title: G3D: A gaming action dataset and real time action recognition evaluation framework

abstract: In this paper a novel evaluation framework for measuring the performance of real-time action recognition methods is presented. The evaluation framework will extend the time-based event detection metric to model multiple distinct action classes. The proposed metric provides more accurate indications of the performance of action recognition algorithms for games and other similar applications since it takes into consideration restrictions related to time and consecutive repetitions. Furthermore, a new dataset, G3D for real-time action recognition in gaming containing synchronised video, depth and skeleton data is provided. Our results indicate the need of an advanced metric especially designed for games and other similar real-time applications.


title: Fog radio access network system control scheme based on the embedded game model

abstract: As a promising paradigm for the 5G wireless communication system, a new evolution of the cloud radio access networks has been proposed, named as fog radio access networks (F-RANs). It is an advanced socially aware mobile networking architecture to provide a high spectral and energy efficiency while reducing backhaul burden. In particular, F-RANs take full advantages of social information and edge computing to efficiently alleviate the end-to-end latency. Based on the benefit of edge and cloud processing, key issues of F-RAN technique are radio resource allocation, caching, and service admission control. In this paper, we develop a novel F-RAN system control scheme based on the embedded game model. In the proposed scheme, spectrum allocation, cache placement, and service admission algorithms are jointly designed to maximize system efficiency. By developing a new embedded game methodology, our approach can capture the dynamics of F-RAN system and effectively compromises the centralized optimality with decentralized distribution intelligence for the faster and less complex decision making process. Through simulations, we compare the performance of our scheme to the existing studies and show how we can achieve a better performance under dynamic F-RAN system environments.


title: Intelligent Traffic Information System Based on Integration of Internet of Things and Agent Technology

abstract: In recent years popularity of private cars is getting urban traffic more and more crowded. As result traffic is becoming one of important problems in big cities in all over the world. Some of the traffic concerns are congestions and accidents which have caused a huge waste of time, property damage and environmental pollution. This research paper presents a novel intelligent traffic administration system, based on Internet of Things, which is featured by low cost, high scalability, high compatibility, easy to upgrade, to replace traditional traffic management system and the proposed system can improve road traffic tremendously. The Internet of Things is based on the Internet, network wireless sensing and detection technologies to realize the intelligent recognition on the tagged traffic object, tracking, monitoring, managing and processed automatically. The paper proposes an architecture that integrates internet of things with agent technology into a single platform where the agent technology handles effective communication and interfaces among a large number of heterogeneous highly distributed, and decentralized devices within the IoT. The architecture introduces the use of an active radio-frequency identification (RFID), wireless sensor technologies, object ad-hoc networking, and Internet-based information systems in which tagged traffic objects can be automatically represented, tracked, and queried over a network. This research presents an overview of a framework distributed traffic simulation model within NetLogo, an agent-based environment, for IoT traffic monitoring system using mobile agent technology.


title: Smart Mobile Healthcare System based on WBSN and 5G

abstract: The intelligent use of resources enabled by Internet of Things has raised the expectations of the technical as well as the consumer community. However there are many challenges in designing an IoT healthcare system, like security, authentication and exchanging data. The IoT healthcare system, is transforming everyday physical objects, medical devices that surround us into an embedded smart healthcare system. Public healthcare has been paid an increasing attention given the human population and medical expenses exponential growth. It is well known that an effective monitoring healthcare system can detect abnormalities of health conditions in time and make diagnoses according to sensing (WBSN) data. This paper propose a general architecture of a smart mobile IoT healthcare system for monitoring patients risk using a smart phone and 5G. The design of multi-protocol unit for universal connectivity. Web and mobile applications developed to meet the needs of patients, doctors, laboratories analysis and hospitals services. The system advises and alerts in real time the doctors/medical assistants about the changing of vital parameters of the patients, such as body temperature, pulse and Oxygen in Blood etc… and also about important changes on environmental parameters, in order to take preventive measures, save lives in critical care and emergency situations.


title: Word of Mouth: Rumor Dissemination in Social Networks

abstract: In this paper we examine the diffusion of competing rumors in social networks. Two players select a disjoint subset of nodes as initiators of the rumor propagation, seeking to maximize the number of persuaded nodes. We use concepts of game theory and location theory and model the selection of starting nodes for the rumors as a strategic game. We show that computing the optimal strategy for both the first and the second player is NP-complete, even in a most restricted model. Moreover we prove that determining an approximate solution for the first player is NP-complete as well. We analyze several heuristics and show that--counter-intuitively--being the first to decide is not always an advantage, namely there exist networks where the second player can convince more nodes than the first, regardless of the first player's decision.


title: The generalized stochastic preference choice model

abstract: We propose a new discrete choice model that generalizes the random utility model (RUM). We show that this model, called the \emph{Generalized Stochastic Preference} (GSP) model can explain several choice phenomena that can't be represented by a RUM. In particular, the model can easily (and also exactly) replicate some well known examples that are not RUM, as well as controlled choice experiments carried since 1980's that possess strong regularity violations. One such regularity violation is the \emph{decoy effect} in which the probability of choosing a product increases when a similar, but inferior product is added to the choice set. An appealing feature of the GSP is that it is non-parametric and therefore it has very high flexibility. The model has also a simple description and interpretation: it builds upon the well known representation of RUM as a stochastic preference, by allowing some additional consumer types to be non-rational.


title: Scalability and Performance of Web Applications in a Compute Cloud

abstract: Scalability and performance are key factors to the success of many enterprises involved in doing business on the web. Maintaining sufficient web resources just to meet performance during peak demands can be costly. Compute Cloud provides a powerful environment to allow dynamic scaling of web applications without the needs for user intervention. In this paper, we present a case study on the scalability and performance of web applications in a Cloud. We describe a novel dynamic scaling architecture with a front-end load-balancer for routing user requests to web applications deployed on virtual machine instances with the goal of maximizing resource utilization in instances while minimizing total number of instances. A scaling algorithm for automated provisioning of virtual resources based on threshold number of active user sessions will be introduced. The on-demand capability of the Cloud to rapidly provision and dynamically allocate resources to users will be discussed. Our work has demonstrated the compelling benefits of a Cloud which is capable of sustaining performance upon sudden load surges, delivering satisfactory IT resources on-demands to users, and maintaining high resource utilization, thus reducing infrastructure and management costs.


Reasoning with UML Class Diagrams : Relevance , Problems , and Solutions – a Survey


title: Prototype design of the plug-and-play desktop robotic system

abstract: This work presents a prototype of a desktop robotic system that enables plug-and-play function to Internet through a USB (universal serial bus) port of a personal computer (PC). Thus a new kind of PC peripheral is invented that has manipulability on desktop. The robotic system is realized on an internally distributed control structure that facilitates higher system reliability. An open control platform is considered. The PID algorithm is at present embedded for system control.


title: Genetic algorithms for credit scoring : Alternative fitness function performance comparison

abstract: Performance of three different fitness functions in credit scoring is evaluated.A novel fitness function based on subsets of client characteristics is proposed.The proposed fitness function shows better accuracy and sensitivity. Credit scoring methods have been widely investigated by researchers; recently, genetic algorithms have attracted particular attention. Many research papers comparing the performance of genetic algorithms and traditional scoring techniques have been published, but most do not provide enough detail about the fitness function used by the genetic algorithm-despite the fact that fitness function has a key influence on the model's overall performance. The aim of this paper is to evaluate the predictive performance of different fitness functions used by genetic algorithms in credit scoring. An alternative fitness function based on a variable bitmask is proposed, and its performance then compared with fitness functions based on a polynomial equation as well as an estimation of parameter range. The results suggest that the bitmask is superior to the two other methods in both accuracy and sensitivity. The Wilcoxon matched-pairs sign rank test and paired t-Test indicate these results are statistically significant.


title: Formalization and Rule-Based Transformation of EMF Ecore-Based Models

abstract: With models becoming a common-place in software and systems development, the support of automatic transformations of those models is an important asset to increase the efficiency and improve the quality of the development process. However, the definition of transformations still is quite complex. Several approaches --- from more imperative to more declarative styles --- have been introduced to support the definition of such transformations. Here, we show how a completely declarative relational style based on the interpretation of a model as single structured term can be used to provide a transformation mechanism allowing a simple, precise, and modular specification of transformations for the EMF Ecore platform, using a Prolog rule-based mechanism.


title: HELIX: automatic parallelization of irregular programs for chip multiprocessing

abstract: We describe and evaluate HELIX, a new technique for automatic loop parallelization that assigns successive iterations of a loop to separate threads. We show that the inter-thread communication costs forced by loop-carried data dependences can be mitigated by code optimization, by using an effective heuristic for selecting loops to parallelize, and by using helper threads to prefetch synchronization signals. We have implemented HELIX as part of an optimizing compiler framework that automatically selects and parallelizes loops from general sequential programs. The framework uses an analytical model of loop speedups, combined with profile data, to choose loops to parallelize. On a six-core Intel® Core i7-980X, HELIX achieves speedups averaging 2.25 x, with a maximum of 4.12x, for thirteen C benchmarks from SPEC CPU2000.


title: ClearPath: highly parallel collision avoidance for multi-agent simulation

abstract: We present a new local collision avoidance algorithm between multiple agents for real-time simulations. Our approach extends the notion of velocity obstacles from robotics and formulates the conditions for collision free navigation as a quadratic optimization problem. We use a discrete optimization method to efficiently compute the motion of each agent. This resulting algorithm can be parallelized by exploiting data-parallelism and thread-level parallelism. The overall approach, ClearPath, is general and can robustly handle dense scenarios with tens or hundreds of thousands of heterogeneous agents in a few milli-seconds. As compared to prior collision avoidance algorithms, we observe more than an order of magnitude performance improvement.


