title: A context-aware approach to detection of short irrelevant texts

abstract: This paper presents a simple and effective framework that can detect irrelevant short text contents following blogs and news articles, etc. in a context-aware and timely fashion. Nowadays, websites such as Linkedin.com and CNN.com allow their visitors to leave comments after articles, and spammers are exploiting this feature to post irrelevant contents. Visited by millions of readers per day, these websites have extremely high visibility, and irrelevant comments have a detrimental effect on the visiting traffic and revenue of these websites. Therefore, it is critical to eliminate these irrelevant comments as accurately and early as possible. Different from traditional text mining tasks, comments following news and blog articles are characterized by briefness and context-dependent semantics, making it difficult to measure semantic relevance. What's worse, there could be only a handful of comments soon after an article is posted, leading to a severe lack of information for semantics and relevance measurement. We propose to infer “context-aware semantics” to address the above challenges in a unified framework. Specifically, we construct contexts for comments using either blocks of surrounding comments, or comments collected via a principled transfer learning approach. The constructed contexts mitigate the sparseness and sharply define context-dependent semantics of comments, even at the early stage of commenting activities, allowing traditional dimension reduction methods to better capture the semantics of short texts in a context-aware way. We confirm the effectiveness of the proposed method on two real world datasets consisting of news and blog articles and comments, with a maximal improvement of 20% in Area Under Precision-Recall Curve.


title: POST OESTRAL VAGINAL PROLAPSE IN A NON-PREGNANT HEIFER (A CASE REPORT)

abstract: The present study reports a case of post oestral vaginal prolapse in a non-pregnant heifer with secondary uterine inflammation. The clinical signs, hematology, biochemistry, ultrasonographic findings and therapy were described. The vaginal prolapse type was recognized as garde III but systemic sings as increased body temperature, digestive tract and locomotors function disturbances were not observed. The blood samples investigation showed decrease of haemoglobin content, red blood cells, haematocrit and phosphorus. Fluid filled uterine horns, open cervical canal, newly formed corpus luteum and follicles into the ovaries were detected by ultrasound examination. The treatment included epidural anaesthesia, prolapsed vagina replacement, Buhner suture setting, human chorion gonadotropin injection and supported therapy by antibiotics, antiphlogistic drugs and analgetics. This clinical case could be in contribution to the veterinary practice.


title: Reducing calorie sales from supermarkets – ‘silent’ reformulation of retailer-brand food products

abstract: BackgroundFood product reformulation is seen as one among several tools to promote healthier eating. Reformulating the recipe for a processed food, e.g. reducing the fat, sugar or salt content of the foods, or increasing the content of whole-grains, can help the consumers to pursue a healthier life style. In this study, we evaluate the effects on calorie sales of a ‘silent’ reformulation strategy, where a retail chain’s private-label brands are reformulated to a lower energy density without making specific claims on the product.MethodsUsing an ecological study design, we analyse 52 weeks’ sales data – enriched with data on products’ energy density - from a Danish retail chain. Sales of eight product categories were studied. Within each of these categories, specific products had been reformulated during the 52 weeks data period. Using econometric methods, we decompose the changes in calorie turnover and sales value into direct and indirect effects of product reformulation.ResultsFor all considered products, the direct effect of product reformulation was a reduction in the sale of calories from the respective product categories - between 0.5 and 8.2%. In several cases, the reformulation led to indirect substitution effects that were counterproductive with regard to reducing calorie turnover. However, except in two insignificant cases, these indirect substitution effects were dominated by the direct effect of the reformulation, leading to net reductions in calorie sales between −3.1 and 7.5%. For all considered product reformulations, the reformulation had either positive, zero or very moderate negative effects on the sales value of the product category to which the reformulated product belonged.ConclusionsBased on these findings, ‘silent’ reformulation of retailer’s private brands towards lower energy density seems to contribute to lowering the calorie intake in the population (although to a moderate extent) with moderate losses in retailer’s sales revenues.


title: Multilevel thresholding selection based on chaotic multi-verse optimization for image segmentation

abstract: Multilevel thresholding is the most important method for image processing. Conventional multilevel thresholding methods have proven to be efficient in bi-level thresholding; however, when extended to multilevel thresholding, they prove to be computationally more costly, as they comprehensively search the optimal thresholds for the objective function. This paper presents a chaotic multi-verse optimizer (CMVO) algorithm using Kapur's objective function in order to determine the optimal multilevel thresholds for image segmentation. The proposed CMVO algorithm was applied to various standard test images, and evaluated by peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). The CMVO algorithm efficiently and accurately searched multilevel thresholds and reduced the required computational times.


title: Canine mast cell tumours: a review of the pathogenesis, clinical features, pathology and treatment

abstract: Mast cells (MCs) are well known for their neoplastic transformation in solitary and multiple cutaneous mast cell tumours (MCTs), as well as visceral and systemic mastocytosis. Dogs have a unique risk of developing cutaneous MCTs, and they account for 7% to 21% of all canine skin tumours. The aetiology of canine MCTs is unknown but is probably multifactorial. This article reviews up-to-date knowledge on the pathogenesis, the clinical presentation, the clinical prognostic factors, the diagnostic workup including clinical staging, cytological findings, histological findings and the various grading systems which have been evaluated based on morphology, the assessment of proliferation markers and other factors such as vessel density. Furthermore, detailed information about current treatment protocols for canine cutaneous MCTs is provided.


title: Adaptive Spatial Modulation Using Huffman Coding

abstract: Antenna switch enables multiple antennas to share a common RF chain, thus an additional spatial dimension, i.e., antenna index, can be utilized in the design of single RF chain MIMO and information can be conveyed via both signal space and spatial dimension. In this paper, we propose a unified adaptive transmission scheme - adaptive spatial modulation that allocates information into signal space and spatial dimension in order to maximize the overall channel capacity for single RF chain MIMO. The proposed adaptive spatial modulation is realized by using Huffman coding, i.e., designing variable length codes to activate the transmit antenna with different probabilities. The optimal antenna activation probability is derived through optimizing channel capacity. To make the optimization tractable, closed form upper bound and lower bound are derived as the effective approximations for channel capacity. Numerical results show that the proposed adaptive spatial modulation offers considerable performance improvement over both spatial modulation and transmit antenna selection.


title: Osteopathic manipulative treatment: A systematic review and critical appraisal of comparative effectiveness and health economics research

abstract: Abstract In recent years, evidence has emerged regarding the effectiveness of osteopathic manipulative treatments (OMT). Despite growing evidence in this field, there is need for appropriate research designs that effectively reflect the person-centred system of care promoted in osteopathy and provide data which can inform policy decisions within the healthcare system. The purpose of this systematic review is to identify, appraise and synthesise the evidence from comparative effectiveness and economic evaluation research involving OMT. A database search was conducted using CINAHL, PubMed, PEDro, AMED, SCOPUS and OSTMED.DR, from their inception to May 2015. Two separate searches were undertaken to identify original research articles encompassing the economic evaluation and comparative effectiveness of OMT. Identified comparative effectives studies were evaluated using the Cochrane risk of bias tool and appraised using the Good Reporting of Comparative Effectiveness (GRACE) principles. Identified economic studies were assessed with the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) guidelines. Sixteen studies reporting the findings of comparative effectiveness (n = 9) and economic evaluation (n = 7) research were included. The comparative effectiveness studies reported outcomes for varied health conditions and the majority (n = 6) demonstrated a high risk of bias. The economic evaluations included a range of analyses and considerable differences in the quality of reporting were evident. Despite some positive findings, published comparative effectiveness and health economic studies in OMT are of insufficient quality and quantity to inform policy and practice. High quality, well-designed, research that aligns with international best practice is greatly needed to build a pragmatic evidence base for OMT.


title: School Leadership and Cyberbullying—A Multilevel Analysis

abstract: Cyberbullying is a relatively new form of bullying, with both similarities and differences to traditional bullying. While earlier research has examined associations between school-contextual characteristics and traditional bullying, fewer studies have focused on the links to students’ involvement in cyberbullying behavior. The aim of the present study is to assess whether school-contextual conditions in terms of teachers’ ratings of the school leadership are associated with the occurrence of cyberbullying victimization and perpetration among students. The data are derived from two separate data collections performed in 2016: The Stockholm School Survey conducted among students in the second grade of upper secondary school (ages 17–18 years) in Stockholm municipality, and the Stockholm Teacher Survey which was carried out among teachers in the same schools. The data include information from 6067 students distributed across 58 schools, linked with school-contextual information based on reports from 1251 teachers. Cyberbullying victimization and perpetration are measured by students’ self-reports. Teachers’ ratings of the school leadership are captured by an index based on 10 items; the mean value of this index was aggregated to the school level. Results from binary logistic multilevel regression models show that high teacher ratings of the school leadership are associated with less cyberbullying victimization and perpetration. We conclude that a strong school leadership potentially prevents cyberbullying behavior among students.


title: Honeypots: concepts, approaches, and challenges

abstract: Information security is a growing concern today for organizations and individuals alike. This has led to growing interest in more aggressive forms of defense to supplement the existing methods. One of these methods involves the use of honeypots. A honeypot is a security resource whose value lies in being probed, attacked or compromised. In this paper we present an overview of honeypots and provide a starting point for persons who are interested in this technology. We examine different kinds of honeypots, honeypot concepts, and approaches to their implementation.


