlying communicative functions (Kreuz 2000). Many scholars have linked verbal irony to situational irony – particularly in how both forms seem to involve, at some level, a contradiction between what is expected, and what occurs. While verbal irony often points to unexpected or unfortunate outcomes in people’s actions (Kumon-Nakamura, Glucksberg, and Brown 1995; Pexman 2008), it does not do so necessarily. At present, most contemporary researchers of figurative language and inferential communication have settled on some version of the basic claim that verbal irony is a class of indirect language use where explicit sentence meanings are conceptually contradictory to a network of related implied propositions. Many other tropes, however, are not obviously distinct (e.g., parody, pretense, double entendre, litotes, etc). One common thread between many theoretical and empirical approaches to verbal irony is the distinction language users must make between layers of meaning. This could be the difference between actual and attributed beliefs (Kreuz and Glucksberg 1989; Sperber and Wilson 1986, 1995), real and imagined discourse acts (Clark and Gerrig 1984), relevant or inappropriate to a particular context (Attardo 2000), what is negated and what is implicated (Giora 1995), or failed expectations and attitudes toward those failures (Kumon-Nakamura, Glucksberg, and Brown 1995). Speakers implicitly highlight the contrasts between these different levels of meaning, and in doing so communicate an attitude toward an attributed belief (Sperber and Wilson 1986, 1995). This attitudinal dissociation is typically considered a hallmark of ironic communication, and necessarily requires an implicit understanding of others’ mental states. Consider the following exchange: John: I got another virus on my laptop. Mary: Aren’t you glad you didn’t switch to Mac? In this example John and Mary are discussing John’s computer problems. John reports that he got a virus on his computer – not his first. Mary asks an ironic rhetorical question expressing her negative opinion of Windows PCs. The literal question is in particular opposition to the implied evaluation – the essence of irony. In this example, the irony is largely contained in a single lexical opposition – ‘‘glad’’ instead of, for example, ‘‘sad,’’ but is also communicated by the rhetorical aspect of the question. The question form is one format speakers use to express ironic intentions, but ironic forms can manifest themselves in various ways linguistically, and in a variety of media including television, music, and visual art (Bryant 2011; El Refaie 2005; Ettema and Glasser 1994; Nuolijarvi and Tiittula 2010; Scott 2003). Figurative language devices such as verbal irony can be quite powerful communicative tools. The sentences we speak are often produced in a manner that will allow our audience to derive certain unstated meanings, and the way we put them is often particularly economical because of our heavy reliance on others’ inferential abilities. These meanings are not just efficient, but unique to indirect communication (Gibbs 2000a). The combination of affect directed toward some attributed belief, along with a direct utterance, makes ironic meanings difficult, if not impossible, to precisely capture. But this is due to inferential processes associated with mindreading and linguistic communication, not some distinct process of irony understanding. Similarly, it is difficult to capture, in linguistic terms, many kinds of inferences regarding others’ intentions that people generate in social contexts. In our example, Mary, of course, communicates much more than a negative opinion of PCs. For instance, she implicitly reminds John of previous interactions, some being debates, when their differences of opinion about computer platforms were discussed (i.e., 674 Gregory A. Bryant a 2012 The Author Language and Linguistics Compass 6/11 (2012): 673–685, 10.1002/lnc3.364 Language and Linguistics Compass a 2012 Blackwell Publishing Ltd she echoes previous opinions expressed, perhaps even through literal quotations) (Kreuz and Glucksberg 1989; Sperber and Wilson 1986, 1995). In doing so she reiterates her claim that John’s decision was a mistake, and that he would regret it. By using an ironic rhetorical question, Mary efficiently conveys a complex set of implied meanings that are relevant to John. The irony is not necessarily obvious to an outsider, as is the case with most occurrences of irony in everyday conversations (Gibbs 2000b), but John understands Mary immediately, and Mary knew he would. In the process, Mary potentially reduces John’s perception that she is being critical, and makes him laugh (while actually criticizing him) (Dews and Winner 1995). Alternatively, Mary might be accentuating her criticism by highlighting a contrast between John’s current situation and his earlier stated preference (Colston 1997). Speakers attempt to fulfill particular communicative goals by using indirect language such as verbal irony, and different forms can result in quite different emotional reactions – we should expect it to be used strategically and variably (Bryant 2011; Bryant and Fox Tree 2005; Leggitt and Gibbs 2000). Scholars have suggested many functions for irony in discourse, including speakers’ attempts to be humorous, create solidarity, appear clever, increase memorability, save face, be polite, or alter the valence of an attack or praise (Gibbs 1994; Roberts and Kreuz 1994; Toplak and Katz 2000). The pragmatic uses of ironic speech are far-reaching – ‘‘what can’t irony do?’’ might be a better question. One reason that irony can fulfill so many discourse goals is that includable tokens in the category need only satisfy a couple conditions; thus, an enormous variety of speech acts can qualify. Burgers, van Mulken, and Schellens (2011) recently proposed a procedure for identifying ironies in discourse, and for a basic definition, they looked at the commonalities between different contemporary theories. In their view, verbal irony involves an expressed evaluative utterance that implies an opposing evaluative appraisal. This implied meaning does not need to be the opposite of the stated meaning, but just differ in a scalar manner. For instance, an understatement might still be negative, but less negative than the intended meaning (e.g., when asked about a personal experience with a


title: Sharpness Enhancement and Super-Resolution of Around-View Monitor Images

text: In the wide-angle (WA) images embedded in an around-view monitor system, the subject(s) in the peripheral region is normally small and has little information. Furthermore, since the outer region suffers from the non-uniform blur phenomenon and artifact caused by the inherent optical characteristic of WA lenses, its visual quality tends to deteriorate. According to our experiments, conventional image enhancement techniques rarely improve the degraded visual quality of the outer region of WA images. In order to solve the above-mentioned problem, this paper proposes a joint sharpness enhancement (SE) and super-resolution (SR) algorithm which can improve the sharpness and resolution of WA images together. The proposed SE algorithm improves the sharpness of the deteriorated WA images by exploiting self-similarity. Also, the proposed SR algorithm generates super-resolved images by using high-resolution information which is classified according to the extended local binary pattern-based classifier and learned on a pattern basis. Experimental results show that the proposed scheme effectively improves the sharpness and resolution of the input deteriorated WA images. Even in terms of quantitative metrics such as just noticeable blur, structural similarity, and peak signal-to-noise ratio. Finally, the proposed scheme guarantees real-time processing such that it achieves 720p video at 29 Hz on a low cost GPU platform.


title: Understanding the Potential of Interpreter-based Optimizations for Python

text: The increasing popularity of scripting languages as general purpose programming environments calls for more efficient execution. Most of these languages, such as Python, Ruby, PHP, and JavaScript are interpreted. Interpretation is a natural implementation given the dynamic nature of these languages and interpreter portability has facilitated wide-spread use. In this work, we analyze the performance of CPython, a commonly used Python interpreter, to identify major sources of overhead. Based on our findings, we investigate the efficiency of a number of optimizations and explore the design options and trade-offs involved.


title: A Fast Parallel Algorithm for Thinning Digital Patterns

text: A fast parallel thinning algorithm is proposed in this paper. It consists of two subiterations: one aimed at deleting the south-east boundary points and the north-west corner points while the other one is aimed at deleting the north-west boundary points and the south-east corner points. End points and pixel connectivity are preserved. Each pattern is thinned down to a "skeleton" of unitary thickness. Experimental results show that this method is very effective.


title: Lifetime study for a poly fuse in a 0.35 /spl mu/m polycide CMOS process

text: Poly fuses are used as the base element for one time programmable cells in a standard CMOS process. Using a defined programming current, the resistance of the poly fuse increases irreversibly over several orders of magnitude. The goal of this study is to show that a poly fuse has a sufficient life time stability to be used as a storage element even in high reliability circuits. This paper shows the drift of the resistance of a poly fuse over the whole range of programming currents for a standard polycide 0.35 /spl mu/m CMOS process. The poly fuse for the selected process is build using two different layers, which gives a special performance in terms of programming current.


title: The relative success of alternative approaches to strategic information systems planning: an empirical analysis

text: Strategic information systems planning (SISP) is an exercise or ongoing activity that enables organisations to develop priorities for information systems development. It has been suggested that the ‘SISP approach’, a combination of method, process and implementation, is the most complete way of describing SISP activity. Based upon questionnaire responses from 267 IT Directors, four distinct approaches to SISP have been derived using cluster analysis. A comparison of these four approaches with five approaches of Earl, M.J., 1993. Experiences in SISP, MIS Quarterly, (March), 1–24, indicates that three bear strong similarities to the ‘organisational’, ‘business-led’, and ‘administrative’ approaches, whilst the fourth cluster is related to both Earl’s ‘method-driven’ and ‘technological’ approaches. An analysis of the relationship between SISP approach and SISP success demonstrates that the ‘organisational approach’ is significantly more successful than the other three approaches. q 1999 Elsevier Science B.V. All rights reserved.