Proposed Hyperchaotic System for Image Encryption Asst


title: A 60-GHz Active Receiving Switched-Beam Antenna Array With Integrated Butler Matrix and GaAs Amplifiers

abstract: This paper presents for the first time a 60-GHz receiving switched-beam antenna on organic liquid crystal polymer (LCP) platform. A 4 × 1 quasi-Yagi array is incorporated with a 4 × 4 Butler matrix beamforming network and GaAs low-noise amplifiers on an LCP substrate. The active beam is controlled by GaAs single-pole-double-throw switches to access the four output states of the Butler matrix. The entire 4 × 1 active array is 1.4 cm × 1.75 cm and consumes 1.1 W of dc power. Successful comparisons of the measured and simulated results verify a working phased array with a return loss better than 10 dB across the frequency band of 56.7-63.7 GHz. A comparison of radiation patterns demonstrate beam steering of ±40° with a peak active gain of 27.5 dB. The combined antenna and receiver noise performance at 60 GHz exhibits an estimated merit G/T of -18.6 dB/K and noise figure of 5.4 dB.


title: Optical physical unclonable function

abstract: Many military and commercial systems require a unique digital identification for authentication, key derivation, and other purposes. Our approach uses an optical physical unclonable function (PUF) that can be implemented on printed circuit boards (PCB). Various environmental factors, such as physical stress, temperature, heat dissipation, and aging, affect the effectiveness of such a PUF. This paper will discuss our recent research in addressing these and other concerns by advancing in the areas of waveguide construction, system longevity, and PCB cooling. We will also discuss the enhanced capability of differentiating between intact and disturbed systems.


title: Factors influencing healthy eating habits among college students: an application of the Health Belief model

abstract: Poor eating habits are an important public health issue that has large health and economic implications. Many food preferences are established early, but because people make more and more independent eating decisions as they move through adolescence, the transition to independent living during the university days is an important event. To study the phenomenon of food selection, the heath belief model was applied to predict the likelihood of healthy eating among university students. Structural equation modeling was used to investigate the validity of the health belief model (HBM) among 194 students, followed by gender-based analyses. The data strongly supported the HBM. Social change campaign implications are discussed.


title: Latent semantic models for collaborative filtering

abstract: Collaborative filtering aims at learning predictive models of user preferences, interests or behavior from community data, that is, a database of available user preferences. In this article, we describe a new family of model-based algorithms designed for this task. These algorithms rely on a statistical modelling technique that introduces latent class variables in a mixture model setting to discover user communities and prototypical interest profiles. We investigate several variations to deal with discrete and continuous response variables as well as with different objective functions. The main advantages of this technique over standard memory-based methods are higher accuracy, constant time prediction, and an explicit and compact model representation. The latter can also be used to mine for user communitites. The experimental evaluation shows that substantial improvements in accucracy over existing methods and published results can be obtained.


title: Extending App Pre-Launch Service with Emotion Context: Poster Abstract

abstract: This paper reports a mobile application pre-launch scheme that is based on user's emotion. Smartphone application's usage and smartwatch's internal sensors are exploited to predict user's intension. User's emotion can be extracted from the PPG sensor in the smartwatch. In this paper, we extend previous App pre-launch service with user's emotion data. Applying machine learning algorithm to the training data, we can predict the application to be executed in near future. With our emotion context, we expect we can predict user's intension more accurately.


title: Cluster Frameworks for Efficient Scheduling and Resource Allocation in Data Center Networks: A Survey

abstract: Data centers are widely used for big data analytics, which often involve data-parallel jobs, including query and web service. Meanwhile, cluster frameworks are rapidly developed for data-intensive applications in data center networks (DCNs). To promote the performance of these frameworks, many efforts have been paid to improve scheduling strategies and resource allocation algorithms. With the deployment of geo-distributed data centers and data-intensive applications, the optimization in DCNs regains pervasive attention in both industry and academia. Many solutions, such as the coflow-aware scheduling and speculative execution, have been proposed to meet various requirements. Therefore, we present a solid starting ground and comprehensive overview in this area to help readers quickly understand state-of-the-art technologies and research progress. We observe that algorithms in cluster frameworks are implemented with different guidelines and can be classified according to scheduling granularity, controller management, and prior-knowledge requirement. In addition, mechanisms for conquering crucial challenges in DCNs are discussed, including providing low latency and minimizing job completion time. Moreover, we analyze desirable properties of fault tolerance and scalability to illuminate the design principles of distributed systems. We hope that this paper will shed light on this promising land and serve as a guide for further researches.


title: Orthogonal RNNs and Long-Memory Tasks

abstract: Although RNNs have been shown to be powerful tools for processing sequential data, finding architectures or optimization strategies that allow them to model very long term dependencies is still an active area of research. In this work, we carefully analyze two synthetic datasets originally outlined in (Hochreiter and Schmidhuber, 1997) which are used to evaluate the ability of RNNs to store information over many time steps. We explicitly construct RNN solutions to these problems, and using these constructions, illuminate both the problems themselves and the way in which RNNs store different types of information in their hidden states. These constructions furthermore explain the success of recent methods that specify unitary initializations or constraints on the transition matrices.


title: Non-contact Low Power EEG/ECG Electrode for High Density Wearable Biopotential Sensor Networks

abstract: A non-contact capacitive biopotential electrode with a common-mode noise suppression circuit is presented. The sensor network utilizes a single conductive sheet to establish a common body wide reference line, eliminating the need for an explicit signal ground connection. Each electrode senses the local biopotential with a differential gain of 46dB over a 1-100Hz bandwidth. Signals are digitized directly on board with a 16-bit ADC. The coin sized electrode consumes 285uA from a single 3.3V supply, and interfaces with a serial data bus for daisy-chain integration in body area sensor networks.


title: A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval

abstract: In this paper, we propose a new latent semantic model that incorporates a convolutional-pooling structure over word sequences to learn low-dimensional, semantic vector representations for search queries and Web documents. In order to capture the rich contextual structures in a query or a document, we start with each word within a temporal context window in a word sequence to directly capture contextual features at the word n-gram level. Next, the salient word n-gram features in the word sequence are discovered by the model and are then aggregated to form a sentence-level feature vector. Finally, a non-linear transformation is applied to extract high-level semantic information to generate a continuous vector representation for the full text string. The proposed convolutional latent semantic model (CLSM) is trained on clickthrough data and is evaluated on a Web document ranking task using a large-scale, real-world data set. Results show that the proposed model effectively captures salient semantic information in queries and documents for the task while significantly outperforming previous state-of-the-art semantic models.


title: A Formalization of Concepts for Generic Programming

abstract: Generic programming is a paradigm for systematic design and classification of software components for optimal reuse. It has been the guiding methodology behind the design of the C++ Standard Template Library and numerous other C++ libraries. Generic programming starts with algorithms, seeking to identify the minimal requirements on types necessary for correct and efficient execution of an algorithm or family of algorithms, leading to generic algorithms that can be applied to arguments of many different types. The term concept is used in this context to mean a set of abstractions (such as types) whose membership is determined by a set of requirements. Despite their importance, concepts are not explicitly represented in traditional programming languages. C++, in particular, lacks any means to express concepts, which has forced all concept development to be done outside the language and thus be unavailable to C++ compilers for static checking or optimization. Several other languages do have features than can approximate certain aspects of concepts, but what is missing is a uniform, language-independent definition of concepts. The definition of concepts in this paper provides a unified framework for realizing concept approximations in existing languages, and we present such descriptions for several popular languages used for generic programming.


title: Defining the execution semantics of stream processing engines

abstract: The ability to process large volumes of data on the fly, as soon as they become available, is a fundamental requirement in today’s information systems. Modern distributed stream processing engines (SPEs) address this requirement and provide low-latency and high-throughput data stream processing in cluster platforms, offering high-level programming interfaces that abstract from low-level details such as data distribution and hardware failures. The last decade saw a rapid increase in the number of available SPEs. However, each SPE defines its own processing model and standardized execution semantics have not emerged yet. This paper tackles this problem and analyzes the execution semantics of some widely adopted modern SPEs, namely Flink, Storm, Spark Streaming, Google Dataflow, and Azure Stream Analytics. We specifically target the notions of windowing and time, traditionally considered the key distinguishing factors that characterize the behavior of SPEs. We rely on the SECRET model, introduced in 2010 to analyze the windowing semantics for the SPEs available at that time. We show that SECRET models well some aspects of the behavior of modern SPEs, and we shed light on the evolution of SPEs after the introduction of SECRET by analyzing the elements that SECRET cannot fully capture. In this way, the paper contributes to the research in the area of stream processing by: (1) contrasting and comparing some widely used modern SPEs based on a formal model of their execution semantics; (2) discussing the evolution of SPEs since the introduction of the SECRET model; (3) suggesting promising research directions to direct further modeling efforts.


title: Online game addiction among adolescents: motivation and prevention factors

abstract: AbstractOnline game addiction has become a common phenomenon that affects many individuals and societies. In this study we rely on the functionalist perspective of human behavior and propose and te...


