title: VideoSET: Video Summary Evaluation through Text

abstract: In this paper we present VideoSET, a method for Video Summary Evaluation through Text that can evaluate how well a video summary is able to retain the semantic information contained in its original video. We observe that semantics is most easily expressed in words, and develop a text-based approach for the evaluation. Given a video summary, a text representation of the video summary is first generated, and an NLP-based metric is then used to measure its semantic distance to ground-truth text summaries written by humans. We show that our technique has higher agreement with human judgment than pixel-based distance metrics. We also release text annotations and ground-truth text summaries for a number of publicly available video datasets, for use by the computer vision community.


title: Absence Makes the Heart Grow Fonder: New Directions for Implantable Medical Device Security

abstract: A fundamental tension exists between safety in the common case and security under adversarial conditions for wireless implantable medical devices. We propose a class of new, fail-open defensive techniques for implantable medical devices that attempt to strike a balance between these two goals. We refer to these defensive techniques as Communication Cloakers. Cloakers are externally worn devices, much like computational Medical Alert bracelets. Cloakers protect the security of an IMD when worn, but allow for open access during emergencies if removed.


Short Text Classification Using Deep Representation: A Case Study of Spanish Tweets in Coset Shared Task


title: Learning socially normative robot navigation behaviors with Bayesian inverse reinforcement learning

abstract: Mobile robots that navigate in populated environments require the capacity to move efficiently, safely and in human-friendly ways. In this paper, we address this task using a learning approach that enables a mobile robot to acquire navigation behaviors from demonstrations of socially normative human behavior. In the past, such approaches have been typically used to learn only simple behaviors under relatively controlled conditions using rigid representations or with methods that scale poorly to large domains. We thus develop a flexible graph-based representation able to capture relevant task structure and extend Bayesian inverse reinforcement learning to use sampled trajectories from this representation. In experiments with a real robot and a large-scale pedestrian simulator, we are able to show that the approach enables a robot to learn complex navigation behaviors of varying degrees of social normativeness using the same set of simple features.


title: Bilingual Word Representations with Monolingual Quality in Mind

abstract: Recent work in learning bilingual representations tend to tailor towards achieving good performance on bilingual tasks, most often the crosslingual document classification (CLDC) evaluation, but to the detriment of preserving clustering structures of word representations monolingually. In this work, we propose a joint model to learn word representations from scratch that utilizes both the context coocurrence information through the monolingual component and the meaning equivalent signals from the bilingual constraint. Specifically, we extend the recently popular skipgram model to learn high quality bilingual representations efficiently. Our learned embeddings achieve a new state-of-the-art accuracy of 80.3 for the German to English CLDC task and a highly competitive performance of 90.7 for the other classification direction. At the same time, our models outperform best embeddings from past bilingual representation work by a large margin in the monolingual word similarity evaluation. 1


title: When Is Selective Self-Presentation Effective? An Investigation of the Moderation Effects of "Self-Esteem" and "Social Trust"

abstract: Abstract This study investigates the relationship between selective self-presentation and online life satisfaction, and how this relationship is influenced by respondents' perceptions of “self” (operationalized by “self-esteem”) and “others” (operationalized by “social trust”). Relying on survey data from 712 Korean online users, two important findings were detected in our study. First, the positive relationship between selective self-presentation and online life satisfaction becomes more prominent among people with low self-esteem compared to those with high self-esteem, and second, this positive relationship is enhanced among people with high levels of social trust compared to those with low trust levels. Theoretical and practical implications of our findings as well as potential limitations are discussed.


title: SAP HANA: The Evolution from a Modern Main-Memory Data Platform to an Enterprise Application Platform

abstract: SAP HANA is a pioneering, and one of the best performing, data platform designed from the grounds up to heavily exploit modern hardware capabilities, including SIMD, and large memory and CPU footprints. As a comprehensive data management solution, SAP HANA supports the complete data life cycle encompassing modeling, provisioning, and consumption. This extended abstract outlines the vision and planned next step of the SAP HANA evolution growing from a core data platform into an innovative enterprise application platform as the foundation for current as well as novel business applications in both on-premise and on-demand scenarios. We argue that only a holistic system design rigorously applying co-design at different levels may yield a highly optimized and sustainable platform for modern enterprise applications.


Effects Of Information Seeking Modes On Users’ Online Social Engineering Vulnerabilities


title: Incentives and Their Dynamics in Public Sector Performance Management Systems

abstract: We use the principal-agent model as a focal theoretical frame for synthesizing what we know, both theoretically and empirically, about the design and dynamics of the implementation of performance management systems in the public sector. In this context, we review the growing body of evidence about how performance measurement and incentive systems function in practice and how individuals and organizations respond and adapt to them over time, drawing primarily on examples from performance measurement systems in public education and social welfare programs. We also describe a dynamic framework for performance measurement systems that takes into account strategic behavior of individuals over time, learning about production functions and individual responses, accountability pressures, and the use of information about the relationship of measured performance to value added. Implications are discussed and recommendations derived for improving public sector performance measurement systems. © 2010 by the Association for Public Policy Analysis and Management.


title: Social Entrepreneurship: A Critique and Future Directions

abstract: Work on social entrepreneurship constitutes a field of study that intersects a number of domains, including entrepreneurial studies, social innovation, and nonprofit management. Scholars are beginning to contribute to the development of this new discipline through efforts that attempt to trace the emergence of social entrepreneurship as well as by comparing it to other organizational activities such as conventional entrepreneurship. However, as a nascent field, social entrepreneurship scholars are in the midst of a number of debates involving definitional and conceptual clarity, boundaries of the field, and a struggle to arrive at a set of relevant and meaningful research questions. This paper examines the promise of social entrepreneurship as a domain of inquiry and suggests a number of research areas and research questions for future study.


title: Towards generating realistic synthetic fingerprint images

abstract: Synthetic fingerprint generation has two major advantages. First, it is possible to create arbitrarily large databases for research purposes e.g. of a million or a billion fingerprints at virtually no cost and without legal constraints. Secondly, together with the generated fingerprint images comes additional ground truth information for free such as e.g. the corresponding minutiae template. However, recently it has been shown that existing methods in the literature synthesize images with unrealistic minutiae configurations, usually not visible to the naked eye of an expert. In this paper, we propose an algorithm called Realistic Fingerprint Creator (RFC) for the generation realistic synthetic fingerprint images, which, as a core ingredient, involves a selection procedure how to choose the most ‘realistic’ synthetic fingerprints to build a database. We have performed a test of realness comparing prints synthesized by RFC and real fingerprints, and we have observed that the proposed RFC is the first method which produces artificial fingerprints that pass this test due to their realistic minutiae configuration.


title: Unpacking Organizational Ambidexterity: Dimensions, Contingencies, and Synergistic Effects

abstract: Significant ambiguity remains in the literature regarding the conceptualization of organizational ambidexterity. We unpack this construct into one with two dimensions we term the balance dimension of ambidexterity (BD) and the combined dimension of ambidexterity (CD). BD corresponds to a firm's orientation to maintain a close relative balance between exploratory and exploitative activities, whereas CD corresponds to their combined magnitude. We reason that these dimensions are conceptually distinct, and rely on different causal mechanisms to enhance firm performance. We find that over and above their independent effects, concurrent high levels of BD and CD yield synergistic benefits. We also find that BD is more beneficial to resource-constrained firms, whereas CD is more beneficial to firms having greater access to internal and/or external resources. These results indicate that managers in resource-constrained contexts may benefit from a focus on managing trade-offs between exploration and exploitation demands, but for firms that have access to sufficient resources, the simultaneous pursuit of exploration and exploitation is both possible and desirable.


An Approach to Domain Transfer in Procedural Content Generation of Two-Dimensional Videogame Levels.


title: A Unified Theory of Development: A Dialectic Integration of Nature and Nurture

abstract: The understanding of nature and nurture within developmental science has evolved with alternating ascendance of one or the other as primary explanations for individual differences in life course trajectories of success or failure. A dialectical perspective emphasizing the interconnectedness of individual and context is suggested to interpret the evolution of developmental science in similar terms to those necessary to explain the development of individual children. A unified theory of development is proposed to integrate personal change, context, regulation, and representational models of development.


Addressing the Racial Disparity in Birth Outcomes: Implications for Maternal Racial Identity on Birthweight


Non-Destructive Techniques Based on Eddy Current Testing


title: Carbon Concentrating Mechanisms in Eukaryotic Marine Phytoplankton

abstract: The accumulation of inorganic carbon from seawater by eukaryotic marine phytoplankton is limited by the diffusion of carbon dioxide (CO2) in water and the dehydration kinetics of bicarbonate to CO2 and by ribulose-1,5-bisphosphate carboxylase/oxygenase's (RubisCO) low affinity for its inorganic carbon substrate, CO2. Nearly all marine phytoplankton have adapted to these limitations and evolved inorganic carbon (or CO2) concentrating mechanisms (CCMs) to support photosynthetic carbon fixation at the concentrations of CO2 present in ocean surface waters (<10–30 μM). The biophysics and biochemistry of CCMs vary within and among the three dominant groups of eukaryotic marine phytoplankton and may involve the activity of external or intracellular carbonic anhydrase, HCO3− transport, and perhaps a C4 carbon pump. In general, coccolithophores have low-efficiency CCMs, and diatoms and the haptophyte genus Phaeocystis have high-efficiency CCMs. Dinoflagellates appear to possess moderately efficient CCMs, which may...