title: Classroom Re-design to Facilitate Student Learning : A Case Study of Changes to a University Classroom

text:
This case study examines the physical aspects of a particular university classroom, and what affect specific changes to the classroom had on the perceptions of students, instructors and observers regarding the room as an effective learning space. We compare survey and focus group data collected from students taking courses in the classroom prior to changes to the physical environment with comparable data from students taking courses in the same classroom after specific changes had been made. Immediately following changes to the classroom, notable increases were observed in reported perceptions of student satisfaction with the physical environment, including perceptions of the classroom as a more effective and engaging learning space. Similar perceptions of improvement as a teaching-learning space were reported by instructors and observers. However, subsequent follow-up data collection and analyses suggested little if any sustained increase in perceptions of efficacy of the room as a learning space; indeed, most reported variables returned to baseline levels. The implications of these findings and their relevance to classroom design nevertheless may provide insight regarding the manner in which physical space might support or even enhance teaching and learning. Keywords: learning spaces, active learning, classrooms, teaching and learning environment, classroom design For a number of years there has been an on-going pedagogical shift in higher education away from a traditional content delivery model of instruction to more active models of learning in which students play more involved and interactive roles within the classroom (Cornell, 2002; Brown, 2006). This movement has been coupled with the recognition that the traditional university classroom, with its unidirectional design and tiered, fixed theatre-like seating, is insufficient to accommodate what have increasingly become more varied teaching and learning practices. This growing realization that as the nature of teaching and learning evolves so too must teaching and learning spaces has, in recent years, resulted in a heightened interest among scholars in the examination of classroom space and, more specifically, the inquiry into the connection between classroom design and pedagogy and learning (Brooks, 2011). This study presents findings from an on-going research project examining classroom spaces on a small university campus. The present case study, which is one component of the larger project, compares perceptions of a specific classroom as an effective learning space before and after relatively extensive changes were made to the physical environment of the room. These changes were guided by feedback from students and instructors as well as by existing literature on innovative classroom designs. In particular, we were interested in assessing if these changes 1
  University
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  Lethbridge,
  Lethbridge,
  Alberta,
  Canada


title: Approximating the Kullback Leibler Divergence Between Gaussian Mixture Models

text: The Kullback Leibler (KL) divergence is a widely used tool in statistics and pattern recognition. The KL divergence between two Gaussian mixture models (GMMs) is frequently needed in the fields of speech and image recognition. Unfortunately the KL divergence between two GMMs is not analytically tractable, nor does any efficient computational algorithm exist. Some techniques cope with this problem by replacing the KL divergence with other functions that can be computed efficiently. We introduce two new methods, the variational approximation and the variational upper bound, and compare them to existing methods. We discuss seven different techniques in total and weigh the benefits of each one against the others. To conclude we evaluate the performance of each one through numerical experiments.


title: Interprocedural Semantic Change-Impact Analysis using Equivalence Relations

text: Change-impact analysis (CIA) is the task of determining the set of program elements impacted by a program change. Precise CIA has great potential to avoid expensive t sting and code reviews for (parts of) changes that are refactoring s (semantics-preserving). Existing CIA is imprecise becaus e it is coarse-grained, deals with only few refactoring patterns,or is unaware of the change semantics. We formalize the notion of change impact in terms of the trace semantics of two program versions. We show how to leverage equivalence relations to make dataflow-based CIA aware of th e change semantics, thereby improving precision in the prese nce of semantics-preserving changes. We propose an anytime algorithm that allows applying costly equivalence relation inference incrementally to refine the set of impacted statements. We ha ve implemented a prototype in SYM DIFF , and evaluated it on 322 real-world changes from open-source projects and benchmar k programs used by prior research. The evaluation results sho w an average 35% improvement in the size of the set of impacted statements compared to standard dataflow-based techniques .


title: Dual Learning based Multi-Objective Pairwise Ranking

text: There are many different recommendation tasks in our real life. The item ranking task is ranking a set of items based on users’ preferences. The user ranking task is referred to as user retrieval, find the potential users and recommend items to them. We find every recommendation task has it’s own dual task, e.g., Recommend an item to a user versus the user is supposed to become the item’s potential interested user. In this paper, we propose a novel dual learning based ranking framework with the overall aim of learning users’ preferences over items and learning items’ preferences over users by minimizing a pairwise ranking loss. We generate effective feedback signal from close loop formed by dual task. Through a reinforcement learning process, we can iteratively update these two tasks’ models to catch relations between the item recommendation task and the user retrieval task. The experiments show that our method outperforms classical approaches for multi-object recommendation tasks, especially for user retrieval tasks.


title: Business Analytics in (a) Blink

text: The Blink project’s ambitious goal is to answer all Business Intelligence (BI) queries in mere seconds, regardless of the database size, with an extremely low total cost of ownership. Blink is a new DBMS aimed primarily at read-mostly BI query processing that exploits scale-out of commodity multi-core processors and cheap DRAM to retain a (copy of a) data mart completely in main memory. Additionally, it exploits proprietary compression technology and cache-conscious algorithms that reduce memory bandwidth consumption and allow most SQL query processing to be performed on the compressed data. Blink always scans (portions of) the data mart in parallel on all nodes, without using any indexes or materialized views, and without any query optimizer to choose among them. The Blink technology has thus far been incorporated into two IBM accelerator products generally available since March 2011. We are now working on the next generation of Blink, which will significantly expand the “sweet spot” of the Blink technology to much larger, disk-based warehouses and allow Blink to “own” the data, rather


title: Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands.

text: The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.


title: The thalamic dynamic core theory of conscious experience

text: I propose that primary conscious awareness arises from synchronized activity in dendrites of neurons in dorsal thalamic nuclei, mediated particularly by inhibitory interactions with thalamic reticular neurons. In support, I offer four evidential pillars: (1) consciousness is restricted to the results of cortical computations; (2) thalamus is the common locus of action of brain injury in vegetative state and of general anesthetics; (3) the anatomy and physiology of the thalamus imply a central role in consciousness; (4) neural synchronization is a neural correlate of consciousness.


title: PFC Cuk Converter-Fed BLDC Motor Drive

text: This paper deals with a power factor correction (PFC)-based Cuk converter-fed brushless dc motor (BLDC) drive as a cost-effective solution for low-power applications. The speed of the BLDC motor is controlled by varying the dc-bus voltage of a voltage source inverter (VSI) which uses a low frequency switching of VSI (electronic commutation of the BLDC motor) for low switching losses. A diode bridge rectifier followed by a Cuk converter working in a discontinuous conduction mode (DCM) is used for control of dc-link voltage with unity power factor at ac mains. Performance of the PFC Cuk converter is evaluated under four different operating conditions of discontinuous and continuous conduction modes (CCM) and a comparison is made to select a best suited mode of operation. The performance of the proposed system is simulated in a MATLAB/Simulink environment and a hardware prototype of the proposed drive is developed to validate its performance over a wide range of speed with unity power factor at ac mains.


title: Pokémon Go: Impact on Yelp Restaurant Reviews

text: Pokémon Go, the popular Augmented Reality based mobile application, launched in July of 2016. The game's meteoric rise in usage since that time has had an impact on not just the mobile gaming industry, but also the physical activity of players, where they travel, where they spend their money, and possibly how they interact with other social media applications. In this paper, we studied the impact of Pokémon Go on Yelp reviews. For restaurants near PokéStops, we found a slight drop in the number of online reviews.


title: CIVSched: A Communication-Aware Inter-VM Scheduling Technique for Decreased Network Latency between Co-Located VMs

text: Server consolidation in cloud computing environments makes it possible for multiple servers or desktops to run on a single physical server for high resource utilization, low cost, and reduced energy consumption. However, the scheduler in the virtual machine monitor (VMM), such as Xen credit scheduler, is agnostic about the communication behavior between the guest operating systems (OS). The aforementioned behavior leads to increased network communication latency in consolidated environments. In particular, the CPU resources management has a critical impact on the network latency between co-located virtual machines (VMs) when there are CPUand I/O-intensive workloads running simultaneously. This paper presents the design and implementation of a communication-aware inter-VM scheduling (CIVSched) technique that takes into account the communication behavior between inter-VMs running on the same virtualization platform. The CIVSched technique inspects the network packets transmitted between local co-resident domains to identify the target VM and process that will receive the packets. Thereafter, the target VM and process are preferentially scheduled by the VMM and the guest OS. The cooperation of these two schedulers makes the network packets to be timely received by the target application. Experimental results on the Xen virtualization platform depict that the CIVSched technique can reduce the average response time of network traffic by approximately 19 percent for the highly consolidated environment, while keeping the inherent fairness of the VMM scheduler.