Document Fraud Detection with the help of Data Mining and Secure Substitution Method with Frequency Analysis


title: Re-conceptualizing Information System Success: The IS-Impact Measurement Model *

abstract: This paper re-conceptualizes 'information system success' as a formative, multidimensional index. A validated and widely accepted such index would facilitate cumulative research on the impacts of IS, while at the same time providing a benchmark for organizations to track their IS performance. The proposed IS-Impact measurement model represents the stream of net benefits from an Information System (IS), to date and anticipated, as perceived by all key-user-groups. Model measures are formulated to be robust, economical and simple, yielding results that are comparable across diverse systems and contexts, and from multiple user perspectives. The model includes 4 dimensions in two halves. The 'impact' half measures benefits to date, or Individual- and Organizational-Impact; the 'quality' half, uses System-Quality and Information-Quality as proxies for probable future impacts. Study findings evidence the necessity, additivity and completeness of these four dimensions. ::: The validation study involved three separate surveys, including exploratory and confirmatory phases preceded by an identification-survey. Content analysis of 485 qualitative 'impacts' cited by 137 respondents from across 27 Australian Government Agencies that implemented SAP Financials in the late 90's, identified salient dimensions and measures. The resultant a-priori model ('pool' of 37 measures) was operationalized in the subsequent specification-survey, yielding 310 responses across the same 27 agencies. The confirmation-survey, employing 27 validated measures from the specification-survey, was next conducted in a large university that had implemented ORACLE Financials. Confirmatory analysis of the 153 responses provides further strong evidence of model validity.


title: Multicenter study of nucleic acid amplification tests for detection of Chlamydia trachomatis and Neisseria gonorrhoeae in children being evaluated for sexual abuse.

abstract: BACKGROUND ::: Diagnosis of sexually transmitted infections in children suspected of sexual abuse is challenging due to the medico-legal implications of test results. Currently, the forensic standard for diagnosis of Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) infections is culture. In adults, nucleic acid amplification tests (NAATs) are superior to culture for CT, but these tests have been insufficiently evaluated in pediatric populations for forensic purposes. ::: ::: ::: METHODS ::: We evaluated the use of NAATs, using urine and genital swabs versus culture for diagnosis of CT and NG in children evaluated for sexual abuse in 4 US cities. Urine and a genital swab were collected for CT and NG NAATs along with routine cultures. NAAT positives were confirmed by PCR, using an alternate target. ::: ::: ::: RESULTS ::: Prevalence of infection among 485 female children were 2.7% for CT and 3.3% for NG by NAAT. The sensitivity of urine NAATs for CT and NG relative to vaginal culture was 100%. Eight participants with CT-positive and 4 with NG-positive NAATs had negative culture results (P = 0.018 for CT urine NAATs vs. culture). There were 24 of 485 (4.9%) female participants with a positive NAAT for CT or NG or both versus 16 of 485 (3.3%) with a positive culture for either, resulting in a 33% increase in children with a positive diagnosis. ::: ::: ::: CONCLUSIONS ::: These results suggest that NAATs on urine, with confirmation, are adequate for use as a new forensic standard for diagnosis of CT and NG in children suspected of sexual abuse. Urine NAATs offer a clear advantage over culture in sensitivity and are less invasive than swabs, reducing patient trauma and discomfort.


title: The biology and management of non-small cell lung cancer

abstract: Important advancements in the treatment of non-small cell lung cancer (NSCLC) have been achieved over the past two decades, increasing our understanding of the disease biology and mechanisms of tumour progression, and advancing early detection and multimodal care. The use of small molecule tyrosine kinase inhibitors and immunotherapy has led to unprecedented survival benefits in selected patients. However, the overall cure and survival rates for NSCLC remain low, particularly in metastatic disease. Therefore, continued research into new drugs and combination therapies is required to expand the clinical benefit to a broader patient population and to improve outcomes in NSCLC.


title: Map-reduce-merge: simplified relational data processing on large clusters

abstract: Map-Reduce is a programming model that enables easy development of scalable parallel applications to process a vast amount of data on large clusters of commodity machines. Through a simple interface with two functions, map and reduce, this model facilitates parallel implementation of many real-world tasks such as data processing jobs for search engines and machine learning. However,this model does not directly support processing multiple related heterogeneous datasets. While processing relational data is a common need, this limitation causes difficulties and/or inefficiency when Map-Reduce is applied on relational operations like joins. We improve Map-Reduce into a new model called Map-Reduce-Merge. It adds to Map-Reduce a Merge phase that can efficiently merge data already partitioned and sorted (or hashed) by map and reduce modules. We also demonstrate that this new model can express relational algebra operators as well as implement several join algorithms.


title: Leveraging Peer Centrality in the Designof Socially-Informed Peer-to-Peer Systems

abstract: Social applications mine user social graphs to improve performance in search, provide recommendations, allow resource sharing and increase data privacy. When such applications are implemented on a peer-to-peer (P2P) architecture, the social graph is distributed on the P2P system: the traversal of the social graph translates into a socially-informed routing in the peer-to-peer layer. In this work we introduce the model of a projection graph that is the result of decentralizing a social graph onto a peer-to-peer network. We focus on three social network metrics: degree, node betweenness and edge betweenness centrality and analytically formulate the relation between metrics in the social graph and in the projection graph. We demonstrate with an application scenario on real social networks the usability of the projection graph properties in designing social search applications and unstructured P2P overlays that exhibit improved performance and reduced overhead over baseline scenarios.


title: Pose space deformation: a unified approach to shape interpolation and skeleton-driven deformation

abstract: Pose space deformation generalizes and improves upon both shape interpolation and common skeleton-driven deformation techniques. This deformation approach proceeds from the observation that several types of deformation can be uniformly represented as mappings from a pose space , defined by either an underlying skeleton or a more abstract system of parameters, to displacements in the object local coordinate frames. Once this uniform representation is identified, previously disparate deformation types can be accomplished within a single unified approach. The advantages of this algorithm include improved expressive power and direct manipulation of the desired shapes yet the performance associated with traditional shape interpolation is achievable. Appropriate applications include animation of facial and body deformation for entertainment, telepresence, computer gaming, and other applications where direct sculpting of deformations is desired or where real-time synthesis of a deforming model is required.


title: A wide frequency range and adjustable duty cycle CMOS ring voltage controlled oscillator

abstract: This paper presents a voltage controlled ring oscillator (VCO) with wide tuning range and adjustable duty cycle. The circuit was designed using Rohm 0.18µm technology with 1.5V supply voltage. The simulation results show that the VCO oscillates from 300Hz up to 1.4GHz, while the duty cycle can be adjusted 20–80% independently from the oscillating frequency.


title: A ray tracing method for predicting path loss and delay spread in microcellular environments

abstract: The ability to predict path loss and delay spread is crucial for determining coverage and for planning interference reduction strategies in wireless radio system design. A promising theoretical method to accurately predict these channel characteristics in microcells is presented. The method uses modified geometrical optics to evaluate average path loss and delay spread. Quantitative building data, such as location, height, and electrical properties, are used to determine the individual multipath component amplitudes and delays. Preliminary verification of the technique against measured data has been conducted. The results illustrate that accurate path loss prediction is possible, with predicted values being within 5 dB of the measured values. As a result of this study, a computer program is being developed to automate the prediction process. The technical issues required for automated propagation prediction are presented. The ray optics model, computer ray tracing techniques, and building data requirements are also described. Comparisons between simulations and measurements are provided. >


title: Bayesian Online Changepoint Detection

abstract: Changepoints are abrupt variations in the generative parameters of a data sequence. Online detection of changepoints is useful in modelling and prediction of time series in application areas such as finance, biometrics, and robotics. While frequentist methods have yielded online filtering and prediction techniques, most Bayesian papers have focused on the retrospective segmentation problem. Here we examine the case where the model parameters before and after the changepoint are independent and we derive an online algorithm for exact inference of the most recent changepoint. We compute the probability distribution of the length of the current ``run,'' or time since the last changepoint, using a simple message-passing algorithm. Our implementation is highly modular so that the algorithm may be applied to a variety of types of data. We illustrate this modularity by demonstrating the algorithm on three different real-world data sets.


title: Increased corpus callosum size in musicians

abstract: Abstract Using in-vivo magnetic resonance morphometry it was investigated whether the midsagittal area of the corpus callosum (CC) would differ between 30 professional musicians and 30 age-, sex- and handedness-matched controls. Our analyses revealed that the anterior half of the CC was significantly larger in musicians. This difference was due to the larger anterior CC in the subgroup of musicians who had begun musical training before the age of 7. Since anatomic studies have provided evidence for a positive correlation between midsagittal callosal size and the number of fibers crossing through the CC, these data indicate a difference in interhemispheric communication and possibly in hemispheric (a)symmetry of sensorimotor areas. Our results are also compatible with plastic changes of components of the CC during a maturation period within the first decade of human life, similar to those observed in animal studies.


title: Mobile robot localization by tracking geometric beacons

abstract: The application of the extended Kaman filter to the problem of mobile robot navigation in a known environment is presented. An algorithm for, model-based localization that relies on the concept of a geometric beacon, a naturally occurring environment feature that can be reliably observed in successive sensor measurements and can be accurately described in terms of a concise geometric parameterization, is developed. The algorithm is based on an extended Kalman filter that utilizes matches between observed geometric beacons and an a priori map of beacon locations. Two implementations of this navigation algorithm, both of which use sonar, are described. The first implementation uses a simple vehicle with point kinematics equipped with a single rotating sonar. The second implementation uses a 'Robuter' mobile robot and six static sonar transducers to provide localization information while the vehicle moves at typical speeds of 30 cm/s. >


title: Analysis and Test of Diode Rectifier Solutions in Grid-Connected Wind Energy Conversion Systems Employing Modular Permanent-Magnet Synchronous Generators

abstract: This paper deals with the ac-dc interface conversion in grid-connected wind energy conversion systems based on modular permanent-magnet synchronous generators. In particular, some solutions based on diode rectifiers are extensively analyzed as for the waveforms, the efficiency, and the torque ripple, by considering several connections, which are allowed by the inherent modularity of the considered generators. Rectifier schemes with a high number of pulses can be easily realized without using special shifter transformers so that these solutions can be attractive for low- and medium-power applications.


title: A Dual Circularly Polarized Horn Antenna in Ku-Band Based on Chiral Metamaterial

abstract: A dual circularly polarized horn antenna, which employs a chiral metamaterial composed of two-layered periodic metallic arc structure, is presented. The whole antenna composite has functions of polarization transformation and band-pass filter. The designed antenna produces left-handed circularly polarized wave in the band from 12.4 GHz to 12.5 GHz, and realizes right-handed circularly polarized wave in the range of 14.2 GHz-14.4 GHz. Due to low loss characteristic of the chiral metamaterial, the measured gains are only reduced by about 0.6 dB at the above two operation frequencies, compared with single horn antenna. The axial ratios are 1.05 dB at 12.45 GHz and 0.95 dB at14.35 GHz.


