title: A modelling case study of an island mode solar power plant

abstract: This paper deals with efficiency analysis of a solar power plant that is considered to be installed in island mode with 2 kWp rated power. The test bed designed in Simulink© consists of solar panel, buck converter, and H-bridge inverter models all based to analytical concepts. The solar panel model is designed according to equation of a solar cell, and all the required parameters such as open circuit voltage, short circuit current etc are considered in order to modify the output power regarding to a commercial photovoltaic (PV) panel. The dc-dc conversion is performed with a buck converter where the optimal duty cycle is dynamically updated by a proportional-integral (PI) controlled generator. The settling time and dc voltage ripples are minimized to increase the efficiency of the dc-dc converter. On the other hand, the single-phase inverter is constructed with an H-bridge that is the most basic multilevel topology known ever. The main intention during the inverter operation was decreasing the total harmonic distortion (THD) ratios as much as possible. Therefore, the modulation scheme is particularly applied to decrease THD by eliminating side band harmonics. The line voltage is properly fixed to 220V/50Hz that is common in northern and central Europe. The THD ratio of the line voltage is measured at 0.03%, while the THD of the current is 0.82%. The power factor of the entire system is measured as 0.99 considering the 8.1° phase displacement between current and voltage waveforms. The analysis results verify the efficiency of the proposed solar power plant and its components.


title: Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis

abstract: Program synthesis is the task of automatically generating a program consistent with a specification. Recent years have seen proposal of a number of neural approaches for program synthesis, many of which adopt a sequence generation paradigm similar to neural machine translation, in which sequence-to-sequence models are trained to maximize the likelihood of known reference programs. While achieving impressive results, this strategy has two key limitations. First, it ignores Program Aliasing: the fact that many different programs may satisfy a given specification (especially with incomplete specifications such as a few input-output examples). By maximizing the likelihood of only a single reference program, it penalizes many semantically correct programs, which can adversely affect the synthesizer performance. Second, this strategy overlooks the fact that programs have a strict syntax that can be efficiently checked. To address the first limitation, we perform reinforcement learning on top of a supervised model with an objective that explicitly maximizes the likelihood of generating semantically correct programs. For addressing the second limitation, we introduce a training procedure that directly maximizes the probability of generating syntactically correct programs that fulfill the specification. We show that our contributions lead to improved accuracy of the models, especially in cases where the training data is limited.


title: The role of the cervical spine in post-concussion syndrome

abstract: While much is known regarding the pathophysiology surrounding concussion injuries in the acute phase, there is little evidence to support many of the theorized etiologies to post-concussion syndrome (PCS); the chronic phase of concussion occurring in ∼ 10-15% of concussed patients. This paper reviews the existing literature surrounding the numerous proposed theories of PCS and introduces another potential, and very treatable, cause of this chronic condition; cervical spine dysfunction due to concomitant whiplash-type injury. We also discuss a short case-series of five patients with diagnosed PCS having very favorable outcomes following various treatment and rehabilitative techniques aimed at restoring cervical spine function.


title: Analyzing the Blogosphere for Predicting the Success of Music and Movie Products

abstract: Over the last decade blogs became an important part of the Web, where people can announce anything that is on their mind. Due to their high popularity blogs have great potential to mine public opinions regarding products. Such knowledge is very valuable as it could be used to adjust marketing campaigns or advertisement of products accordingly. In this paper we investigate how the blogosphere can be used to predict the success of products in the domain of music and movies. We analyze and characterize the blogging behavior in both domains particularly around product releases, propose different methods for extracting characteristic features from the blogosphere, and show that our predictions correspond to the real world measures Sales Rank and box office revenue respectively.


title: A Secure Mobile Wallet Framework with Formal Verification

abstract: This paper proposes a Secure Mobile Wallet Framework (SMWF) using WPKI (Wireless Public Key Infrastructure) and UICC (Universal Integrated Circuit Card) by defining (a) a procedure of personalizing UICC by the client, (b) a procedure of provisioning and personalization (Mutual Authentication and Key Agreement Protocol) of Mobile Payments Application (which is on UICC) by the Bank and (c) our proposed mobile wallet is will have mobile wallet manager managed by CA (acting as TSM), every mobile application is independent, protected by firewalls and encrypted data is stored in the mobile wallet application. Their proposed Mobile Wallet ensures end to end security. The authors' proposed SMWF is compared with recent works and found to be better in terms of generating client's credentials, implementation of WPKI in UICC, personalization of mobile payment application by the bank and in ensuring end to end security (i.e., from Mobile Payments Application in UICC to the Bank Server). The proposed mobile payment protocol originating from Mobile Payment Application (which is on UICC) to the Bank Server realizes Fair Exchange ensures Confidentiality, Authentication, Integrity and Non Repudiation, prevents double spending, over spending and money laundering, and withstands replay, Man in the Middle (MITM) and Impersonation attacks. Proposed mobile payment protocol is formally verified using AVISPA and Scyther Tool and presented with results.


title: Photocatalytic Reduction of Hexavalent Chromium over ZnO Nanorods Immobilized on Kaolin

abstract: The photocatalytic reduction of hexavalent chromium (Cr(VI)) using ZnO nanorods immobilized on kaolin clay was studied. Scanning electron microscopy (SEM) and Fourier transform infrared (FT-IR) analysis demonstrated favorable immobilization of ZnO nanorods onto the kaolin. The efficiency of the UV/ZnO/kaolin process for reduction of Cr(VI) was about 88.0%, which was more effective than the UV/ZnO process (43.7%). The photocatalytic reduction of Cr(VI) was increased from 35.7 to 97.1%, with increasing photocatalyst dosage from 0.25 to 3 g/L, respectively. The reaction rate constant (kobs) was decreased from 0.0769 to 0.0072 1/min, and the value of electrical energy per order (EEo) was increased from 62.4 to 666.7 (kW·h/m3) with increasing initial Cr(VI) concentration from 10 to 50 mg/L, respectively. The photocatalytic reduction of Cr(VI) was increased from 88.3 to 98.5% in the presence of citric acid, while the presence of phenol, ethylenediaminetetraacetic acid and oxalic acid resulted in decreasing the ...


title: Task difficulty, risk, effort and comfort in a simulated driving task--Implications for Risk Allostasis Theory

abstract: Abstract Risk Allostasis Theory states that drivers seek to maintain a feeling of risk within a preferred range [Fuller, R., 2008. What drives the driver? Surface tensions and hidden consensus. In: Keynote at the 4th International Conference on Traffic and Transport Psychology, Washington, DC, August 31–September 4, 2008]. Risk Allostasis Theory is the latest version of Task-Difficulty Homeostasis theory, and is in part based on the findings of experiments where participants were asked to rate the task difficulty, feeling of risk and chance of collision of scenes shown in digitally altered video clips [Fuller, R., McHugh, C., Pender, S., 2008b. Task difficulty and risk in the determination of driver behaviour. Revue europeenne de psychologie appliqee 58, 13–21]. The focus of the current research was to expand upon the previous video based experiments using a driving simulator. This allowed participants to be in control of the vehicle rather than acting as passive observers, as well as providing additional speed cues. The results support previous findings that ratings of task difficulty and feeling of risk are related, and that they are also highly related to ratings of effort and moderately related to ratings of comfort and habit. However, the linearly increasing trend for task difficulty and feeling of risk described by the previous research was not observed: instead the findings of this experiment support a threshold effect where ratings of risk (feeling of and chance of loss of control/collision), difficulty, effort, and comfort go through a period of stability and only start to increase once a certain threshold has been crossed. It is within the period of stability where subjective experience of risk and difficulty is low, or absent, that drivers generally prefer to operate.


title: Virtual topology mapping in elastic optical networks

abstract: Virtualization improves the efficiency of networks by allowing multiple virtual networks to share a single physical network's resources. Next-generation optical transport networks are expected to support virtualization by accommodating multiple virtual networks with different topologies and bit rate requirements. Meanwhile, Optical Orthogonal Frequency-Division Multiplexing (OOFDM) is emerging as a viable technique for efficiently using the optical fiber's bandwidth in an elastic manner. OOFDM partitions the fiber's bandwidth into hundreds or even thousands of OFDM subcarriers that may be allocated to services. In this paper, we consider an OOFDM-based optical network and formulate a virtual network mapping problem for both static and dynamic traffic. This problem has several natural applications, such as e-Science, Grid, and cloud computing. The objective for static traffic is to maximize the subcarrier utilization, while minimizing the blocking ratio is the aim for dynamic traffic. Two heuristics are proposed and compared. Simulation results are presented to demonstrate the effectiveness of the proposed approaches.