title: Classification of plant leaf images with complicated background

text: Keywords: Image segmentation Plant leaf Complicated background Watershed segmentation Hu geometric moments Zernike moment Moving center hypersphere (MCH) classifier a b s t r a c t Classifying plant leaves has so far been an important and difficult task, especially for leaves with complicated background where some interferents and overlapping phenomena may exist. In this paper, an efficient classification framework for leaf images with complicated background is proposed. First, a so-called automatic marker-controlled watershed segmen-tation method combined with pre-segmentation and morphological operation is introduced to segment leaf images with complicated background based on the prior shape information. Then, seven Hu geometric moments and sixteen Zernike moments are extracted as shape features from segmented binary images after leafstalk removal. In addition , a moving center hypersphere (MCH) classifier which can efficiently compress feature data is designed to address obtained mass high-dimensional shape features. Finally, experimental results on some practical plant leaves show that proposed classification framework works well while classifying leaf images with complicated background. There are twenty classes of practical plant leaves successfully classified and the average correct classification rate is up to 92.6%. Plants play the most important part in the cycle of nature. They are the primary producers that sustain all other life forms including people. This is because plants are the only organisms that can convert light energy from the sun into food. Animals, incapable of making their own food, depend directly or indirectly on plants for their supply of food. Moreover, all of the oxygen available for living organisms comes from plants. Plants are also the primary habitat for thousands of other organisms. In addition, many of the fuel people use today, such as coal, natural gas and gasoline, were made from plants that lived millions of years ago. However, in recent years, people have been seriously destroying the natural environments, so that many plants constantly die and even die out every year. Conversely, the resulting ecological crisis has brought many serious consequences including land desertion, climate anomaly, land flood, and so on, which have menaced the survival of human being and the development of society. Now, people have realized the importance and urgency of protecting plant resource. Besides taking effective measures to protect plants, it is important for ordinary people to know or classify plants which can further enhance the public's consciousness of plant protection. Therefore, besides professional botanists, many non-professional researchers have paid more …


title: How do I communicate my emotions on SNS and IMs?

text: With influx of new devices and applications over the past few years, computer mediated communication has developed as an alternate to face-to-face communication. Through our study we attempt to understand how individuals communicate in mediated settings in emotion-laden situations. We explore their preferred medium of communication in different situations along with analysis of the content of communication. Spatial arrays, lexical surrogates, vocal spellings and grammatical markers were used as strategies by individuals for communicating non-verbal cues in text based communication. We also look at how messages sent on IMs or posts on social networks are interpreted by readers in terms of the emotional state of the sender. We found that while valence of the sender gets easily and accurately communicated, arousal is misinterpreted in most situations. In this paper, we present findings from our study which can be valuable for technology companies looking to better the current communication experience across different media.


title: Handling Multiword Expressions in Causality Estimation

text: Previous studies on causality estimation mainly aquire causal event pairs from a large corpus based on lexico-syntactic patterns and coreference relations, and estimate causality by a statistical method. However, most of the previous studies assume event pairs can be represented by a pair of single words, therefore they cannot estimate multiword causality correctly (e.g.“tired”-“give up”) . In this paper, we create a list of multiword expressions and extend an existing method. Our evaluation demonstrates that the proper treatment of multiword expression events is effective and the proposed method outperforms the state-of-the-art causality estimation model.


title: Health-Related Disaster Communication and Social Media: Mixed-Method Systematic Review.

text: This mixed-method evidence synthesis drew on Cochrane methods and principles to systematically review literature published between 2003 and 2016 on the best social media practices to promote health protection and dispel misinformation during disasters. Seventy-nine studies employing quantitative, qualitative, and mixed methods on risk communication during disasters in all UN-languages were reviewed, finding that agencies need to contextualize the use of social media for particular populations and crises. Social media are tools that still have not become routine practices in many governmental agencies regarding public health in the countries studied. Social media, especially Twitter and Facebook (and equivalents in countries such as China), need to be incorporated into daily operations of governmental agencies and implementing partners to build familiarity with them before health-related crises happen. This was especially observed in U.S. agencies, local government, and first responders but also for city governments and school administrations in Europe. For those that do use social media during health-related risk communication, studies find that public relations officers, governmental agencies, and the general public have used social media successfully to spread truthful information and to verify information to dispel rumors during disasters. Few studies focused on the recovery and preparation phases and on countries in the Southern hemisphere, except for Australia. The vast majority of studies did not analyze the demographics of social media users beyond their geographic location, their status of being inside/outside the disaster zone; and their frequency and content of posting. Socioeconomic demographics were not collected and/or analyzed to drill deeper into the implications of using social media to reach vulnerable populations. Who exactly is reached via social media campaigns and who needs to be reached with other means has remained an understudied area.


title: Don't fall into a trap: Physical side-channel analysis of ChaCha20-Poly1305

text: The stream cipher ChaCha20 and the MAC function Poly1305 have been published as IETF RFC 7539. Since then, the industry is starting to use it more often. For example, it has been implemented by Google in their Chrome browser for TLS and also support has been added to OpenSSL, as well as OpenSSH. It is often claimed, that the algorithms are designed to be resistant to side-channel attacks. However, this is only true, if the only observable side-channel is the timing behavior. In this paper, we show that ChaCha20 is susceptible to power and EM side-channel analysis, which also translates to an attack on Poly1305, if used together with ChaCha20 for key generation. As a first countermeasure, we analyze the effectiveness of randomly shuffling the operations of the ChaCha round function.


title: Depressive realism: a meta-analytic review.

text: The current investigation represents the first meta-analysis of the depressive realism literature. A search of this literature revealed 75 relevant studies representing 7305 participants from across the US and Canada, as well as from England, Spain, and Israel. Results generally indicated a small overall depressive realism effect (Cohen's d=-.07). Overall, however, both dysphoric/depressed individuals (d=.14) and nondysphoric/nondepressed individuals evidenced a substantial positive bias (d=.29), with this bias being larger in nondysphoric/nondepressed individuals. Examination of potential moderator variables indicated that studies lacking an objective standard of reality (d=-.15 versus -.03, for studies possessing such a standard) and that utilize self-report measures to measure symptoms of depression (d=.16 versus -.04, for studies which utilize structured interviews) were more likely to find depressive realism effects. Methodological paradigm was also found to influence whether results consistent with depressive realism were found (d's ranged from -.09 to .14).


title: Pattern Reconfigurable Antenna Based on Morphing Bistable Composite Laminates

text: In this paper, a novel pattern reconfigurable antenna based on morphing bistable composite laminates is presented. The bistable asymmetric glass-fiber reinforced polymer (GFRP) composite laminates have two stable configurations with curvatures of opposite signs. The antenna pattern is reconfigured by transforming the configuration of the bistable GFRP laminate which acts as the substrate of the antenna. The coplanar waveguide transmission lines feeding technique is used for the microstrip quasi-Yagi antenna. A prototype of the proposed antenna is fabricated using a semi-automatic screen printer and an autoclave. The transformation between the two stable states of the proposed antenna using Ni/Ti shape memory alloy springs is investigated experimentally. The out-of-plane displacements, reflection coefficients and radiation patterns for the two stable configurations of the antenna are measured, which agree well with the simulated results. The main beam direction is 89° and 59° for the two stable configurations, respectively. In addition, the influences of various bending radii on the radiation patterns are investigated to gain a thorough understanding of the reconfigurable mechanism of the proposed antenna. Finally, a two-element array of such an antenna is presented and measured. The proposed antenna provides a potential application in multifunctional, conformal, morphing, and integrated structures.


title: Ventilation performance prediction for buildings : A method overview and recent applications

text: This paper presented an overview of the tools used to predict ventilation performance in buildings. The tools reviewed were analytical models, empirical models, small-scale experimental models, full-scale experimental models, multizone network models, zonal models, and Computational Fluid Dynamics (CFD) models. This review found that the analytical and empirical models had made minimal contributions to the research literature in the past year. The smalland full-scale experimental models were mainly used to generate data to validate numerical models. The multizone models were improving, and they were the main tool for predicting ventilation performance in an entire building. The zonal models had limited applications and could be replaced by the coarse-grid CFD models. The CFD models were most popular and contributed to 70 percent of the literature found in this review. Considerable efforts were still made to seek more reliable and accurate models. It has been a trend to improve their performance by coupling CFD with other building simulation models. The applications of CFD models were mainly for studying indoor air quality, natural ventilation, and stratified ventilation as they were difficult to be predicted by other models.