title: Growing up in a Material World: Age Differences in Materialism in Children and Adolescents

abstract: We examine age differences in materialism with children and adolescents 8–18 years old. In study 1, we find materialism increases from middle childhood to early adolescence and declines from early to late adolescence. Further, we find that age differences are mediated by changes in self-esteem occurring from middle childhood through adolescence. In study 2, we prime self-esteem to obtain further evidence of a causal link between self-esteem and materialism. As expected, we find that inducing high self-esteem decreases expressions of materialism. Inducing high self-esteem reduces materialism among adolescents so dramatically that age differences in materialism disappear.


title: The Google Similarity Distance

abstract: Words and phrases acquire meaning from the way they are used in society, from their relative semantics to other words and phrases. For computers, the equivalent of "society" is "database," and the equivalent of "use" is "a way to search the database". We present a new theory of similarity between words and phrases based on information distance and Kolmogorov complexity. To fix thoughts, we use the World Wide Web (WWW) as the database, and Google as the search engine. The method is also applicable to other search engines and databases. This theory is then applied to construct a method to automatically extract similarity, the Google similarity distance, of words and phrases from the WWW using Google page counts. The WWW is the largest database on earth, and the context information entered by millions of independent users averages out to provide automatic semantics of useful quality. We give applications in hierarchical clustering, classification, and language translation. We give examples to distinguish between colors and numbers, cluster names of paintings by 17th century Dutch masters and names of books by English novelists, the ability to understand emergencies and primes, and we demonstrate the ability to do a simple automatic English-Spanish translation. Finally, we use the WordNet database as an objective baseline against which to judge the performance of our method. We conduct a massive randomized trial in binary classification using support vector machines to learn categories based on our Google distance, resulting in an a mean agreement of 87 percent with the expert crafted WordNet categories


title: Multidisciplinary Instruction with the Natural Language Toolkit

abstract: The Natural Language Toolkit (NLTK) is widely used for teaching natural language processing to students majoring in linguistics or computer science. This paper describes the design of NLTK, and reports on how it has been used effectively in classes that involve different mixes of linguistics and computer science students. We focus on three key issues: getting started with a course, delivering interactive demonstrations in the classroom, and organizing assignments and projects. In each case, we report on practical experience and make recommendations on how to use NLTK to maximum effect.


title: Suppression of Read Disturb Fail Caused by Boosting Hot Carrier Injection Effect for 3-D Stack NAND Flash Memories

abstract: A new bias pulse method was proposed to suppress read disturbance in unselected strings of 3-D stack NAND flash memories. Using the proposed read method, we could suppress effectively a large cell Vth shift generated by boosting hot carrier injection. As a result, the cell Vth shift in unselected string is quite similar to normal read disturbance in select string. The proposed read method was verified by both measurement and simulation.


title: Full-frame video stabilization

abstract: Video stabilization is an important video enhancement technology which aims at removing annoying shaky motion from videos. We propose a practical and robust approach of video stabilization that produces full-frame stabilized videos with good visual quality. While most previous methods end up with producing low resolution stabilized videos, our completion method can produce full-frame videos by naturally filling in missing image parts by locally aligning image data of neighboring frames. To achieve this, motion inpainting is proposed to enforce spatial and temporal consistency of the completion in both static and dynamic image areas. In addition, image quality in the stabilized video is enhanced with a new practical deblurring algorithm. Instead of estimating point spread functions, our method transfers and interpolates sharper image pixels of neighbouring frames to increase the sharpness of the frame. The proposed video completion and deblurring methods enabled us to develop a complete video stabilizer which can naturally keep the original image quality in the stabilized videos. The effectiveness of our method is confirmed by extensive experiments over a wide variety of videos.


title: Automated Differentiation between Normal Sinus Rhythm, Atrial Tachycardia, Atrial Flutter and Atrial Fibrillation during Electrophysiology

abstract: Intracardiac Electrogram (IEGM) are examined during Cardiac Electrophysiology (EP) for detection, differentiation, analysis and treatment of different arrhythmias. The arrhythmia detection involves EP stimulation, observing IEGM response on monitor screens, and manual evaluation of IEGM key features. The process is time consuming and requires high level of expertise of Electro physiologists. During an EP stimulation process, a patient may develop Atrial Fibrillation (AF) and it is important for patient to be taken out of the AF before further proceeding with the procedure. It is required to automate the arrhythmia detection process during an EP study for real time monitoring of the patient condition and safety. In our previous work, successful detection of Atrio-Ventricular Reentrant Tachycardia and Atrio-Ventricular Nodal Re-entry Tachycardia was achieved in time domain. This work has been undertaken to automatically detect the AF as well as differentiate it from Atrial Flutter (AFL), Atrial Tachycardia (AT) and Normal Sinus Rhythm (NSR). In proposed work, non parametric technique has been applied on atrial IEGM signal for estimation of Dominant frequency (DF) to find out atrial activation rate during NSR, AT, AFL and AF. A new spectral parameter, Average Power Spectral Ratio (APSR), has been defined for ensuring reliability of DF for AF detection as well as differentiation of AF from other atrial arrhythmias. The proposed system successfully detects and differentiates between NSR, AT, AFL and AF with an accuracy of 99.52%. The proposed system can also be effectively used for additional therapeutic application by implantable cardioverter defibrillators.


title: SkipNet: Learning Dynamic Routing in Convolutional Networks

abstract: While deeper convolutional networks are needed to achieve maximum accuracy in visual perception tasks, for many inputs shallower networks are sufficient. We exploit this observation by learning to skip convolutional layers on a per-input basis. We introduce SkipNet, a modified residual network, that uses a gating network to selectively skip convolutional blocks based on the activations of the previous layer. We formulate the dynamic skipping problem in the context of sequential decision making and propose a hybrid learning algorithm that combines supervised learning and reinforcement learning to address the challenges of non-differentiable skipping decisions. We show SkipNet reduces computation by 30-90% while preserving the accuracy of the original model on four benchmark datasets and outperforms the state-of-the-art dynamic networks and static compression methods. We also qualitatively evaluate the gating policy to reveal a relationship between image scale and saliency and the number of layers skipped.


title: Current mode charge pump: topology, modeling and control

abstract: Current-mode control, the standard method to control inductive switching power supplies can also be used in switched capacitor converters. Here, regulation is achieved by operating one transistor in the charge pump output stage as a controlled current source. Compared with voltage mode operation where the transistor on-resistances is regulated, current mode keeps the small signal output resistance of the converter stage high even with high load currents. This always keeps the output pole, which is the dominant pole in current mode charge pumps at low frequencies even at heavy loads and makes the system easy to stabilize. Provided that the output pole is kept three to five times smaller than any parasitic internal poles, than a first order system is possible. When the controlled current source is placed in the discharge path then the converter always runs with a fully charged flying capacitor, which improves transient response. The universal second order current mode charge pump small signal model presented in this paper consists of a gm-stage error amplifier and a gm-output stage as regulated section. The model also includes the output resistance of the gm-stages, parasitic capacitances, the internal R-C compensation and the external components like the feedback divider, output resistor and load capacitor. The flying capacitor is modeled with a voltage source. By giving this voltage source different values the model can be used with any charge pump topology (doubler, tripler, inverter....). Experimental results show that by comparing the transient response the small signal model well matches with the measured performance. Since model can be used for AC and transient analysis an early prediction of stability and dynamic behavior of the converter is possible. Like inductive current mode converters the maximum output current is limited in the regulated section, which makes the converter short circuit protected.


title: Neocognitron trained with winner-kill-loser rule

abstract: The neocognitron, which was proposed by Fukushima (1980), is a hierarchical multi-layered neural network capable of robust visual pattern recognition. It acquires the ability to recognize patterns through learning. This paper proposes a new rule for competitive learning, named winner-kill-loser, and apply it to the neocognitron. The winner-kill-loser rule resembles the winner-take-all rule. Every time when a training stimulus is presented, non-silent cells compete with each other. The winner, however, not only takes all, but also kills losers. In other words, the winner learns the training stimulus, and losers are removed from the network. If all cells are silent, a new cell is generated and it learns the training stimulus. Thus feature-extracting cells gradually come to distribute uniformly in the feature space. The use of winner-kill-loser rule is not limited to the neocognitron. It is useful for various types of competitive learning, in general. This paper also proposes several improvements made on the neocognitron: such as, disinhibition to the inhibitory surround in the connections to C-cells (or complex cells) from S-cells (or simple cells); and square root shaped saturation in the input-to-output characteristics of C-cells. As a result of these improvements, the recognition rate of the neocognitron has been largely increased.


title: The green blockchain: Managing decentralized energy production and consumption

abstract: Energy systems are evolving towards a more decentralized model accommodate with heterogeneous but competitive energy sources and energy storage systems (ESS). This will enable peer to peer energy transactions through microgrids architectures. This paper explores the use of blockchain technology implemented on an Industrial operating system (Predix) for a use case of green certificates, demonstrated within an eco-district.


title: Tuple spaces implementations and their efficiency

abstract: Among the paradigms for parallel and distributed computing, the one popularized with Linda and based on tuple spaces is the least used one, despite the fact of being intuitive, easy to understand and to use. A tuple space is a repository of tuples, where process can add, withdraw or read tuples by means of atomic operations. Tuples may contain different values, and processes can inspect the content of a tuple via pattern matching. The lack of a reference implementations for this paradigm has prevented its widespread. In this paper, first we do an extensive analysis on what are the state of the art implementations and summarise their characteristics. Then we select three implementations of the tuple space paradigm and compare their performances on three different case studies that aim at stressing different aspects of computing such as communication, data manipulation, and cpu usage. After reasoning on strengths and weaknesses of the three implementations, we conclude with some recommendations for future work towards building an effective implementation of the tuple space paradigm.