title: Recent Advances in the Applications of Convolutional Neural Networks to Medical Image Contour Detection

abstract: The fast growing deep learning technologies have become the main solution of many machine learning problems for medical image analysis. Deep convolution neural networks (CNNs), as one of the most important branch of the deep learning family, have been widely investigated for various computer-aided diagnosis tasks including long-term problems and continuously emerging new problems. Image contour detection is a fundamental but challenging task that has been studied for more than four decades. Recently, we have witnessed the significantly improved performance of contour detection thanks to the development of CNNs. Beyond purusing performance in existing natural image benchmarks, contour detection plays a particularly important role in medical image analysis. Segmenting various objects from radiology images or pathology images requires accurate detection of contours. However, some problems, such as discontinuity and shape constraints, are insufficiently studied in CNNs. It is necessary to clarify the challenges to encourage further exploration. The performance of CNN based contour detection relies on the state-of-the-art CNN architectures. Careful investigation of their design principles and motivations is critical and beneficial to contour detection. In this paper, we first review recent development of medical image contour detection and point out the current confronting challenges and problems. We discuss the development of general CNNs and their applications in image contours (or edges) detection. We compare those methods in detail, clarify their strengthens and weaknesses. Then we review their recent applications in medical image analysis and point out limitations, with the goal to light some potential directions in medical image analysis. We expect the paper to cover comprehensive technical ingredients of advanced CNNs to enrich the study in the medical image domain.


title: Phrase-based Image Captioning with Hierarchical LSTM Model

abstract: Automatic generation of caption to describe the content of an image has been gaining a lot of research interests recently, where most of the existing works treat the image caption as pure sequential data. Natural language, however possess a temporal hierarchy structure, with complex dependencies between each subsequence. In this paper, we propose a phrase-based hierarchical Long Short-Term Memory (phi-LSTM) model to generate image description. In contrast to the conventional solutions that generate caption in a pure sequential manner, our proposed model decodes image caption from phrase to sentence. It consists of a phrase decoder at the bottom hierarchy to decode noun phrases of variable length, and an abbreviated sentence decoder at the upper hierarchy to decode an abbreviated form of the image description. A complete image caption is formed by combining the generated phrases with sentence during the inference stage. Empirically, our proposed model shows a better or competitive result on the Flickr8k, Flickr30k and MS-COCO datasets in comparison to the state-of-the art models. We also show that our proposed model is able to generate more novel captions (not seen in the training data) which are richer in word contents in all these three datasets.


title: Using Examples for Teaching Software Design: An Experiment Using a Repository of UML Class Diagrams

abstract: Context: This research is positioned in the field of methods for creating software design and the teaching thereof. Goal: The goal of this research is to study the effects of using a collection of examples for creating a software design. Method: We ran a controlled experiment for evaluating the use of a broad collection of examples for creating software designs by software engineering students. In this study, we focus on software designs as represented through UML class diagrams. The treatment is the use of the collection of examples. These examples are offered via a searchable repository. The outcome variable we study is the quality of the design (as assessed by a group of experts). After this, all students were offered the opportunity to improve their design using the collection of examples. We ran a post-assignment questionnaire to collect qualitative data about the experience of the participants. Results: Considering six quality attributes measured by experts, our results show that: 1) the models of the students who used examples are 18% better than those of who did not use examples. 2) the models of the students who did not use examples for constructing became 19% better after updating their models using examples. We complement our statistical analysis with insights from the post assignment questionnaire. Also, we observed that students are more confident about their design when they use examples. Conclusion: Students deliver better software designs when they use a collection of example software designs.


Design and Simulation of Perturb and Observe MPPT Algorithm for 72 Cell Solar PV System


title: Approximation algorithms design for disk partial covering problem

abstract: Mobile servers are established to provide services for mobile nodes in an anticipated area. If the distribution of mobile nodes can be foreseen, the location of mobile servers becomes critical to the QoS of wireless systems. Under resource and topology constraints, it is very difficult to figure out a solution, or unable to cover all given mobile nodes within limited number of mobile servers. In this paper, we study the issue of the partial covering problem such that part of mobile nodes to be covered. Several approximation algorithms are proposed to cover the maximum number of elements. For real time systems, such as the battlefield communication system, the proposed algorithms with polynomial-time complexity can be efficiently applied. The algorithm complexity analysis illustrates the improvement made by our algorithms. The experimental results show that the performance of our algorithms is much better than other existing 3-approximation algorithm for the robust k-center problem.


title: Penile measurements in normal adult Jordanians and in patients with erectile dysfunction

abstract: The purpose of this work was to determine penile size in adult normal (group one, 271) and impotent (group two, 109) Jordanian patients. Heights of the patients, the flaccid and fully stretched penile lengths were measured in centimeters in both groups. Midshaft circumference in the flaccid state was recorded in group one. Penile length in the fully erect penis was measured in group two. In group one mean midshaft circumference was 8.98+/-1.4, mean flaccid length was mean 9.3+/-1.9, and mean stretched length was 13.5+/-2.3. In group two, mean flaccid length was 7.7+/-1.3, and mean stretched length was 11.6+/-1.4. The mean of fully erect penile length after trimex injection was 11.8+/-1.5. In group 1 there was no correlation between height and flaccid length or stretched length, but there was a significant correlation between height and midpoint circumference, flaccid and stretched lengths, and between stretched lengths and midpoint circumference. In group 2 there was no correlation between height and flaccid, stretched, or fully erect lengths. On the other hand, there was a significant correlation between the flaccid, stretched and fully erect lengths. Comparing group 1 and group 2, the patients in group 1 were slightly older than in group 2 (P=0.035), but there was no significant difference in their height. However, there was a significant difference regarding the mean flaccid length 9.3 vs 7.7 (P=0.001), and the mean stretched length 13.5 vs 11.6 (P=0.000). We divided both groups into those who are less than 40 y of age, and over 40 y old. There was no statistical difference in the stretched and flaccid lengths between the younger and older individuals in each group. However, when we compared the stretched and flaccid lengths in those of less than 40 y old in group 1 and 2, a significant difference was noticed. Similarly, a significant difference in the stretched and flaccid lengths in those patients over 40 y of age was also present.


title: A Fiber Bragg Grating Sensor System for Train Axle Counting

abstract: Railway signaling facilitates two main functions, namely, train detection and train control, in order to maintain safe separations among the trains. Track circuits are the most commonly used train detection means with the simple open/close circuit principles; and subsequent adoption of axle counters further allows the detection of trains under adverse track conditions. However, with electrification and power electronics traction drive systems, aggravated by the electromagnetic interference in the vicinity of the signaling system, railway engineers often find unstable or even faulty operations of track circuits and axle counting systems, which inevitably jeopardizes the safe operation of trains. A new means of train detection, which is completely free from electromagnetic interference, is therefore required for the modern railway signaling system. This paper presents a novel optical fiber sensor signaling system. The sensor operation, field setup, axle detection solution set, and test results of an installation in a trial system on a busy suburban railway line are given.


title: Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation

abstract: Today, increasing attention is being paid to research into spike-based neural computation both to gain a better understanding of the brain and to explore biologically-inspired computation. Within this field, the primate visual pathway and its hierarchical organisation have been extensively studied. Spiking Neural Networks (SNNs), inspired by the understanding of observed biological structure and function, have been successfully applied to visual recognition and classification tasks. In addition, implementations on neuromorphic hardware have enabled large-scale networks to run in (or even faster than) real time, making spike-based neural vision processing accessible on mobile robots. Neuromorphic sensors such as silicon retinas are able to feed such mobile systems with real-time visual stimuli. A new set of vision benchmarks for spike-based neural processing are now needed to measure progress quantitatively within this rapidly advancing field. We propose that a large dataset of spike-based visual stimuli is needed to provide meaningful comparisons between different systems, and a corresponding evaluation methodology is also required to measure the performance of SNN models and their hardware implementations. In this paper we first propose an initial NE (Neuromorphic Engineering) dataset based on standard computer vision benchmarks and that uses digits from the MNIST database. This dataset is compatible with the state of current research on spike-based image recognition. The corresponding spike trains are produced using a range of techniques: rate-based Poisson spike generation, rank order encoding, and recorded output from a silicon retina with both flashing and oscillating input stimuli. In addition, a complementary evaluation methodology is presented to assess both model-level and hardware-level performance. Finally, we demonstrate the use of the dataset and the evaluation methodology using two SNN models to validate the performance of the models and their hardware implementations. With this dataset we hope to (1) promote meaningful comparison between algorithms in the field of neural computation, (2) allow comparison with conventional image recognition methods, (3) provide an assessment of the state of the art in spike-based visual recognition, and (4) help researchers identify future directions and advance the field.


The Dundee Treebank


The Application of the Maturity Model SIMMI 4.0 in Selected Enterprises.