A Survey on Authorship Profiling Techniques


title: Minimum-effort driven dynamic faceted search in structured databases

abstract: In this paper, we propose minimum-effort driven navigational techniques for enterprise database systems based on the faceted search paradigm. Our proposed techniques dynamically suggest facets for drilling down into the database such that the cost of navigation is minimized. At every step, the system asks the user a question or a set of questions on different facets and depending on the user response, dynamically fetches the next most promising set of facets, and the process repeats. Facets are selected based on their ability to rapidly drill down to the most promising tuples, as well as on the ability of the user to provide desired values for them. Our facet selection algorithms also work in conjunction with any ranked retrieval model where a ranking function imposes a bias over the user preferences for the selected tuples. Our methods are principled as well as efficient, and our experimental study validates their effectiveness on several application scenarios.


title: Neuromuscular and athletic performance following core strength training in elite youth soccer: Role of instability.

abstract: Cross-sectional studies revealed that inclusion of unstable elements in core-strengthening exercises produced increases in trunk muscle activity and thus potential extra stimuli to induce more pronounced performance enhancements in youth athletes. Thus, the purpose of the study was to investigate changes in neuromuscular and athletic performance following core strength training performed on unstable (CSTU) compared with stable surfaces (CSTS) in youth soccer players. Thirty-nine male elite soccer players (age: 17 ± 1 years) were assigned to two groups performing a progressive core strength-training program for 9 weeks (2-3 times/week) in addition to regular in-season soccer training. CSTS group conducted core exercises on stable (i.e., floor, bench) and CSTU group on unstable (e.g., Thera-Band® Stability Trainer, Togu© Swiss ball) surfaces. Measurements included tests for assessing trunk muscle strength/activation, countermovement jump height, sprint time, agility time, and kicking performance. Statistical analysis revealed significant main effects of test (pre vs post) for trunk extensor strength (5%, P < 0.05, d = 0.86), 10-20-m sprint time (3%, P < 0.05, d = 2.56), and kicking performance (1%, P < 0.01, d = 1.28). No significant Group × test interactions were observed for any variable. In conclusion, trunk muscle strength, sprint, and kicking performance improved following CSTU and CSTS when conducted in combination with regular soccer training.


title: Indoors forensic entomology: Colonization of human remains in closed environments by specific species of sarcosaprophagous flies

abstract: Fly species that are commonly recovered on human corpses concealed in houses or other dwellings are often dependent on human created environments and might have special features in their biology that allow them to colonize indoor cadavers. In this study we describe nine typical cases involving forensically relevant flies on human remains found indoors in southern Finland. Eggs, larvae and puparia were reared to adult stage and determined to species. Of the five species found the most common were Lucilia sericata Meigen, Calliphora vicina Robineau-Desvoidy and Protophormia terraenovae Robineau-Desvoidy. The fleshfly Sarcophaga caerulescens Zetterstedt is reported for the first time to colonize human cadavers inside houses and a COI gene sequence based DNA barcode is provided for it to help facilitate identification in the future. Fly biology, colonization speed and the significance of indoors forensic entomological evidence are discussed.


title: Aspects of Data Ethics in a Changing World: Where Are We Now?

abstract: Abstract Ready data availability, cheap storage capacity, and powerful tools for extracting information from data have the potential to significantly enhance the human condition. However, as with a...


title: When Thinking Back Can Hold Us Back: How Being a Follower Can Affect Women’s Loss-Aversion

abstract: Despite the persistent gender gap in many organizational leadership positions, researchers have not yet examined objective predictors of this gap. A fully crossed 3 (Role Prime: leader, follower, control) × 2 (Gender Prime: present, absent) × 2 (Sex: male, female) experimental design examined the effect of group role (i.e., leader or follower) and gender on loss-aversion. Participants (192 total; 96 female) were asked to name either their former or current leader ("superior") or follower ("subordinate"), compared with a no prime condition. Results suggest that women primed with a follower role were more loss-averse than men primed with a follower role, and were more loss-averse than women primed with the leader role or in the control condition. However, the role prime did not affect men's loss-aversion. The current research suggests that researchers and practitioners should consider the effects of group role on loss-aversion, as this may contribute to gender gaps in the workplace. (PsycINFO Database Record (c) 2019 APA, all rights reserved).


title: Big data analytics: Understanding its capabilities and potential benefits for healthcare organizations

abstract: To date, health care industry has not fully grasped the potential benefits to be gained from big data analytics. While the constantly growing body of academic research on big data analytics is mostly technology oriented, a better understanding of the strategic implications of big data is urgently needed. To address this lack, this study examines the historical development, architectural design and component functionalities of big data analytics. From content analysis of 26 big data implementation cases in healthcare, we were able to identify five big data analytics capabilities: analytical capability for patterns of care, unstructured data analytical capability, decision support capability, predictive capability, and traceability. We also mapped the benefits driven by big data analytics in terms of information technology (IT) infrastructure, operational, organizational, managerial and strategic areas. In addition, we recommend five strategies for healthcare organizations that are considering to adopt big data analytics technologies. Our findings will help healthcare organizations understand the big data analytics capabilities and potential benefits and support them seeking to formulate more effective data-driven analytics strategies.


title: Time-dependent land uplift and subsidence in the Santa Clara valley, California, from a large interferometric synthetic aperture radar data set: SANTA CLARA VALLEY INSAR TIME SERIES

abstract: [1] We invert 115 differential interferograms derived from 47 synthetic aperture radar (SAR) scenes for a time-dependent deformation signal in the Santa Clara valley, California. The time-dependent deformation is calculated by performing a linear inversion that solves for the incremental range change between SAR scene acquisitions. A nonlinear range change signal is extracted from the ERS InSAR data without imposing a model of the expected deformation. In the Santa Clara valley, cumulative land uplift is observed during the period from 1992 to 2000 with a maximum uplift of 41 ± 18 mm centered north of Sunnyvale. Uplift is also observed east of San Jose. Seasonal uplift and subsidence dominate west of the Silver Creek fault near San Jose with a maximum peak-to-trough amplitude of ∼35 mm. The pattern of seasonal versus long-term uplift provides constraints on the spatial and temporal characteristics of water-bearing units within the aquifer. The Silver Creek fault partitions the uplift behavior of the basin, suggesting that it acts as a hydrologic barrier to groundwater flow. While no tectonic creep is observed along the fault, the development of a low-permeability barrier that bisects the alluvium suggests that the fault has been active since the deposition of Quaternary units.


title: Evolution of crossmodal reorganization of the voice area in cochlear-implanted deaf patients†

abstract: r Abstract: Psychophysical and neuroimaging studies in both animal and human subjects have clearly demon- strated that cortical plasticity following sensory deprivation leads to a brain functional reorganization that favors the spared modalities. In postlingually deaf patients, the use of a cochlear implant (CI) allows a recovery of the auditory function, which will probably counteract the cortical crossmodal reorganization induced by hearing loss. To study the dynamics of such reversed crossmodal plasticity, we designed a longitudinal neuro- imaging study involving the follow-up of 10 postlingually deaf adult CI users engaged in a visual speechread- ing task. While speechreading activates Broca's area in normally hearing subjects (NHS), the activity level elicited in this region in CI patients is abnormally low and increases progressively with post-implantation time. Furthermore, speechreading in CI patients induces abnormal crossmodal activations in right anterior regions of the superior temporal cortex normally devoted to processing human voice stimuli (temporal voice- sensitive areas-TVA). These abnormal activity levels diminish with post-implantation time and tend towards the levels observed in NHS. First, our study revealed that the neuroplasticity after cochlear implantation involves not only auditory but also visual and audiovisual speech processing networks. Second, our results suggest that during deafness, the functional links between cortical regions specialized in face and voice proc- essing are reallocated to support speech-related visual processing through cross-modal reorganization. Such reorganization allows a more efficient audiovisual integration of speech after cochlear implantation. These compensatory sensory strategies are later completed by the progressive restoration of the visuo-audio-motor speech processing loop, including Broca's area. Hum Brain Mapp 33:1929-1940, 2012. V C 2011 Wiley Periodicals, Inc.


title: Construction and validation of a measure of integrative well-being in seven languages: The Pemberton Happiness Index

abstract: We introduce the Pemberton Happiness Index (PHI), a new integrative measure of well-being in seven languages, detailing the validation process and presenting psychometric data. The scale includes eleven items related to different domains of remembered well-being (general, hedonic, eudaimonic, and social well-being) and ten items related to experienced well-being (i.e., positive and negative emotional events that possibly happened the day before); the sum of these items produces a combined well-being index. A distinctive characteristic of this study is that to construct the scale, an initial pool of items, covering the remembered and experienced well-being domains, were subjected to a complete selection and validation process. These items were based on widely used scales (e.g., PANAS, Satisfaction With Life Scale, Subjective Happiness Scale, and Psychological Well-Being Scales). Both the initial items and reference scales were translated into seven languages and completed via Internet by participants (N = 4,052) aged 16 to 60 years from nine countries (Germany, India, Japan, Mexico, Russia, Spain, Sweden, Turkey, and USA). Results from this initial validation study provided very good support for the psychometric properties of the PHI (i.e., internal consistency, a single-factor structure, and convergent and incremental validity). Given the PHI’s good psychometric properties, this simple and integrative index could be used as an instrument to monitor changes in well-being. We discuss the utility of this integrative index to explore well-being in individuals and communities.