Damage Awards: Jurors' Sense of Entitlement as a Predictor


title: Achieving Secure, Scalable, and Fine-grained Data Access Control in Cloud Computing

abstract: Cloud computing is an emerging computing paradigm in which resources of the computing infrastructure are provided as services over the Internet. As promising as it is, this paradigm also brings forth many new challenges for data security and access control when users outsource sensitive data for sharing on cloud servers, which are not within the same trusted domain as data owners. To keep sensitive user data confidential against untrusted servers, existing solutions usually apply cryptographic methods by disclosing data decryption keys only to authorized users. However, in doing so, these solutions inevitably introduce a heavy computation overhead on the data owner for key distribution and data management when fine-grained data access control is desired, and thus do not scale well. The problem of simultaneously achieving fine-grainedness, scalability, and data confidentiality of access control actually still remains unresolved. This paper addresses this challenging open issue by, on one hand, defining and enforcing access policies based on data attributes, and, on the other hand, allowing the data owner to delegate most of the computation tasks involved in fine-grained data access control to untrusted cloud servers without disclosing the underlying data contents. We achieve this goal by exploiting and uniquely combining techniques of attribute-based encryption (ABE), proxy re-encryption, and lazy re-encryption. Our proposed scheme also has salient properties of user access privilege confidentiality and user secret key accountability. Extensive analysis shows that our proposed scheme is highly efficient and provably secure under existing security models.


title: Effects of a short-term plyometric and resistance training program on fitness performance in boys age 12 to 15 years.

abstract: The purpose of this study was to compare the effects of a six week training period of combined plyometric and resistance training (PRT, n = 13) or resistance training alone (RT, n = 14) on fitness performance in boys (12-15 yr). The RT group performed static stretching exercises followed by resistance training whereas the PRT group performed plyometric exercises followed by the same resistance training program. The training duration per session for both groups was 90 min. At baseline and after training all participants were tested on the vertical jump, long jump, medicine ball toss, 9.1 m sprint, pro agility shuttle run and flexibility. The PRT group made significantly (p < 0.05) greater improvements than RT in long jump (10.8 cm vs. 2.2 cm), medicine ball toss (39.1 cm vs. 17.7 cm) and pro agility shuttle run time (-0.23 sec vs. -0.02 sec) following training. These findings suggest that the addition of plyometric training to a resistance training program may be more beneficial than resistance training and static stretching for enhancing selected measures of upper and lower body power in boys. Key pointsYouth conditioning programs which include different types of training and different loading schemes (e.g., high velocity plyometrics and resistance training) may be most effective for enhancing power performance.The effects of resistance training and plyometric training may be synergistic in children, with their combined effects being greater that each program performed alone.


title: Single-inductor four-switch non-inverting buck-boost dc-dc converter

abstract: A single-inductor four-switch non-inverting buck-boost dc-dc converter was designed. Compared to other conventional buck-boost typologies, the presented converter reduces the number of external passive components and chip/PCB area. The chip was implemented by using the TSMC 0.35um 3.3V/5V 2P4M polycide CMOS process. The input voltage range of the presented converter covers the full output voltage range of a Li-ion battery, its output voltage is 3.3V, and its maximal load current is 300 mA. The die area of the chip is 1.38 ×1.80 mm2, packed with a 40 S/B package.


Antibacterial Mechanisms of Metallic Nanoparticles : A Review


Priapism: Management with Corpus-Saphenous Shunt


title: CMOS three axis Hall sensor and joystick application

abstract: We present for the first time a three-axis CMOS Hall sensor based on integrated magnetic concentrator technology (IMC). The sensor measures the two in-plane magnetic field components Bx and By and the vertical component Bz and generates three output voltages proportional to them. The sensing core consists of four Hall elements arranged at 90/spl deg/ under the edge of a ferromagnetic disk (IMC), which is attached to the silicon die. By subtracting the Hall voltages of two opposite Hall elements a voltage proportional to the in-plane components is generated and by adding them a voltage proportional to the perpendicular component. In such a way a planar structure is used to implement a three-axis sensor device. The sensor further contains current sources, dynamic offset compensation and signal amplification and conditioning. The sensor aims for applications where two translatory or rotational movements have to be measured independently and precisely over a large temperature range. Examples are joysticks, car mirror sensors and other control devices.


title: Analysis of copy number variations in the sheep genome using 50K SNP BeadChip array

abstract: BackgroundIn recent years, genome-wide association studies have successfully uncovered single-nucleotide polymorphisms (SNPs) associated with complex traits such as diseases and quantitative phenotypes. These variations account for a small proportion of heritability. With the development of high throughput techniques, abundant submicroscopic structural variations have been found in organisms, of which the main variations are copy number variations (CNVs). Therefore, CNVs are increasingly recognized as an important and abundant source of genetic variation and phenotypic diversity.ResultsAnalyses of CNVs in the genomes of three sheep breeds were performed using the Ovine SNP50 BeadChip array. A total of 238 CNV regions (CNVRs) were identified, including 219 losses, 13 gains, and six with both events (losses and gains), which cover 60.35 Mb of the sheep genomic sequence and correspond to 2.27% of the autosomal genome sequence. The length of the CNVRs on autosomes range from 13.66 kb to 1.30 Mb with a mean size of 253.57 kb, and 75 CNVRs events had a frequency > 3%. Among these CNVRs, 47 CNVRs identified by the PennCNV overlapped with the CNVpartition. Functional analysis indicated that most genes in the CNVRs were significantly enriched for involvement in the environmental response. Furthermore, 10 CNVRs were selected for validation and 6 CNVRs were further experimentally confirmed by qPCR. In addition, there were 57 CNVRs overlapped in our new dataset and other published ruminant CNV studies.ConclusionsIn this study, we firstly constructed a sheep CNV map based on the Ovine SNP50 array. Our results demonstrated the differences of two detection tools and integration of multiple algorithms can enhance the detection of sheep genomic structure variations. Furthermore, our findings would be of help for understanding the sheep genome and provide preliminary foundation for carrying out the CNVs association studies with economically important phenotypes of sheep in the future.


title: Three-phase flyback/current-fed push-pull dc-dc converter with y-Δ connected transformer

abstract: This paper presents the three-phase dc-dc flyback/current-fed push-pull converter. The main features of the proposed converter are: flyback operation for a duty cycle less than 1/3; boost operation for a duty cycle range from 1/3 to 1; input and output ripple current cancellation for a duty cycle of 1/3 or 2/3; reduced inrush current in flyback mode operation; the voltage and current frequencies in the output filter are three times higher than the switching frequency; The Y-Δ connection allows a reduction of reactive power processed by transformer. Typical applications include charging stations for electric vehicles, installations fed by battery units, photovoltaic arrays or fuel cell systems. This paper gives theoretical analysis, simulation and experimental result data for a 2 kW; 150 Vdc input; output from 100 Vdc to 540 Vdc and, 40 kHz switching frequency.


title: Electric Flight - Potential and Limitations

abstract: During the last years, the development of electric propulsion systems is pushed strongly, most notably for automotive applications. For ground based transportation, the system mass is relevant, but of relatively low importance. The paper addresses the application of electric propulsion systems in aeronautics, where all systems are much more constrained by their mass. After comparing different propulsion system architectures the focus is cast on the energy storage problem and here especially on battery storage systems. Using first order principles the limitations and required technology developments are demonstrated by introducing battery powered electric propulsion systems to small and medium sized aircraft.


title: Global MPPT of grid connected solar PV inverter under partially shaded condition

abstract: The power generated by a solar photovoltaic (SPV) system depends upon the solar radiation level and cell temperature. A suitable maximum power point tracking (MPPT) algorithm is required to extract the maximum power from the SPV. However at a partial shading condition (PSC) the conventional MPPT techniques may lead to the operation at a local maximum power point (LMPP) instead of global maximum power point (GMPP). This paper used a GMPPT algorithm to extract maximum power from the solar PV system, and a DC/AC inverter is used to convert extracted solar DC power into AC power to inject into the grid. A three-leg intelligent power module (IPM) is used for implementation of both DC-DC converter and DC-AC inverter. A hysteresis current control (HCC) is used to track the inverter current. All the simulation studies have been done using PSCAD (4.5.1 ver.) simulation software. An experimental setup is developed which consists of IPM, capable of MPPT with DC/DC converter and generates AC output using DC/AC inverter. A solar array simulator (E4260A) is used for laboratory generation of the solar power. In this paper FPGA controller has been used to implement the GMPPT and HCC algorithms using LabVIEW platform.