Biometric recognition using three-dimensional ear shape


title: Performance characterization of a high power dual active bridge DC/DC converter

abstract: The performance of a high-power, high-power-density DC-to-DC converter based on the single-phase dual active bridge (DAB) topology is described. The dual active bridge converter has been shown to have very attractive features in terms of low device and component stresses, small filter components, low switching losses, high power density and high efficiency, bidirectional power flow, buck-boost operation, and low sensitivity to system parasitics. For high output voltages, on the order of kilovolts, a cascaded output structure is considered. The effects of snubber capacitance and magnetizing inductance on the soft switching region of control are discussed. Various control schemes are outlined. Coaxial transformer design techniques have been utilized to carefully control leakage inductance. The layout and experimental performance of a prototype 50 kW 50 kHz unit operating with an input voltage of 200 V DC and an output voltage of 1600 V DC are presented. >


title: MACRANSAC: a robust algorithm for the recognition of multiple objects

abstract: This paper addresses the problem of recognizing multiple rigid objects that are common to two images. We propose a generic algorithm that allows to simultaneously decide if one or several objects are common to the two images and to estimate the corresponding geometric transformations. The considered transformations include similarities, homographies and epipolar geometry. We first propose a generalization of an "a contrario" formulation of the RANSAC algorithm proposed in [Moisan and Stival 04]. We then introduce an algorithm for the detection of multiple transformations between images and show its efficiency on various experiments.


title: Implementing Image Processing Algorithms on FPGAs

abstract: FPGAs are often used as implementation platforms for real-time image processing applications because their structure is able to exploit spatial and temporal parallelism. Such parallelisation is subject to the processing mode and hardware constraints of the system. These constraints can force the designer to reformulate the algorithm. This paper presents some general techniques for dealing with the various constraints and efficient mappings for three types of image processing operations.


title: Towards Privacy-Aware Smart Buildings: Capturing, Communicating, and Enforcing Privacy Policies and Preferences

abstract: The Internet of Things (IoT) is changing the way we interact with our environment in domains as diverse as health, transportation, office buildings and our homes. In smart building environments, information captured about the building and its inhabitants will aid in development of services that improve productivity, comfort, social interactions, safety, energy savings and more. However, by collecting and sharing information about building's inhabitants and their activities, these services also open the door to privacy risks. In this paper, we introduce a framework where IoT Assistants capture and manage the privacy preferences of their users and communicate them to privacy-aware smart buildings, which enforce them when collecting user data or sharing it with building services. We outline elements necessary to support such interactions and also discuss important privacy policy attributes that need to be captured. This includes looking at attributes necessary to describe -- (1) the data collection and sharing practices associated with deployed sensors and services in smart buildings as well as (2) the privacy preferences to help users manage their privacy in such environments.


title: The impact of ERP systems on organizational performance: In Lebanese wholesale engineering companies

abstract: This research explores the effect of the implementation status of Enterprise Resource Planning ERP system on operational performance. Through the use of questionnaire, the collected data indicated that the implementation status of ERP modules have a positive varying effect on operational performance measures. The results also showed that each of the modules have an impact on the overall operational performance, specifically Controlling 37.5%, Sales and distribution 37.4%, Customer relationship management 37.4%, Project System 28.4%, General Logistics 24.7%, Materials Management 24.1%, Advance planner and optimizer/Advance planner and scheduler 19.6% and Financials 18.7%


title: Counter Chain: A New Block Cipher Mode of Operation

abstract: In this paper, we propose a novel block cipher mode of operation, which is known as the counter chain (CC) mode. The proposed CC mode integrates the cipher block chaining (CBC) block cipher mode of operation with the counter (CTR) mode in a consistent fashion. In the CC mode, the confidentiality and authenticity of data are assured by the CBC mode, while speed is achieved through the CTR mode. The proposed mode of operation overcomes the parallelization deficiency of the CBC mode and the chaining dependency of the counter mode. Experimental results indicate that the proposed CC mode achieves the encryption speed of the CTR mode, which is exceptionally faster than the encryption speed of the CBC mode. Moreover, our proposed CC mode provides better security over the CBC mode. In summary, the proposed CC block cipher mode of operation takes the advantages of both the Counter mode and the CBC mode, while avoiding their shortcomings.


title: Shape descriptors for non-rigid shapes with a single closed contour

abstract: The Core Experiment CE-Shape-1 for shape descriptors performed for the MPEG-7 standard gave a unique opportunity to compare various shape descriptors for non-rigid shapes with a single closed contour. There are two main differences with respect to other comparison results reported in the literature: (1) For each shape descriptor the experiments were carried out by an institute that is in favor of this descriptor. This implies that the parameters for each system were optimally determined and the implementations were thoroughly rested. (2) It was possible to compare the performance of shape descriptors based on totally different mathematical approaches. A more theoretical comparison of these descriptors seems to be extremely hard. In this paper we report on the MPEG-7 Core Experiment CE-Shape.


Benchmarking question answering systems


title: Achieving real-time communication over Ethernet with adaptive traffic smoothing

abstract: Ethernet continues to be one of the most popular LAN technologies. Due to the low price and robustness resulting from its wide acceptance and deployment, there has been an attempt to build Ethernet-based real-time control networks for manufacturing automation. However, it is difficult to build a real-time control network using the standard UDP or TCP/IP and Ethernet, because the Ethernet MAC protocol, the 1-persistent CSMA/CD protocol has unpredictable delay characteristics. When both real-time (RT) and non-real-time packets are transported over an ordinary Ethernet, RT packets from a node may experience a large delay due to: contention with non-RT packets in the originating node; and collision with RT and non-RT packets from the other nodes. To resolve this problem, we designed, implemented, and evaluated adaptive traffic smoothing. Specifically, a traffic smoother is installed between the UDP or TCP/IP layer and the Ethernet MAC layer, and works as an interface between them. The traffic smoother first gives RT packets priority over non-RT packets in order to eliminate contention within each local node. Second, it smooths a non-RT stream so as to reduce collision with RT packets from the other nodes. This traffic smoothing can dramatically decrease the packet-collision ratio on the network.


title: ButterflyNet: a mobile capture and access system for field biology research

abstract: Through a study of field biology practices, we observed that biology fieldwork generates a wealth of heterogeneous information, requiring substantial labor to coordinate and distill. To manage this data, biologists leverage a diverse set of tools, organizing their effort in paper notebooks. These observations motivated ButterflyNet, a mobile capture and access system that integrates paper notes with digital photographs captured during field research. Through ButterflyNet, the activity of leafing through a notebook expands to browsing all associated digital photos. ButterflyNet also facilitates the transfer of captured content to spreadsheets, enabling biologists to share their work. A first-use study with 14 biologists found this system to offer rich data capture and transformation, in a manner felicitous with current practice.


title: Smart Coat with a Fully-Embedded Textile Antenna for IoT Applications

abstract: The Internet of Things (IoT) scenario is strongly related with the advance of the development of wireless sensor networks (WSN) and radio frequency identification (RFID) systems. Additionally, in the WSN context, for a continuous feed, the integration of textile antennas for energy harvesting into smart clothing is a particularly interesting solution when the replacement of batteries is not easy to practice, such as in wearable devices. This paper presents the E-Caption: Smart and Sustainable Coat. It has an embedded dual-band textile antenna for electromagnetic energy harvesting, operating at global system for mobile communication (GSM) 900 and digital cellular system (DCS) 1800 bands. This printed antenna is fully integrated, as its dielectric is the textile material composing the coat itself. The E-Caption illustrates the innovative concept of textile antennas that can be manipulated as simple emblems. Seven prototypes of these “emblem” antennas, manufactured by lamination and embroidering techniques are also presented. It is shown that the orientation of the conductive fabric does not influence the performance of the antenna. It is also shown that the direction and number of the stitches in the embroidery may influence the performance of the antenna. Moreover, the comparison of results obtained before and after the integration of the antenna into cloth shows the integration does not affect the behavior of the antenna.


title: Wavelet Domain Residual Network (WavResNet) for Low-Dose X-ray CT Reconstruction

abstract: Model based iterative reconstruction (MBIR) algorithms for low-dose X-ray CT are computationally complex because of the repeated use of the forward and backward projection. Inspired by this success of deep learning in computer vision applications, we recently proposed a deep convolutional neural network (CNN) for low-dose X-ray CT and won the second place in 2016 AAPM Low-Dose CT Grand Challenge. However, some of the texture are not fully recovered, which was unfamiliar to some radiologists. To cope with this problem, here we propose a direct residual learning approach on directional wavelet domain to solve this problem and to improve the performance against previous work. In particular, the new network estimates the noise of each input wavelet transform, and then the de-noised wavelet coefficients are obtained by subtracting the noise from the input wavelet transform bands. The experimental results confirm that the proposed network has significantly improved performance, preserving the detail texture of the original images.


title: Sign Language Recognition and Translation: A Multidisciplined Approach From the Field of ARTIFICIAL INTELLIGENCE

abstract: In recent years, research has progressed steadily in regard to the use of computers to recognize and render sign language. This paper reviews significant projects in the field beginning with finger-spelling hands such as "Ralph" (robotics), Cyber-Gloves (virtual reality sensors to capture isolated and continuous signs), camera-based projects such as the CopyCat interactive American Sign Language game (computer vision), and sign recognition software (Hidden Markov Modeling and neural network systems). Avatars such as "Tessa" (Text and Sign Support Assistant; three-dimensional imaging) and spoken language to sign language translation systems such as Poland's project entitled "THETOS" (Text into Sign Language Automatic Translator, which operates in Polish; natural language processing) are addressed. The application of this research to education is also explored. The "ICICLE" (Interactive Computer Identification and Correction of Language Errors) project, for example, uses intelligent computer-aided instruction to build a tutorial system for deaf or hard-of-hearing children that analyzes their English writing and makes tailored lessons and recommendations. Finally, the article considers synthesized sign, which is being added to educational material and has the potential to be developed by students themselves.