title: Bayesian algorithms for adaptive change detection in image sequences using Markov random fields

abstract: In many conventional methods for change detection, the detections are carried out by comparing a test statistic, which is computed locally for each location on the image grid, with a global threshold. These ‘nonadaptive’ methods for change detection suffer from the dilemma of either causing many false alarms or missing considerable parts of non-stationary areas. This contribution presents a way out of this dilemma by viewing change detection as an inverse, ill-posed problem. As such, the problem can be solved using prior knowledge about typical properties of change masks. This reasoning leads to a Bayesian formulation of change detection, where the prior knowledge is brought to bear by appropriately specified a priori probabilities. Based on this approach, a new, adaptive algorithm for change detection is derived where the decision thresholds vary depending on context, thus improving detection performance substantially. The algorithm requires only a single raster scan per picture and increases the computional load only slightly in comparison to non-adaptive techniques.


title: A Multiagent Modeling and Investigation of Smart Homes With Power Generation, Storage, and Trading Features

abstract: Smart homes, as active participants in a smart grid, may no longer be modeled by passive load curves; because their interactive communication and bidirectional power flow within the smart grid affects demand, generation, and electricity rates. To consider such dynamic environmental properties, we use a multiagent-system-based approach in which individual homes are autonomous agents making rational decisions to buy, sell, or store electricity based on their present and expected future amount of load, generation, and storage, accounting for the benefits each decision can offer. In the proposed scheme, home agents prioritize their decisions based on the expected utilities they provide. Smart homes' intention to minimize their electricity bills is in line with the grid's aim to flatten the total demand curve. With a set of case studies and sensitivity analyses, we show how the overall performance of the home agents converges-as an emergent behavior-to an equilibrium benefiting both the entities in different operational conditions and determines the situations in which conventional homes would benefit from purchasing their own local generation-storage systems.


title: A Survey of Channel Modeling for UAV Communications

abstract: Unmanned aerial vehicles (UAVs) have attracted great interest in rapid deployment for both civil and military applications. UAV communication has its own distinctive channel characteristics compared to the widely used cellular or satellite systems. Accurate channel characterization is crucial for the performance optimization and design of efficient UAV communication. However, several challenges exist in UAV channel modeling. For example, the propagation characteristics of UAV channels are under explored for spatial and temporal variations in non–stationary channels. Additionally, airframe shadowing has not yet been investigated for small size rotary UAVs. This paper provides an extensive survey of the measurement methods proposed for UAV channel modeling that use low altitude platforms and discusses various channel characterization efforts. We also review from a contemporary perspective of UAV channel modeling approaches, and outline future research challenges in this domain.


title: Kapre: On-GPU Audio Preprocessing Layers for a Quick Implementation of Deep Neural Network Models with Keras

abstract: We introduce Kapre, Keras layers for audio and music signal preprocessing. Music research using deep neural networks requires a heavy and tedious preprocessing stage, for which audio processing parameters are often ignored in parameter optimisation. To solve this problem, Kapre implements time-frequency conversions, normalisation, and data augmentation as Keras layers. We report simple benchmark results, showing real-time on-GPU preprocessing adds a reasonable amount of computation.


title: Filtering spam with behavioral blacklisting

abstract: Spam filters often use the reputation of an IP address (or IP address range) to classify email senders. This approach worked well when most spam originated from senders with fixed IP addresses, but spam today is also sent from IP addresses for which blacklist maintainers have outdated or inaccurate information (or no information at all). Spam campaigns also involve many senders, reducing the amount of spam any particular IP address sends to a single domain; this method allows spammers to stay "under the radar". The dynamism of any particular IP address begs for blacklisting techniques that automatically adapt as the senders of spam change. This paper presents SpamTracker, a spam filtering system that uses a new technique called behavioral blacklisting to classify email senders based on their sending behavior rather than their identity. Spammers cannot evade SpamTracker merely by using "fresh" IP addresses because blacklisting decisions are based on sending patterns, which tend to remain more invariant. SpamTracker uses fast clustering algorithms that react quickly to changes in sending patterns. We evaluate SpamTracker's ability to classify spammers using email logs for over 115 email domains; we find that SpamTracker can correctly classify many spammers missed by current filtering techniques. Although our current datasets prevent us from confirming SpamTracker's ability to completely distinguish spammers from legitimate senders, our evaluation shows that SpamTracker can identify a significant fraction of spammers that current IP-based blacklists miss. SpamTracker's ability to identify spammers before existing blacklists suggests that it can be used in conjunction with existing techniques (e.g., as an input to greylisting). SpamTracker is inherently distributed and can be easily replicated; incorporating it into existing email filtering infrastructures requires only small modifications to mail server configurations.


title: Review on psychophysiological methods in game research

abstract: This article reviews the psychophysiological method in game research. Psychophysiological measurements provide an objective, continuous, real-time, noninvasive, precise and sensitive way to assess the game experience. However, the best results require controlled experiments with careful monitoring of variables, large enough sample sizes and expertise in electrical signal processing. We briefly explain the theory behind the method and present the most useful measures: electromyography (EMG), electrodermal activity (EDA), electroencephalography (EEG) and cardiac measures. We review previous studies that have used psychophysiological measures in game research and illustrate some future directions. Our article covers several research lines using the psychophysiological method in game studies, and offers a comprehensive list of references for those interested in the field.


title: A Review of Software Quality Models for the Evaluation of Software Products

abstract: Actually, software products are increasing in a fast way and are used in almost all activities of human life. Consequently measuring and evaluating the quality of a software product has become a critical task for many companies. Several models have been proposed to help diverse types of users with quality issues. The development of techniques for building software has influenced the creation of models to assess the quality. Since 2000 the construction of software started to depend on generated or manufactured components and gave rise to new challenges for assessing quality. These components introduce new concepts such as configurability, reusability, availability, better quality and lower cost. Consequently the models are classified in basic models which were developed until 2000, and those based on components called tailored quality models. The purpose of this article is to describe the main models with their strengths and point out some deficiencies. In this work, we conclude that in the present age, aspects of communications play an important factor in the quality of software


title: One-time cookies: Preventing session hijacking attacks with stateless authentication tokens

abstract: HTTP cookies are the de facto mechanism for session authentication in Web applications. However, their inherent security weaknesses allow attacks against the integrity of Web sessions. HTTPS is often recommended to protect cookies, but deploying full HTTPS support can be challenging due to performance and financial concerns, especially for highly distributed applications. Moreover, cookies can be exposed in a variety of ways even when HTTPS is enabled. In this article, we propose one-time cookies (OTC), a more robust alternative for session authentication. OTC prevents attacks such as session hijacking by signing each user request with a session secret securely stored in the browser. Unlike other proposed solutions, OTC does not require expensive state synchronization in the Web application, making it easily deployable in highly distributed systems. We implemented OTC as a plug-in for the popular WordPress platform and as an extension for Firefox and Firefox for mobile browsers. Our extensive experimental analysis shows that OTC introduces a latency of less than 6 ms when compared to cookies—a negligible overhead for most Web applications. Moreover, we show that OTC can be combined with HTTPS to effectively add another layer of security to Web applications. In so doing, we demonstrate that one-time cookies can significantly improve the security of Web applications with minimal impact on performance and scalability.


title: Object Recognition in 3D Point Clouds Using Web Data and Domain Adaptation

abstract: In recent years, object detection has become an increasingly active field of research in robotics. An important problem in object detection is the availability of a sufficient amount of labeled training data to learn good classifiers. In this paper we show how to significantly reduce the need for manually labeled training data by leveraging data sets available on the World Wide Web. Specifically, we show how to use objects from Google’s 3D Warehouse to train an object detection system for 3D point clouds collected by robots navigating through both urban and indoor environments. In order to deal with the different characteristics of the web data and the real robot data, we additionally use a small set of labeled point clouds and perform domain adaptation. Our experiments demonstrate that additional data taken from the 3D Warehouse along with our domain adaptation greatly improves the classification accuracy on real-world environments.


title: Marine Algae as a Potential Source for Anti-Obesity Agents

abstract: Obesity is a major epidemic that poses a worldwide threat to human health, as it is also associated with metabolic syndrome, type 2 diabetes and cardiovascular disease. Therapeutic intervention through weight loss drugs, accompanied by diet and exercise, is one of the options for the treatment and management of obesity. However, the only approved anti-obesity drug currently available in the market is orlistat, a synthetic inhibitor of pancreatic lipase. Other anti-obesity drugs are still being evaluated at different stages of clinical trials, while some have been withdrawn due to their severe adverse effects. Thus, there is a need to look for new anti-obesity agents, especially from biological sources. Marine algae, especially seaweeds are a promising source of anti-obesity agents. Four major bioactive compounds from seaweeds which have the potential as anti-obesity agents are fucoxanthin, alginates, fucoidans and phlorotannins. The anti-obesity effects of such compounds are due to several mechanisms, which include the inhibition of lipid absorption and metabolism (e.g., fucoxanthin and fucoidans), effect on satiety feeling (e.g., alginates), and inhibition of adipocyte differentiation (e.g., fucoxanthin). Further studies, especially testing bioactive compounds in long-term human trials are required before any new anti-obesity drugs based on algal products can be developed.