Address extraction using hidden markov models.” For submission to


title: Improved nearest-neighbor parameters for predicting DNA duplex stability.

abstract: Thermodynamic data were determined from UV absorbance vs temperature profiles of 23 oligonucleotides. These data were combined with data from the literature for 21 sequences to derive improved parameters for the 10 Watson-Crick nearest neighbors. The observed trend in nearest-neighbor stabilities at 37 degrees C is GC > CG > GG > GA approximately GT approximately CA > CT > AA > AT > TA (where only the top strand is shown for each nearest neighbor). This trend suggests that both sequence and base composition are important determinants of DNA duplex stability. On average, the improved parameters predict deltaG degrees(37), deltaH degrees, deltaS degrees, and T(m) within 4%, 7%, 8%, and 2 degrees C, respectively. The parameters are optimized for the prediction of oligonucleotides dissolved in 1 M NaC1.


Bangla Digit Recognition Using Deep Learning


title: "Molecular" MR imaging at high fields.

abstract: Magnetic resonance imaging (MRI) and spectroscopy (MRS) have contributed considerably to clinical radiology, and a variety of MR techniques have been developed to evaluate pathological processes as well as normal tissue biology at the cellular and molecular level. However, in comparison to nuclear imaging, MRI has relatively poor sensitivity for detecting true molecular changes or for detecting the presence of targeted contrast agents, though these remain under active development. In recent years very high field (7T and above) MRI systems have been developed for human studies and these provide new opportunities and technical challenges for molecular imaging. We identify 5 types of intrinsic contrast mechanisms that do not require the use of exogenous agents but which can provide molecular and cellular information. We can derive information on tissue composition by (i) imaging different nuclei, especially sodium (ii) exploiting chemical shift differences as in MRS (iii) exploiting specific relaxation mechanisms (iv) exploiting tissue differences in the exchange rates of molecular species such as amides or hydroxyls and (v) differences in susceptibility. The increased signal strength at higher fields enables higher resolution images to be acquired, along with increased sensitivity to detecting subtle effects caused by molecular changes in tissues.


title: Transforming Graph Data for Statistical Relational Learning

abstract: Relational data representations have become an increasingly important topic due to the recent proliferation of network datasets (e.g., social, biological, information networks) and a corresponding increase in the application of Statistical Relational Learning (SRL) algorithms to these domains. In this article, we examine and categorize techniques for transforming graph-based relational data to improve SRL algorithms. In particular, appropriate transformations of the nodes, links, and/or features of the data can dramatically affect the capabilities and results of SRL algorithms. We introduce an intuitive taxonomy for data representation transformations in relational domains that incorporates link transformation and node transformation as symmetric representation tasks. More specifically, the transformation tasks for both nodes and links include (i) predicting their existence, (ii) predicting their label or type, (iii) estimating their weight or importance, and (iv) systematically constructing their relevant features. We motivate our taxonomy through detailed examples and use it to survey competing approaches for each of these tasks. We also discuss general conditions for transforming links, nodes, and features. Finally, we highlight challenges that remain to be addressed.


title: Blepharokeratoconjunctivitis in childhood: corneal involvement and visual outcome

abstract: PURPOSE ::: The main objective of this study is to describe the prevalence, degree and risk of corneal involvement, and visual impact in a pediatric population with blepharokeratoconjunctivitis (BKC). ::: ::: ::: METHODS ::: Retrospective, observational, case-control study. Clinical records of patients ≤16 years old with BKC seen between 2006 and 2012 were reviewed. The prevalence and relative risk of corneal involvement was evaluated between patients with and without corneal affection through a univariate and multivariate analysis with logistic regression. Visual acuity at presentation and at last follow-up visit was also analyzed. ::: ::: ::: RESULTS ::: One hundred and fourteen children with BKC, with a male-to-female ratio of 1 : 1 and a mean age at diagnosis of 9.13 years. The mean follow-up time was 26.4 (±25) months. Corneal involvement was present in 39.5% of patients, varying from superficial punctate keratitis to perforation. Corneal changes were not seen in children under 4 years old. The risk of corneal affection was greater in patients with photophobia, hordeolum, female gender and asymmetric disease (OR of 2.69, 11.6, 2.35 and 2.77, respectively). The mean best-corrected visual acuity at presentation was 0.20 (corneal affected group), compared to 0.11 (unaffected group; P=0.02). ::: ::: ::: CONCLUSIONS ::: Our study showed an older age at time of diagnosis and a worse visual outcome in patients with BKC and corneal disease compared with previous reports. Early diagnosis and detection of risk factors for corneal involvement, as well as adequate treatment, is mandatory to prevent serious long-term visual repercussions in children with BKC.


title: Carcinoid tumors of the gastrointestinal tract

abstract: SummaryFifty-four cases of carcinoid tumors of the gastrointestinal tract are reported. Thirty-two involved the appendix; nine, the small intestine; three, the ileocecal area; four, the colon; four, the rectum, and one each, the stomach and duodenum. In one patient, the site of origin was not established.The historic backgrounds, pathologic descriptions, incidences, ages of the patients, and locations of the lesions are presented.Methods for diagnosis and treatment, according to the location of the primary lesion, are proposed, and special emphasis is directed to resection of all regional metastases.Reference is made to the carcinoid syndrome, which occurs in the presence of widespread metastasis and involvement of the liver and circulating serotonin.


title: Data Linkage in Smart Internet of Things Systems: A Consideration from a Privacy Perspective

abstract: Smart IoT systems can integrate knowledge from the surrounding environment, and they are critical components of the next-generation Internet. Such systems usually collect data from various dimensions via numerous devices, and the collected data are usually linkable. This means that they can be combined to derive abundant valuable knowledge. However, the collected data may also be accessed by malicious third parties to reveal sensitive information. In this article, we investigate the privacy issues of linkable data in smart IoT systems, which have not been thoroughly studied in previous works. We first discuss the available data sources in smart IoT systems and their linkage. Then we introduce some third parties who may access and utilize the linkable data. The potential threats are comprehensively elaborated for both individuals and crowds in smart IoT systems. Finally, we highlight some challenges and open problems for privacy preservation of linkable data in smart IoT systems.


Deep Domain Adaptation in Action Space


title: Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Point Clouds

abstract: The ability to segment unknown objects in depth images has potential to enhance robot skills in grasping and object tracking. Recent computer vision research has demonstrated that Mask R-CNN can be trained to segment specific categories of objects in RGB images when massive hand labeled datasets are available. As generating these datasets is time-consuming, we instead train with synthetic depth images. Many robots now use depth sensors, and recent results suggest training on synthetic depth data can generalize well to the real world. We present a method for automated dataset generation and rapidly generate a training dataset of 50k depth images and 320k object masks synthetically using simulated scenes of 3D CAD models. We train a variant of Mask R-CNN on the generated dataset to perform category-agnostic instance segmentation without hand-labeled data. We evaluate the trained network, which we refer to as Synthetic Depth (SD) Mask R-CNN, on a set of real, high-resolution images of challenging, densely cluttered bins containing objects with highly-varied geometry. SD Mask R-CNN outperforms point cloud clustering baselines by an absolute 15% in Average Precision and 20% in Average Recall, and achieves performance levels similar to a Mask RCNN trained on a massive, hand-labeled RGB dataset and fine-tuned on real images from the experimental setup. The network also generalizes well to a lower-resolution depth sensor. We deploy the model in an instance-specific grasping pipeline to demonstrate its usefulness in a robotics application. Code, the synthetic training dataset, and supplementary material are available at https://bit.ly/2letCuE .


title: Analysis and Optimization of Deep Counterfactual Value Networks

abstract: Recently a strong poker-playing algorithm called DeepStack was published, which is able to find an approximate Nash equilibrium during gameplay by using heuristic values of future states predicted by deep neural networks. This paper analyzes new ways of encoding the inputs and outputs of DeepStack’s deep counterfactual value networks based on traditional abstraction techniques, as well as an unabstracted encoding, which was able to increase the network’s accuracy.


title: Passive Attacks Against Searchable Encryption

abstract: Searchable encryption (SE) provides a privacy-preserving mechanism for data users to search over encrypted data stored on a remote server. Researchers have designed a number of SE schemes with high efficiency yet allowing some degree of leakage profile to the remote server. The leakage, however, should be further measured to allow us to understand what types of attacks an SE scheme would encounter. This paper considers passive attacks that make inferences based on prior knowledge and observations on queries issued by users. This is in contrast to previously studied active attacks that adaptively inject files and queries. We consider several assumptions on the types or prior knowledge the attacker possessed and propose a few passive attacks. In particular, under the “full-fledged” assumption, the keyword recovery rate of our attack is optimal in the sense that it is equal to the theoretical upper bound. We further present several enhanced attacks under other weaker assumptions on various levels of the prior knowledge that the attacker can obtain, in which the keyword recovery rates are optimal or nearly optimal (i.e., approaching the theoretical upper bound). In addition, we provide extensive experiments to show the “power” of our passive attacks. This paper highlights the importance of minimizing the prior knowledge of a server and the leakage of search queries. It also shows that simply distorting the frequency of the keyword to hold against our passive attacks may not scale well.


title: A 28 GHz transceiver chip for 5G beamforming data links in SiGe BiCMOS

abstract: This paper presents a 28–32 GHz transceiver chip architecture in SiGe BiCMOS to meet the requirements of 5G phased-array communication links. An asymmetric design is employed for the transmit and receive paths to deliver an output P1dB of 8 dBm in TX mode and to achieve an input P1dB of 0 dBm in RX mode. The chip can operate with an external LO at 10–16 GHz and 20–28 GHz with the use of an on-chip doubler option. All switches on RF, LO and IF paths are implemented using SiGe HBTs for low loss and wideband operation. An on-chip elliptic filter is implemented in the TX path to reject the upconverted image and LO leakage to meet spectral mask requirements. The chip was tested in the TX mode with an 802.11ad MCS-10 waveform and achieves 3.9% EVM at 3 Gbps physical rate.