title: QBIC project: querying images by content, using color, texture, and shape

abstract: In the query by image content (QBIC) project we are studying methods to query large on-line image databases using the images' content as the basis of the queries. Examples of the content we use include color, texture, and shape of image objects and regions. Potential applications include medical (`Give me other images that contain a tumor with a texture like this one'), photo-journalism (`Give me images that have blue at the top and red at the bottom'), and many others in art, fashion, cataloging, retailing, and industry. Key issues include derivation and computation of attributes of images and objects that provide useful query functionality, retrieval methods based on similarity as opposed to exact match, query by image example or user drawn image, the user interfaces, query refinement and navigation, high dimensional database indexing, and automatic and semi-automatic database population. We currently have a prototype system written in X/Motif and C running on an RS/6000 that allows a variety of queries, and a test database of over 1000 images and 1000 objects populated from commercially available photo clip art images. In this paper we present the main algorithms for color texture, shape and sketch query that we use, show example query results, and discuss future directions.© (1993) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.


title: Parameter tuning for ant colony optimization: A review

abstract: Ant Colony Optimization (ACO) has enjoyed development and improvement since it was introduced in 1990s. The development of ACO was primarily driven by its convergence problem. Balancing between intensification and diversification in the search space is an important factor to intelligently improve solutions and avoid premature convergence. Balancing intensification and diversification can be gained by controlling the parameters value (this is called parameter tuning). Unfortunately, only little research has been reported to adopt parameter tuning as a strategy to balance intensification and diversification in ACO. This paper review parameter tuning in ACO published in the literature.


title: Air-core transformer integration for GaN VHF converters

abstract: This paper proposes an air-core transformer integration method, which mounts the transformer straightly into the multi-layer PCB, and maintains the proper distance between the inner transformer and other components on the top layer. Compared with other 3D integration method, the air-core transformer is optimized and modeled carefully to avoid the electromagnetic interference (EMI) of the magnetic fields. The integration method reduces the PCB area significantly, ensuring higher power density and similar efficiency as the conventional planar layout because the air-core transformer magnetic field does not affect other components. Moreover, the converters with the integrated PCB transformer can be manufactured with high consistency. With the air-core transformer, the overall height is only the sum of twice the PCB thickness and components height. In addition, the proposed integration method reduces the power loop inductance by 64%. It is applied to two resonant flyback converters operating at 20 MHz with Si MOSFETs, and 30 MHz with eGaN HEMTs respectively. The full load efficiency of the 30 MHz prototype is 80.1% with 5 V input and 5 V/ 2 W output. It achieves the power density of 32 W/in3.


title: Multi-Type UAVs Cooperative Task Allocation Under Resource Constraints

abstract: Coordinated task allocation for multiple unmanned aerial vehicles (multi-UAVs) is an important problem. Taking considerations of the types of UAVs, and the resources are extremely significant in the coordinated control of multi-UAVs. In the interests of assigning tasks efficiently and accurately for the cooperative UAVs of different types, the advanced multi-UAVs control technology requires a universal task assignment method under resource constraints. In this paper, we introduce a novel multi-type UAVs coordinated task allocation method based on cross-entropy (CE), and take the resources required for tasks into account. The CE method takes random samples from the candidate solutions, and then uses them to update the allocation probability matrix. We address the specific processes of CE dealing with the constrained multi-type UAVs task allocation problem, and reveal that CE has the advantage of solving large scale allocation problems. Furthermore, numerical simulations of CE handling task assignment, and comparisons with the exhaust search method are conducted to validate the merits of the cross-entropy method dealing with the considered problem.


title: Measuring and Managing the Smartness of Cities: A Framework for Classifying Performance Indicators

abstract: Due to the continuous increase of the world population living in cities, it is crucial to identify strategic plans and perform associated actions to make cities smarter, i.e., more operationally efficient, socially friendly, and environmentally sustainable, in a cost effective manner. To achieve these goals, emerging smart cities need to be optimally and intelligently measured, monitored, and managed. In this context the paper proposes the development of a framework for classifying performance indicators of a smart city. It is based on two dimensions: the degree of objectivity of observed variables and the level of technological advancement for data collection. The paper shows an application of the presented framework to the case of the Bari municipality (Italy).


title: Variable-Length Word Encodings for Neural Translation Models

abstract: Recent work in neural machine translation has shown promising performance, but the most eective architectures do not scale naturally to large vocabulary sizes. We propose and compare three variable-length encoding schemes that represent a large vocabulary corpus using a much smaller vocabulary with no loss in information. Common words are unaected by our encoding, but rare words are encoded using a sequence of two pseudo-words. Our method is simple and eective: it requires no complete dictionaries, learning procedures, increased training time, changes to the model, or new parameters. Compared to a baseline that replaces all rare words with an unknown word symbol, our best variable-length encoding strategy improves WMT English-French translation performance by up to 1.7 BLEU.


title: 12-to-1 bandwidth all-metal Vivaldi array element

abstract: The notch element is a classic example of a wideband antenna that functions very well as a stand-alone radiator and also as an element in wideband phased arrays [1, 2]. Also known as a Vivaldi Aerial or tapered-slot antenna, the Vivaldi has seen perhaps the most widespread use in ultra-high bandwidth applications (≫ 3:1 Bandwidth) of any type of element due to its robustness in design and range of manufacturability. Part of its popularity stems from the ease with which inexpensive printed-circuit board manufacturing can be used to create large arrays. It is also popular in high-power radar applications as well as ultra-wideband military applications, where all-metal designs are typically preferred. In this paper, a 12:1 bandwidth all-metal Vivaldi array element design is presented that can be easily machined from metal sheets and fed via standard SMA coax connectors. No soldering is required and assembly is simple and modular.


title: A novel approach for ANFIS modelling based on full factorial design

abstract: Adaptive neural network based fuzzy inference system (ANFIS) is an intelligent neuro-fuzzy technique used for modelling and control of ill-defined and uncertain systems. ANFIS is based on the input-output data pairs of the system under consideration. The size of the input-output data set is very crucial when the data available is very less and the generation of data is a costly affair. Under such circumstances, optimization in the number of data used for learning is of prime concern. In this paper, we have proposed an ANFIS based system modelling where the number of data pairs employed for training is minimized by application of an engineering statistical technique called full factorial design. Our proposed method is experimentally validated by applying it to the benchmark Box and Jenkins gas furnace data and a data set collected from a thermal power plant of the North Eastern Electric Power Corporation (NEEPCO) Limited. By employing our proposed method the number of data required for learning in the ANFIS network could be significantly reduced and thereby computation time as well as computation complexity is remarkably reduced. The results obtained by applying our proposed method are compared with those obtained by using conventional ANFIS network. It was found that our model compares favourably well with conventional ANFIS model.


title: A case study of mobile robot's energy consumption and conservation techniques

abstract: Mobile robots are used in many applications, such as carpet cleaning, pickup and delivery, search and rescue, and entertainment. Energy limitation is one of the most important challenges for mobile robots. Most existing studies on mobile robots focus on motion planning to reduce motion power. However, motion is not the only power consumer. In this paper, we present a case study of a mobile robot called Pioneer 3DX. We analyze the energy consumers. We build power models for motion, sonar sensing and control based on experimental results. The results show that motion consume less than 50% power on average. Therefore, it is important to consider the other components in energy-efficient designs. We introduce two energy-conservation techniques: dynamic power management and real-time scheduling. We provide several examples showing how these techniques can be applied to robots. These techniques together with motion planning provide greater opportunities to achieve better energy efficiency for mobile robots. Although our study is based on a specific robot, the approach can be applied to other types of robots


title: Neural aspects of second language representation and language control

abstract: Abstract A basic issue in the neurosciences of language is whether an L2 can be processed through the same neural mechanism underlying L1 acquisition and processing. In the present paper I review data from functional neuroimaging studies focusing on grammatical and lexico-semantic processing in bilinguals. The available evidence indicates that the L2 seems to be acquired through the same neural structures responsible for L1 acquisition. This fact is also observed for grammar acquisition in late L2 learners contrary to what one may expect from critical period accounts. However, neural differences for an L2 may be observed, in terms of more extended activity of the neural system mediating L1 processing. These differences may disappear once a more ‘native-like’ proficiency is established, reflecting a change in language processing mechanisms: from controlled processing for a weak L2 system (i.e., a less proficient L2) to more automatic processing. The neuroimaging data reviewed in this paper also support the notion that language control is a crucial aspect specific to the bilingual language system. The activity of brain areas related to cognitive control during the processing of a ‘weak’ L2 may reflect competition and conflict between languages which may be resolved with the intervention of these areas.


title: Factors associated with delays in screening of self-detected breast changes in African-American women.