Effects of Anesthetic Agents and Physiologic Changes on Intraoperative Motor Evoked Potentials


title: Video Segmentation by Non-Local Consensus voting.

abstract: We address the problem of Foreground/Background segmentation of “unconstrained” video. By “unconstrained” we mean that the moving objects and the background scene may be highly non-rigid (e.g., waves in the sea); the camera may undergo a complex motion with 3D parallax; moving objects may suffer from motion blur, large scale and illumination changes, etc. Most existing segmentation methods fail on such unconstrained videos, especially in the presence of highly non-rigid motion and low resolution. We propose a computationally efficient algorithm which is able to produce accurate results on a large variety of unconstrained videos. This is obtained by casting the video segmentation problem as a voting scheme on the graph of similar (‘re-occurring’) regions in the video sequence. We start from crude saliency votes at each pixel, and iteratively correct those votes by ‘consensus voting’ of re-occurring regions across the video sequence. The power of our consensus voting comes from the non-locality of the region re-occurrence, both in space and in time – enabling propagation of diverse and rich information across the entire video sequence. Qualitative and quantitative experiments indicate that our approach outperforms current state-of-the-art methods.


title: Investigation of the chick embryo as a potential alternative to the mouse for evaluation of radiopharmaceuticals.

abstract: INTRODUCTION ::: The chick embryo is an emerging in vivo model in several areas of pre-clinical research including radiopharmaceutical sciences. Herein, it was evaluated as a potential test system for assessing the biodistribution and in vivo stability of radiopharmaceuticals. For this purpose, a number of radiopharmaceuticals labeled with (18)F, (125)I, (99m)Tc, and (177)Lu were investigated in the chick embryo and compared with the data obtained in mice. ::: ::: ::: METHODS ::: Chick embryos were cultivated ex ovo for 17-19 days before application of the radiopharmaceutical directly into the peritoneum or intravenously using a vein of the chorioallantoic membrane (CAM). At a defined time point after application of radioactivity, the embryos were euthanized by shock-freezing using liquid nitrogen. Afterwards they were separated from residual egg components for post mortem imaging purposes using positron emission tomography (PET) or single photon emission computed tomography (SPECT). ::: ::: ::: RESULTS ::: SPECT images revealed uptake of [(99m)Tc]pertechnetate and [(125)I]iodide in the thyroid of chick embryos and mice, whereas [(177)Lu]lutetium, [(18)F]fluoride and [(99m)Tc]-methylene diphosphonate ([(99m)Tc]-MDP) were accumulated in the bones. [(99m)Tc]-dimercaptosuccinic acid ((99m)Tc-DMSA) and the somatostatin analog [(177)Lu]-DOTATOC, as well as the folic acid derivative [(177)Lu]-DOTA-folate showed accumulation in the renal tissue whereas [(99m)Tc]-mebrofenin accumulated in the gall bladder and intestine of both species. In vivo dehalogenation of [(18)F]fallypride and of the folic acid derivative [(125)I]iodo-tyrosine-folate was observed in both species. In contrast, the 3'-aza-2'-[(18)F]fluorofolic acid ([(18)F]-AzaFol) was stable in the chick embryo as well as in the mouse. ::: ::: ::: CONCLUSIONS ::: Our results revealed the same tissue distribution profile and in vivo stability of radiopharmaceuticals in the chick embryo and the mouse. This observation is promising with regard to a potential use of the chick embryo as an inexpensive and simple test model for preclinical screening of novel radiopharmaceuticals.


corps dans la schizophrénie ense of body in schizophrenia


title: Scalable Tucker Factorization for Sparse Tensors - Algorithms and Discoveries

abstract: Given sparse multi-dimensional data (e.g., (user, movie, time; rating) for movie recommendations), how can we discover latent concepts/relations and predict missing values? Tucker factorization has been widely used to solve such problems with multi-dimensional data, which are modeled as tensors. However, most Tucker factorization algorithms regard and estimate missing entries as zeros, which triggers a highly inaccurate decomposition. Moreover, few methods focusing on an accuracy exhibit limited scalability since they require huge memory and heavy computational costs while updating factor matrices. In this paper, we propose P-Tucker, a scalable Tucker factorization method for sparse tensors. P-Tucker performs alternating least squares with a row-wise update rule in a fully parallel way, which significantly reduces memory requirements for updating factor matrices. Furthermore, we offer two variants of P-Tucker: a caching algorithm P-Tucker-Cache and an approximation algorithm P-Tucker-Approx, both of which accelerate the update process. Experimental results show that P-Tucker exhibits 1.7-14.1x speed-up and 1.4-4.8x less error compared to the state-of-the-art. In addition, P-Tucker scales near linearly with the number of observable entries in a tensor and number of threads. Thanks to P-Tucker, we successfully discover hidden concepts and relations in a large-scale real-world tensor, while existing methods cannot reveal latent features due to their limited scalability or low accuracy.


title: Pervasive, hard-wired and male: Qualitative study of how UK adolescents view alcohol-related aggression

abstract: Laboratory studies of alcohol-inexperienced adolescents show that aggression can be primed by alcohol-related stimuli, suggesting that alcohol-related aggression is partly socially learned. Script theory proposes that alcohol-related aggression 'scripts' for social behaviors are culturally-available and learned by individuals. The purpose of the study was to understand the content and origins of alcohol-related aggression scripts learned by adolescents. This qualitative focus group study of 40 adolescents (ages 14-16 years) examined alcohol-related aggression scripts. Participants believed aggression and severe injury to be pervasive when young people drink. Viewed through a biological lens, participants described aggression as an 'instinctive' and 'hard-wired' male trait facilitated by intoxication. As such, alcohol-related aggression was not seen as intended or personally controllable and participants did not see it in moral terms. Females were largely viewed as either bystanders of inter-male aggression or potential victims of male sexual aggression. Participants attributed their views on the frequency and nature of alcohol-related aggression to current affairs and reality television, which they felt portrayed a reality of which they had little experience. The origins of the explicitly biological frameworks that participants used seemed to lie in pre-existing beliefs about the nature of gender differences. Perceptions of the pervasiveness of male alcohol-related aggression, and the consequent failure to view alcohol-related aggression in moral terms, could dispose some young people to alcohol-related aggression. Interventions could target (1) the beliefs that alcohol-related aggression is pervasive and uncontrollable in males, and (2) participants' dysfunctional views of masculinity that underpin those beliefs.


title: A Rectilinear Distance Round-Trip Location Problem

abstract: The problem considered is that of finding the location of a facility in the plane so that the maximum weighted rectilinear round-trip distance between the facility and N pairs of existing facilities is minimized. The round-trip distance is the total distance traveled starting from the new facility via a pair of existing facilities and back to the new facility. An efficient one-pass solution procedure is developed for finding all the optimal locations to the problem, and is compared computationally with the simplex method. Two special cases are investigated, namely, when the existing facilities lie on a line, and when all the weights are equal.


Small intestinal obstruction after appendectomy: an avoidable complication?


title: Extreme Point-Based Heuristics for Three-Dimensional Bin Packing

abstract: One of the main issues in addressing three-dimensional packing problems is finding an efficient and accurate definition of the points at which to place the items inside the bins, because the performance of exact and heuristic solution methods is actually strongly influenced by the choice of a placement rule. We introduce the extreme point concept and present a new extreme point-based rule for packing items inside a three-dimensional container. The extreme point rule is independent from the particular packing problem addressed and can handle additional constraints, such as fixing the position of the items. The new extreme point rule is also used to derive new constructive heuristics for the three-dimensional bin-packing problem. Extensive computational results show the effectiveness of the new heuristics compared to state-of-the-art results. Moreover, the same heuristics, when applied to the two-dimensional bin-packing problem, outperform those specifically designed for the problem.


title: Functional connectivity hubs of the mouse brain

abstract: Abstract Recent advances in functional connectivity methods have made it possible to identify brain hubs — a set of highly connected regions serving as integrators of distributed neuronal activity. The integrative role of hub nodes makes these areas points of high vulnerability to dysfunction in brain disorders, and abnormal hub connectivity profiles have been described for several neuropsychiatric disorders. The identification of analogous functional connectivity hubs in preclinical species like the mouse may provide critical insight into the elusive biological underpinnings of these connectional alterations. To spatially locate functional connectivity hubs in the mouse brain, here we applied a fully-weighted network analysis to map whole-brain intrinsic functional connectivity (i.e., the functional connectome) at a high-resolution voxel-scale. Analysis of a large resting-state functional magnetic resonance imaging (rsfMRI) dataset revealed the presence of six distinct functional modules related to known large-scale functional partitions of the brain, including a default-mode network (DMN). Consistent with human studies, highly-connected functional hubs were identified in several sub-regions of the DMN, including the anterior and posterior cingulate and prefrontal cortices, in the thalamus, and in small foci within well-known integrative cortical structures such as the insular and temporal association cortices. According to their integrative role, the identified hubs exhibited mutual preferential interconnections. These findings highlight the presence of evolutionarily-conserved, mutually-interconnected functional hubs in the mouse brain, and may guide future investigations of the biological foundations of aberrant rsfMRI hub connectivity associated with brain pathological states.


title: CHAOS: A Data Stream Analysis Architecture for Enterprise Applications

abstract: In this paper, we describe the design of our architecture for Continuous, Heterogeneous Analysis Over Streams, aka CHAOS that combines stream processing, approximation techniques, mining, complex event processing and visualization. CHAOS, with the novel concept of Computational Stream Analysis Cube, provides an effective, scalable platform for near real time processing of business and enterprise streams. We describe our approach with a real data center temperature analysis application.