title: Analytical Calculation of the Magnetic Field Created by Permanent-Magnet Rings

abstract: We present analytical formulations, based on a coulombian approach, of the magnetic field created by permanent-magnet rings. For axially magnetized magnets, we establish the expressions for the three components. We also give the analytical 3-D formulation of the created magnetic field for radially magnetized rings. We compare the results determined by a 2-D analytical approximation to those for the 3-D analytical formulation, in order to determine the range of validity of the 2-D approximation.


title: Continuous Integration and Its Tools

abstract: Continuous integration has been around for a while now, but the habits it suggests are far from common practice. Automated builds, a thorough test suite, and committing to the mainline branch every day sound simple at first, but they require a responsible team to implement and constant care. What starts with improved tooling can be a catalyst for long-lasting change in your company's shipping culture. Continuous integration is more than a set of practices, it's a mindset that has one thing in mind: increasing customer value. The Web extra at http://youtu.be/tDl_cHfrJZo is an audio podcast of the Tools of the Trade column discusses how continuous integration is more than a set of practices, it's a mindset that has one thing in mind: increasing customer value.


title: Learning the variance of the reward-to-go

abstract: In Markov decision processes (MDPs), the variance of the reward-to-go is a natural measure of uncertainty about the long term performance of a policy, and is important in domains such as finance, resource allocation, and process control. Currently however, there is no tractable procedure for calculating it in large scale MDPs. This is in contrast to the case of the expected reward-to-go, also known as the value function, for which effective simulation-based algorithms are known, and have been used successfully in various domains. In this paper we extend temporal difference (TD) learning algorithms to estimating the variance of the reward-to-go for a fixed policy. We propose variants of both TD(0) and LSTD(λ) with linear function approximation, prove their convergence, and demonstrate their utility in an option pricing problem. Our results show a dramatic improvement in terms of sample efficiency over standard Monte-Carlo methods, which are currently the state-of-the-art.


title: Mobility management enhancements for 5G low latency services

abstract: The 5G vision is to create a network that outperforms the current mobile networks in terms of flexibility, performance and use cases. This raises the requirements of the network to a totally new level. In order to achieve the latency goals the related applications and network functions need to be placed into the network edge. Full mobility support requires also enhancements to the current mobility management procedures. These include a gateway selection algorithm that is topology aware, handover procedures that are able to switch the user plane as quickly as possible and a seamless gateway relocation procedure. The low latency applications should also be able to manage the state between the application instances in different edge nodes. In this paper we introduce a 5G low latency network slice that offers 5G low latency services from the closest network edge node. Our prototype implementation verifies that this can be achieved by re-evaluating the optimality of the mobility anchor during each handover and executing a gateway relocation procedure when needed.


title: Effects of Inhalation of Essential Oil of Citrus aurantium L. var. amara on Menopausal Symptoms, Stress, and Estrogen in Postmenopausal Women: A Randomized Controlled Trial

abstract: This study aimed to investigate the effects of inhalation of the essential oil of Citrus aurantium L. var. amara (neroli oil) on menopausal symptoms, stress, and estrogen in postmenopausal women. Sixty-three healthy postmenopausal women were randomized to inhale 0.1% or 0.5% neroli oil or almond oil (control) for 5 minutes twice daily for 5 days. Menopause-related symptoms, as determined by the Menopause-Specific Quality of Life Questionnaire (MENQOL); sexual desire visual analog scale (VAS); serum cortisol and estrogen concentrations, blood pressure, pulse, and stress VAS, were measured before and after inhalation. Compared with the control group, the two neroli oil groups showed significant improvements in the physical domain score of the MENQOL and in sexual desire. Systolic blood pressure was significantly lower in the group inhaling 0.5% neroli oil than in the control group. Compared with the control group, the two neroli oil groups showed significantly lower diastolic blood pressure and tended to improve pulse rate and serum cortisol and estrogen concentrations. These findings indicate that inhalation of neroli oil helps relieve menopausal symptoms, increase sexual desire, and reduce blood pressure in postmenopausal women. Neroli oil may have potential as an effective intervention to reduce stress and improve the endocrine system.


title: Why do you play World of Warcraft? An in-depth exploration of self-reported motivations to play online and in-game behaviours in the virtual world of Azeroth

abstract: Massively multiplayer online role-playing games (MMORPGs) are video games in which players create an avatar that evolves and interacts with other avatars in a persistent virtual world. Motivations to play MMORPGs are heterogeneous (e.g. achievement, socialisation, immersion in virtual worlds). This study investigates in detail the relationships between self-reported motives and actual in-game behaviours. We recruited a sample of 690 World of Warcraft players (the most popular MMORPG) who agreed to have their avatar monitored for 8months. Participants completed an initial online survey about their motives to play. Their actual in-game behaviours were measured through the game's official database (the Armory website). Results showed specific associations between motives and in-game behaviours. Moreover, longitudinal analyses revealed that teamwork- and competition-oriented motives are the most accurate predictors of fast progression in the game. In addition, although specific associations exist between problematic use and certain motives (e.g. advancement, escapism), longitudinal analyses showed that high involvement in the game is not necessarily associated with a negative impact upon daily living.


title: A simulation framework for real-time assessment of dynamic ride sharing demand responsive transportation models

abstract: Sustainable mobility is not merely a technological question. While automotive technology will be part of the solution, it will also be combined with a paradigm shift from car ownership to vehicle usage, which itself will be facilitated by the application of Information and Communication Technologies that make it possible for a user to have access to a mobility service from anywhere to anywhere at any time. Multiple Passenger Ridesharing and its variants appear to be one of the promising mobility concepts that are emerging. However, in implementing these systems while accounting specifically for time dependencies and time windows that reflect user needs, challenges are raised in terms of real-time fleet dispatching and dynamic route calculation. This paper analyzes and evaluates both aspects through microscopic simulation emulating real-time traffic information while also interacting with a Decision Support System. The paper presents and discusses the obtained results for a Barcelona model.


title: Human–Robot Interaction: Kinematics and Muscle Activity Inside a Powered Compliant Knee Exoskeleton

abstract: Until today it is not entirely clear how humans interact with automated gait rehabilitation devices and how we can, based on that interaction, maximize the effectiveness of these exoskeletons. The goal of this study was to gain knowledge on the human-robot interaction, in terms of kinematics and muscle activity, between a healthy human motor system and a powered knee exoskeleton (i.e., KNEXO). Therefore, temporal and spatial gait parameters, human joint kinematics, exoskeleton kinetics and muscle activity during four different walking trials in 10 healthy male subjects were studied. Healthy subjects can walk with KNEXO in patient-in-charge mode with some slight constraints in kinematics and muscle activity primarily due to inertia of the device. Yet, during robot-in-charge walking the muscular constraints are reversed by adding positive power to the leg swing, compensating in part this inertia. Next to that, KNEXO accurately records and replays the right knee kinematics meaning that subject-specific trajectories can be implemented as a target trajectory during assisted walking. No significant differences in the human response to the interaction with KNEXO in low and high compliant assistance could be pointed. This is in contradiction with our hypothesis that muscle activity would decrease with increasing assistance. It seems that the differences between the parameter settings of low and high compliant control might not be sufficient to observe clear effects in healthy subjects. Moreover, we should take into account that KNEXO is a unilateral, 1 DOF device. Language: en


title: Understanding U.S. regional linguistic variation with Twitter data analysis

abstract: We analyze a Big Data set of geo-tagged tweets for a year (Oct. 2013–Oct. 2014) to understand the regional linguistic variation in the U.S. Prior work on regional linguistic variations usually took a long time to collect data and focused on either rural or urban areas. Geo-tagged Twitter data offers an unprecedented database with rich linguistic representation of fine spatiotemporal resolution and continuity. From the one-year Twitter corpus, we extract lexical characteristics for twitter users by summarizing the frequencies of a set of lexical alternations that each user has used. We spatially aggregate and smooth each lexical characteristic to derive county-based linguistic variables, from which orthogonal dimensions are extracted using the principal component analysis (PCA). Finally a regionalization method is used to discover hierarchical dialect regions using the PCA components. The regionalization results reveal interesting linguistic regional variations in the U.S. The discovered regions not only confirm past research findings in the literature but also provide new insights and a more detailed understanding of very recent linguistic patterns in the U.S.