Non-line-of-sight microwave backhaul for small cells


title: Description of outdoor air quality in a typical residential area in Kuwait

abstract: Abstract This paper presents a statistical analysis of the data collected by the air pollution mobile laboratory operated by Kuwait University. The experimental work was based on operating the mobile laboratory in the Mansouriya residential area for a period of 1 month (May 1994). The site was selected to represent a typical residential area which is impacted mainly by the heavy traffic into and out of Kuwait city. The levels of carbon monoxide (CO), nitrogen oxide (NO), nitrogen dioxide (NO 2 ) and ozone (O 3 ) were selected for analysis. These are the pollutants likely to result from traffic movement in any urban area. Sulphur dioxide (SO 2 ) was also monitored during the same period. The measured variables include some meteorological parameters such as temperature, relative humidity, atmospheric pressure, solar radiation, wind speed and wind direction, which were also recorded at the same time. The study investigates the atmospheric levels of pollutants in the Mansouriya area and the expected source contributing to these pollutants. The objective of this work was to measure the atmospheric levels of pollution in terms of NO, CO, NO 2 , SO 2 and O 3 and to compare with the international standard limits for urban areas. Another objective of the study was to study the diurnal variations of these pollutants. The results of this study indicate that the levels of air pollutants are within the recommended range for residential areas according to US Environmental Protection Agency standards. The distribution of CO was correlated with heavy traffic movement during rush hours. However, SO 2 levels also followed a similar pattern. This was attributed to heavy diesel operational equipment and trucks at the highway construction site near the area of study. The hourly distributions of CO, NO and NO 2 were also compared over the days of the week. The results show that no morning peaks were detected for these gases during weekends. Correlation between O 3 levels and NO and NO 2 was also carried out. The O 3 levels show a peak at the early morning hours and a major peak during midday. This is attributed to the photochemical reactions during the month of May which is the real start of summer in this area.


Classifying Benign and Malignant Mass using GLCM and GLRLM based Texture Features from Mammogram Aswini Kumar Mohanty*, Swapnasikta Beberta**, Saroj Kumar Lenka***


title: Autism and social robotics: A systematic review

abstract: Social robotics could be a promising method for Autism Spectrum Disorders (ASD) treatment. The aim of this article is to carry out a systematic literature review of the studies on this topic that were published in the last 10 years. We tried to address the following questions: can social robots be a useful tool in autism therapy? We followed the PRISMA guidelines, and the protocol was registered within PROSPERO database (CRD42015016158). We found many positive implications in the use of social robots in therapy as for example: ASD subjects often performed better with a robot partner rather than a human partner; sometimes, ASD patients had, toward robots, behaviors that TD patients had toward human agents; ASDs had a lot of social behaviors toward robots; during robotic sessions, ASDs showed reduced repetitive and stereotyped behaviors and, social robots manage to improve spontaneous language during therapy sessions. Therefore, robots provide therapists and researchers a means to connect with autistic subjects in an easier way, but studies in this area are still insufficient. It is necessary to clarify whether sex, intelligence quotient, and age of participants affect the outcome of therapy and whether any beneficial effects only occur during the robotic session or if they are still observable outside the clinical/experimental context. Autism Res 2016, 9: 165–183. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.


title: Robust Visual Tracking and Vehicle Classification via Sparse Representation

abstract: In this paper, we propose a robust visual tracking method by casting tracking as a sparse approximation problem in a particle filter framework. In this framework, occlusion, noise, and other challenging issues are addressed seamlessly through a set of trivial templates. Specifically, to find the tracking target in a new frame, each target candidate is sparsely represented in the space spanned by target templates and trivial templates. The sparsity is achieved by solving an l1-regularized least-squares problem. Then, the candidate with the smallest projection error is taken as the tracking target. After that, tracking is continued using a Bayesian state inference framework. Two strategies are used to further improve the tracking performance. First, target templates are dynamically updated to capture appearance changes. Second, nonnegativity constraints are enforced to filter out clutter which negatively resembles tracking targets. We test the proposed approach on numerous sequences involving different types of challenges, including occlusion and variations in illumination, scale, and pose. The proposed approach demonstrates excellent performance in comparison with previously proposed trackers. We also extend the method for simultaneous tracking and recognition by introducing a static template set which stores target images from different classes. The recognition result at each frame is propagated to produce the final result for the whole video. The approach is validated on a vehicle tracking and classification task using outdoor infrared video sequences.


title: Automatic verification of EMC immunity by simulation

abstract: Immunity of analog circuit blocks is becoming a major design risk. This paper presents an automated methodology to simulate the susceptibility of a circuit during the design phase. More specifically, we propose a CAD tool which determines the fail/pass criteria of a signal under direct power injection (DPI). This contribution describes the function of the tool which is validated by a LDO regulator.


title: Reasoning in Multiple Belief Spaces

abstract: MBR is a reasoning system which allows multiple bellets (beliets from multiple agents, contradictory beliefs, hypothetical beliefs) to be represented simultaneously in the same knowledge base and performs reasoning with in sets of these beliefs. MBR also contains provisos to detect contradictions and to recover from them. ::: ::: This paper describes MBR's method of detecting and recording contradictions with in beliefs of different agents, showing an example of such process.


A Comparison of BPMN and UML 2 . 0 Activity Diagrams


title: Research strategy of the German Agricultural Research Alliance (DAFA) for the development of the organic farming and food sector in Germany

abstract: The Federal Government of Germany regards organic farming as particularly resource-efficient and environmentally sustainable economic activity. It therefore supports the expansion of organic farming up to 20% of the agricultural area. Against this background, the German Agricultural Research Alliance (DAFA) together with a broad alliance of representatives from business, science, and public policy developed this research strategy in a theme-finding and prioritization process that ran over more than 2 years. It sets out how German agricultural research can make a substantial contribution to noticeably improving the performance and competitiveness of organic food and farming while at the same time helping the sector meet its own goals and be an example as an especially sustainable type of economic activity in terms of the four international umbrella organization of the organic world (IFOAM) principles of organic farming (health, environment, fairness, and care).


title: Correlates of weight loss and muscle-gaining behavior in 10- to 14-year-old males and females

abstract: Abstract Background . This study examined the influence of appearance and social acceptance esteem, awareness and internalization of media stereotypes, body size acceptance, and teasing on the weight loss and muscle-gaining behaviors of 10- to 14-year-old boys and girls. Methods . Male ( n = 670) and female ( n = 788) students were drawn from one of four public senior middle schools (grades 6–8) in Southern Ontario as part of a longitudinal outcome-based study. Students' baseline self-report questionnaires, measuring the above variables, were analyzed for the purposes of this study. Results . A higher percentage of girls reported engaging in weight loss behaviors, whereas a higher percentage of boys admitted to muscle gaining and the use of specific weight control methods such as laxative use and vomiting. Regression analyses revealed that internalization of media messages and body size acceptance were equally predictive of boys' weight loss and muscle-gaining behaviors, while teasing was found to also predict their muscle-gaining behavior. Among the girls, appearance esteem, internalization of media stereotypes, and body size acceptance were predictive of weight loss behaviors. None of the study variables were predictive of girls' muscle-gaining behavior. Conclusions . Weight loss and muscle-gaining behaviors appear to have their onset in children as young as 10 years. The findings support the need for prevention programs that focus on media literacy and ways to decrease weight-based teasing in the school setting.


title: Valuing Real Options by Spreadsheet: Parking Garage Case Example

abstract: This technical note shows how designers of infrastructure systems can evaluate flexibility in engineering systems in fairly simple ways. Specifically, it illustrates a spreadsheet approach to valuing “real options” in a project. The model avoids complex financial procedures, which are both inappropriate for most design issues and constitute barriers to understanding and thus achieving the substantial improvement in performance that real options enable. The spreadsheet approach uses standard procedures; is based on data available in practice; and provides graphics that explain the results intuitively. It should thus be readily accessible to practicing professionals responsible for engineering design and management. A practical application to the design of a parking garage demonstrates the ease of use and presentation of results of this approach.


title: Noise reduction using an undecimated discrete wavelet transform

abstract: A new nonlinear noise reduction method is presented that uses the discrete wavelet transform. Similar to Donoho (1995) and Donohoe and Johnstone (1994, 1995), the authors employ thresholding in the wavelet transform domain but, following a suggestion by Coifman, they use an undecimated, shift-invariant, nonorthogonal wavelet transform instead of the usual orthogonal one. This new approach can be interpreted as a repeated application of the original Donoho and Johnstone method for different shifts. The main feature of the new algorithm is a significantly improved noise reduction compared to the original wavelet based approach. This holds for a large class of signals, both visually and in the l/sub 2/ sense, and is shown theoretically as well as by experimental results.


title: Agent-mediated Integrative Negotiation for Retail Electronic Commerce

abstract: Software agents help automate a variety of tasks including those involved in buying and selling products over the Internet. Although shopping agents provide convenience for consumers and yield more efficient markets, today's first-generation shopping agents are limited to comparing merchant offerings only on price instead of their full range of value. As such, they do a disservice to both consumers and retailers by hiding important merchant value-added services from consumer consideration. Likewise, the increasingly popular online auctions pit sellers against buyers in distributive negotiation tug-of-wars over price. This paper analyzes these approaches from economic, behavioral, and software agent perspectives then proposes integrative negotiation as a more suitable approach to retail electronic commerce. Finally, we identify promising techniques (e.g., multi-attribute utility theory, distributed constraint satisfaction, and conjoint analysis) for implementing agent-mediated integrative negotiation.


title: Tanagra : A Mixed-Initiative Level Design Tool

abstract: Tanagra is a prototype mixed-initiative design tool for 2D platformer level design, in which a human and computer can work together to produce a level. The human designer can place constraints on a continuously running level generator, in the form of exact geometry placement and manipulation of the level's pacing. The computer then fills in the rest of the level with geometry that guarantees playability, or informs the designer that there is no level that meets their requirements. This paper presents the design of Tanagra, a discussion of the editing operations it provides to the designer, and an evaluation of the expressivity of its generator.