title: Bioconductor: open software development for computational biology and bioinformatics

text: The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.


title: State of the Art in LP-WAN Solutions for Industrial IoT Services

text: The emergence of low-cost connected devices is enabling a new wave of sensorization services. These services can be highly leveraged in industrial applications. However, the technologies employed so far for managing this kind of system do not fully cover the strict requirements of industrial networks, especially those regarding energy efficiency. In this article a novel paradigm, called Low-Power Wide Area Networking (LP-WAN), is explored. By means of a cellular-type architecture, LP-WAN-based solutions aim at fulfilling the reliability and efficiency challenges posed by long-term industrial networks. Thus, the most prominent LP-WAN solutions are reviewed, identifying and discussing the pros and cons of each of them. The focus is also on examining the current deployment state of these platforms in Spain. Although LP-WAN systems are at early stages of development, they represent a promising alternative for boosting future industrial IIoT (Industrial Internet of Things) networks and services.


title: Facial performance sensing head-mounted display

text: There are currently no solutions for enabling direct face-to-face interaction between virtual reality (VR) users wearing head-mounted displays (HMDs). The main challenge is that the headset obstructs a significant portion of a user's face, preventing effective facial capture with traditional techniques. To advance virtual reality as a next-generation communication platform, we develop a novel HMD that enables 3D facial performance-driven animation in real-time. Our wearable system uses ultra-thin flexible electronic materials that are mounted on the foam liner of the headset to measure surface strain signals corresponding to upper face expressions. These strain signals are combined with a head-mounted RGB-D camera to enhance the tracking in the mouth region and to account for inaccurate HMD placement. To map the input signals to a 3D face model, we perform a single-instance offline training session for each person. For reusable and accurate online operation, we propose a short calibration step to readjust the Gaussian mixture distribution of the mapping before each use. The resulting animations are visually on par with cutting-edge depth sensor-driven facial performance capture systems and hence, are suitable for social interactions in virtual worlds.


title: Machine Learning for the Internet of Things Security: A Systematic Review

text: Internet of things (IoT) is nowadays one of the fastest growing technologies for both private and business purposes. Due to a big number of IoT devices and their rapid introduction to the market, security of things and their services is often not at the expected level. Recently, machine learning algorithms, techniques, and methods are used in research papers to enhance IoT security. In this paper, we systematically review the state-of-the art to classify the research on machine learning for the IoT security. We analysed the primary studies, identify types of studies and publication fora. Next, we have extracted all machine learning algorithms and techniques described in primary studies, and identified the most used ones to tackle IoT security issues. We classify the research into three main categories (intrusion detection, authentication and other) and describe the primary studies in detail to analyse existing relevant works and propose topics for future research.


title: The impact of data replication on job scheduling performance in the Data Grid

text: In the Data Grid environment, the primary goal of data replication is to shorten the data access time experienced by the job and consequently reduce the job turnaround time. After introducing a Data Grid architecture that supports efficient data access for the Grid job, the dynamic data replication algorithms are put forward. Combined with different Grid scheduling heuristics, the performances of the data replication algorithms are evaluated with various simulations. The simulation results demonstrate f shortest lacement data e ists, d the ten-


title: Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

text: We develop a face recognition algorithm which is insensitive to large variation in lighting direction and facial expression. Taking a pattern classification approach, we consider each pixel in an image as a coordinate in a high-dimensional space. We take advantage of the observation that the images of a particular face, under varying illumination but fixed pose, lie in a 3D linear subspace of the high dimensional image space—if the face is a Lambertian surface without shadowing. However, since faces are not truly Lambertian surfaces and do indeed produce self-shadowing, images will deviate from this linear subspace. Rather than explicitly modeling this deviation, we linearly project the image into a subspace in a manner which discounts those regions of the face with large deviation. Our projection method is based on Fisher’s Linear Discriminant and produces well separated classes in a low-dimensional subspace, even under severe variation in lighting and facial expressions. The Eigenface technique, another method based on linearly projecting the image space to a low dimensional subspace, has similar computational requirements. Yet, extensive experimental results demonstrate that the proposed “Fisherface” method has error rates that are lower than those of the Eigenface technique for tests on the Harvard and Yale Face Databases. Index Terms —Appearance-based vision, face recognition, illumination invariance, Fisher’s linear discriminant. —————————— ✦ ——————————


title: Hardware, Design and Implementation Issues on a Fpga-Based Smart Camera

text: Processing images to extract useful information in real-time is a complex task, dealing with large amounts of iconic data and requiring intensive computation. Smart cameras use embedded processing to save the host system from the low-level processing load and to reduce communication flows and overheads. Field programmable devices present special interest for smart cameras design: flexibility, reconfigurability and parallel processing skills are some specially important features. In this paper we present a FPGA-based smart camera research platform. The hardware architecture is described, and some design issues are discussed. Our goal is to use the possibility to reconfigure the FPGA device in order to adapt the system architecture to a given application. To that, a design methodology, based on pre-programmed processing elements, is proposed and sketched. Some implementation issues are discussed and a template tracking application is given as example, with its experimental results.


title: Oboe: auto-tuning video ABR algorithms to network conditions

text: Most content providers are interested in providing good video delivery QoE for all users, not just on average. State-of-the-art ABR algorithms like BOLA and MPC rely on parameters that are sensitive to network conditions, so may perform poorly for some users and/or videos. In this paper, we propose a technique called Oboe to auto-tune these parameters to different network conditions. Oboe pre-computes, for a given ABR algorithm, the best possible parameters for different network conditions, then dynamically adapts the parameters at run-time for the current network conditions. Using testbed experiments, we show that Oboe significantly improves BOLA, MPC, and a commercially deployed ABR. Oboe also betters a recently proposed reinforcement learning based ABR, Pensieve, by 24% on average on a composite QoE metric, in part because it is able to better specialize ABR behavior across different network states.


title: An efficient method of license plate location

text: License plate location is an important stage in vehicle license plate recognition for automated transport system. This paper presents a real time and robust method of license plate location. License plate area contains rich edge and texture information. We first extract out the vertical edges of the car image using image enhancement and Sobel operator, then remove most of the background and noise edges by an effective algorithm, and finally search the plate region by a rectangle window in the residual edge image and segment the plate out from the original car image. Experimental results demonstrate the great robustness and efficiency of our method. 2005 Elsevier B.V. All rights reserved.


title: How to Increase Users' Social Commerce Engagement? A Technology Attractiveness Model

text: With the proliferation of social networking and electronic commerce, social commerce helps people engage in various forms of online social commercial activities through sharing their product or service knowledge and experiences. A better understanding of users’ engagement in social commerce websites thus become increasingly important. Based on the attractiveness theory, this study proposes a research model that highlights the unique role of technology attractiveness, including task, social, and physical attractiveness, in promoting user involvement, which in turn affects social commerce engagement. Results demonstrate that users’ perceptions of technology attractiveness are positively associated with their involvement with social commerce websites, and further stimulate engagement. In addition, website involvement partially and fully mediates the effects of social and physical attractiveness, respectively, on social commerce engagement. The limitations and implications of this study for research and practice are further discussed.


title: Geometry-Driven Diffusion in Computer Vision

text: Inevitably, reading is one of the requirements to be undergone. To improve the performance and quality, someone needs to have something new every day. It will suggest you to have more inspirations, then. However, the needs of inspirations will make you searching for some sources. Even from the other people experience, internet, and many books. Books and internet are the recommended media to help you improving your quality and performance.


title: 3D face matching and registration based on hyperbolic Ricci flow

text: 3D surface matching is fundamental for shape analysis. As a powerful method in geometric analysis, Ricci flow can flexibly design metrics by prescribed target curvature. In this paper we describe a novel approach for matching surfaces with complicated topologies based on hyperbolic Ricci flow. For surfaces with negative Euler characteristics, such as a human face with holes (eye contours), the canonical hyperbolic metric is conformal to the original and can be efficiently computed. Then the surface can be canonically decomposed to hyperbolic hexagons. By matching the corresponding hyperbolic hexagons, the matching between surfaces can be easily established. Compared to existing methods, hyperbolic Ricci flow induces diffeomorphisms between surfaces with complicated topologies with negative Euler characteristics, while avoiding singularities. Furthermore, all the boundaries are intrinsically mapped to hyperbolic lines as alignment constraints. Finally, we demonstrate the applicability of this intrinsic shape representation for 3D face matching and registration.