Improving semantic topic clustering for search queries with word co-occurrence and bigraph co-clustering


title: Particle Filter-based Fingertip Tracking with Circular Hough Transform Features

abstract: In this work, we present a fingertip tracking framework which allows observation of finger movements in task space. By applying a multi-scale edge extraction technique, an edge map is generated in which low contrast edges are preserved while noise is suppressed. Based on circular image features, determined from the map using Hough transform, the fingertips are accurately tracked by combining a particle filter and a subsequent mean-shift procedure. To increase the robustness of the proposed method, dynamical motion models are trained for the prediction of the finger displacements. Experiments were conducted on various image sequences from which statements on the performance of the framework can be derived.


title: Introducing the Check-Off Password System (COPS): An Advancement in User Authentication Methods and Information Security

abstract: The objective of information system security management is information assurance: to maintain confidentiality (privacy), integrity, and availability of information resources for authorized organizational end users. User authentication is a foundation procedure in the overall pursuit of these objectives, and password procedures have historically been the primary method of user authentication. There is an inverse relationship between the level of security provided by a password procedure and ease of recall for users. The longer the password and the more variability in its characters, the higher the level of security provided by such a password (because they are more difficult to violate or “crack”). However, such passwords tend to be more difficult for end users to remember, particularly when the password does not spell a recognizable word (or includes non-alphanumeric characters such as punctuation marks or other symbols). Conversely, when end users select their own more easily remembered passwords, the passwords may also be easier to crack. This study presents a new approach to entering passwords, which combines a high level of security with easy recall for the end user. The Check-Off Password System (COPS) is more secure than self-selected passwords as well as high-protection, assigned-password procedures. The present study investigates trade-offs between using COPS and three traditional password procedures, and provides a preliminary assessment of the efficacy of COPS. The study offers evidence that COPS is a valid alternative to current user authentication systems. End users perceive all password procedures tested to have equal usefulness, but the perceived ease of use of COPS passwords equals that of an established highsecurity password, and the new interface does not negatively affect user performance compared with that high-security password. Further research will be conducted to investigate long-term benefits.


title: Trajectory privacy in location-based services and data publication

abstract: The ubiquity of mobile devices with global positioning functionality (e.g., GPS and AGPS) and Internet connectivity (e.g., 3G andWi-Fi) has resulted in widespread development of location-based services (LBS). Typical examples of LBS include local business search, e-marketing, social networking, and automotive traffic monitoring. Although LBS provide valuable services for mobile users, revealing their private locations to potentially untrusted LBS service providers pose privacy concerns. In general, there are two types of LBS, namely, snapshot and continuous LBS. For snapshot LBS, a mobile user only needs to report its current location to a service provider once to get its desired information. On the other hand, a mobile user has to report its location to a service provider in a periodic or on-demand manner to obtain its desired continuous LBS. Protecting user location privacy for continuous LBS is more challenging than snapshot LBS because adversaries may use the spatial and temporal correlations in the user's location samples to infer the user's location information with higher certainty. Such user location trajectories are also very important for many applications, e.g., business analysis, city planning, and intelligent transportation. However, publishing such location trajectories to the public or a third party for data analysis could pose serious privacy concerns. Privacy protection in continuous LBS and trajectory data publication has increasingly drawn attention from the research community and industry. In this survey, we give an overview of the state-of-the-art privacy-preserving techniques in these two problems.


title: Towards geographical referencing of monocular SLAM reconstruction using 3D city models: Application to real-time accurate vision-based localization

abstract: In the past few years, lots of works were achieved on Simultaneous Localization and Mapping (SLAM). It is now possible to follow in real time the trajectory of a moving camera in an unknown environment. However, current SLAM methods are still prone to drift errors, which prevent their use in large-scale applications. In this paper, we propose a solution to reduce those errors a posteriori. Our solution is based on a postprocessing algorithm that exploits additional geometric constraints, relative to the environment, to correct both the reconstructed geometry and the camera trajectory. These geometric constraints are obtained through a coarse 3D modelisation of the environment, similar to those provided by GIS database. First, we propose an original articulated transformation model in order to roughly align the SLAM reconstruction with this 3D model through a non-rigid ICP step. Then, to refine the reconstruction, we introduce a new bundle adjustment cost function that includes, in a single term, the usual 3D point/ID observation consistency constraint as well as the geometric constraints provided by the 3D model. Results on large-scale synthetic and real sequences show that our method successfully improves SLAM reconstructions. Besides, experiments prove that the resulting reconstruction is accurate enough to be directly used for global relocalization applications.


title: Super-Enhancers in the Control of Cell Identity and Disease

abstract: SUMMARY Super-enhancers are large clusters of transcriptional enhancers that drive expression of genes that define cell identity. Improved understanding of the roles that super-enhancers play in biology would be afforded by knowing the constellation of factors that constitute these domains and by identifying super-enhancers across the spectrum of human cell types. We describe here the population of transcription factors, cofactors, chromatin regulators, and transcription apparatus occupying super-enhancers in embryonic stem cells and evidence that super-enhancers are highly transcribed. We produce a catalog of super-enhancers in a broad range of human cell types and find that super-enhancers associate with genes that control and define the biology of these cells. Interestingly, disease-associated variation is especially enriched inthe super-enhancersof disease-relevantcelltypes.Furthermore,wefindthat cancer cells generate super-enhancers at oncogenes and other genes important in tumor pathogenesis. Thus, super-enhancers play key roles in human cell identity in health and in disease.


title: Nonrigid 2D/3D Registration of Coronary Artery Models With Live Fluoroscopy for Guidance of Cardiac Interventions

abstract: A 2D/3D nonrigid registration method is proposed that brings a 3D centerline model of the coronary arteries into correspondence with bi-plane fluoroscopic angiograms. The registered model is overlaid on top of interventional angiograms to provide surgical assistance during image-guided chronic total occlusion procedures, thereby reducing the uncertainty inherent in 2D interventional images. The proposed methodology is divided into two parts: global structural alignment and local nonrigid registration. In both cases, vessel centerlines are automatically extracted from the 2D fluoroscopic images, and serve as the basis for the alignment and registration algorithms. In the first part, an energy minimization method is used to estimate a global affine transformation that aligns the centerline with the angiograms. The performance of nine general purpose optimizers has been assessed for this problem, and detailed results are presented. In the second part, a fully nonrigid registration method is proposed and used to compensate for any local shape discrepancy. This method is based on a variational framework, and uses a simultaneous matching and reconstruction process to compute a nonrigid registration. With a typical run time of less than 3 s, the algorithms are fast enough for interactive applications. Experiments on five different subjects are presented and show promising results.


title: Layered Object Models for Image Segmentation

abstract: We formulate a layered model for object detection and image segmentation. We describe a generative probabilistic model that composites the output of a bank of object detectors in order to define shape masks and explain the appearance, depth ordering, and labels of all pixels in an image. Notably, our system estimates both class labels and object instance labels. Building on previous benchmark criteria for object detection and image segmentation, we define a novel score that evaluates both class and instance segmentation. We evaluate our system on the PASCAL 2009 and 2010 segmentation challenge data sets and show good test results with state-of-the-art performance in several categories, including segmenting humans.


title: Geometric Folding Algorithms: Linkages, Origami, Polyhedra

abstract: How can linkages, pieces of paper, and polyhedra be folded? The authors present hundreds of results and over 60 unsolved 'open problems' in this comprehensive look at the mathematics of folding, with an emphasis on algorithmic or computational aspects. Folding and unfolding problems have been implicit since Albrecht Drer in the early 1500s, but have only recently been studied in the mathematical literature. Over the past decade, there has been a surge of interest in these problems, with applications ranging from robotics to protein folding. A proof shows that it is possible to design a series of jointed bars moving only in a flat plane that can sign a name or trace any other algebraic curve. One remarkable algorithm shows you can fold any straight-line drawing on paper so that the complete drawing can be cut out with one straight scissors cut. Aimed primarily at advanced undergraduate and graduate students in mathematics or computer science, this lavishly illustrated book will fascinate a broad audience, from high school students to researchers.


title: Simulation of dynamics and realistic contact forces for manipulators and legged robots with high joint elasticity

abstract: In this paper, multibody system dynamics simulation for manipulators and legged robots with high joint elasticities, particularly with focus on collision modeling, is addressed. We present the architecture of a newly developed toolbox in conjunction with a detailed discussion of a realistic contact, friction and stiction model, which is validated with real measurement data of a bouncing ball. The work presented is driven and inspired by two concrete robot developments in the authors' group: the manipulator BioRob and the biped BioBiped. The libraries are used to develop kinematic and kinetic models of these bio-inspired and highly elastic robots. Models and simulation of both robots are discussed, as well as occurring forces during collisions of the BioRob-X4 arm with the ground. We are also able to demonstrate good agreement of ground contact forces measured during slow jogging motion of a human subject with simulation results obtained with BioBiped1.


title: Using Kohonen’s selforganizing feature map to uncover automobile bodily injury claims fraud

abstract: Claims fraud is an increasingly vexing problem confronting the insurance industry. In this empirical study, we apply Kohonen's Self-Organizing Feature Map to classify automobile bodily injury (BI) claims by the degree of fraud suspicion. Feed forward neural networks and a back propagation algorithm are used to investigate the validity of the Feature Map approach. Comparative experiments illustrate the potential usefulness of the proposed methodology. We show that this technique performs better than both an insurance adjuster's fraud assessment and an insurance investigator's fraud assessment with respect to consistency and reliability.


title: Monolithic integration of trench vertical DMOS (VDMOS) power transistors into a BCD process

abstract: The monolithic integration of trench vertical DMOS (VDMOS) n-channel transistors into an IC BCD process is reported for the first time. The integration scheme for the trench VDMOS module is discussed and silicon results are compared with TCAD simulations. For a 50-V device, the integrated trench device is shown to offer at least a factor-of-two R/sub DS(ON)/ /spl times/ area advantage over its planar counterpart. An R/sub DS(ON)/ /spl times/ area value of 80 m/spl Omega/mm/sup 2/ is achieved for the integrated trench VDMOS using a minimum feature size of 1 /spl mu/m.


title: Pyrolysis and dehalogenation of plastics from waste electrical and electronic equipment (WEEE): a review.