title: Computing Epipolar Geometry from Unsynchronized Cameras

abstract: Recently, many application systems have been developed by using a large number of cameras. If the 3D points are observed from synchronized cameras, the multiple view geometry of these cameras can be computed and the 3D reconstruction of the scene is available. Thus, the synchronization of multiple cameras is essential. In this paper, we propose a method for finding synchronization of multiple cameras and for computing the epipolar geometry from un- calibrated and unsynchronized cameras. In particular we use the affine invariance on frame numbers of camera images for finding the synchronization. The proposed method is tested by using real image sequences taken from uncalibrated and unsynchronized cameras.


title: Visual Programming Language for Thymio II Robot

abstract: This paper introduces a visual programming language (vpl) for Thymio II, an educational robot. Our vpl is intended for children in primary school and aims at making robotics programming approachable for young children by creating a close correspondence between the icons of the programming language and the design of the robot. Its two modes of operation | basic and advanced | allow children to learn programming at a level suitable for their current skill. Moreover, our vpl provides a live generation of textual code that eases the transition to textual programming for more advanced children. This paper describes the goals and the guiding principles behind the design of our vpl and demonstrates how an iterative development process with evaluations with children resulted in an improved vpl.


title: Automated car parking system commanded by Android application

abstract: The aim of this paper is to automate the car and the car parking as well. It discusses a project which presents a miniature model of an automated car parking system that can regulate and manage the number of cars that can be parked in a given space at any given time based on the availability of parking spot. Automated parking is a method of parking and exiting cars using sensing devices. The entering to or leaving from the parking lot is commanded by an Android based application.


title: A comparative evaluation of heuristic-based usability inspection methods

abstract: Given that heuristic evaluation (HE) is a popular evaluation method among practitioners despite criticisms surrounding its performance and reliability, there is a need to improve the method's performance. Several studies have shown HE-Plus, an emerging variant of HE, to outperform HE in both effectiveness and reliability. HE-Plus uses the same set of heuristics as HE; the only difference between these two methods is the 'usability problems profile' element in HE-Plus. This paper reports our attempt to verify the original profile employed in HE-Plus based on usability problem classification in the User Action Framework and an experiment evaluating its outcome by comparing HE with two HE variants using a profile (HE-Plus and HE++) and a control group. Our results confirmed the role of the 'usability problems profiles' on improving the performance and reliability of heuristic evaluation: both HE-Plus and HE++ outperformed HE in terms of effectiveness as well as reliability.


title: Shift-Invariant and Sampling Spaces Associated with the Special Affine Fourier Transform

abstract: Abstract The Special Affine Fourier Transformation or the SAFT generalizes a number of well known unitary transformations as well as signal processing and optics related mathematical operations. Shift-invariant spaces also play an important role in sampling theory, multiresolution analysis, and many other areas of signal and image processing. Shannon's sampling theorem, which is at the heart of modern digital communications, is a special case of sampling in shift-invariant spaces. Furthermore, it is well known that the Poisson summation formula is equivalent to the sampling theorem and that the Zak transform is closely connected to the sampling theorem and the Poisson summation formula. These results have been known to hold in the Fourier transform domain for decades and were recently shown to hold in the Fractional Fourier transform domain by A. Bhandari and A. Zayed. The main goal of this article is to show that these results also hold true in the SAFT domain. We provide a short, self-contained proof of Shannon's theorem for functions bandlimited in the SAFT domain and then show that sampling in the SAFT domain is equivalent to orthogonal projection of functions onto a subspace of bandlimited basis associated with the SAFT domain. This interpretation of sampling leads to least-squares optimal sampling theorem. Furthermore, we show that this approximation procedure is linked with convolution and semi-discrete convolution operators that are associated with the SAFT domain. We conclude the article with an application of fractional delay filtering of SAFT bandlimited functions.


title: Conditions for acceptance and usage of mobile payment procedures

abstract: Mobile payment (MP) is crucial for, but not limited to mobile commerce. The key to mobile payment acceptance is in the hands of customers. In this paper we examine the conditions for acceptance and actual usage of MP procedures by the customer. We identify essential conditions which belong to the categories costs, security and convenience. Different preferences lead to an individual set of essential conditions for any single user. We propose a scheme for their representation and comparison and, based on these results, examine the relevance of the different criteria with empirical results. Additionally, we propose an approach to a commensurate condition for the usage of MP procedures based on the theory of informational added values. Finally, applications and constrictions of the results are shown and an outlook on the future of mobile payment is given.


title: Forecastable Component Analysis

abstract: Introduce Forecastable Component Analysis (ForeCA), a novel dimension reduction technique for temporally dependent signals. Based on a new forecastability measure, ForeCA finds an optimal transformation to separate a multivariate time series into a forecastable and an orthogonal white noise space. I present a converging algorithm with a fast eigenvector solution. Applications to financial and macro-economic time series show that ForeCA can successfully discover informative structure, which can be used for forecasting as well as classification. ::: ::: The R package ForeCA accompanies this work and is publicly available on CRAN.


title: Analysis of rail potential and stray current for Taipei Metro

abstract: Taipei Metro adopted the diode-grounded scheme for stray current collection in construction of its cross rail network. During operation of the network, a high rail-to-earth potential (V/sub rail/) has been observed at the east end of the Blue Line (i.e., stations BL13-BL16). To find effective countermeasures, a series of field tests in a step-by-step development nature was conducted from 1999-2000, which led to the decision of disconnecting the impedance bond at G11 of the tie line so that the negative return current of the Blue Line cannot flow to the rails of the Red-Green Line, and vice versa (detailed in Sections III-A and V-C). This decision was implemented through contract-out work in 2003. Since then, the V/sub rail/ has been lowered by almost half before disconnection. To gain the insight characteristic before the contract-out, numerical simulations were also conducted by simulating the multi-train and multisection features of the cross transportation network. The simulation results (for V/sub rail/ and stray current, or I/sub stray/) were consistent with the field-test results. This paper presents the design of these field tests and their test results in comparison with the simulation results, based on which the countermeasures for reducing V/sub rail/ and the present status after V/sub rail/ reduction at Taipei Metro are presented.


title: Using design thinking to improve psychological interventions: The case of the growth mindset during the transition to high school.

abstract: There are many promising psychological interventions on the horizon, but there is no clear methodology for preparing them to be scaled up. Drawing on design thinking, the present research formalizes a methodology for redesigning and tailoring initial interventions. We test the methodology using the case of fixed versus growth mindsets during the transition to high school. Qualitative inquiry and rapid, iterative, randomized “A/B” experiments were conducted with ∼3,000 participants to inform intervention revisions for this population. Next, 2 experimental evaluations showed that the revised growth mindset intervention was an improvement over previous versions in terms of short-term proxy outcomes (Study 1, N = 7,501), and it improved 9th grade core-course GPA and reduced D/F GPAs for lower achieving students when delivered via the Internet under routine conditions with ∼95% of students at 10 schools (Study 2, N = 3,676). Although the intervention could still be improved even further, the current research provides a model for how to improve and scale interventions that begin to address pressing educational problems. It also provides insight into how to teach a growth mindset more effectively. (PsycINFO Database Record (c) 2016 APA, all rights reserved)