title: Leaf segmentation in plant phenotyping: a collation study

abstract: Image-based plant phenotyping is a growing application area of computer vision in agriculture. A key task is the segmentation of all individual leaves in images. Here we focus on the most common rosette model plants, Arabidopsis and young tobacco. Although leaves do share appearance and shape characteristics, the presence of occlusions and variability in leaf shape and pose, as well as imaging conditions, render this problem challenging. The aim of this paper is to compare several leaf segmentation solutions on a unique and first-of-its-kind dataset containing images from typical phenotyping experiments. In particular, we report and discuss methods and findings of a collection of submissions for the first Leaf Segmentation Challenge of the Computer Vision Problems in Plant Phenotyping workshop in 2014. Four methods are presented: three segment leaves by processing the distance transform in an unsupervised fashion, and the other via optimal template selection and Chamfer matching. Overall, we find that although separating plant from background can be accomplished with satisfactory accuracy ($$>$$>90 % Dice score), individual leaf segmentation and counting remain challenging when leaves overlap. Additionally, accuracy is lower for younger leaves. We find also that variability in datasets does affect outcomes. Our findings motivate further investigations and development of specialized algorithms for this particular application, and that challenges of this form are ideally suited for advancing the state of the art. Data are publicly available (online at http://www.plant-phenotyping.org/datasets) to support future challenges beyond segmentation within this application domain.


title: Blind high resolution localization and tracking of multiple frequency hopped signals

abstract: This paper considers the problem of blind localization and tracking of multiple frequency-hopped spread-spectrum signals using a uniform linear antenna array without knowledge of hopping patterns or directions of arrival. As a preprocessing step, we propose to identify a hop-free subset of data by discarding high-entropy spectral slices from the spectrogram. High-resolution localization is then achieved via either quadrilinear regression of four-way data generated by capitalizing on both spatial and temporal shift invariance or a new maximum likelihood (ML)-based two-dimensional (2-D) harmonic retrieval algorithm. The latter option achieves the best-known model identifiability bound while remaining close to the Cramer-Rao bound even at low signal-to-noise ratios (SNRs). Following beamforming using the recovered directions, a dynamic programming approach is developed for joint ML estimation of signal frequencies and hop instants in single-user tracking. The efficacy of the proposed algorithms is illustrated in pertinent simulations.


title: A Comparative Study on Vulnerabilities in Categories of Clones and Non-cloned Code

abstract: Code clones are serious code smells. To investigate bug-proneness of clones as opposed to clone-free source code, earlier attempts have studied the stability of code clones and their contributions to program faults. This paper presents a comparative study on different types of clones and non-cloned code on the basis of their vulnerabilities, which may lead to software defects and issues in future. The empirical study along this new dimension examines source code of 97 software systems and derives results based on quantitative analysis with statistical significance. The findings from this work add to our under-standing of the characteristics and impacts of clones, which can be useful in clone-aware software development and in devising techniques for minimizing the negative impacts of code clones.


title: How product owner teams scale agile methods to large distributed enterprises

abstract: Software development teams in large scale offshore enterprise development programmes are often under intense pressure to deliver high quality software within challenging time contraints. Project failures can attract adverse publicity and damage corporate reputations. Agile methods have been advocated to reduce project risks, improving both productivity and product quality. This article uses practitioner descriptions of agile method tailoring to explore large scale offshore enterprise development programmes with a focus on product owner role tailoring, where the product owner identifies and prioritises customer requirements. In globalised projects, the product owner must reconcile competing business interests, whilst generating and then prioritising large numbers of requirements for numerous development teams. The study comprises eight international companies, based in London, Bangalore and Delhi. Interviews with 46 practitioners were conducted between February 2010 and May 2012. Grounded theory was used to identify that product owners form into teams. The main contribution of this research is to describe the nine product owner team functions identified: groom, prioritiser, release master, technical architect, governor, communicator, traveller, intermediary and risk assessor. These product owner functions arbitrate between conflicting customer requirements, approve release schedules, disseminate architectural design decisions, provide technical governance and propogate information across teams. The functions identified in this research are mapped to a scrum of scrums process, and a taxonomy of the functions shows how focusing on either decision-making or information dissemination in each helps to tailor agile methods to large scale offshore enterprise development programmes.


title: Some antecedents and effects of trust in virtual communities

abstract: This study explores several downstream effects of trust in virtual communities and the antecedents of trust in this unique type of environment. The data, applying an existing scale to measure two dimensions of trust (ability and benevolence/integrity), show that trust had a downstream effect on members' intentions to both give information and get information through the virtual community. Both these apparent dimensions of trust were increased through perceived responsive relationships in the virtual community, by a general disposition to trust, and by the belief that others confide personal information.


title: Normally-off AlGaN/GaN HFET with p-type GaN gate and AlGaN buffer

abstract: A 1.5 A normally-off GaN transistor for power applications in p-type GaN gate technology with a modified epitaxial concept is presented. A higher threshold voltage is achieved while keeping the on-state resistance low by using an AlGaN buffer instead of a GaN buffer. Additionally, the AlGaN buffer acts as a back-barrier and suppresses source-drain punch-through currents in the off-state. P-GaN gate GaN transistors with AlGaN buffer will therefore yield higher breakdown voltages as compared to standard GaN buffer versions which results in an excellent VBr-to-RON ratio. The proposed normally-off technology shows save operation under elevated ambient temperature up to 200 °C without thermal runaway. In contrast to standard normally-on AlGaN/GaN HEMTs, a reverse diode operation is possible for offstate conditions which may enable improved inverter circuits.


title: Commutation torque ripple reduction in brushless DC motor drives using a single DC current sensor

abstract: This paper presents a comprehensive study on reducing commutation torque ripples generated in brushless DC motor drives with only a single DC-link current sensor provided. In such drives, commutation torque ripple suppression techniques that are practically effective in low speed as well as high speed regions are scarcely found. The commutation compensation technique proposed here is based on a strategy that the current slopes of the incoming and the outgoing phases during the commutation interval can be equalized by a proper duty-ratio control. Being directly linked with deadbeat current control scheme, the proposed control method accomplishes suppression of the spikes and dips superimposed on the current and torque responses during the commutation intervals of the inverter. Effectiveness of the proposed control method is verified through simulations and experiments.


title: Hardware-driven nonlinear activation for stochastic computing based deep convolutional neural networks

abstract: Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecedented progress, achieving the accuracy close to, or even better than human-level perception in various tasks. There is a timely need to map the latest software DCNNs to application-specific hardware, in order to achieve orders of magnitude improvement in performance, energy efficiency and compactness. Stochastic Computing (SC), as a low-cost alternative to the conventional binary computing paradigm, has the potential to enable massively parallel and highly scalable hardware implementation of DCNNs. One major challenge in SC based DCNNs is designing accurate nonlinear activation functions, which have a significant impact on the network-level accuracy but cannot be implemented accurately by existing SC computing blocks. In this paper, we design and optimize SC based neurons, and we propose highly accurate activation designs for the three most frequently used activation functions in software DCNNs, i.e, hyperbolic tangent, logistic, and rectified linear units. Experimental results on LeNet-5 using MNIST dataset demonstrate that compared with a binary ASIC hardware DCNN, the DCNN with the proposed SC neurons can achieve up to 61X, 151X, and 2X improvement in terms of area, power, and energy, respectively, at the cost of small precision degradation. In addition, the SC approach achieves up to 21X and 41X of the area, 41X and 72X of the power, and 198200X and 96443X of the energy, compared with CPU and GPU approaches, respectively, while the error is increased by less than 3.07%. ReLU activation is suggested for future SC based DCNNs considering its superior performance under a small bit stream length.


title: Asymptotically Optimal Energy-Aware Routing for Multihop Wireless Networks With Renewable Energy Sources

abstract: In this paper, we develop a model to characterize the performance of multihop radio networks in the presence of energy constraints and design routing algorithms to optimally utilize the available energy. The energy model allows us to consider different types of energy sources in heterogeneous environments. The proposed algorithm is shown to achieve a competitive ratio (i.e., the ratio of the performance of any offline algorithm that has knowledge of all past and future packet arrivals to the performance of our online algorithm) that is asymptotically optimal with respect to the number of nodes in the network. The algorithm assumes no statistical information on packet arrivals and can easily be incorporated into existing routing schemes (e.g., proactive or on-demand methodologies) in a distributed fashion. Simulation results confirm that the algorithm performs very well in terms of maximizing the throughput of an energy-constrained network. Further, a new threshold-based scheme is proposed to reduce the routing overhead while incurring only minimum performance degradation.


title: A survey on methods to provide multipath transmission in wired packet networks

abstract: IP networks were designed to provide general connectivity. At their advent, routing methods focused only on finding one optimal path between given endpoints. Although many solutions to sending traffic via multiple paths have appeared over time, the majority of current IP networks are still managed to support only single-path transmissions. This survey examines various approaches which can provide multipath transmissions in existing IP networks. Firstly, the most recognizable solutions are presented, and later, less well-known proposals are introduced. We show how it is possible to realize multipath transmission in source and hop-by-hop routing, multi-topology routing, bio-inspired routing solutions, Valiant's routing, Multi-Protocol Label Switching, Software-Defined Networks, Flow-Aware Multi-Topology Adaptive Routing, Shortest-Path Bridging, Transparent Interconnection of Lots of Links, network virtualization, and Multipath TCP. Moreover, the mentioned approaches are compared, contrasted and subjectively assessed. The goal of the survey is to show that multipath transmissions can be achieved in the current IP networks and in many different ways.