abstract: Breast cancer mortality is higher among African-American women than among White women. African-American women are 25% more likely to present with late stage breast cancer and 20% more likely to die from breast cancer than White women. Treatment delay of 3 months is a significant factor in breast cancer mortality The purpose of this integrative review is to explore factors that impact delays in screening The most common patient-controlled delays were lack of education and knowledge about the perceived seriousness of breast symptoms, the associated risk factors, limited knowledge regarding the potential benefits of early detection in improving breast cancer survival, and expressed fatalistic perspectives about breast cancer. Other variables related to delays included factors such as advancing age, low socioeconomic status, fear of diagnosis, consequences of cancer treatments, shame and embarrassment, misconceptions about the etiology of breast cancer, family priorites, denial, and spirituality including faith-influenced delays.


title: Research Note - Privacy Concerns and Privacy-Protective Behavior in Synchronous Online Social Interactions

abstract: Privacy is of prime importance to many individuals when they attempt to develop online social relationships. Nonetheless, it has been observed that individuals' behavior is at times inconsistent with their privacy concerns, e.g., they disclose substantial private information in synchronous online social interactions, even though they are aware of the risks involved. Drawing on the hyperpersonal framework and the privacy calculus perspective, this paper elucidates the interesting roles of privacy concerns and social rewards in synchronous online social interactions by examining the causes and the behavioral strategies that individuals utilize to protect their privacy. An empirical study involving 251 respondents was conducted in online chat rooms. Our results indicate that individuals utilize both self-disclosure and misrepresentation to protect their privacy and that social rewards help explain why individuals may not behave in accordance with their privacy concerns. In addition, we find that perceived anonymity of others and perceived intrusiveness affect both privacy concerns and social rewards. Our findings also suggest that higher perceived anonymity of self decreases individuals' privacy concerns, and higher perceived media richness increases social rewards. Generally, this study contributes to the information systems literature by integrating the hyperpersonal framework and the privacy calculus perspective to identify antecedents of privacy trade-off and predict individuals' behavior in synchronous online social interactions.


MASSAlign: Alignment and Annotation of Comparable Documents


title: K-plet and Coupled BFS : A Graph Based Fingerprint Representation and Matching Algorithm

abstract: In this paper, we present a new fingerprint matching algorithm based on graph matching principles. We define a new representation called K-plet to encode the local neighborhood of each minutiae. We also present CBFS (Coupled BFS), a new dual graph traversal algorithm for consolidating all the local neighborhood matches and analyze its computational complexity. The proposed algorithm is robust to non-linear distortion. Ambiguities in minutiae pairings are solved by employing a dynamic programming based optimization approach. We present an experimental evaluation of the proposed approach and showed that it exceeds the performance of the NIST BOZORTH3 [3] matching algorithm.


title: Modeling Strategy for Back-to-Back Three-Level Converters Applied to High-Power Wind Turbines

abstract: Three-level converters are becoming a realistic alternative to the conventional converters in high-power wind-energy applications. In this paper, a complete analytical strategy to model a back-to-back three-level converter is described. This tool permits us to adapt the control strategy to the specific application. Moreover, the model of different loads can be incorporated to the overall model. Both control strategy and load models are included in the complete system model. The proposed model pays special attention to the unbalance in the capacitors' voltage of three-level converters, including the dynamics of the capacitors' voltage. In order to validate the model and the control strategy proposed in this paper, a 3-MW three-level back-to-back power converter used as a power conditioning system of a variable speed wind turbine has been simulated. Finally, the described strategy has been implemented in a 50-kVA scalable prototype as well, providing a satisfactory performance


title: Toward a Deeper Understanding of Service Marketing: The Past, the Present, and the Future

abstract: The authors investigate the intellectual pillars of service marketing and its evolution through key subareas during 1992–2009 using a citation-based approach. They derive insights for the most promising research directions. The results reveal the dynamic influences of different research topics on service marketing. In a graphical representation, the authors further show that the main topics have changed their research orientations over time. For example, the literature on online service & technology infusion reveals an increasingly operational and customer-focused orientation. A citation-based measure of the significance of research opportunities and a comparison with the topics found in recent literature reviews indicate that research on managing business-to-business services & service infusion, complaint handling & service recovery, and enhancing and managing the service value chain are promising topics. These results assist academics and practitioners by revealing what we know about service research and what we need to know in the future.


title: Electronic Transport Properties of Individual Chemically Reduced Graphene Oxide Sheets

abstract: Individual graphene oxide sheets subjected to chemical reduction were electrically characterized as a function of temperature and external electric fields. The fully reduced monolayers exhibited conductivities ranging between 0.05 and 2 S/cm and field effect mobilities of 2−200 cm2/Vs at room temperature. Temperature-dependent electrical measurements and Raman spectroscopic investigations suggest that charge transport occurs via variable range hopping between intact graphene islands with sizes on the order of several nanometers. Furthermore, the comparative study of multilayered sheets revealed that the conductivity of the undermost layer is reduced by a factor of more than 2 as a consequence of the interaction with the Si/SiO2 substrate.


title: A Tale of Two Studies: The Best and Worst of YubiKey Usability

abstract: Two-factor authentication (2FA) significantly improves the security of password-based authentication. Recently, there has been increased interest in Universal 2nd Factor (U2F) security keys—small hardware devices that require users to press a button on the security key to authenticate. To examine the usability of security keys in non-enterprise usage, we conducted two user studies of the YubiKey, a popular line of U2F security keys. The first study tasked 31 participants with configuring a Windows, Google, and Facebook account to authenticate using a YubiKey. This study revealed problems with setup instructions and workflow including users locking themselves out of their operating system or thinking they had successfully enabled 2FA when they had not. In contrast, the second study had 25 participants use a YubiKey in their daily lives over a period of four weeks, revealing that participants generally enjoyed the experience. Conducting both a laboratory and longitudinal study yielded insights into the usability of security keys that would not have been evident from either study in isolation. Based on our analysis, we recommend standardizing the setup process, enabling verification of success, allowing shared accounts, integrating with operating systems, and preventing lockouts.


title: Fundamental analysis for visible-light communication system using LED lights

abstract: White LED offers advantageous properties such as high brightness, reliability, lower power consumption and long lifetime. White LEDs are expected to serve in the next generation of lamps. An indoor visible-light communication system utilizing white LED lights has been proposed from our laboratory. In the proposed system, these devices are used not only for illuminating rooms but also for an optical wireless communication system. Generally, plural lights are installed in our room. So, their optical path difference must be considered. In this paper, we discuss about the influence of interference and reflection. Based on numerical analyses, we show that the system is expected to be the indoor communication of the next generation.


title: Similar Handwritten Chinese Character Recognition Based on CNN-SVM

abstract: For the past several decades, offline handwritten character recognition is widely and deeply studied. The requirements of the identification results are constantly improving in practical applications. However, the recognition rates of the similar handwritten Chinese characters are not very high in different writing style, writing environment and writing mode. We propose a method of combining deep convolution neural network and support vector machine together. Using the deep convolution neural network to learn and extract Chinese characters features automatically, and then the extracted features are classified and identified by the support vector machine. Experiments show that the deep convolution neural network can extract the features effectively, which avoided the shortage of artificial feature extraction, then using the support vector machine to classify and identify that, the accuracy rate is further improved.


title: An Event-B formalization of KAOS goal refinement patterns

abstract: Goals play an important role in requirements engineering process, and consequently in systems development process. Whereas specifications allow us to answer the question ”WHAT the system does”, goals allow us to address the ”WHY, WHO, WHEN” questions . Up to now, the main software development approaches using formal methods, ::: such as Event-B, begins at the specification level. Our objective is to include requirements analysis within this process, and more precisely the KAOS method, which is a goal-oriented methodology for requirements engineering. The latter allows analysts to build requirements models and to derive requirements documents. Existing work that combine KAOS with formal methods generate a formal specification model from a KAOS requirements model. We aim at expressing KAOS goal models with a formal language (Event-B), hence staying at the same abstraction level. Thus we take advantage from the Event-B method: it is possible to use the method during the whole development pro- ::: cess and (ii) we can benefit from the industrial maturity of tools supporting the method. For that purpose, we propose a constructive approach in which Event-B models are built incrementally from KAOS goal models, driven by goal refinement patterns.


title: Online Planning for Large MDPs with MAXQ Decomposition

abstract: Markov decision processes (MDPs) provide an expressive framework for planning in stochastic domains. However, exactly solving a large MDP is often intractable due to the curse of dimensionality. Online algorithms help overcome the high computational complexity by avoiding computing a policy for each possible state. Hierarchical decomposition is another promising way to help scale MDP algorithms up to large domains by exploiting their underlying structure. In this paper, we present an eort on combining the benets of a general hierarchical structure based on MAXQ value function decomposition with the power of heuristic and approximate techniques for developing an online planning framework, called MAXQ-OP. The proposed framework provides a principled approach for programming autonomous agents in a large stochastic domain. We have been conducting a long-term case-study with the RoboCup soccer simulation 2D domain, which is extremely larger than domains usually studied in literature, as the major benchmark to this research. The case-study showed that the agents developed with this framework and the related techniques reached outstanding performances, showing its high scalability to very large domains.


title: Software development: do good manners matter?