title: Surgical Correction of an Accessory Auricle, Polyotia

abstract: Polyotia is an extremely rare congenital anomaly of the external auricle. This condition is defined as an accessory auricle that is large enough to closely resemble an additional pinna rather than a skin remnant and cartilage [1]. Polyotia, also known as mirror ear or accessory ear, is a type of ear anomaly in the tragus area, but this term refers to substantial anomalies which resemble an accessory ear, unlike a pre-auricular tag. We report a case in which the patient had a duplicated auricle that was corrected successfully. A 9-year-old boy presented with a large accessory anomalous auricle on his left ear (Fig. 1). His accessory structure was approximately 2.3×2.0 cm in size and was composed of an elastic cartilaginous component. This duplicated structure was positioned anteriorly to the original auricle. There was a cartilaginous concave bowl that resembled the conchal hollow of the human ear just behind this duplicated auricular structure. This accessory anomaly was not as large as the patient's external auricle, but it mirrored his left external auricle. One auricular canal existed between the two auricle-concha structures. The patient also had a right pre-auricular skin tag, bilateral prominent ears and left-sided hemifacial microsomia. Although his other facial conditions could have been considered for surgical correction, we preferentially decided to correct his extra auricle. Surgical correction occurred via two main procedures. The goal of the first procedure was to correct the tragus area. We utilized the curved shape of the accessory auricle to simultaneously deconstruct the excess cartilaginous structure and to reconstruct the tragus. The accessory structure was resected in a wedge shape, remaining inferiorly based chondrocutaneous flap. The curved shape of the remaining chondrocutaneous composite flap was perfect for a new tragus (Fig. 2). The goal of the second procedure was to eliminate the concha-resembling cartilaginous bowl. Because of the possibility of variation in the facial nerve course [2], we avoided deep dissection for complete elimination of the cartilaginous component. We elevated the skin flap and only the superficial aspect of the cartilaginous bowl. Then, two quilting sutures using 4-0 prolene were placed to support the collapsed cartilaginous bowl (Fig. 3). The remnant skin flap was excised and trimmed to resemble an ear shape. After the operation and throughout the twelve months of follow-up, there have not been any complications. The patient's left tragus and external auricle have a natural-looking and symmetric appearance (Figs. 4, ,5).5). Since the first report of polyotia by von Bol et al. 1918, no more than thirty cases have been reported worldwide [2,3]. Some cases were diagnosed with other congenital facial anomalies or craniofacial syndromes such as Goldenhar syndrome or Treacher-Collins syndrome [2,3]. In addition, polyotia can present even in patients with normal ear conditions, but sometimes a constricted ear or a microtic ear can accompany [3]. In our case report, the patient presented with left polyotia and with bilateral prominent ears. The precise etiology of polyotia remains unclear. Embryologically, the external part of the human ear is derived from first (mandibular) and second (hyoid) branchial arches. The tragus and the crus of helix are derived from the first branchial arch and other external structures are derived from the second branchial arch [4]. A recent etiology suggested that polyotia is caused by the extraordinary migration of neural crest cells in the branchial arch during embryologic development. Lammer [5] insisted that fetal exposure to isotretinoin (retinoic acid) affects migration of neural crest cells, which then provokes external ear abnormalities including duplication. Surgical techniques to correct polyotia have not been established because of its rarity and shape variation. Gore et al. [2] reported eight cases of polyotia and presented five salient points for surgical correction. The five points were: releasing the skin of the extra component, excision of extra cartilage, remnant skin trimming, preservation of facial nerve, and timing of operation. Previous reported surgical corrections for polyotia recommend excision of all accessory structures and using the excised cartilage to fill the accessory conchal hollow [2,3]. In those cases, extra conchal hollows of polyotia were maintained as cartilage-linked cheek defects. The cheek defects were filled using excised accessory cartilages. In our case, however, the patient only had a conchal hollow without a linked cheek defect and the hollow was small. Therefore, we decided to remove this hollow by collapsing the concha-resembling cartilage instead of filling the defect with excised cartilage. After the skin flap on the cartilaginous bowl was released, the cartilaginous hollow was collapsed using quilting sutures. In addition, we reconstructed a new tragus using the chondrocutaneous composite flap from the marginal portion of the excessive structure, as opposed to just trimming or following the previously mentioned technique, which excised all of the accessory components. By collapsing the unnecessary space and reconstructing a new tragus, we achieved an ideal distance from the new tragus to the auditory canal, which could not be attained by filling the hollow using cartilage graft. Because the shape and conditions of polyotia are very inconstant and the incidence of this anomaly is rare, it is difficult to establish a uniform surgical technique. We report our experience with polyotia and successful application of surgical technique: we utilized the shape of the excess auricle to build a new tragus and collapsed the concha-resembling hollow with quilting sutures. In addition, this is the first formal case report of polyotia in Korea. ::: ::: ::: ::: Fig. 1 ::: ::: A 9-year-old boy presented with left polyotia. He also had a right pre-auricular skin tag, bilateral prominent ears, and left-sided hemifacial microsomia. ::: ::: ::: ::: ::: ::: Fig. 2 ::: ::: After wedge resection, the remaining inferiorly-based chondrocutaneous flap was used for a new tragus. ::: ::: ::: ::: ::: ::: Fig. 3 ::: ::: After elevation of skin, the concha-resembling hollow was obliterated by quilting sutures. ::: ::: ::: ::: ::: ::: Fig. 4 ::: ::: Postoperative appearance of left auricle at the 6 months follow-up. ::: ::: ::: ::: ::: ::: Fig. 5 ::: ::: Photograph of the patient's right ear. Postoperative left ear shown in Fig. 4 have a symmetric appearance compared with right ear.


title: An approach to localize the retinal blood vessels using bit planes and centerline detection

abstract: The change in morphology, diameter, branching pattern or tortuosity of retinal blood vessels is an important indicator of various clinical disorders of the eye and the body. This paper reports an automated method for segmentation of blood vessels in retinal images. A unique combination of techniques for vessel centerlines detection and morphological bit plane slicing is presented to extract the blood vessel tree from the retinal images. The centerlines are extracted by using the first order derivative of a Gaussian filter in four orientations and then evaluation of derivative signs and average derivative values is performed. Mathematical morphology has emerged as a proficient technique for quantifying the blood vessels in the retina. The shape and orientation map of blood vessels is obtained by applying a multidirectional morphological top-hat operator with a linear structuring element followed by bit plane slicing of the vessel enhanced grayscale image. The centerlines are combined with these maps to obtain the segmented vessel tree. The methodology is tested on three publicly available databases DRIVE, STARE and MESSIDOR. The results demonstrate that the performance of the proposed algorithm is comparable with state of the art techniques in terms of accuracy, sensitivity and specificity.


title: Algorithm 659: Implementing Sobol's quasirandom sequence generator

abstract: We compare empirically accuracy and speed of low-discrepancy sequence generators of Sobol' and Faure. These generators are useful for multidimensional integration and global optimization. We discuss our implementation of the Sobol' generator.


title: Short-Term Effects of Rolling Massage on Energy Cost of Running and Power of the Lower Limbs.

abstract: Purpose:Self-myofascial release (SMFR) is a type of self-massage that is becoming popular among athletes. However, SMFR effects on running performance have not been investigated yet. The aim of the present study was to evaluate the effects of SMFR on cost of running (Cr). In addition, we evaluated the effects of SMFR on lower limbs muscle power. Methods:The measurement of Cr and lower limb muscle power during squat jump (SJ) and counter movement jump (CMJ) were performed before (PRE), immediately after (POST) and 3hours after (POST 3h) a SMFR protocol (experimental condition). In the “control condition” testing session, the same measurements were performed without undergoing the SMFR protocol. Experimental and control conditions were tested in a randomized order. Results:Cr at POST trended to increase as compared to PRE (+6.2±8.3%, p=0.052), while at POST 3h Cr was restored to PRE values (+0.28±9.5%, p=0.950). In the experimental condition, no significant “Time” effect was observed for maximal power exert...


Graphene/Polyaniline Aerogel with Superelasticity and High Capacitance as Highly Compression-Tolerant Supercapacitor Electrode


Facets of Nanotechnology as Seen in Food Processing, Packaging, and Preservation Industry


title: Corrosion protection of carbon fibre reinforced aluminium composite by diamondlike carbon coatings

abstract: AbstractCarbon fibre reinforced aluminium exhibits poor resistance against electrochemical corrosion in 3·5 wt-%NaCl solution. Diamondlike carbon (DLC) coatings provide properties which make them interesting materials for external corrosion protection on metal matrix composites (MMCs). The electrochemical corrosion behaviour of uncoated and DLC coated carbon fibre reinforced aluminium was tested in 3·5 wt-%NaCl solution. It has been found that the pitting potential is shifted significantly in the anodic direction and the corrosion current density is much lower due to the presence of the sealing DLC coating. Additionally, scratch tests and SEM studies were carried out in order to characterise the adhesion of the DLC films on the heterogeneous MMCs. Reliable corrosion protection is connected with sufficient coating durability under loading. In order to ensure sufficient loading capacity of the DLC coating under tribological conditions, wear tests were undertaken which revealed a considerable improvement in ...


title: Ensemble Video Object Cut in Highly Dynamic Scenes

abstract: We consider video object cut as an ensemble of frame-level background-foreground object classifiers which fuses information across frames and refine their segmentation results in a collaborative and iterative manner. Our approach addresses the challenging issues of modeling of background with dynamic textures and segmentation of foreground objects from cluttered scenes. We construct patch-level bag-of-words background models to effectively capture the background motion and texture dynamics. We propose a foreground salience graph (FSG) to characterize the similarity of an image patch to the bag-of-words background models in the temporal domain and to neighboring image patches in the spatial domain. We incorporate this similarity information into a graph-cut energy minimization framework for foreground object segmentation. The background-foreground classification results at neighboring frames are fused together to construct a foreground probability map to update the graph weights. The resulting object shapes at neighboring frames are also used as constraints to guide the energy minimization process during graph cut. Our extensive experimental results and performance comparisons over a diverse set of challenging videos with dynamic scenes, including the new Change Detection Challenge Dataset, demonstrate that the proposed ensemble video object cut method outperforms various state-of-the-art algorithms.


title: Summing Up Hours of Any Type of Practice Versus Identifying Optimal Practice Activities

abstract: In their original article, Ericsson, Krampe, and Tesch-Romer (1993) reviewed the evidence concerning the conditions of optimal learning and found that individualized practice with training tasks (selected by a supervising teacher) with a clear performance goal and immediate informative feedback was associated with marked improvement. We found that this type of deliberate practice was prevalent when advanced musicians practice alone and found its accumulated duration related to attained music performance. In contrast, Macnamara, Moreau, and Hambrick’s (2016, this issue) main meta-analysis examines the use of the term deliberate practice to refer to a much broader and less defined concept including virtually any type of sport-specific activity, such as group activities, watching games on television, and even play and competitions. Summing up every hour of any type of practice during an individual’s career implies that the impact of all types of practice activity on performance is equal—an assumption that I ...


title: Review Special Issue: Cognition in Neuropsychiatric Disorders Computational psychiatry

abstract: Computational ideas pervade many areas of science and have an integrative explanatory role in neuroscience and cognitive science. However, computational depictions of cognitive function have had surprisingly little impact on the way we assess mental illness because diseases of the mind have not been systematically conceptualized in computational terms. Here, we outline goals and nascent efforts in the new field of computational psychiatry, which seeks to characterize mental dysfunction in terms of aberrant computations over multiple scales. We highlight early efforts in this area that employ reinforcement learning and game theoretic frameworks to elucidate decision-making in health and disease. Looking forwards, we emphasize a need for theory development and large-scale computational phenotyping in human subjects.


title: Performance Monitoring and Root Cause Analysis for Cloud-hosted Web Applications

abstract: In this paper, we describe Roots - a system for automatically identifying the "root cause" of performance anomalies in web applications deployed in Platform-as-a-Service (PaaS) clouds. Roots does not require application-level instrumentation. Instead, it tracks events within the PaaS cloud that are triggered by application requests using a combination of metadata injection and platform-level instrumentation. ::: ::: We describe the extensible architecture of Roots, a prototype implementation of the system, and a statistical methodology for performance anomaly detection and diagnosis. We evaluate the efficacy of Roots using a set of PaaS-hosted web applications, and detail the performance overhead and scalability of the implementation.