title: The weight consistency matrix framework for general non-binary LDPC code optimization: Applications in flash memories

text: Transmission channels underlying modern memory systems, e.g., Flash memories, possess a significant amount of asymmetry. While existing LDPC codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are fairly inadequate. We propose a new, general, combinatorial framework for the analysis and design of non-binary LDPC (NB-LDPC) codes for asymmetric channels. We introduce a refined definition of absorbing sets, which we call general absorbing sets (GASs), and an important subclass of GASs, which we refer to as general absorbing sets of type two (GASTs). Additionally, we study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Based on these new concepts, we then develop a general code optimization framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Our optimized codes enjoy over one order (resp., half of an order) of magnitude performance gain in the uncorrectable BER (UBER) relative to the unoptimized codes (resp. the codes optimized for symmetric channels).


title: An approach to interactive deep reinforcement learning for serious games

text: Serious games receive increasing interest in the area of e-learning. Their development, however, is often still a demanding, specialized and arduous process, especially when regarding reasonable non-player character behaviour. Reinforcement learning and, since recently, also deep reinforcement learning have proven to automatically generate successful AI behaviour to a certain degree. These methods are computationally expensive and hardly scalable to various complex serious game scenarios. For this reason, we introduce a new approach of augmenting the application of deep reinforcement learning methods by interactively making use of domain experts' knowledge to guide the learning process. Thereby, we aim to create a synergistic combination of experts and emergent cognitive systems. We call this approach interactive deep reinforcement learning and point out important aspects regarding realization within a framework.


title: Gesture recognition using kinect for sign language translation

text: Sign Language is a widely used method of communication among the community of deaf-mute people. It contains some series of body gestures, which enables a person to interact without the need of spoken words. Although the use of sign language is very popular among the deaf-mute people but the other communities don't even try to learn it, this creates a gulf of communication and hence becomes a cause of the isolation of physically impaired people. The problem creates a requirement of a system which can facilitate a way of communication between these two communities. This paper presents a novel method for identification of an isolated sign language gesture using Microsoft Kinect. This paper presents the way of extracting some highly robust features from the depth image provided by Kinect and to use them in creating a robust and accurate gesture recognition system, for the purpose of sign language translation. Apart from translation, the proposed system also opens the doors of endless applications in the field of Human Computer Interaction. The proposed algorithm helps in translating a sign language gesture performed by a user, which in-turn can be used as an input for different types of applications.


title: Software and Algorithms for Graph Queries on Multithreaded Architectures

text: Search-based graph queries, such as finding short paths and isomorphic subgraphs, are dominated by memory latency. If input graphs can be partitioned appropriately, large cluster-based computing platforms can run these queries. However, the lack of compute-bound processing at each vertex of the input graph and the constant need to retrieve neighbors implies low processor utilization. Furthermore, graph classes such as scale-free social networks lack the locality to make partitioning clearly effective. Massive multithreading is an alternative architectural paradigm, in which a large shared memory is combined with processors that have extra hardware to support many thread contexts. The processor speed is typically slower than normal, and there is no data cache. Rather than mitigating memory latency, multithreaded machines tolerate it. This paradigm is well aligned with the problem of graph search, as the high ratio of memory requests to computation can be tolerated via multithreading. In this paper, we introduce the multithreaded graph library (MTGL), generic graph query software for processing semantic graphs on multithreaded computers. This library currently runs on serial machines and the Cray MTA-2, but Sandia is developing a run-time system that will make it possible to run MTGL-based code on symmetric multiprocessors. We also introduce a multithreaded algorithm for connected components and a new heuristic for inexact subgraph isomorphism We explore the performance of these and other basic graph algorithms on large scale-free graphs. We conclude with a performance comparison between the Cray MTA-2 and Blue Gene/Light for s-t connectivity.


title: The hymen morphology in normal newborn Saudi girls.

text:
BACKGROUND
Hymen morphology has a medico-legal importance. In view of the lack of national norms, establishing the hymen morphology of Saudi newborn infants is essential.

SUBJECTS AND METHODS
Over a period of 4 months, the genitalia of 345 full-term female newborn infants were examined to determine the shape of the hymen. A previously described labia traction technique was used to classify the hymen morphology into annular, sleeve-like, fimbriated, crescentric, and other types.

RESULTS
The hymen was present in all 345 female newborn infants examined. A total of 207 (60%) were of the annular type, 76 (22%) were sleeve-like, 43 (12.5%) fimbriated, 17 (4.9%) crescentric, and 2 (0.6%) of other types.

CONCLUSION
The most common hymen morphology in Saudi newborn girls was annular, followed by sleeve-like, fimbriated, and crescentric. This study may be the first to define normal configuration of the hymen in this community.


title: Self-Attentive Feature-Level Fusion for Multimodal Emotion Detection

text: Multimodal emotion recognition is the task of detecting emotions present in user-generated multimedia content. Such resources contain complementary information in multiple modalities. A stiff challenge often faced is the complexity associated with feature-level fusion of these heterogeneous modes. In this paper, we propose a new feature-level fusion method based on self-attention mechanism. We also compare it with traditional fusion methods such as concatenation, outer-product, etc. Analyzed using textual and speech (audio) modalities, our results suggest that the proposed fusion method outperforms others in the context of utterance-level emotion recognition in videos.


title: Provenance: On and Behind the Screens

text: Collecting and processing provenance, i.e., information describing the production process of some end product, is important in various applications, e.g., to assess quality, to ensure reproducibility, or to reinforce trust in the end product. In the past, different types of provenance meta-data have been proposed, each with a different scope. The first part of the proposed tutorial provides an overview and comparison of these different types of provenance. To put provenance to good use, it is essential to be able to interact with and present provenance data in a user-friendly way. Often, users interested in provenance are not necessarily experts in databases or query languages, as they are typically domain experts of the product and production process for which provenance is collected (biologists, journalists, etc.). Furthermore, in some scenarios, it is difficult to use solely queries for analyzing and exploring provenance data. The second part of this tutorial therefore focuses on enabling users to leverage provenance through adapted visualizations. To this end, we will present some fundamental concepts of visualization before we discuss possible visualizations for provenance.


title: Using Genetic Algorithm to Solve Game of Go-Moku

text: Genetic algorithm is a stochastic parallel beam search that can be applied to many typical search problems. This paper describes a genetic algorithmic approach to a problem in artificial intelligence. During the process of evolution, the environment cooperates with the population by continuously making itself friendlier so as to lower the evolutionary pressure. Evaluations show the performance of this approach seems considerably effective in solving this type of board games. Game-playing programs are often described as being a combination of search and


title: How to Normalize Co-Occurrence Data ? An Analysis of Some Well-Known Similarity Measures Nees

text: AND


title: An improved algorithm for feature selection using fractal dimension

text: Dimensionality reduction is an important issue in data mining and machine learning. Traina[1] proposed a feature selection algorithm to select the most important attributes for a given set of n-dimensional vectors based on correlation fractal dimension. The author used a kind of multi-dimensional “quad-tree” structure to compute the fractal dimension. Inspired by his work, we propose a new and simpler algorithm to compute the fractal dimension, and design a novel and faster feature selection algorithm using correlation fractal dimension, whose time complexity is lower than that of Traina’s. The main idea is when computing the fractal dimension of (d-1)-dimensional data, the intermediate generated results of the extended d-dimensional data is reused. It inherits the desirable properties described as in [1]. Also, Our algorithm does not require the grid sizes decrease by half as the original “quad-tree” algorithm. Experiments show our feature selection algorithm has a good efficiency over the test dataset.


title: Advancing interactive collaborative mediums through tele-immersive dance (TED): a symbiotic creativity and design environment for art and computer science

text: The Tele-immersive Dance Environment (TED) is a geographically distributed, real-time 3-D virtual room where multiple participants interact independent of physical distance. TED, a highly interactive collaborative environment, offers digital options with multiple viewpoints, enhancing the creative movement composition involved with dance choreography. A symbiotic relationship for creativity and design exists between dance artists and computer scientists as the tele-immersive environment is analyzed as a creativity and learning tool. We introduce the advancements of the interactive digital options, new interface developments, user study results, and the possibility of a computational model for human creativity through Laban Movement Analysis.


title: A Survey on Security for Mobile Devices

text: Nowadays, mobile devices are an important part of our everyday lives since they enable us to access a large variety of ubiquitous services. In recent years, the availability of these ubiquitous and mobile services has significantly increased due to the different form of connectivity provided by mobile devices, such as GSM, GPRS, Bluetooth and Wi-Fi. In the same trend, the number and typologies of vulnerabilities exploiting these services and communication channels have increased as well. Therefore, smartphones may now represent an ideal target for malware writers. As the number of vulnerabilities and, hence, of attacks increase, there has been a corresponding rise of security solutions proposed by researchers. Due to the fact that this research field is immature and still unexplored in depth, with this paper we aim to provide a structured and comprehensive overview of the research on security solutions for mobile devices. This paper surveys the state of the art on threats, vulnerabilities and security solutions over the period 2004-2011, by focusing on high-level attacks, such those to user applications. We group existing approaches aimed at protecting mobile devices against these classes of attacks into different categories, based upon the detection principles, architectures, collected data and operating systems, especially focusing on IDS-based models and tools. With this categorization we aim to provide an easy and concise view of the underlying model adopted by each approach.