title: Self-Construal as a Mediator Between Identity Structure and Subjective Well-Being

abstract: An examination of the assumptions underlying identity conceptualizations in psychology of self indicates the assumptions are based on an independent, individualistic view of self. If self is constructed as interdependent with others, such identity characteristic as a sense of uniqueness, separateness, and continuity may be less important in promoting well-being. The results of the conducted study (N = 226) indicated that there were weaker relations between various features of identity structure and subjective well-being for individuals with a highly interdependent self-construal than for those with a highly independent self-construal. The results also showed that specificity, separateness, and stability of identity content influenced positive and negative affect through the mediating agency of independent and interdependent self-construals. These findings emphasize the importance of applying a self-construal perspective in considering adaptive functions of identity.


title: Angiotensin II Infusion Does Not Cause Abdominal Aortic Aneurysms in Apolipoprotein E-Deficient Rats

abstract: The apolipoprotein E-deficient (apoE-/-) mouse model has advanced our understanding of cardiovascular disease mechanisms and experimental therapeutics. This spontaneous model recapitulates aspects of human atherosclerosis, and allows for the development of dissecting abdominal aortic aneurysms (AAAs) when combined with angiotensin II. We characterized apoE-/- rats and hypothesized that, similar to mice, they would develop dissecting AAAs. We created rats with a 16-bp deletion of the apoE gene using transcription activator-like effector nucleases. We imaged the suprarenal aorta for 28 days after implantation of miniosmotic pumps that infuse angiotensin II (AngII, 200 ng/kg/min). Blood pressure (BP), serum lipids and lipoproteins, and histology were also analyzed. These rats did not develop pathological aortic dissection, but we did observe a decrease in circumferential cyclic strain, a rise in BP, and microstructural changes in the aortic medial layer. We also measured increased serum lipids with and without administration of a high-fat diet, but did not detect atherosclerotic plaques. Chronic infusion of AngII did not lead to the formation of dissecting AAAs or atherosclerosis in the rats used in this study. While reduced amounts of atherosclerosis may explain this resistance to dissecting aneurysms, further investigation is needed to fully characterize species-specific differences.


title: Explorations in engagement for humans and robots

abstract: This paper explores the concept of engagement, the process by which individuals in an interaction start, maintain and end their perceived connection to one another. The paper reports on one aspect of engagement among human interactors--the effect of tracking faces during an interaction. It also describes the architecture of a robot that can participate in conversational, collaborative interactions with engagement gestures. Finally, the paper reports on findings of experiments with human participants who interacted with a robot when it either performed or did not perform engagement gestures. Results of the human-robot studies indicate that people become engaged with robots: they direct their attention to the robot more often in interactions where engagement gestures are present, and they find interactions more appropriate when engagement gestures are present than when they are not.


title: Factors Affecting the Online Shopping Behavior: An Empirical Investigation in Vietnam

abstract: Online shopping has become new type of retail shopping. It has now been adopted all over the world including Vietnam. This shopping method is still not as well known or accepted as in many other countries, and though the knowledge of online shopping in Vietnam is now beginning to increase rapidly, to know the factors influencing online shopping behavior of Vietnam consumers there are several articles written. The main objective of this study is to analyze factors affecting on online shopping behavior of consumers that might be one of the most important issues of e-commerce and marketing field. However, there is very limited knowledge about online consumer behavior because it is a complicated socio-technical phenomenon and involves too many factors. The model was assessed based on the data collected from 238 participants using a survey questionnaire. Finally regression analysis was used on data in order to test hypothesizes of study. This study can be considered as an applied research from purpose perspective and descriptive-survey with regard to the nature and method.


title: Effective conditioning of female soccer players

abstract: We compared the efficacy of three physical conditioning programmes provided over a 12 week period (24 h in total) on selected anthropometric and physical fitness parameters in female soccer players. Two of the groups received physical conditioning training in accordance with speed, agility and quickness (SAQ); one group used specialized resistance and speed development SAQ equipment (equipment group; n = 12), while the other group used traditional soccer coaching equipment (non-equipment group; n = 12). A third group received their regular fitness sessions (active control group; n = 12). All three interventions decreased (P <0.001) the participants' body mass index (−3.7%) and fat percentage (−1.7%), and increased their flexibility (+14.7%) and maximal aerobic capacity ([Vdot]O2max) (+18.4%). The participants in the equipment and non-equipment conditioning groups showed significantly (P <0.005) greater benefits from their training programme than those in the active control group by performing significantly better on the sprint to fatigue (−11.6% for both the equipment and non-equipment groups versus −6.2% for the active control group), 25 m sprint (−4.4% vs −0.7%), left (−4.5% vs −1.0%) and right (−4.0% vs −1.4%) side agility, and vertical (+18.5% vs +4.8%) and horizontal (+7.7% vs +1.6%) power tests. Some of these differences in improvements in physical fitness between the equipment and non-equipment conditioning groups on the one hand and the active control group on the other hand were probably due to the specificity of the training programmes. It was concluded that SAQ training principles appear to be effective in the physical conditioning of female soccer players. Moreover, these principles can be implemented during whole team training sessions without the need for specialized SAQ equipment. Finally, more research is required to establish the relationship between physical fitness and soccer performance as well as the principles underlying the improvements seen through the implementation of SAQ training programmes.


title: Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization

abstract: There is a natural correlation between the visual and auditive elements of a video. In this work we leverage this connection to learn general and effective models for both audio and video analysis from self-supervised temporal synchronization. We demonstrate that a calibrated curriculum learning scheme, a careful choice of negative examples, and the use of a contrastive loss are critical ingredients to obtain powerful multi-sensory representations from models optimized to discern temporal synchronization of audio-video pairs. Without further finetuning, the resulting audio features achieve performance superior or comparable to the state-of-the-art on established audio classification benchmarks (DCASE2014 and ESC-50). At the same time, our visual subnet provides a very effective initialization to improve the accuracy of video-based action recognition models: compared to learning from scratch, our self-supervised pretraining yields a remarkable gain of +19.9% in action recognition accuracy on UCF101 and a boost of +17.7% on HMDB51.


title: Survey on Abstractive Text Summarization

abstract: This paper provides a review on some of the significant research work done on abstractive text summarization. The process of generating the summary from one or more text corpus, by keeping the key points in the corpus is called text summarization. The most prominent technique in text summarization is an abstractive and extractive method. The extractive summarization is purely based on the algorithm and it just copies the most relevant sentence/words from the input text corpus and creating the summary. An abstractive method generates new sentences/words that may/may not be in the input corpus. This paper focuses on the abstractive text summarization. This paper explains the overview of the various processes in abstractive text summarization. It includes data processing, word embedding, basic model architecture, training, and validation process and the paper narrates the current research in this field. It includes different types of architectures, attention mechanism, supervised and reinforcement learning, the pros and cons of different architecture. Systematic comparison of different text summarization models will provide the future direction of text summarization.


title: A Brief Review of Snubber Circuits for Flyback Converter

abstract: This paper reviews the different snubber circuit topologies for flyback converters. At low power levels, flyback converters are required to operate at fast switching frequencies to achieve higher power densities, low flux linkage and reduced converter size. However, at high frequencies, switching losses in flyback converters increase along with voltage and current stresses on the main electronic switches. Moreover, additional stored energy in the transformer's leakage inductance can give rise to high EMI losses and reduce the overall efficiency of the converter. Different proposed snubber circuit schemes to mitigate these problems in a flyback converter are reviewed and discussed. Finally, the features of these snubber circuits are analyzed and compared based on their advantages, possible improvements and number of components used.


title: Designing for Labour: Uber and the On-Demand Mobile Workforce

abstract: Apps allowing passengers to hail and pay for taxi service on their phone? such as Uber and Lyft-have affected the livelihood of thousands of workers worldwide. In this paper we draw on interviews with traditional taxi drivers, rideshare drivers and passengers in London and San Francisco to understand how "ride-sharing" transforms the taxi business. With Uber, the app not only manages the allocation of work, but is directly involved in "labour issues": changing the labour conditions of the work itself. We document how Uber driving demands new skills such as emotional labour, while increasing worker flexibility. We discuss how the design of new technology is also about creating new labour opportunities -- jobs -- and how we might think about our responsibilities in designing these labour relations.