abstract: The research presented in this paper was partly funded by the Engineering and Physical ::: Sciences Research Council (EPSRC) of the UK under grant ref: EP/M024083/1.


title: An adaptive testing system for supporting versatile educational assessment

abstract: With the rapid growth of computer and mobile technology, it is a challenge to integrate computer based test (CBT) with mobile learning (m-learning) especially for formative assessment and self-assessment. In terms of self-assessment, computer adaptive test (CAT) is a proper way to enable students to evaluate themselves. In CAT, students are assessed through a process that uses item response theory (IRT), a well-founded psychometric theory. Furthermore, a large item bank is indispensable to a test, but when a CAT system has a large item bank, the test item selection of IRT becomes more tedious. Besides the large item bank, item exposure mechanism is also essential to a testing system. However, IRT all lack the above-mentioned points. These reasons have motivated the authors to carry out this study. This paper describes a design issue aimed at the development and implementation of an adaptive testing system. The system can support several assessment functions and different devices. Moreover, the researchers apply a novel approach, particle swarm optimization (PSO) to alleviate the computational complexity and resolve the problem of item exposure. Throughout the development of the system, a formative evaluation was embedded into an integral part of the design methodology that was used for improving the system. After the system was formally released onto the web, some questionnaires and experiments were conducted to evaluate the usability, precision, and efficiency of the system. The results of these evaluations indicated that the system provides an adaptive testing for different devices and supports versatile assessment functions. Moreover, the system can estimate students' ability reliably and validly and conduct an adaptive test efficiently. Furthermore, the computational complexity of the system was alleviated by the PSO approach. By the approach, the test item selection procedure becomes efficient and the average best fitness values are very close to the optimal solutions.


title: Aggregating local descriptors into a compact image representation

abstract: We address the problem of image search on a very large scale, where three constraints have to be considered jointly: the accuracy of the search, its efficiency, and the memory usage of the representation. We first propose a simple yet efficient way of aggregating local image descriptors into a vector of limited dimension, which can be viewed as a simplification of the Fisher kernel representation. We then show how to jointly optimize the dimension reduction and the indexing algorithm, so that it best preserves the quality of vector comparison. The evaluation shows that our approach significantly outperforms the state of the art: the search accuracy is comparable to the bag-of-features approach for an image representation that fits in 20 bytes. Searching a 10 million image dataset takes about 50ms.


title: Job sculpting: the art of retaining your best people.

abstract: Hiring good people is tough, but keeping them can be even tougher. The professionals streaming out of today's MBA programs are so well educated and achievement oriented that they could do well in virtually any job. But will they stay? According to noted career experts Timothy Butler and James Waldroop, only if their jobs fit their deeply embedded life interests--that is, their long-held, emotionally driven passions. Butler and Waldroop identify the eight different life interests of people drawn to business careers and introduce the concept of job sculpting, the art of matching people to jobs that resonate with the activities that make them truly happy. Managers don't need special training to job sculpt, but they do need to listen more carefully when employees describe what they like and dislike about their jobs. Once managers and employees have discussed deeply embedded life interests--ideally, during employee performance reviews--they can work together to customize future work assignments. In some cases, that may mean simply adding another assignment to existing responsibilities. In other cases, it may require moving that employee to a new position altogether. Skills can be stretched in many directions, but if they are not going in the right direction--one that is congruent with deeply embedded life interests--employees are at risk of becoming dissatisfied and uncommitted. And in an economy where a company's most important asset is the knowledge, energy, and loyalty of its people, that's a large risk to take.


A Unified Passivity Based Control Framework for Position, Torque and Impedance Control of Flexible Joint Robots.


title: Improving foreground segmentations with probabilistic superpixel Markov random fields

abstract: We propose a novel post-processing framework to improve foreground segmentations with the use of Probabilistic Superpixel Markov Random Fields. First, we convert a given pixel-based segmentation into a probabilistic superpixel representation. Based on these probabilistic superpixels, a Markov random field exploits structural information and similarities to improve the segmentation. We evaluate our approach on all categories of the Change Detection 2012 dataset. Our approach improves all performance measures simultaneously for eight different basis foreground segmentation algorithms.


title: Autosomal dominant inheritance of Weaver syndrome.

abstract: Most report of Weaver syndrome have been sporadic cases and the genetic basis of the syndrome is uncertain. This report of an affected father and daughter provides evidence for autosomal dominant inheritance.


title: An introduction to the syntax and content of Cyc

abstract: Spring Symposium on Formalizing and Compiling Background Knowledge and Its Applications to Knowledge Representation and Question Answering, Stanford, CA, March 2006.


title: Using Heterogeneous Wireless Sensor Networks in a Telemonitoring System for Healthcare

abstract: Ambient intelligence has acquired great importance in recent years and requires the development of new innovative solutions. This paper presents a distributed telemonitoring system, aimed at improving healthcare and assistance to dependent people at their homes. The system implements a service-oriented architecture based platform, which allows heterogeneous wireless sensor networks to communicate in a distributed way independent of time and location restrictions. This approach provides the system with a higher ability to recover from errors and a better flexibility to change their behavior at execution time. Preliminary results are presented in this paper.


title: The primes contain arbitrarily long arithmetic progressions

abstract: We prove that there are arbitrarily long arithmetic progressions of primes. ::: There are three major ingredients. The first is Szemeredi's theorem, which asserts that any subset of the integers of positive density contains progressions of arbitrary length. The second, which is the main new ingredient of this paper, is a certain transference principle. This allows us to deduce from Szemeredi's theorem that any subset of a sufficiently pseudorandom set of positive relative density contains progressions of arbitrary length. The third ingredient is a recent result of Goldston and Yildirim. Using this, one may place the primes inside a pseudorandom set of ``almost primes'' with positive relative density.


title: Diversity in smartphone usage

abstract: Using detailed traces from 255 users, we conduct a comprehensive study of smartphone use. We characterize intentional user activities -- interactions with the device and the applications used -- and the impact of those activities on network and energy usage. We find immense diversity among users. Along all aspects that we study, users differ by one or more orders of magnitude. For instance, the average number of interactions per day varies from 10 to 200, and the average amount of data received per day varies from 1 to 1000 MB. This level of diversity suggests that mechanisms to improve user experience or energy consumption will be more effective if they learn and adapt to user behavior. We find that qualitative similarities exist among users that facilitate the task of learning user behavior. For instance, the relative application popularity for can be modeled using an exponential distribution, with different distribution parameters for different users. We demonstrate the value of adapting to user behavior in the context of a mechanism to predict future energy drain. The 90th percentile error with adaptation is less than half compared to predictions based on average behavior across users.


title: GlobeNet: Convolutional Neural Networks for Typhoon Eye Tracking from Remote Sensing Imagery

abstract: Advances in remote sensing technologies have made it possible to use high-resolution visual data for weather observation and forecasting tasks. We propose the use of multi-layer neural networks for understanding complex atmospheric dynamics based on multichannel satellite images. The capability of our model was evaluated by using a linear regression task for single typhoon coordinates prediction. A specific combination of models and different activation policies enabled us to obtain an interesting prediction result in the northeastern hemisphere (ENH).


title: Future directions for heterodox economics

abstract: This work is a comprehensive survey of the current state - and future direction - of heterodox economic thought. Twenty-first century economists will have to understand and improve a post-Cold War world in which no single economic theory or system holds the key to human betterment. Heterodox economists have much to contribute to this effort, as a wave of pluralism spawns new lines of research and new dialogues among non-mainstream economists. ""Future Directions for Heterodox Economics"" showcases the full range of heterodox ideas, surveying leading-edge discussions of pluralism; socially-grounded reconstructions of the individual in economic theory; the goals and tools of economic measurement and professional ethics; the complexities of policymaking in today's global political economy; and innovative connections among formerly separate theoretical traditions (Marxian, Austrian, feminist, ecological, Sraffian, institutionalist, and post-Keynesian).


title: TapSkin: Recognizing On-Skin Input for Smartwatches

abstract: The touchscreen has been the dominant input surface for smartphones and smartwatches. However, its small size compared to a phone limits the richness of the input gestures that can be supported. We present TapSkin, an interaction technique that recognizes up to 11 distinct tap gestures on the skin around the watch using only the inertial sensors and microphone on a commodity smartwatch. An evaluation with 12 participants shows our system can provide classification accuracies from 90.69% to 97.32% in three gesture families -- number pad, d-pad, and corner taps. We discuss the opportunities and remaining challenges for widespread use of this technique to increase input richness on a smartwatch without requiring further on-body instrumentation.


title: Social risk and depression: Evidence from manual and automatic facial expression analysis

abstract: Investigated the relationship between change over time in severity of depression symptoms and facial expression. Depressed participants were followed over the course of treatment and video recorded during a series of clinical interviews. Facial expressions were analyzed from the video using both manual and automatic systems. Automatic and manual coding were highly consistent for FACS action units, and showed similar effects for change over time in depression severity. For both systems, when symptom severity was high, participants made more facial expressions associated with contempt, smiled less, and those smiles that occurred were more likely to be accompanied by facial actions associated with contempt. These results are consistent with the “social risk hypothesis” of depression. According to this hypothesis, when symptoms are severe, depressed participants withdraw from other people in order to protect themselves from anticipated rejection, scorn, and social exclusion. As their symptoms fade, participants send more signals indicating a willingness to affiliate. The finding that automatic facial expression analysis was both consistent with manual coding and produced the same pattern of depression effects suggests that automatic facial expression analysis may be ready for use in behavioral and clinical science.