title: End-to-End Blind Image Quality Assessment Using Deep Neural Networks

text: We propose a multi-task end-to-end optimized deep neural network (MEON) for blind image quality assessment (BIQA). MEON consists of two sub-networks—a distortion identification network and a quality prediction network—sharing the early layers. Unlike traditional methods used for training multi-task networks, our training process is performed in two steps. In the first step, we train a distortion type identification sub-network, for which large-scale training samples are readily available. In the second step, starting from the pre-trained early layers and the outputs of the first sub-network, we train a quality prediction sub-network using a variant of the stochastic gradient descent method. Different from most deep neural networks, we choose biologically inspired generalized divisive normalization (GDN) instead of rectified linear unit as the activation function. We empirically demonstrate that GDN is effective at reducing model parameters/layers while achieving similar quality prediction performance. With modest model complexity, the proposed MEON index achieves state-of-the-art performance on four publicly available benchmarks. Moreover, we demonstrate the strong competitiveness of MEON against state-of-the-art BIQA models using the group maximum differentiation competition methodology.


title: Quality, productivity and economic benefits of software reuse: a review of industrial studies

text: Systematic software reuse is proposed to increase productivity and software quality and lead to economic benefits. Reports of successful software reuse programs in industry have been published. However, there has been little effort to organize the evidence systematically and appraise it. This review aims to assess the effects of software reuse in industrial contexts. Journals and major conferences between 1994 and 2005 were searched to find observational studies and experiments conducted in industry, returning eleven papers of observational type. Systematic software reuse is significantly related to lower problem (defect, fault or error) density in five studies and to decreased effort spent on correcting problems in three studies. The review found evidence for significant gains in apparent productivity in three studies. Other significant benefits of software reuse were reported in single studies or the results were inconsistent. Evidence from industry is sparse and combining results was done by vote-counting. Researchers should pay more attention to using comparable metrics, performing longitudinal studies, and explaining the results and impact on industry. For industry, evaluating reuse of COTS or OSS components, integrating reuse activities in software processes, better data collection and evaluating return on investment are major challenges.


title: NoSQL Systems for Big Data Management

text: The advent of Big Data created a need for out-of-the-box horizontal scalability for data management systems. This ushered in an array of choices for Big Data management under the umbrella term NoSQL. In this paper, we provide a taxonomy and unified perspective on NoSQL systems. Using this perspective, we compare and contrast various NoSQL systems using multiple facets including system architecture, data model, query language, client API, scalability, and availability. We group current NoSQL systems into seven broad categories: Key-Value, Table-type/Column, Document, Graph, Native XML, Native Object, and Hybrid databases. We also describe application scenarios for each category to help the reader in choosing an appropriate NoSQL system for a given application. We conclude the paper by indicating future research directions.


title: Interoperable Data Migration between NoSQL Columnar Databases

text: NoSQL databases have emerged as the solution to handle large quantities of user-generated contents still guaranteeing fault tolerance, availability and scalability. Each NoSQL database offers differentiated properties and characteristics as well as different data models and architectures. As a result, the development of applications exploiting such kind of technology is strictly dependent on the specific NoSQL solution being adopted, and the migration from a NoSQL to the other requires the development of ad-hoc code managing the transfer of data. In order to mitigate such issue, this paper proposes an interoperable migration system for columnar NoSQL databases. The proposed approach is based on an orginal Metamodel, capable of preserving both strong and weak consistency between data updates, secondary indexes and various data types. Moreover, the approach allows developers to easily add support for new databases.


title: SEQUEL: A Structured English Query Language

text: In this paper we present the data manipulation facility for a structured English query language (SEQUEL) which can be used for accessing data in an integrated relational data base. Without resorting to the concepts of bound variables and quantifiers SEQUEL identifies a set of simple operations on tabular structures, which can be shown to be of equivalent power to the first order predicate calculus. A SEQUEL user is presented with a consistent set of keyword English templates which reflect how people use tables to obtain information. Moreover, the SEQUEL user is able to compose these basic templates in a structured manner in order to form more complex queries. SEQUEL is intended as a data base sublanguage for both the professional programmer and the more infrequent data base user.


title: CAP twelve years later: How the "rules" have changed

text: The CAP theorem asserts that any networked shared-data system can have only two of three desirable properties. However, by explicitly handling partitions, designers can optimize consistency and availability, thereby achieving some trade-off of all three. The featured Web extra is a podcast from Software Engineering Radio, in which the host interviews Dwight Merriman about the emerging NoSQL movement, the three types of nonrelational data stores, Brewer's CAP theorem, and much more.


title: Research Methods in Computer Science: The Challenges and Issues

text: Research methods are essential parts in conducting any research project. Although they have been theorized and summarized based on best practices, every field of science requires an adaptation of the overall approaches to perform research activities. In addition, any specific research needs a particular adjustment to the generalized approach and specializing them to suit the project in hand. However, unlike most well-established science disciplines, computing research is not supported by well-defined, globally accepted methods. This is because of its infancy and ambiguity in its definition, on one hand, and its extensive coverage and overlap with other fields, on the other hand. This article discusses the research methods in science and engineering in general and in computing in particular. It shows that despite several special parameters that make research in computing rather unique, it still follows the same steps that any other scientific research would do. The article also shows the particularities that researchers need to consider when they conduct research in this field.


title: Abiotic and Biotic Stress Responses in Solanum tuberosum Group Phureja DM1-3 516 R44 as Measured through Whole Transcriptome Sequencing

text: This study conducted an in-depth analysis of the potato (Solanum tuberosum L.) transcriptome in response to abiotic (salinity, drought, and heat) and biotic (Phytophthora infestans, DL-b amino-n-butyric acid, and acibenzolar-s-methyl) stresses and plant hormone treatment (abscisic acid, 6-benzylaminopurine, gibberellic acid, and indole-3-acetic acid) using ribonucleic acid sequencing (RNA-seq) of the doubled monoploid S. tuberosum Group Phureja DM1-3 516 R44 clone. Extensive changes in gene expression were observed with 37% of the expressed genes being differentially expressed in at least one comparison of stress to control tissue. Stress-inducible genes known to function in stress tolerance or to be involved in the regulation of gene expression were among the highest differentially expressed. Members of the MYB, APETALA2 (AP2)/ethylene-responsive element binding factor (ERF), and NAM, ATAF1/2, and CUC2 (NAC) transcription factor families were the most represented regulatory genes. A weighted gene co-expression network analysis yielded 37 co-expression modules containing 9198 genes. Fifty percent of the genes within these co-expression modules were specific to a stress condition indicating conditionspecific responses. Cross-species comparison between potato and Arabidopsis thaliana (L.) Heynh. uncovered differentially expressed orthologs and defined evolutionary conserved genes. Collectively, the transcriptional profiling of RNA-seq data presented here provide a valuable reference for potato stress responses to environmental factors that is supported by statistically significant differences in expression changes, highly interconnected genes in co-expression networks, and evidence of evolutionary conservation. Plants growing in natural habitats are exposed to multiple environmental stresses resulting from abiotic and biotic factors. Adaptation and response to these stresses is highly complex and involve changes at the molecular, cellular, and physiological levels. Abiotic stress factors such as heat, drought, and salinity have a significant impact on cultivated potato, affecting yield, tuber quality, and market value (Wang-Pruski and Schofield, 2012). Water availability is by far the most important limiting factor in crop production. Potato plants use water relatively efficiently; however, due in part to its sparse and shallow root system, potato is considered a drought-sensitive crop (Yuan et al., 2003). Salinity is another serious threat to crop production that may increase under anticipated climate change scenarios (Yeo, 1998). Although potatoes are considered moderately salt sensitive (Katerji et al., 2000), significant variations in salt tolerance exist among Solanum tuberosum cultivars and wild Solanum species (Khrais et al., 1998). Furthermore, potato responses to salt stress are related to the responses of other abiotic stresses, as revealed by microarray analysis of leaf responses to cold and salt Published in The Plant Genome 6 doi: 10.3835/plantgenome2013.05.0014 © Crop Science Society of America 5585 Guilford Rd., Madison, WI 53711 USA An open-access publication All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Dep. of Plant Biology, Michigan State Univ., East Lansing, MI 48824. Received 17 May 2013. *Corresponding author (buell@


title: G2G interaction among local agencies in developing countries based on diffusion of innovations theory

text: Technological advancement has allowed governments to meet the demands of its citizens electronically. Electronic government (e-Government) facilitates accurate and fast transactions and delivery of services and information to businesses, citizens, and government agencies. Moreover, e-Government helps enhance democracy. Agencies interact with one another electronically through the e-Government, which enhances efficiency. e-Government utilizes information and communication technology to provide the public access to various services. Leaders and information technology executives in the public sector have recognized the importance of sharing inter-organizational information to improve the efficiency of government agencies. Therefore, this study takes the diffusion of innovations theory as context to identify the most important factor affecting the electronic interaction between local agencies in developing countries.