Gaussian Prediction Based Attention for Online End-to-End Speech Recognition.


title: Present status and self-reported diseases of the Korean atomic bomb survivors: a mail questionnaire survey.

abstract: Many Koreans were forced to move to Japan while Korea was occupied by Japan. Consequently, when the atomic bombs were dropped on Hiroshima and Nagasaki an estimated 40,000 Koreans died and 30,000 survived. In 2004, 2,235 Koreans were registered as A-bomb survivors in South Korea. A mail questionnaire survey to evaluate the present status and self-reported diseases of the Korean survivors was conducted. In total, 1,256 questionnaires were returned and analysed. The most frequent chronic diseases reported by Korean survivors were hypertension (40.1 per cent), peptic ulcer disease (25.7 per cent), anaemia (23.3 per cent) and cataracts (23.1 per cent). The most frequent malignant diseases were stomach cancer (1.9 per cent), colon cancer (0.5 per cent) and leukaemia/multiple myeloma (0.4 per cent). This study suggests that further investigations are needed into the health concerns of the survivors and into health protection measures.


title: Zero-Shot Adaptive Transfer for Conversational Language Understanding

abstract: Conversational agents such as Alexa and Google Assistant constantly need to increase their language understanding capabilities by adding new domains. A massive amount of labeled data is required for training each new domain. While domain adaptation approaches alleviate the annotation cost, prior approaches suffer from increased training time and suboptimal concept alignments. To tackle this, we introduce a novel Zero-Shot Adaptive Transfer method for slot tagging that utilizes the slot description for transferring reusable concepts across domains, and enjoys efficient training without any explicit concept alignments. Extensive experimentation over a dataset of 10 domains relevant to our commercial personal digital assistant shows that our model outperforms previous state-of-the-art systems by a large margin, and achieves an even higher improvement in the low data regime.


title: Addressing Security and Privacy Challenges in Internet of Things

abstract: Internet of Things (IoT), also referred to as the Internet of Objects, is envisioned as a holistic and transformative approach for providing numerous services. The rapid development of various communication protocols and miniaturization of transceivers along with recent advances in sensing technologies offer the opportunity to transform isolated devices into communicating smart things. Smart things, that can sense, store, and even process electrical, thermal, optical, chemical, and other signals to extract user-/environment-related information, have enabled services only limited by human imagination. ::: Despite picturesque promises of IoT-enabled systems, the integration of smart things into the standard Internet introduces several security challenges because the majority of Internet technologies, communication protocols, and sensors were not designed to support IoT. Several recent research studies have demonstrated that launching security/privacy attacks against IoT-enabled systems, in particular wearable medical sensor (WMS)-based systems, may lead to catastrophic situations and life-threatening conditions. Therefore, security threats and privacy concerns in the IoT domain need to be proactively studied and aggressively addressed. In this thesis, we tackle several domain-specific security/privacy challenges associated with IoT-enabled systems.


title: Antimicrobial activities of commercial essential oils and their components against food-borne pathogens and food spoilage bacteria

abstract: This study was undertaken to determine the in vitro antimicrobial activities of 15 commercial essential oils and their main components in order to pre-select candidates for potential application in highly perishable food preservation. The antibacterial effects against food-borne pathogenic bacteria (Listeria monocytogenes, Salmonella Typhimurium, and enterohemorrhagic Escherichia coli O157:H7) and food spoilage bacteria (Brochothrix thermosphacta and Pseudomonas fluorescens) were tested using paper disk diffusion method, followed by determination of minimum inhibitory (MIC) and bactericidal (MBC) concentrations. Most of the tested essential oils exhibited antimicrobial activity against all tested bacteria, except galangal oil. The essential oils of cinnamon, oregano, and thyme showed strong antimicrobial activities with MIC ≥ 0.125 μL/mL and MBC ≥ 0.25 μL/mL. Among tested bacteria, P. fluorescens was the most resistant to selected essential oils with MICs and MBCs of 1 μL/mL. The results suggest that the activity of the essential oils of cinnamon, oregano, thyme, and clove can be attributed to the existence mostly of cinnamaldehyde, carvacrol, thymol, and eugenol, which appear to possess similar activities against all the tested bacteria. These materials could be served as an important natural alternative to prevent bacterial growth in food products.


title: Comparing potential and actual innovators: an empirical study of mobile data services innovation

abstract: Firms are increasingly opening up their innovation efforts to allow users to tap into the benefits they can offer, such as mobile data service (MDS) innovation on iOS and Google Android platforms. For this purpose, platforms typically provide toolkits to facilitate user participation, aiming to create an ecosystem for sustainable innovation. However, with the barriers to user innovation and attrition of existing innovators, it could be challenging for firms to attract and sustain users' MDS innovation. With the possible benefits from user innovation, and considering the challenges faced, firms need to understand how to influence potential user innovators to take part and to encourage extant user innovators to innovate again. However, there is a lack of comprehensive research and understanding of what drives users' intentions to innovate services and the differences in the antecedents of such intention between potential and actual user innovators. Further, although prior studies have suggested that toolkits can support user innovation, little research has theorized and empirically tested their influence. Motivated thus, this study proposes a model based on (1) user innovation theory to explain the antecedents (including toolkit support) of user MDS innovation intention and (2) construal level theory to explain the differential effects of the antecedents for actual and potential user innovators. We tested the model through survey data from potential and actual MDS user innovators on Google Android and iOS platforms. We find that trend leadership and anticipated extrinsic reward influence both potential and actual user innovators' intentions to innovate. However, anticipated recognition and toolkit support affect only actual user innovators, while anticipated enjoyment affects only potential user innovators. Interestingly, toolkit support strengthens the influence of anticipated enjoyment for actual user innovators but weakens its influence for potential user innovators. Further, potential user innovators value anticipated extrinsic rewards less than actual innovators do. The implications for research and practice are discussed.


title: Plant Leaf Recognition using Shape Based Features and Neural Network Classifiers

abstract: This paper proposes an automated system for recognizing plant species based on leaf images. Plant leaf images corresponding to three plant types, are analyzed using two different shape modeling techniques, the first based on the Moments-Invariant (M-I) model and the second on the Centroid- Radii (C-R) model. For the M-I model the first four normalized central moments have been considered and studied in various combinations viz. individually, in joint 2-D and 3-D feature spaces for producing optimum results. For the C-R model an edge detector has been used to identify the boundary of the leaf shape and 36 radii at 10 degree angular separation have been used to build the feature vector. To further improve the accuracy, a hybrid set of features involving both the M-I and C-R models has been generated and explored to find whether the combination feature vector can lead to better performance. Neural networks are used as classifiers for discrimination. The data set consists of 180 images divided into three classes with 60 images each. Accuracies ranging from 90%-100% are obtained which are comparable to the best figures reported in extant literature. Keywords-plant recognition; moment invariants; centroid-radii model; neural network; computer vision.


title: A Chaincode Based Scheme for Fingerprint Feature Extraction Abstract

abstract: A feature extraction method using the chaincode representation of fingerprint ridge contours is presented. The representation allows efficient image quality enhancement and detection of fine minutiae feature points. The direction field is estimated from a set of selected chaincodes. The original gray-scale image is enhanced using a dynamic filtering scheme that takes advantage of the estimated direction flow of the contours. Minutiae are generated using ridge contour following.


title: An Improved Ant Colony Optimization Algorithm Based on Fractional Order Memory for Traveling Salesman Problems

abstract: Ant Colony Optimization (ACO) algorithm has a wide array of applications to solve combinatorial optimization problems, especially Traveling Salesman Problems (TSPs). The major limitations of ACO algorithm are premature convergence, the possibility that trapped in the local optima. In this paper, an improved Ant Colony Optimization algorithm is proposed which uses fractional order difference for pheromone updating and a weighted combined transition probability. The fractional order difference with the characteristic of long-term memory helps the algorithm make full use of the historical information, and the combined transition probability enhances the exploration ability of the algorithm by using the information of a few steps forward. The performance of the proposed algorithm is tested on various data sets from the standard TSP Library compared with the corresponding integer order algorithm and some evolutionary algorithms. According to the empirical results, our algorithm based on fractional order difference overcomes the classic integer order. Furthermore, the results on a number of TSP instances demonstrate that compared with other evolutionary algorithms, the proposed method can obtain the better solutions on most instances with stronger robustness.


title: Electro-Thermal Battery Modeling and Identification for Automotive Applications

abstract: In this paper, a methodology for modeling and identification of the electro-thermal dynamic behavior of batteries is developed with an equivalent circuit model for use in automotive applications. The developed model has a simple structure but can capture sufficient dynamics under both temperature and state of charge (SoC) variation, thus making it applicable for use with real-time model-based estimation algorithms (for example, in state of charge and state of health estimation). A systematic procedure is outlined for the data acquisition and identification process, and experimental results are presented for an A123 lithiumion iron phosphate battery.Copyright © 2009 by ASME


title: Study on frequency response of implantable microphone and vibrating transducer for the gain compensation of implantable middle ear hearing aid

abstract: ACROSS device, which is composed of an implantable microphone, a signal processor, and a vibrating transducer, is a fullyimplantable middle ear hearing device(F-IMEHD) for the recovery of patients with hearing loss. And since a microphone is implanted under skin and tissue at the temporal bones, the amplitude of the sound wave is attenuated by absorption and scattering. And the vibrating transducer attached to the ossicular chain caused also the different displacement from characteristic of the stapes. For the gain control of auditory signals, most of implantable hearing devices with the digital audio signal processor still apply to fitting rules of conventional hearing aid without regard to the effect of the implanted microphone and the vibrating transducer. So it should be taken into account the effect of the implantable microphone and the vibrating transducer to use the conventional audio fitting rule. The aim of this study was to measure gain characteristics caused by the implanted microphone and the vibrating transducer attached to the ossicle chains for the gain compensation of ACROSS device. Differential floating mass transducers (DFMT) of ACROSS device were clipped on four cadaver temporal bones. And after placing the DFMT on them, displacements of the ossicle chain with the DFMT operated by 1 current was measured using laser Doppler vibrometer. And the sensitivity of microphones under the sampled pig skin and the skin of 3 rat back were measured by stimulus of pure tones in frequency from 0.1 to 8.9 kHz. And we confirmed that the microphone implanted under skin showed poorer frequency response in the acoustic high-frequency band than it in the low- to mid- frequency band, and the resonant frequency of the stapes vibration was changed by attaching the DFMT on the incus, the displacement of the DFMT driven with 1 was higher by the amount of about 20 dB than that of cadaver`s stapes driven by the sound presssure of 94 dB SPL in resonance frequency range.