The 5G channel code contenders


title: Online cost-sensitive neural network classifiers for non-stationary and imbalanced data streams

abstract: Classifying non-stationary and imbalanced data streams encompasses two important challenges, namely concept drift and class imbalance. Concept drift is changes in the underlying function being learnt, and class imbalance is vast difference between the numbers of instances in different classes of data. Class imbalance is an obstacle for the efficiency of most classifiers. Previous methods for classifying non-stationary and imbalanced data streams mainly focus on batch solutions, in which the classification model is trained using a chunk of data. Here, we propose two online classifiers. The classifiers are one-layer NNs. In the proposed classifiers, class imbalance is handled with two separate cost-sensitive strategies. The first one incorporates a fixed and the second one an adaptive misclassification cost matrix. The proposed classifiers are evaluated on 3 synthetic and 8 real-world datasets. The results show statistically significant improvements in imbalanced data metrics.


title: Modeling pixel process with scale invariant local patterns for background subtraction in complex scenes

abstract: Background modeling plays an important role in video surveillance, yet in complex scenes it is still a challenging problem. Among many difficulties, problems caused by illumination variations and dynamic backgrounds are the key aspects. In this work, we develop an efficient background subtraction framework to tackle these problems. First, we propose a scale invariant local ternary pattern operator, and show that it is effective for handling illumination variations, especially for moving soft shadows. Second, we propose a pattern kernel density estimation technique to effectively model the probability distribution of local patterns in the pixel process, which utilizes only one single LBP-like pattern instead of histogram as feature. Third, we develop multimodal background models with the above techniques and a multiscale fusion scheme for handling complex dynamic backgrounds. Exhaustive experimental evaluations on complex scenes show that the proposed method is fast and effective, achieving more than 10% improvement in accuracy compared over existing state-of-the-art algorithms.


title: Perspectives on Media Literacy, Digital Literacy and Information Literacy

abstract: The cultural landscape poses different challenges for teachers. Beyond developing reading and writing skills, it is necessary to emerge in the digital culture and master the different codes of different languages. In this context, media education studies discuss the educational possibilities of interpreting, problematizing, and producing different kinds of texts in critical and creative ways, through the use of all means, languages and technologies available. Considering that media cannot be excluded from literacy programs, it is essential to reflect on the definition of â€œliterateâ€ today. These reflections examine the resignification of concepts like literacy, media literacy, digital literacy and information literacy.


title: Early differentiation between drawing and writing in Chinese children

abstract: Abstract Children under 3½ years of age or so are often thought to produce the same types of scribbles for writing and drawing. We tested this idea by asking Chinese 2- to 6-year-olds to write and draw four targets. In Study 1, Chinese adults judged the status of the productions as writings or drawings. The adults performed significantly above the level expected by chance even with the productions of 2- to 2½-year-olds. In Study 2, we examined specific characteristics of the children’s writings and drawings. Although the younger children’s scribbles bore little resemblance to the correct characters, they tended to be smaller, sparser, and more angular than their artwork, with less filling in. Differences were also found in paper use and implement use. Children did not appear to distinguish writing from drawing for their own names before they did so for other targets.


title: Competitive Targeted Advertising Over Networks

abstract: Recent advances in information technology have allowed firms to gather vast amounts of data regarding consumers’ preferences and the structure and intensity of their social interactions. This paper examines a game-theoretic model of competition between firms that can target their marketing budgets to individuals embedded in a social network. We provide a sharp characterization of the optimal targeted advertising strategies and highlight their dependence on the underlying social network structure. Furthermore, we provide conditions under which it is optimal for the firms to asymmetrically target a subset of the individuals and establish a lower bound on the ratio of their payoffs in these asymmetric equilibria. Finally, we find that at equilibrium firms invest inefficiently high in targeted advertising and the extent of the inefficiency is increasing in the centralities of the agents they target. Taken together, these findings shed light on the effect of the network structure on the outcome of marketing competition between the firms.


title: Case studies for software engineers

abstract: The topic of this full-day tutorial was the correct use and interpretation of case studies as an empirical research method. Using an equal blend of lecture and discussion, it gave attendees a foundation for conducting, reviewing, and reading case studies. There were lessons for software engineers as researchers who conduct and report case studies, reviewers who evaluate papers, and practitioners who are attempting to apply results from papers. The main resource for the course was the book Case Study Research: Design and Methods by Robert K. Yin. This text was supplemented with positive and negative examples from the literature.


title: Real-time tracking management system using GPS, GPRS and Google earth

abstract: Due to the high cost of fossil-based energy, several methods are proposed to reduce the usage of the energy in logistics and fleet management to be even more. GPS tracking system is a common approach to get vehicle location information in real-time for fleet planning. We proposed a GPS tracking system called Goo-Tracking that is composed of commodity hardware, open source software and an easy-to-manage user interface via a Web server with Google Map or via Google Earth software. The system includes a GPS/GPRS module to location acquisition and message transmission, MMC to temporary store location information, and an 8-bit AVR microcontroller. Our system prototype is shown and tested on a trip from Bangkok to Chonburi. It has shown great stability and also robust message transfer protocol that most of locations are accurately acquired and transmitted to the server in real-time.


title: Towards Online Spam Filteringin Social Networks

abstract: Online social networks (OSNs) are extremely popular among Internet users. Unfortunately, in the wrong hands, they are also effective tools for executing spam campaigns. In this paper, we present an online spam filtering system that can be deployed as a component of the OSN platform to inspect messages generated by users in real-time. We propose to reconstruct spam messages into campaigns for classification rather than examine them individually. Although campaign identification has been used for offline spam analysis, we apply this technique to aid the online spam detection problem with sufficiently low overhead. Accordingly, our system adopts a set of novel features that effectively distinguish spam campaigns. It drops messages classified as “spam” before they reach the intended recipients, thus protecting them from various kinds of fraud. We evaluate the system using 187 million wall posts collected from Facebook and 17 million tweets collected from Twitter. In different parameter settings, the true positive rate reaches 80.9% while the false positive rate reaches 0.19% in the best case. In addition, it stays accurate for more than 9 months after the initial training phase. Once deployed, it can constantly secure the OSNs without the need for frequent re-training. Finally, tested on a server machine with eight cores (Xeon E5520 2.2Ghz) and 16GB memory, the system achieves an average throughput of 1580 messages/sec and an average processing latency of 21.5ms on the Facebook dataset.


title: Advances in the application of information technology to sport performance

abstract: This paper overviews the diverse information technologies that are used to provide athletes with relevant feedback. Examples taken from various sports are used to illustrate selected applications of technology-based feedback. Several feedback systems are discussed, including vision, audition and proprioception. Each technology described here is based on the assumption that feedback would eventually enhance skill acquisition and sport performance and, as such, its usefulness to athletes and coaches in training is critically evaluated.


title: Incorporating loose-structured knowledge into conversation modeling via recall-gate LSTM

abstract: Modeling human conversations is the essence for building satisfying chat-bots with multi-turn dialog ability. Conversation modeling will notably benefit from domain knowledge since the relationships between sentences can be clarified due to semantic hints introduced by knowledge. In this paper, a deep neural network is proposed to incorporate background knowledge for conversation modeling. Through a specially designed Recall gate, domain knowledge can be transformed into the extra global memory of Long Short-Term Memory (LSTM), so as to enhance LSTM by cooperating with its local memory to capture the implicit semantic relevance between sentences within conversations. In addition, this paper introduces the loose structured domain knowledge base, which can be built with slight amount of manual work and easily adopted by the Recall gate. Our model is evaluated on the context-oriented response selecting task, and experimental results on both two datasets have shown that our approach is promising for modeling human conversations and building key components of automatic chatting systems.


title: A Comprehensive Survey of Brain Interface Technology Designs

abstract: In this work we present the first comprehensive survey of Brain Interface (BI) technology designs published prior to January 2006. Detailed results from this survey, which was based on the Brain Interface Design Framework proposed by Mason and Birch, are presented and discussed to address the following research questions: (1) which BI technologies are directly comparable, (2) what technology designs exist, (3) which application areas (users, activities and environments) have been targeted in these designs, (4) which design approaches have received little or no research and are possible opportunities for new technology, and (5) how well are designs reported. The results of this work demonstrate that meta-analysis of high-level BI design attributes is possible and informative. The survey also produced a valuable, historical cross-reference where BI technology designers can identify what types of technology have been proposed and by whom.