abstract: Plastics from waste electrical and electronic equipment (WEEE) have been an important environmental problem because these plastics commonly contain toxic halogenated flame retardants which may cause serious environmental pollution, especially the formation of carcinogenic substances polybrominated dibenzo dioxins/furans (PBDD/Fs), during treat process of these plastics. Pyrolysis has been proposed as a viable processing route for recycling the organic compounds in WEEE plastics into fuels and chemical feedstock. However, dehalogenation procedures are also necessary during treat process, because the oils collected in single pyrolysis process may contain numerous halogenated organic compounds, which would detrimentally impact the reuse of these pyrolysis oils. Currently, dehalogenation has become a significant topic in recycling of WEEE plastics by pyrolysis. In order to fulfill the better resource utilization of the WEEE plastics, the compositions, characteristics and dehalogenation methods during the pyrolysis recycling process of WEEE plastics were reviewed in this paper. Dehalogenation and the decomposition or pyrolysis of WEEE plastics can be carried out simultaneously or successively. It could be 'dehalogenating prior to pyrolysing plastics', 'performing dehalogenation and pyrolysis at the same time' or 'pyrolysing plastics first then upgrading pyrolysis oils'. The first strategy essentially is the two-stage pyrolysis with the release of halogen hydrides at low pyrolysis temperature region which is separate from the decomposition of polymer matrixes, thus obtaining halogenated free oil products. The second strategy is the most common method. Zeolite or other type of catalyst can be used in the pyrolysis process for removing organohalogens. The third strategy separate pyrolysis and dehalogenation of WEEE plastics, which can, to some degree, avoid the problem of oil value decline due to the use of catalyst, but obviously, this strategy may increase the cost of whole recycling process.


title: Safe Exploration in Markov Decision Processes

abstract: In environments with uncertain dynamics exploration is necessary to learn how to perform well. Existing reinforcement learning algorithms provide strong exploration guarantees, but they tend to rely on an ergodicity assumption. The essence of ergodicity is that any state is eventually reachable from any other state by following a suitable policy. This assumption allows for exploration algorithms that operate by simply favoring states that have rarely been visited before. For most physical systems this assumption is impractical as the systems would break before any reasonable exploration has taken place, i.e., most physical systems don't satisfy the ergodicity assumption. In this paper we address the need for safe exploration methods in Markov decision processes. We first propose a general formulation of safety through ergodicity. We show that imposing safety by restricting attention to the resulting set of guaranteed safe policies is NP-hard. We then present an efficient algorithm for guaranteed safe, but potentially suboptimal, exploration. At the core is an optimization formulation in which the constraints restrict attention to a subset of the guaranteed safe policies and the objective favors exploration policies. Our framework is compatible with the majority of previously proposed exploration methods, which rely on an exploration bonus. Our experiments, which include a Martian terrain exploration problem, show that our method is able to explore better than classical exploration methods.


title: Internal Coupled-Fed Shorted Monopole Antenna for GSM850/900/1800/1900/UMTS Operation in the Laptop Computer

abstract: A simple shorted strip monopole with a coupling feed for penta-band WWAN (Wireless Wide Area Network) operation in the laptop computer is presented. With the coupling feed, which effectively compensates for the large inductive reactance of the antenna, a dual-resonance excitation for the antenna's lower band at about 1 GHz is achieved; the obtained bandwidth reaches 500 MHz, allowing the antenna to easily cover GSM850/900 operation. Also, a wide operating band is achieved for the antenna's upper band at about 1.9 GHz with a bandwidth of 540 MHz, hence easily covering GSM1800/1900/UMTS operation. With two wide operating bands achieved, the antenna occupies a thickness of 5 mm only and a small area of 9 times 79 mm2 (not including the ground plane), making it very promising to be embedded inside the casing of the laptop computer as an internal WWAN antenna. The proposed antenna is studied in detail in this study.


title: Impact of Smart Grid on distribution system design

abstract: There has been much recent discussion on what distribution systems can and should look like in the future. Terms related to this discussion include smart grid, distribution system of the future, and others. Functionally, a smart grid should be able to provide new abilities such as self-healing, high reliability, energy management, and real-time pricing. From a design perspective, a smart grid will likely incorporate new technologies such as advanced metering, automation, communication, distributed generation, and distributed storage. This paper discussed the potential impact that issues related to smart grid will have on distribution system design.


title: GIAA TECHNINAL REPORT GIAA2010E001 On Current Model-Building Methods for Multi-Objective Estimation of Distribution Algorithms: Shortcommings and Directions for Improvement

abstract: There are some issues with multi-objective esti- mation of distribution algorithms (MOEDAs) that have been undermining their performance when dealing with problems with many objectives. In this paper we examine the model-building issue related to estimation of distribution algorithms (EDAs) and show that some of their, as yet overlooked, characteristics render most current MOEDAs unviable in the presence of many objectives. First, we present model-building as a problem with particular requirements and explain why some current approaches cannot properly deal with some of these conditions. Then, we discuss the strategies proposed for adapting EDAs to this problem. To validate our working hypothesis, we carry out an experimental study comparing different model-building algorithms. In the final part of the paper, we provide an in-depth discussion on viable alternatives to overcome the limitations of current MOEDAs in many-objective optimization.


title: High Isolation Internal Dual-Band Planar Inverted-F Antenna Diversity System with Band-Notched Slots for MIMO Terminals

abstract: Internal dual-band planar inverted-F antenna (PIFA) diversity system for portable devices, operating in the 2.4-GHz band (2400-2484MHz) and 5.2-GHz band (5150-5350MHz), is presented. To reduce the mutual coupling and get the high isolation between the two internal dual-band antennas, we proposed the band-notched lambda/4 slots on the ground plane. The optimized band-notched slots for high isolation, high radiation efficiency and high effective diversity gain are analyzed. The band-notched slots can be used to the small MIMO terminals which require high isolation between antennas


title: Diversification of Chemoreceptors in Ectocarpus, Sphacelaria, and Adenocystis (Phaeophyceae)

abstract: Abstract Ectocarpene, (+)-(6S)-(1Z-butenyl)-2,5-cycloheptadiene, is the mating pherom one of the three distantly related seaweeds Ectocarpus siliculosus, Sphacelaria rigidula and Adenocystis utricularis. Analogu es of this pheromone, differing in position and π-electron density of the double bond in the C4-side chain, were synthesized and assayed for biological activity. The results suggest, that the fundamental molecular recognition process is conservative in all species, while receptor dynamics and -topologies have been modified by individual developments and expressions during plant phylogeny.


title: Misuse of automated decision aids: Complacency, automation bias and the impact of training experience

abstract: The present study investigates automation misuse based on complacency and automation bias in interacting with a decision aid in a process control system. The effect of a preventive training intervention which includes exposing participants to rare automation failures is examined. Complacency is reflected in an inappropriate checking and monitoring of automated functions. In interaction with automated decision aids complacency might result in commission errors, i.e., following automatically generated recommendations even though they are false. Yet, empirical evidence proving this kind of relationship is still lacking. A laboratory experiment (N=24) was conducted using a process control simulation. An automated decision aid provided advice for fault diagnosis and management. Complacency was directly measured by the participants' information sampling behavior, i.e., the amount of information sampled in order to verify the automated recommendations. Possible commission errors were assessed when the aid provided false recommendations. The results provide clear evidence for complacency, reflected in an insufficient verification of the automation, while commission errors were associated with high levels of complacency. Hence, commission errors seem to be a possible, albeit not an inevitable consequence of complacency. Furthermore, exposing operators to automation failures during training significantly decreased complacency and thus represents a suitable means to reduce this risk, even though it might not avoid it completely. Potential applications of this research include the design of training protocols in order to prevent automation misuse in interaction with automated decision aids.


title: Socket intents: leveraging application awareness for multi-access connectivity

abstract: In today's Internet, almost all end devices have multiple interfaces built in. This enables users to seamlessly switch between different access networks or even use them simultaneously; to better use the resources available to them and to better satisfy their needs. This is referred to as mobile data offloading and has received lots of attention recently in both the research community and in the industry. However, all the proposed data solutions either rely on static configuration policies or are reactive rather than proactive with regards to the application needs. In this paper, we propose a proactive, application informed approach, Socket Intents. Socket Intents augment the socket interface to enable the application to express what it knows about its communication patterns and preferences. This information can then be used by our proactive policies to choose the appropriate interface, tune the network parameters, or even combine multiple interfaces. We provide a prototype implementation of our Socket Intents and present a first evaluation of the Intents and its benefits.


title: Deep Brain Photoreceptor (val-opsin) Gene Knockout Using CRISPR/Cas Affects Chorion Formation and Embryonic Hatching in the Zebrafish

abstract: Non-rod non-cone photopigments in the eyes and the brain can directly mediate non-visual functions of light in non-mammals. This was supported by our recent findings on vertebrate ancient long (VAL)-opsin photopigments encoded by the val-opsinA (valopa) and val-opsinB (valopb) genes in zebrafish. However, the physiological functions of valop isoforms remain unknown. Here, we generated valop-mutant zebrafish using CRISPR/Cas genome editing, and examined the phenotypes of loss-of-function mutants. F0 mosaic mutations and germline transmission were confirmed via targeted insertions and/or deletions in the valopa or valopb gene in F1 mutants. Based on in silico analysis, frameshift mutations converted VAL-opsin proteins to non-functional truncated forms with pre-mature stop codons. Most F1 eggs or embryos from F0 female valopa/b mutants showed either no or only partial chorion elevation, and the eggs or embryos died within 26 hour-post-fertilization. However, most F1 embryos from F0 male valopa mutant developed but hatched late compared to wild-type embryos, which hatched at 4 day-post-fertilization. Late-hatched F1 offspring included wild-type and mutants, indicating the parental effects of valop knockout. This study shows valop gene knockout affects chorion formation and embryonic hatching in the zebrafish.