title: OptoCOMM: Introducing a new optical underwater wireless communication modem

abstract: OptoCOMM aims at demonstrating the potential, at physical level, of a communication facility for the SUNRISE platform constituted by an Optical Underwater Wireless Communication (OUWC) module with target performance of 10 Mb/s transmission rate at 10 meters range in shallow medium/high turbidity harbour waters. The module, which is based on blue Light Emitting Diode (LED) units and common photodiodes, is an evolution of the proof-of-principle prototype already proven in laboratory (pool). It will constitute an additional node integrated in the Littoral Ocean Observatory Network (LOON) test-bed of the SUNRISE infrastructures, providing a high speed and short-range communication node, which will complete the capability of acoustic modems already present in the test-bed. Three modules (nodes) will be developed and experimentally demonstrated: one for direct integration with the LOON infrastructures, one, battery powered, to be potentially installed on buoys, Remotely Operated Vehicles (ROVs), etc., and one to be installed on the eFolaga Autonomous Underwater Vehicle (AUV) of the proponents. The paper describes in detail the development of the modems as well as the first lab experiments, where the core technology has been successfully tested.


title: Comparison of main control strategies for DC/DC stage of bidirectional vehicle charger

abstract: This paper presents comparison of two control algorithms for DC/DC converters in vehicle chargers. It presents operation in phase-shifting algorithm and resonant LLC algorithm, their implementation, and test results.


title: Design and Analysis of a Hybrid Permanent Magnet Assisted Synchronous Reluctance Motor Considering Magnetic Saliency and PM Usage

abstract: This paper proposes a new hybrid permanent magnet (PM)-assisted synchronous reluctance motor, where two types of PM materials of rare-earth PMs and ferrite PMs are employed in its rotor. To reduce the usage of rare-earth materials, a hierarchical design method is adopted in its rotor design, in which the design is divided into two levels: saliency ratio design level and PM usage design level. In saliency ratio design level, proper flux barrier dimensions are confirmed based on the principle of reluctance torque maximization. In PM usage design level, the optimal magnet ratio is first determined according to the relationship of main flux and leakage flux. Then, a tradeoff design is conducted to seek the superior combination of low torque ripple, high efficiency, and high power factor. Finally, for the purpose of validation, the electromagnetic performances of the new designed motor are investigated, including torque characteristics and antidemagnetization capabilities of ferrite.


OF PUBLIC PRIVATE PARTERSHIP ( PPP ) OUTCOMES IN E-GOVERNMENT – A SOCIAL CAPITAL PERSPECTIVE


title: Mars Base Camp: An architecture for sending humans to Mars by 2028

abstract: Orion, the Multi-Purpose Crew Vehicle, is a key piece of the NASA human exploration architecture for beyond earth orbit (BEO). Lockheed Martin was awarded the contracts for the design, development, test, and production for Orion up through the Exploration Mission 2 (EM-2). Lockheed Martin is also working on defining the cis-lunar Proving Ground mission architecture, in partnership with NASA. In addition, Lockheed Martin is exploring the definition of Mars missions as the horizon goal to provide input to the plans for human exploration of the solar system. This paper describes an architecture to determine the feasibility of a Mars Base Camp architecture within about a decade. This architecture would involve human exploration of both Martian moons, and provide an opportunity for the crew to interact with pre-staged robotic assets on Mars. This study is a high-level assessment to identify architecture drivers and science opportunities. There are several key tenets for this architecture. For this first human interplanetary mission, system redundancy and a self-rescue capability is required. The number of system developments is minimized, and the use of the already developed systems like the Space Launch System and Orion is maximized. To minimize the number of events that could lead to the loss of the whole crew, the architecture does not require rendezvous and docking of pre-staged elements necessary for crew survival during the mission. This paper will describe the different enabling technologies required. The trajectory assumptions will be described, including the results of studies performed for the transit to Mars and return to Earth, in addition to mission design trades for the exploration of the Martian system. The transfer vehicle module design concept will be detailed. Possible science activities will be described. Study results for propulsion technology, assembly methods, and the mission campaign will also be addressed, as well as a discussion of planned forward work. The results of this architecture study will show that a near term Mars mission is compelling and feasible, and will highlight the required key systems.


title: Auto-Sizing Neural Networks: With Applications to n-gram Language Models

abstract: Neural networks have been shown to improve performance across a range of natural-language tasks. However, designing and training them can be complicated. Frequently, researchers resort to repeated experimentation to pick optimal settings. In this paper, we address the issue of choosing the correct number of units in hidden layers. We introduce a method for automatically adjusting network size by pruning out hidden units through‘1,1 and ‘2,1 regularization. We apply this method to language modeling and demonstrate its ability to correctly choose the number of hidden units while maintaining perplexity. We also include these models in a machine translation decoder and show that these smaller neural models maintain the significant improvements of their unpruned versions.


title: Spatial Cognition and the Brain

abstract: Recent advances in the understanding of spatial cognition are reviewed, focusing on memory for locations in large-scale space and on those advances inspired by single-unit recording and lesion studies in animals. Spatial memory appears to be supported by multiple parallel representations, including egocentric and allocentric representations, and those updated to accommodate self-motion. The effects of these representations can be dissociated behaviorally, developmentally, and in terms of their neural bases. It is now becoming possible to construct a mechanistic neural-level model of at least some aspects of spatial memory and imagery, with the hippocampus and medial temporal lobe providing allocentric environmental representations, the parietal lobe egocentric representations, and the retrosplenial cortex and parieto-occipital sulcus allowing both types of representation to interact. Insights from this model include a common mechanism for the construction of spatial scenes in the service of both imagery and episodic retrieval and a role for the remainder of Papez's circuit in orienting the viewpoint used. In addition, it appears that hippocampal and striatal systems process different aspects of environmental layout (boundaries and local landmarks, respectively) and do so using different learning rules (incidental learning and associative reinforcement, respectively).


title: Full-speed testing of A/D converters

abstract: Improved computer-aided analog-to-digital converter (ADC) characterization methods based on the code density test and spectral analysis using the fast Fourier transform are described. The code density test produces a histogram of the digital output codes of an ADC sampling a known input. The code density can be interpreted to compute the differential and integral nonlinearities, gain error, offset error, and internal noise. Conversion-rate and frequency-dependent behavior can also be measured.


title: CCA-secure ABE with outsourced decryption for fog computing

abstract: Fog computing is not a replacement but an extension of cloud computing for the prevalence of the Internet of Things (IoT) applications. In particular, fog computing inserts a middle layer named fog into the infrastructure of cloud computing to obtain the low latency, mobility and location-awareness. Due to the fog layer, the sensitive data stored in fog computing is facing more sophisticated attacks, such as chosen ciphertext attacks, than that in cloud computing. Currently, the attribute-based encryption (ABE) with outsourced decryption is the best solution for data protection in cloud computing for IoT applications. However, none of the existing schemes are CCA secure. To fill this gap, we firstly propose the CCA security model for ABE with outsourced decryption, and then present a concrete CCA-secure ABE scheme with outsourced decryption. The security analysis and experimental results show that our proposal is secure and practical for fog computing. The CCA security model for ABE with outsourced decryption is proposed.A concrete CCA-secure ABE scheme with outsourced decryption is proposed.The security analysis and experimental results show that our proposal is secure and practical for fog computing.


title: Introduction of Surgical Safety Checklists in Ontario, Canada

abstract: Background Evidence from observational studies that the use of surgical safety checklists results in striking improvements in surgical outcomes led to the rapid adoption of such checklists worldwide. However, the effect of mandatory adoption of surgical safety checklists is unclear. A policy encouraging the universal adoption of checklists by hospitals in Ontario, Canada, provided a natural experiment to assess the effectiveness of checklists in typical practice settings. Methods We surveyed all acute care hospitals in Ontario to determine when surgical safety checklists were adopted. Using administrative health data, we compared operative mortality, rate of surgical complications, length of hospital stay, and rates of hospital readmission and emergency department visits within 30 days after discharge among patients undergoing a variety of surgical procedures before and after adoption of a checklist. Results During 3-month periods before and after adoption of a surgical safety checklist, a total of 101 hospitals performed 109,341 and 106,370 procedures, respectively. The adjusted risk of death during a hospital stay or within 30 days after surgery was 0.71% (95% confidence interval [CI], 0.66 to 0.76) before implementation of a surgical checklist and 0.65% (95% CI, 0.60 to 0.70) afterward (odds ratio, 0.91; 95% CI, 0.80 to 1.03; P = 0.13). The adjusted risk of surgical complications was 3.86% (95% CI, 3.76 to 3.96) before implementation and 3.82% (95% CI, 3.71 to 3.92) afterward (odds ratio, 0.97; 95% CI, 0.90 to 1.03; P = 0.29). Conclusions Implementation of surgical safety checklists in Ontario, Canada, was not associated with significant reductions in operative mortality or complications. (Funded by the Canadian Institutes of Health Research.)


title: Acousto-Ultrasonic Optical Fiber Sensors: Overview and State-of-the-Art

abstract: This paper gives a review of acoustic and ultrasonic optical fiber sensors (OFSs). The review covers optical fiber sensing methods for detecting dynamic strain signals, including general sound and acoustic signals, high-frequency signals, i.e., ultrasonic/ultrasound, and other signals such as acoustic emissions, and impact induced dynamic strain. Several optical fiber sensing methods are included, in an attempted to summarize the majority of optical fiber sensing methods used to date. The OFS include single fiber sensors and optical fiber devices, fiber-optic interferometers, and fiber Bragg gratings (FBGs). The single fiber and fiber device sensors include optical fiber couplers, microbend sensors, refraction-based sensors, and other extrinsic intensity sensors. The optical fiber interferometers include Michelson, Mach-Zehnder, Fabry-Perot, Sagnac interferometers, as well as polarization and model interference. The specific applications addressed in this review include optical fiber hydrophones, biomedical sensors, and sensors for nondestructive evaluation and structural health monitoring. Future directions are outlined and proposed for acousto-ultrasonic OFS.


title: A Comprehensive SOA Governance Framework Based on COBIT

abstract: SOA governance has a critical role in achieving success and realizing the benefits of SOA. Without effective SOA governance, organizations will experience some predictable challenges including difficulties in designing effective decision structures and building a SOA roadmap, lack of service funding, lack of consistent governance processes and gap between IT and business. Study of existing SOA governance frameworks reveals that these frameworks do not completely document SOA processes, governance procedures and SOA roadmap, and also they are not expressive enough to cover all important elements of SOA governance. Therefore, in this paper, we propose a new framework named AUT SOA governance framework based on COBIT that is more comprehensive and expressive than its counterparts. The proposed framework is obtained by enforcing control and governance aspects of COBIT and applying service management activities into a lifecycle approach. This framework is a perceptible framework that clarifies all processes, their relationships, related roles and responsibilities and measurement metrics and promotes control and policy enforcement by defining management control objectives. Also, imperative elements of SOA governance that existing frameworks do not cover them completely specially, service portfolio management, SOA roadmap, performance metrics and evaluation processes have been completely added and described in this framework.