title: Psychoanalysis in a changing Cuba: A note from the field

abstract: In 2015 and 2016, the author and four other psychoanalysts from New York City visited Havana and met with the Psychoanalytic Association of Cuba (APDECU), a study group of the International Federation of Psychoanalytic Societies (IFPS). These meetings provided an important opportunity to learn about psychoanalysis in Cuba, a little known topic. The author discusses the APDECU’s history and its members’ interest in psychoanalysis, describes the trajectory of psychoanalysis since the Cuban Revolution of 1959, and observes how economic, political, and social change has affected this trajectory. Psychoanalytic private practice, as we know it in capitalist countries, ended with the revolution, and psychoanalytically-oriented clinicians are employed by state-run public health institutions. Cuba’s leaders have introduced unprecedented economic change since 2008, resulting in an increasing marketization and privatization of the economy, which they refer to as “updating” or “reforming” socialism. The author explores the impact that economic reform may have on the future development of psychoanalysis and on the professional identity of psychotherapists.


title: Analysis of brushless permanent magnet synchronous motors

abstract: A brief design review of permanent magnet synchronous motors has been presented. A procedure has been developed to predict the steady state and dynamic performances of a brushless permanent magnet synchronous motor. Finite element analysis has been combined with a lumped parameter circuit model in order to provide satisfactory engineering information. To this end, two coordinated steps are involved. One is to develop a unified lumped parameter circuit model for both steady state and dynamic analysis. The second step is to extract the individual lumped parameters from finite element solutions based on corresponding equivalent circuits, each with a pre-determined topology. The proposed techniques have been experimentally verified in a laboratory permanent magnet synchronous motor.


title: A Framework for Quality Assurance of Machine Learning Applications

abstract: Some machine learning applications are intended to learn properties of data sets where the correct answers are not already known to human users. It is challenging to test and debug such ML software, because there is no reliable test oracle. We describe a framework and collection of tools aimed to assist with this problem. We present our findings from using the testing framework with three implementations of an ML ranking algorithm (all of which had bugs).


title: Sentiment Classification of Movie Reviews Using Contextual Valence Shifters

abstract: We present two methods for determining the sentiment expressed by a movie review. The semantic orientation of a review can be positive, negative, or neutral. We examine the effect of valence shifters on classifying the reviews. We examine three types of valence shifters: negations, intensifiers, and diminishers. Negations are used to reverse the semantic polarity of a particular term, while intensifiers and diminishers are used to increase and decrease, respectively, the degree to which a term is positive or negative. The first method classifies reviews based on the number of positive and negative terms they contain. We use the General Inquirer to identify positive and negative terms, as well as negation terms, intensifiers, and diminishers. We also use positive and negative terms from other sources, including a dictionary of synonym differences and a very large Web corpus. To compute corpus-based semantic orientation values of terms, we use their association scores with a small group of positive and negative terms. We show that extending the term-counting method with contextual valence shifters improves the accuracy of the classification. The second method uses a Machine Learning algorithm, Support Vector Machines. We start with unigram features and then add bigrams that consist of a valence shifter and another word. The accuracy of classification is very high, and the valence shifter bigrams slightly improve it. The features that contribute to the high accuracy are the words in the lists of positive and negative terms. Previous work focused on either the term-counting method or the Machine Learning method. We show that combining the two methods achieves better results than either method alone.


title: Quality Ranking Algorithms for Knowledge Objects in Knowledge Management Systems

abstract: The emergence of web-based Knowledge Management Systems (KMS) has raised several concerns about the quality of Knowledge Objects (KO), which are the building blocks of knowledge expertise. Web-based KMSs offer large knowledge repositories with millions of resources added by experts or uploaded by users, and their content must be assessed for accuracy and relevance. To improve the efficiency of ranking KOs, two models are proposed for KO evaluation. Both models are based on user interactions and exploit user reputation as an important factor in quality estimation. For the purpose of evaluating the performance of the two proposed models, the algorithms were implemented and incorporated in a KMS. The results of the experiment indicate that the two models are comparable in accuracy, and that the algorithms can be integrated in the search engine of a KMS to estimate the quality of KOs and accordingly rank the results of user searches.


Does syntax help discourse segmentation? Not so much


title: Big-Five Personality Prediction Based on User Behaviors at Social Network Sites

abstract: Many customer services are already available at Social Network Sites (SNSs), including user recommendation and media interaction, to name a few. There are strong desires to provide online users more dedicated and personalized services that fit into individual's need, usually strongly depending on the inner personalities of the user. However, little has been done to conduct proper psychological analysis, crucial for explaining the user's outer behaviors from their inner personality. In this paper, we propose an approach that intends to facilitate this line of research by directly predicting the so called Big-Five Personality from user's SNS behaviors. Comparing to the conventional inventory-based psychological analysis, we demonstrate via experimental studies that users' personalities can be predicted with reasonable precision based on their online behaviors. Except for proving some former behavior-personality correlation results, our experiments show that extraversion is positively related to one's status republishing proportion and neuroticism is positively related to the proportion of one's angry blogs (blogs making people angry).


title: Graphene and boron nitride lateral heterostructures for atomically thin circuitry

abstract: This versatile and scalable ‘patterned regrowth’ fabrication process produces one-atom-thick sheets containing lateral junctions between electrically conductive graphene and insulating hexagonal boron nitride, paving the way for flexible, transparent electronic device films.


VIRAL ADVERTISING IN SOCIAL MEDIA : PARTICIPATION IN FACEBOOK GROUPS AND RESPONSES AMONG COLLEGE-AGED USERS


AUTOMATIC FINGERING SYSTEM (AFS)


title: Automatic selection of social media responses to news

abstract: Social media responses to news have increasingly gained in importance as they can enhance a consumer's news reading experience, promote information sharing and aid journalists in assessing their readership's response to a story. Given that the number of responses to an online news article may be huge, a common challenge is that of selecting only the most interesting responses for display. This paper addresses this challenge by casting message selection as an optimization problem. We define an objective function which jointly models the messages' utility scores and their entropy. We propose a near-optimal solution to the underlying optimization problem, which leverages the submodularity property of the objective function. Our solution first learns the utility of individual messages in isolation and then produces a diverse selection of interesting messages by maximizing the defined objective function. The intuitions behind our work are that an interesting selection of messages contains diverse, informative, opinionated and popular messages referring to the news article, written mostly by users that have authority on the topic. Our intuitions are embodied by a rich set of content, social and user features capturing the aforementioned aspects. We evaluate our approach through both human and automatic experiments, and demonstrate it outperforms the state of the art. Additionally, we perform an in-depth analysis of the annotated ``interesting'' responses, shedding light on the subjectivity around the selection process and the perception of interestingness.


title: Design and experimental verification of ridge gap waveguide in bed of nails for parallel-plate mode suppression

abstract: This study describes the design and experimental verification of the ridge gap waveguide, appearing in the gap between parallel metal plates. One of the plates has a texture in the form of a wave-guiding metal ridge surrounded by metal posts. The latter posts, referred to as a pin surface or bed of nails, are designed to give a stopband for the normal parallel-plate modes between 10 and 23 GHz. The hardware demonstrator includes two 90 bends and two capacitive coupled coaxial transitions enabling measurements with a vector network analyser (VNA). The measured results verify the large bandwidth and low losses of the quasi-transverse electromagnetic (TEM) mode propagating along the guiding ridge, and that 90 bends can be designed in the same way as for microstrip lines. The demonstrator is designed for use around 15 GHz. Still, the ridge gap waveguide is more advantageous for frequencies above 30 GHz, because it can be realised entirely from metal using milling or moulding, and there are no requirements for conducting joints between the two plates that otherwise is a problem when realising conventional hollow waveguides.


title: Perceived Organizational Support and Extra-Role Performance: Which Leads to Which?

abstract: L. Rhoades and R. Eisenberger (2002) reported the meta-analytic finding of a highly statistically significant relation between perceived organizational support (POS) and performance but concluded that the reviewed studies' methodology allowed no conclusion concerning the direction of the association. To investigate this issue, the authors assessed POS and extra-role performance 2 times, separated by a 3-year interval, among 199 employees of an electronic and appliance sales organization. Using a cross-lagged panel design, the authors found that POS was positively associated with a temporal change in extra-role performance. In contrast, the relation between extra-role performance and temporal change in POS was not statistically significant. These findings provide evidence that POS leads to extra-role performance.


title: Mammalian hibernation: cellular and molecular responses to depressed metabolism and low temperature

abstract: Mammalian hibernators undergo a remarkable phenotypic switch that involves profound changes in physiology, morphology, and behavior in response to periods of unfavorable environmental conditions. The ability to hibernate is found throughout the class Mammalia and appears to involve differential expression of genes common to all mammals, rather than the induction of novel gene products unique to the hibernating state. The hibernation season is characterized by extended bouts of torpor, during which minimal body temperature (Tb) can fall as low as -2.9 degrees C and metabolism can be reduced to 1% of euthermic rates. Many global biochemical and physiological processes exploit low temperatures to lower reaction rates but retain the ability to resume full activity upon rewarming. Other critical functions must continue at physiologically relevant levels during torpor and be precisely regulated even at Tb values near 0 degrees C. Research using new tools of molecular and cellular biology is beginning to reveal how hibernators survive repeated cycles of torpor and arousal during the hibernation season. Comprehensive approaches that exploit advances in genomic and proteomic technologies are needed to further define the differentially expressed genes that distinguish the summer euthermic from winter hibernating states. Detailed understanding of hibernation from the molecular to organismal levels should enable the translation of this information to the development of a variety of hypothermic and hypometabolic strategies to improve outcomes for human and animal health.