title: Two Approaches to Event Definition

abstract: We compare two approaches to event definition, deriving from the Active Database and Knowledge Representation communities. We relate these approaches by taking a system of the former kind, displaying some of its shortcomings, and rectifying them by remodelling the system in the latter style. We further show the extent to which the original system can be recreated within the remodelled system. This bridge between the two approaches should provide a starting point for fruitful interaction between the two communities.


title: Which process metrics can significantly improve defect prediction models? An empirical study

abstract: The knowledge about the software metrics which serve as defect indicators is vital for the efficient allocation of resources for quality assurance. It is the process metrics, although sometimes difficult to collect, which have recently become popular with regard to defect prediction. However, in order to identify rightly the process metrics which are actually worth collecting, we need the evidence validating their ability to improve the product metric-based defect prediction models. This paper presents an empirical evaluation in which several process metrics were investigated in order to identify the ones which significantly improve the defect prediction models based on product metrics. Data from a wide range of software projects (both, industrial and open source) were collected. The predictions of the models that use only product metrics (simple models) were compared with the predictions of the models which used product metrics, as well as one of the process metrics under scrutiny (advanced models). To decide whether the improvements were significant or not, statistical tests were performed and effect sizes were calculated. The advanced defect prediction models trained on a data set containing product metrics and additionally Number of Distinct Committers (NDC) were significantly better than the simple models without NDC, while the effect size was medium and the probability of superiority (PS) of the advanced models over simple ones was high ( $$p=.016$$ p = . 016 , $$r=-.29$$ r = - . 29 , $$\hbox {PS}=.76$$ PS = . 76 ), which is a substantial finding useful in defect prediction. A similar result with slightly smaller PS was achieved by the advanced models trained on a data set containing product metrics and additionally all of the investigated process metrics ( $$p=.038$$ p = . 038 , $$r=-.29$$ r = - . 29 , $$\hbox {PS}=.68$$ PS = . 68 ). The advanced models trained on a data set containing product metrics and additionally Number of Modified Lines (NML) were significantly better than the simple models without NML, but the effect size was small ( $$p=.038$$ p = . 038 , $$r=.06$$ r = . 06 ). Hence, it is reasonable to recommend the NDC process metric in building the defect prediction models.


title: GPU acceleration of real time Viola-Jones face detection

abstract: Face detection is a stepping stone to all facial processing systems such as face recognition with the task of determining face region from the input frame for applications like surveillance and law enforcement. However, face detection is a computational expensive process and thus, with acceleration it can influence the performance of the system. The latest Graphics Processing Unit (GPU) technology via Compute Unified Device Architecture (CUDA) has proven its capability to accelerate computation intensive algorithms to improve overall system performance. Thus, in this paper, a GPU acceleration of frontal face detection system utilizing Viola-Jones algorithm based on the Adaptive Boosting (Adaboost) using OpenCV and CUDA is presented. Experiments results show that the proposed GPU acceleration of face detection is able to achieve a speed up of up to 18 times, as compared to the conventional Central Processing Unit (CPU) version algorithm and yet maintain its detection accuracy.


title: Contextualizing organizational interventions of knowledge management systems: A design science perspective

abstract: We address how individuals’ (workers) knowledge needs influence the design of knowledge management systems (KMS), enabling knowledge creation and utilization. It is evident that KMS technologies and activities are indiscriminately deployed in most organizations with little regard to the actual context of their adoption. Moreover, it is apparent that the extant literature pertaining to knowledge management projects is frequently deficient in identifying the variety of factors indicative for successful KMS. This presents an obvious business practice and research gap that requires a critical analysis of the necessary intervention that will actually improve how workers can leverage and form organization-wide knowledge. This research involved an extensive review of the literature, a grounded theory methodological approach and rigorous data collection and synthesis through an empirical case analysis (Parsons Brinckerhoff and Samsung). The contribution of this study is the formulation of a model for designing KMS based upon the design science paradigm, which aspires to create artifacts that are interdependent of people and organizations. The essential proposition is that KMS design and implementation must be contextualized in relation to knowledge needs and that these will differ for various organizational settings. The findings present valuable insights and further understanding of the way in which KMS design efforts should be focused. © 2012 Wiley Periodicals, Inc.


title: Universal spaces for -trees

abstract: R-trees arise naturally in the study of groups of isometries of hyperboIic space. An R-tree is a uniquely arcwise connected metric space in which each arc is isometric to a subarc of the reals. It follows that an R-tree is locally arcwise connected, contractible, and one-dimensional. Unique and local arcwise connectivity characterize R-trees among metric spaces. A universal R-tree would be of interest in attempting to classify the actions of groups of isometries on R-trees. It is easy to see that there is no universal R-tree. However, we show that there is a universal separable R-tree T ℵ 0


A Review on Technology Forecasting Methods and Their Application Area


title: E-Learning Change Management: Challenges And Opportunities

abstract: The role of e-learning technologies entirely depends on the acceptance and execution of required-change in the thinking and behaviour of the users of institutions. The research are constantly reporting that many e-learning projects are falling short of their objectives due to many reasons but on the top is the user resistance to change according to the digital requirements of new era. It is argued that the suitable way for change management in e-learning environment is the training and persuading of users with a view to enhance their digital literacy and thus gradually changing the users’ attitude in positive direction. This paper discusses change management in transition to e-learning system considering pedagogical, cost and technical implications. It also discusses challenges and opportunities for integrating these technologies in higher learning institutions with examples from Turkey GATA (Gulhane Askeri Tip Akademisi-Gulhane Military Medical Academy).


Dietary fat consumption in the management of type 2 diabetes Summary


title: Generation and validation of virtual point cloud data for automated driving systems

abstract: The performance of an automated driving system is crucially affected by its environmental perception. The vehicle's perception of its environment provides the foundation for the automated responses computed by the system's logic algorithms. As perception relies on the vehicle's sensors, simulating sensor behavior in a virtual world constitutes virtual environmental perception. This is the task performed by sensor models. In this work, we introduce a real-time capable model of the measurement process for an automotive lidar sensor employing a ray tracing approach. The output of the model is point cloud data based on the geometry and material properties of the virtual scene. With this low level sensor data as input, a vehicle internal representation of the environment is constructed by means of an occupancy grid mapping algorithm. By using a virtual environment that has been constructed from high-fidelity measurements of a real world scenario, we are able to establish a direct link between real and virtual world sensor data. Directly comparing the resulting sensor output and environment representations from both cases, we are able to quantitatively explore the validity and fidelity of the proposed sensor measurement model.


title: Can a chronic dental infection be considered a cause of cardiovascular disease? A review of the literature.

abstract: Cardiovascular diseases (CVD) have a complex etiology determined by risk factors, which are in turn associated to a strong genetic component and to environmental factors. In the biological background for the development of CVD, low-grade chronic inflammation plays a role as a pathogenetic determinant of atherosclerosis. Dental infections have been associated with CVD. Periodontal disease is a chronic infection of the supporting tissues of the tooth that can lead to teeth loss. In recent years, a number of reports have demonstrated the possible relationship between periodontal disease and CVD. Apical periodontitis, on the other hand, is the late consequence of an endodontic infection, which is caused by the persistence of coronal caries and involves the root canal system of the tooth. Most of the time, it is a chronic infection. Some studies have found a correlation between a "composite status" of oral health (eg. caries, tooth loss, periodontal disease) and CVD, but only a few of them have addressed the association between apical periodontitis and CVD. This "state of the art" paper represents the first stage of an incoming study on the relationship between chronic endodontic infection and CVD.


title: Innovative and Reliable Power Modules: A Future Trend and Evolution of Technologies

abstract: Since the introduction of the first power module by Semikron in 1975, many innovations have been made to improve the thermal, electrical, and mechanical performance of power modules. These innovations in packaging technology focus on the enhancement of the heat dissipation and thermal cycling capability of the modules. Thermal cycles, caused by varying load and environmental operating conditions, induce high mechanical stress in the interconnection layers of the power module due to the different coefficients of thermal expansion (CTE), leading to fatigue and growth of microcracks in the bonding materials. As a result, the lifetime of power modules can be severely limited in practical applications. Furthermore, to reduce the size and weight of converters, the semiconductors are being operated at higher junction temperatures. Higher temperatures are especially of great interest for use of wide-?bandgap materials, such as SiC and GaN, because these materials leverage their material characteristics, particularly at higher temperatures. To satisfy these tightened requirements, on the one hand, conventional power modules, i.e., direct bonded Cu (DBC)-based systems with bond wire contacts, have been further improved. On the other hand, alternative packaging techniques, e.g., chip embedding into printed circuit boards (PCBs) and power module packaging based on the selective laser melting (SLM) technique, have been developed, which might constitute an alternative to conventional power modules in certain applications.