How Much Attention Do You Need? A Granular Analysis of Neural Machine Translation Architectures


title: Does Use of Text-to-Speech and Related Read-Aloud Tools Improve Reading Comprehension for Students With Reading Disabilities? A Meta-Analysis:

abstract: Text-to-speech and related read-aloud tools are being widely implemented in an attempt to assist students’ reading comprehension skills. Read-aloud software, including text-to-speech, is used to translate written text into spoken text, enabling one to listen to written text while reading along. It is not clear how effective text-to-speech is at improving reading comprehension. This study addresses this gap in the research by conducting a meta-analysis on the effects of text-to-speech technology and related read-aloud tools on reading comprehension for students with reading difficulties. Random effects models yielded an average weighted effect size of (d¯ = .35, with a 95% confidence interval of .14 to .56, p < .01). Moderator effects of study design were found to explain some of the variance. Taken together, this suggests that text-to-speech technologies may assist students with reading comprehension. However, more studies are needed to further explore the moderating variables of text-to-speech and read-a...


title: UAV-Enabled Radio Access Network: Multi-Mode Communication and Trajectory Design

abstract: In this paper, we consider an unmanned aerial vehicle (UAV)-enabled radio access network (RAN) with the UAV acting as an aerial platform to communicate with a set of ground users (GUs) in a variety of modes of practical interest, including data collection in the uplink, data transmission in the downlink, and data relaying between GUs involving both the uplink and downlink. Under this general framework, two UAV operation scenarios are considered: periodic operation, where the UAV serves the GUs in a periodic manner by following a certain trajectory repeatedly, and one-time operation where the UAV serves the GUs with one single fly and then leaves for another mission. In each scenario, we aim to minimize the UAV periodic flight duration or mission completion time, while satisfying the target rate requirement of each GU via a joint UAV trajectory and communication resource allocation design approach. Iterative algorithms are proposed to find efficient locally optimal solutions by utilizing successive convex optimization and block coordinate descent techniques. Moreover, as the quality of the solutions obtained by the proposed algorithms critically depends on the initial UAV trajectory adopted, we propose new methods to design the initial trajectories for both operation scenarios by leveraging the existing results for solving the classic Traveling Salesman Problem (TSP) and Pickup-and-Delivery Problem (PDP). Numerical results show that the proposed trajectory initialization designs lead to significant performance gains compared to the benchmark initialization based on circular trajectory.


title: Revisiting the hallmarks of cancer.

abstract: The hallmarks of cancer described by Hanahan and Weinberg have proved seminal in our understanding of cancer's common traits and in rational drug design. Not free of critique and with understanding of different aspects of tumorigenesis coming into clearer focus in the recent years, we attempt to draw a more organized and updated picture of the cancer hallmarks. We define seven hallmarks of cancer: selective growth and proliferative advantage, altered stress response favoring overall survival, vascularization, invasion and metastasis, metabolic rewiring, an abetting microenvironment, and immune modulation, while highlighting some considerations for the future of the field.


title: Models for Teaching Culture in Computer-Assisted Language Learning

abstract: CALL (computer-assisted language learning) has tremendously transformed the teaching of language, with its wide application in many aspects of language teaching. However, how to integrate CALL into the teaching of culture is still rarely discussed. The purpose of the paper is to explore feasible models for teaching culture in CALL and their effects on students’ acquisition process. Based on two fundamental pedagogical approaches (participatory pedagogy and multiliteracies pedagogy) for teaching culture, this paper proposes three pedagogical models (problem-posing model, web-quest model, and computer-supported collaborative learning model) for teaching culture in CALL. In the end, this paper illustrates a combination of the three models in real CALL setting by a cultural teaching case. A questionnaire survey and interviews are conducted to reflect on students’ feedback, which gives an insight into possible adjustments in teaching models and the paper also proposes future possibilities in applying these models into teaching culture.


title: A 0.8-V, 1-MS/s, 10-bit SAR ADC for Multi-Channel Neural Recording

abstract: This paper presents a 10-bit single-ended SAR ADC suitable for multi-channel neural recording. The proposed ADC introduces several power saving techniques to boost the energy efficiency. The ADC is built with on-chip common-mode buffer for input tracking, which is reused as the pre-amplifier of a current-mode comparator during conversion. A small capacitor is inserted between the amplifier and the capacitive DAC array in order to reduce the capacitive load on the amplifier. A split capacitor array with dual thermometer decoders is proposed to reduce the switching energy. Implemented in 0.13- $\mu{\rm m}$ CMOS technology, the ADC achieved a maximum differential nonlinearity (DNL) of $-$ 0.33/ $+$ 0.56 LSB, maximum integral nonlinearity (INL) of $-$ 0.61/ $+$ 0.55 LSB, effective number-of-bits (ENOB) of 8.8, and a power consumption of 9- $\mu{\rm W}$ .


title: DESIGN OF A CIRCULARLY POLARIZED MICROSTRIP ANTENNA FOR WLAN

abstract: The design and performance of a circularly polarized microstrip patch antenna, for the application in Wireless Local Area Network (WLAN), are reported here. The antenna is a proximity coupled microstrip patch antenna where the radiating patch is loaded by a V-slot. This miniaturized microstrip antenna has wide bandwidth in the frequency band of WLAN and exhibits circularly polarized far field with very good axial ratio bandwidth. The simulated results using IE3D software are verified by measurement.


Multiclass Classification of Unconstrained Handwritten Arabic Words Using Machine Learning Approaches


title: Lessons Learned: The Complexity of Accurate Identification of in-Text Citations

abstract: The importance of citations is widely recognized by the scientific community. Citations are being used in making a number of vital decisions such as calculating impact factor of journals, calculating impact of a researcher (H-Index), ranking universities and research organizations. Furthermore, citation indexes, along with other criteria, employ citation counts to retrieve and rank relevant research papers. However, citing patterns and in-text citation frequency are not used for such important decisions. The identification of in-text citation from a scientific document is an important problem. However, identification of in-text citation is a tough ask due to the ambiguity between citation tag and content. This research focuses on in-text citation analysis and makes the following specific contributions such as: Provides detailed in-text citation analysis on 16,000 citations of an online journal, reports different pattern of citations-tags and its in-text citations and highlights the problems (mathematical ambiguities, wrong allotments, commonality in content and string variation) in identifying in-text citations from scientific documents. The accurate identification of in-text citations will help information retrieval systems, digital libraries and citation indexes.


title: Insights from Deploying See-Through Augmented Reality Signage in the Wild

abstract: Typically the key challenges with interactive digital signage are (1) interaction times are short (usually in the order of seconds), (2) interaction needs to be very easy to understand, and (3) interaction needs to provide a benefit that justifies the effort to engage. To tackle these challenges, we propose a see-through augmented reality application for digital signage that enables passersby to observe the area behind the display, augmented with useful data. We report on the development and deployment of our application in two public settings: a public library and a supermarket. Based on observations of 261 (library) and 661 (supermarket) passersby and 14 interviews, we provide early insights and implications for application designers. Our results show a significant increase in attention: the see-through signage was noticed by 46% of the people, compared to 14% with the non-see through version. Furthermore, findings indicate that to best benefit the passersby, the AR displays should clearly communicate their purpose.


title: Minimization of cogging torque in a small axial-flux PMSG with a parallel-teeth stator

abstract: A stator with a steel core is well suited for small, low speed PM machines, where core losses are much lower than copper losses. However, a slotted stator introduces cogging torque. A stator with parallel-teeth inherently lowers cogging torque but there is need to further reduce it. This is particularly important in wind generators since it raises the cut-in wind speed, thereby lowering the energy captured yield for a given installed capacity. Pulsating torques also produces noise and mechanical vibrations which accelerates the wear of the machine and its support structure. This paper presents some effective methods of minimizing cogging torque, which have minimal effects on the performance of the machine. Three PM rotor configurations were considered, which include: a pole-arc ratio of 0.80, alternating pole-arcs of 0.61 and 0.80, and skewed PM poles with a skew one slot-pitch. The 3 rotor configurations were simulated numerically using 3D Finite Element Analysis (FEA) and tested experimentally with the same stator. The machine topology with a rotor pole-arc ratio of 0.80 was used as the reference design. From the experimental results, the alternating pole-arcs effectively reduced cogging-torque by 73% whereas the skewed poles reduced it by 48%. The 3D-FEA and experimental cogging torque results are also comparable. The paper also compares cogging torque reduction techniques which are well suited for a parallel-teeth stator.