title: A Kinect-Based Wearable Face Recognition System to Aid Visually Impaired Users

text: In this paper, we introduce a real-time face recognition (and announcement) system targeted at aiding the blind and low-vision people. The system uses a Microsoft Kinect sensor as a wearable device, performs face detection, and uses temporal coherence along with a simple biometric procedure to generate a sound associated with the identified person, virtualized at his/her estimated 3-D location. Our approach uses a variation of the K-nearest neighbors algorithm over histogram of oriented gradient descriptors dimensionally reduced by principal component analysis. The results show that our approach, on average, outperforms traditional face recognition methods while requiring much less computational resources (memory, processing power, and battery life) when compared with existing techniques in the literature, deeming it suitable for the wearable hardware constraints. We also show the performance of the system in the dark, using depth-only information acquired with Kinect's infrared camera. The validation uses a new dataset available for download, with 600 videos of 30 people, containing variation of illumination, background, and movement patterns. Experiments with existing datasets in the literature are also considered. Finally, we conducted user experience evaluations on both blindfolded and visually impaired users, showing encouraging results.


title: Agent based Architecture for Modeling and Analysis of Self Adaptive Systems using Formal Methods

text: Self-adaptive systems (SAS) can modify their behavior during execution; this modification is done because of change in internal or external environment. The need for selfadaptive software systems has increased tremendously in last decade due to ever changing user requirements, improvement in technology and need for building software that reacts to user preferences. To build this type of software we need well establish models that have the flexibility to adjust to the new requirements and make sure that the adaptation is efficient and reliable. Feedback loop has proven to be very effective in modeling and developing SAS, these loops help the system to sense, analyze, plan, test and execute the adaptive behavior at runtime. Formal methods are well defined, rigorous and reliable mathematical techniques that can be effectively used to reason and specify behavior of SAS at design and run-time. Agents can play an important role in modeling SAS because they can work independently, with other agents and with environment as well. Using agents to perform individual steps in feedback loop and formalizing these agents using Petri nets will not only increase the reliability, but also, the adaptation can be performed efficiently for taking decisions at run time with increased confidence. In this paper, we propose a multi-agent framework to model self-adaptive systems using agent based modeling. This framework will help the researchers in implementation of SAS, which is more dependable, reliable, autonomic and flexible because of use of multi-agent based formal approach. Keywords—Formal methods; self-adaptive systems; agent based modeling; feedback loop; Petri nets


title: Development of folded dual-polarization dividers for broadband ortho-mode transducers

text: A waveguide divider with folded lateral arms is presented for separating dual orthogonal linear polarizations in broadband ortho-mode transducers. The structure is based on a well-known double symmetry junction, where the metallic pins have been eliminated and the lateral outputs have been folded to achieve a combined effect: matching for the vertical polarization and a very significant size reduction. In addition, since the path for the lateral branches has been reduced, the insertion losses for the different polarizations are balanced. The isolation between orthogonal polarizations is kept because of the double-symmetry of the junction. From the mechanical point of view, the proposed junction allows a more simple manufacture and assembly of the ortho-mode transducer parts, which has been shown with a Ku-band design, covering the full Ku-band from 12.6 to 18.25 GHz. The experimental prototype has demonstrated a measured return loss better than 28 dB in the design band and insertion loss smaller than 0.15 dB for both polarizations.


title: Real-time wireless communication with per-packet deadlines

text: The last decades’ tremendous advances in wireless communications have been driven mainly by personal communications. Radio resource allocation mechanisms for optimizing key metrics, such as average throughput and delay, for such traffic are by now rather well-developed. However, with the increased interest in wireless machine-to-machine communication, e.g. for industrial control or monitoring of large-scale infrastructures, new challenges emerge. The performance of an estimator or closed-loop control system that operates over an unreliable wireless network depends on the full latency and loss distributions and not only on their averages. For these applications, more suitable performance metrics are per-packet guarantees on latency and reliability (on-time delivery). This thesis studies optimal forwarding of deadline-constrained traffic over lossy multi-hop networks. We assume a routing topology in the form of a directed graph with packet loss on links described by finite-state Markov chains, and focus on a single transient packet scenario. Two problems are considered: maximizing the probability that packets are delivered within their specified deadline; and minimizing the expected energy cost with a guaranteed probability of on-time delivery. The first problem can be formulated as a finite-horizon Markov decision process (MDP), while the second problem is a finite-horizon constrained Markov decision process (CMDP). A general dynamic programming framework that solves a weighted sum of reliability and energy maximization problem is proposed. The maximum deadline-constrained reliability problem is solved by studying a simplification of the general dynamic programming. The minimum energy optimal policy is a random selection between two deterministic and computable forwarding policies, each of which can be found via a dynamic programming framework. Particular instances with Bernoulli and Gilbert-Elliot loss models that admit numerically efficient solutions are discussed. Finally, we show the application of the technique for a co-design of forwarding policies and controller for wireless control. Based on the recent result on the monotonicity of the optimal control loss, the problem of minimum control loss and the problem of minimum energy cost with a guaranteed control performance can be solved optimally.


Numerical methods for least square problems


title: Analysis and Control of Multiphase Inductively Coupled Resonant Converter for Wireless Electric Vehicle Charger Applications

text: In this paper, an inductively coupled multiphase resonant converter is presented for wireless electric vehicle charging applications. As an alternative to the traditional frequency and phase shift control methods, a hybrid phase-frequency control strategy is implemented to improve the system efficiency. A theoretical analysis of the proposed system is carried out considering a wide battery state-of-charging range. In order to confirm the proposed converter and control technique, a laboratory prototype wireless charger is designed using 8-in air-gap coreless transformer and rectifier. The proposed control is compared with the conventional control methods for various load conditions at the different power levels. In comparison results, the proposed hybrid control methodology demonstrates the efficiency improvements of 1.1% at the heaviest load condition and 5.7% at the lightest load condition.


title: Arduino-based smart irrigation using water flow sensor, soil moisture sensor, temperature sensor and ESP8266 WiFi module

text: Emergence of Controlled Environment Agriculture (CEA) ranging from computer controlled water irrigation system to lightning and ventilation has changed the conventional scenario of farming. This paper proposes and demonstrate an economical and easy to use arduino based controlled irrigation system. The designed system deals with various environmental factors such as moisture, temperature and amount of water required by the crops using sensors like water flow sensor, temperature sensor and soil moisture sensor. Datas are collected and received by arduino which can be linked to an interactive website which show the real time values along with the standard values of different factor required by a crop. This allows user to control irrigation pumps and sprinklers from far distance through a website and to meet the standard values which would help the farmer to yield maximum and quality crops. Studies conducted on laboratory prototype suggested the designed system to be applicable which can be implemented.


title: Methods for the prevention, detection and removal of software security vulnerabilities

text: Over the past decade, the need to build secure software has become a dominant goal in software development. Consequently, software researchers and practitioners have identified ways that malicious users can exploit software and how developers can fix the vulnerabilities. They have also built a variety of source code security checking software applications to partially automate the task of performing a security analysis of a program. Although great advances have been made in this area, the core problem of how the security vulnerabilities occur still exists. An answer to this problem could be a paradigm shift from imperative to functional programming techniques. This may hold the key to removing software vulnerabilities altogether.


title: Neurocognitive Architecture of Working Memory

text: A crucial role for working memory in temporary information processing and guidance of complex behavior has been recognized for many decades. There is emerging consensus that working-memory maintenance results from the interactions among long-term memory representations and basic processes, including attention, that are instantiated as reentrant loops between frontal and posterior cortical areas, as well as sub-cortical structures. The nature of such interactions can account for capacity limitations, lifespan changes, and restricted transfer after working-memory training. Recent data and models indicate that working memory may also be based on synaptic plasticity and that working memory can operate on non-consciously perceived information.


title: Imago: presence and emotion in virtual reality

text:
As virtual reality becomes available to a wider audience, filmmakers are being challenged to create ever more immersive and creative narratives for this quickly evolving medium. While many of the early attempts at virtual reality filmmaking have been devoted to the creation of quick paced and aw-inspiring experiences, filmmakers such as Chris Milk and Oculus Story Studio have been more focused on more story driven experiences, using the medium to tell narratives in a new and exciting way.
 Project Hypnos was created at Carnegie Mellon University to explore immersive narrative filmmaking techniques for virtual reality. The resulting proof-of-concept film, Imago, was created using the techniques developed during this research. Imago plays with the concept of a viewer's presence in a film in an attempt to elicit both negative and positive emotions. The result is a story-driven experience that comes to life through live-action drama, dance, and abstract CG imagery.


title: Representations of recent and remote autobiographical memories in hippocampal subfields

text: The hippocampus has long been implicated in supporting autobiographical memories, but little is known about how they are instantiated in hippocampal subfields. Using high-resolution functional magnetic resonance imaging (fMRI) combined with multivoxel pattern analysis we found that it was possible to detect representations of specific autobiographical memories in individual hippocampal subfields. Moreover, while subfields in the anterior hippocampus contained information about both recent (2 weeks old) and remote (10 years old) autobiographical memories, posterior CA3 and DG only contained information about the remote memories. Thus, the hippocampal subfields are differentially involved in the representation of recent and remote autobiographical memories during vivid recall.


system for handling the design of elevator systems that is currently in use at Westinghouse Elevator Company Although VT tries to postpone each decision in creating a design until all information that constrains the decision is known, for many decisions this postponement is not possible In these cases, VT uses the strategy of constructing a plausible approximation and successively refining it VT uses domain-specific knowledge to guide its backtracking search for successful refinements The VT architecture provides the basis for a knowledge representation that is used by SALT, an automated knowledge-acquisition tool SALT was used to build VT and provides an analysis of VT’s knowledge base to assess its potential for convergence on a solution VT: An Expert Elevator Designer That Uses Knowledge-Based Backtracking Sandra Marcus, Jeffrey Stout, John McDermott


title: Trust and Recommendations

text: Recommendation technologies and trust metrics constitute the two pillars of trust-enhanced recommender systems. We discuss and illustrate the basic trust concepts such as trust and distrust modeling, propagation and aggregation. These concepts are needed to fully grasp the rationale behind the trust-enhanced recommender techniques that are discussed in the central part of the chapter, which focuses on the application of trust metrics and their operators in recommender systems. We explain the benefits of using trust in recommender algorithms and give an overview of state-of-the-art approaches for trust-enhanced recommender systems. Furthermore, we explain the details of three well-known trust-based systems and provide a comparative analysis of their performance. We conclude with a discussion of some recent developments and open challenges, such as visualizing trust relationships in a recommender system, alleviating the cold start problem in a trust network of a recommender system, studying the effect of involving distrust in the recommendation process, and investigating the potential of other types of social relationships.


title: The YAP Prolog System

text: Yet Another Prolog (YAP) is a Prolog system originally developed in the mid-eighties and that has been under almost constant development since then. This paper presents the general structure and design of the YAP system, focusing on three important contributions to the Logic Programming community. First, it describes the main techniques used in YAP to achieve an efficient Prolog engine. Second, most Logic Programming systems have a rather limited indexing algorithm. YAP contributes to this area by providing a dynamic indexing mechanism, or just-in-time indexer (JITI). Third, a important contribution of the YAP system has been the integration of both or-parallelism and tabling in a single Logic Programming system.


title: B-spline-based road model for 3d lane recognition

text: The assumption of a planar road is rarely fulfilled on rural roads and often violated in construction zones. Hills and dips are common and curves with small radius often have an inclination towards the center. In this paper a novel road model is presented, which uses B-Spline modeling to describe the 3D road course. The right and left vertical road courses are modeled separately to represent the roll angle of the road. The well-proven clothoid model used for lateral road course estimation is extended with a B-Spline curve resulting in a more flexible road model as needed for rural roads and construction sites. This road model is tracked over time using a Kalman filter. Stereo measurements provide height information of the road surface, which are used for the 3D lane recognition.


title: Are web applications ready for parallelism?

text: In recent years, web applications have become pervasive. Their backbone is JavaScript, the only programming language supported by all major web browsers. Most browsers run on desktop or mobile devices with parallel hardware. However, JavaScript is by design sequential, and current web applications make little use of hardware parallelism. Are web applications ready to exploit parallel hardware? We answer the question in two steps: First, we survey 174 web developers about the potential and challenges of using parallelism. Then, we study the performance and computation shape of a set of web applications that are representative for the emerging web. Our findings indicate that emerging web applications do have latent data parallelism, and JavaScript developers' programming style is not a significant impediment to exploiting this parallelism.


Gradient-based learning algorithms for recurrent networks and their computational complexity


title: Professor Forcing: A New Algorithm for Training Recurrent Networks

text: The Teacher Forcing algorithm trains recurrent networks by supplying observed sequence values as inputs during training and using the network’s own one-stepahead predictions to do multi-step sampling. We introduce the Professor Forcing algorithm, which uses adversarial domain adaptation to encourage the dynamics of the recurrent network to be the same when training the network and when sampling from the network over multiple time steps. We apply Professor Forcing to language modeling, vocal synthesis on raw waveforms, handwriting generation, and image generation. Empirically we find that Professor Forcing acts as a regularizer, improving test likelihood on character level Penn Treebank and sequential MNIST. We also find that the model qualitatively improves samples, especially when sampling for a large number of time steps. This is supported by human evaluation of sample quality. Trade-offs between Professor Forcing and Scheduled Sampling are discussed. We produce T-SNEs showing that Professor Forcing successfully makes the dynamics of the network during training and sampling more similar.


title: Style-based inverse kinematics

text: This paper presents an inverse kinematics system based on a learned model of human poses. Given a set of constraints, our system can produce the most likely pose satisfying those constraints, in real-time. Training the model on different input data leads to different styles of IK. The model is represented as a probability distribution over the space of all possible poses. This means that our IK system can generate any pose, but prefers poses that are most similar to the space of poses in the training data. We represent the probability with a novel model called a Scaled Gaussian Process Latent Variable Model. The parameters of the model are all learned automatically; no manual tuning is required for the learning component of the system. We additionally describe a novel procedure for interpolating between styles.Our style-based IK can replace conventional IK, wherever it is used in computer animation and computer vision. We demonstrate our system in the context of a number of applications: interactive character posing, trajectory keyframing, real-time motion capture with missing markers, and posing from a 2D image.


title: Impact of increased penetration of photovoltaic generation on power systems

text: Present renewable portfolio standards are changing power systems by replacing conventional generation with alternate energy resources such as photovoltaic (PV) systems. With the increase in penetration of PV resources, power systems are expected to experience a change in dynamic and operational characteristics. This paper studies the impact of increased penetration of PV systems on static performance as well as transient stability of a large power system, in particular the transmission system. Utility scale and residential rooftop PVs are added to the aforementioned system to replace a portion of conventional generation resources. While steady state voltages are observed under various PV penetration levels, the impact of reduced inertia on transient stability performance is also examined. The studied system is a large test system representing a portion of the Western U.S. interconnection. The simulation results obtained effectively identify both detrimental and beneficial impacts of increased PV penetration both for steady state stability and transient stability performance.


title: Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts

text: We present a Bayesian tensor factorization model for inferring latent group structures from dynamic pairwise interaction patterns. For decades, political scientists have collected and analyzed records of the form "country i took action a toward country j at time t" - known as dyadic events - in order to form and test theories of international relations. We represent these event data as a tensor of counts and develop Bayesian Poisson tensor factorization to infer a low-dimensional, interpretable representation of their salient patterns. We demonstrate that our model's predictive performance is better than that of standard non-negative tensor factorization methods. We also provide a comparison of our variational updates to their maximum likelihood counterparts. In doing so, we identify a better way to form point estimates of the latent factors than that typically used in Bayesian Poisson matrix factorization. Finally, we showcase our model as an exploratory analysis tool for political scientists. We show that the inferred latent factor matrices capture interpretable multilateral relations that both conform to and inform our knowledge of international a airs.


title: Optimizing Players' Expected Enjoyment in Interactive Stories

text: In interactive storytelling systems and other story-based computer games, a drama manager is a background agent that aims to bring about an enjoyable and coherent experience for the players. In this paper, we present a personalized drama manager that increases a player’s expected enjoyment without removing player agency. Our personalized drama manager models a player’s preference using data-driven techniques, predicts the probability the player transitioning to different story experiences, selects an objective experience that can maximize the player’s expected enjoyment, and guides the player to the selected story experience. Human study results show that our drama manager can significantly increase players’ enjoyment ratings in an interactive storytelling testbed, compared to drama managers in pre-