title: Understanding and Designing New Server Architectures for Emerging Warehouse-Computing Environments

abstract: This paper seeks to understand and design next-generation servers for emerging "warehouse-computing" environments. We make two key contributions. First, we put together a detailed evaluation infrastructure including a new benchmark suite for warehouse-computing workloads, and detailed performance, cost, and power models, to quantitatively characterize bottlenecks. Second, we study a new solution that incorporates volume non-server-class components in novel packaging solutions, with memory sharing and flash-based disk caching. Our results show that this approach has promise, with a 2X improvement on average in performance-per-dollar for our benchmark suite.


title: Antibacterial effectiveness of ciprofloxacin 0.3% ophthalmic solution in the treatment of bacterial conjunctivitis.

abstract: Two hundred eighty-eight cases of culture-proven bacterial conjunctivities were evaluated as part of two multicentered, randomized, prospective clinical studies comparing the antibacterial efficacy of topically administered ciprofloxacin 0.3% either with a placebo or with tobramycin 0.3%. In the first study, ciprofloxacin was significantly (P less than .001) more effective than the placebo. It eradicated or reduced the various bacterial pathogens in 93.6% of patients, compared to 59.5% for the placebo. In the second study, ciprofloxacin (94.5%) and tobramycin (91.9%) were equally effective. Topically applied ciprofloxacin eradicated or reduced all isolated bacterial species, attesting to its broad antibacterial spectrum and its potential usefulness in treating external ocular infections.


Introduction to Probability Theory for Graduate Economics


title: Real-time relief mapping on arbitrary polygonal surfaces

abstract: We present a technique for mapping relief textures onto arbitrary polygonal models in real time, producing correct self-occlusions, interpenetrations, shadows and per-pixel lighting. The technique uses a pixel-driven formulation based on an efficient ray-height-field intersection implemented on the GPU. It has very low memory requirements, supports extreme close-up views of the surfaces and can be applicable to surfaces undergoing deformation.


title: Supporting Scaling Agile with Portfolio Management: Case Paf.com

abstract: This paper is a descriptive case study of how one department at Paf, Paf.com, introduced portfolio management to help support scaling agile software development. Paf.com had experienced problems with long time-to-market due to thrashing, which was caused by frequently changing priorities due to an ad-hoc prioritization process and handovers. Also, there was lack of visibility into projects entering and progressing in the development pipeline. No structured way of starting projects was enforced company-wide, and too many parallel projects got started. As a result of introducing a structured portfolio management process, the number of ongoing projects has dramatically reduced, from over 200 to 30, reducing thrashing. Listing all projects in priority order in the Paf.com backlog provides visibility into what is currently ongoing, helping coordinate the work of multiple Scrum teams. The portfolio follow-up function provides progress data on the projects, helping managers make more informed decisions, considering the whole portfolio.


title: Development of a semi self-contained wall climbing robot with scanning type suction cups

abstract: A semi self-contained wall climbing robot with scanning type suction cups is developed and rested. This robot has two vacuum pumps on it. The robot is connected to the equipment on the ground only through the electric power cables and information cables. From the experimental results, the robot can walk around on walls, clear steps, and stick on cracks and gaps. The walking speed attains 138 cm/min, which is 59% faster than the wall climbing robot I with tubes connected to the external vacuum pump on the ground. These experimental results show higher possibility towards the development of a complete self-contained wall climbing robot by putting a battery and a CPU on the robot.


title: HexType: Efficient Detection of Type Confusion Errors for C++

abstract: Type confusion, often combined with use-after-free, is the main attack vector to compromise modern C++ software like browsers or virtual machines. Typecasting is a core principle that enables modularity in C++. For performance, most typecasts are only checked statically, i.e., the check only tests if a cast is allowed for the given type hierarchy, ignoring the actual runtime type of the object. Using an object of an incompatible base type instead of a derived type results in type confusion. Attackers abuse such type confusion issues to attack popular software products including Adobe Flash, PHP, Google Chrome, or Firefox. We propose to make all type checks explicit, replacing static checks with full runtime type checks. To minimize the performance impact of our mechanism HexType, we develop both low-overhead data structures and compiler optimizations. To maximize detection coverage, we handle specific object allocation patterns, e.g., placement new or reinterpret_cast which are not handled by other mechanisms. Our prototype results show that, compared to prior work, HexType has at least 1.1 -- 6.1 times higher coverage on Firefox benchmarks. For SPEC CPU2006 benchmarks with overhead, we show a 2 -- 33.4 times reduction in overhead. In addition, HexType discovered 4 new type confusion bugs in Qt and Apache Xerces-C++.


title: Some Like it Hoax: Automated Fake News Detection in Social Networks

abstract: In recent years, the reliability of information on the Internet has emerged as a crucial issue of modern society. Social network sites (SNSs) have revolutionized the way in which information is spread by allowing users to freely share content. As a consequence, SNSs are also increasingly used as vectors for the diffusion of misinformation and hoaxes. The amount of disseminated information and the rapidity of its diffusion make it practically impossible to assess reliability in a timely manner, highlighting the need for automatic hoax detection systems. ::: As a contribution towards this objective, we show that Facebook posts can be classified with high accuracy as hoaxes or non-hoaxes on the basis of the users who "liked" them. We present two classification techniques, one based on logistic regression, the other on a novel adaptation of boolean crowdsourcing algorithms. On a dataset consisting of 15,500 Facebook posts and 909,236 users, we obtain classification accuracies exceeding 99% even when the training set contains less than 1% of the posts. We further show that our techniques are robust: they work even when we restrict our attention to the users who like both hoax and non-hoax posts. These results suggest that mapping the diffusion pattern of information can be a useful component of automatic hoax detection systems.


title: Validation of the small-signal model of a forward-biased p–n junction diode

abstract: Abstract Small-signal parameters of an abrupt p–n junction diode under forward bias are computed numerically by solving Poisson's equation and continuity equations together. The parameter values are compared with those obtained with analytical expressions. It is found that the depletion capacitance is underestimated when the depletion approximation is used. The diffusion conductance and capacitance values agree with theory only in a limited range of forward bias voltages, and this range becomes smaller as the minority carrier lifetime decreases. The reasons behind the discrepancy are discussed.


title: Business Intelligence & Analytics and Decision Quality – Insights on Analytics Specialization and Information Processing Modes

abstract: Leveraging the benefits of business intelligence and analytics (BI&A) and improving decision quality does not only depend on establishing BI&A technology, but also on the organization and characteristics of decision processes. This research investigates new perspectives on these decision processes and establishes a link between characteristics of BI&A support and decision makers’ modes of information processing behavior, and how these ultimately contribute to the quality of decision outcomes. We build on the heuristic–systematic model (HSM) of information processing, as a central explanatory mechanism for linking BI&A support and decision quality. This allows us examining the effects of decision makers’ systematic and heuristic modes of information processing behavior in decision making processes. We further elucidate the role of analytics experts in influencing decision makers’ utilization of analytic advice. The analysis of data from 136 BI&A-supported decisions reveals how high levels of analytics elaboration can have a negative effect on decision makers’ information processing behavior. We further show how decision makers’ systematic processing contributes to decision quality and how heuristic processing restrains it. In this context we also find that trustworthiness in the analytics expert plays an important role for the adoption of analytic advice.


title: The economic and social burden of malaria

abstract: Where malaria prospers most, human societies have prospered least. The global distribution of per-capita gross domestic product shows a striking correlation between malaria and poverty, and malaria-endemic countries also have lower rates of economic growth. There are multiple channels by which malaria impedes development, including effects on fertility, population growth, saving and investment, worker productivity, absenteeism, premature mortality and medical costs.


title: Timely Query Processing in Smart Electric Grids: Algorithms and Performance

abstract: Smart-grid applications have widely varying data needs as well as bandwidth and latency requirements. The usual approach to collecting the available data (e.g., from Phasor Measurement Units) at a centralized site continuously and executing all the applications there leads to large latencies and requirements for high communication bandwidth. This paper proposes and evaluates, using real data, techniques wherein the data packets are disseminated based on the applications' data needs and semantics. These techniques systematically filter data in the dissemination network and reduce bandwidth requirements while resulting in low latency solutions. For example, based on the results from our testbed for the Indian Electric Grid, we show that the processing overheads decrease by at least 50% for the large PMU data sizes compared to the traditional centralized approach.


title: Variable step-size NLMS and affine projection algorithms

abstract: This letter proposes two new variable step-size algorithms for normalized least mean square and affine projection. The proposed schemes lead to faster convergence rate and lower misadjustment error.


title: An IoT based smart solution for leaf disease detection

abstract: Internet of things is a system consists of actuators or sensors or both that provides connectivity to the internet directly or indirectly. Internet of Things (IoT) advances can be used in smart farming to enhance quality of agriculture. Agriculture, the backbone of Indian economy, contributes to the overall economic growth of the country. But our productivity is very less as compared to world standards due to the use of obsolete farming technology, and nowadays people from rural areas migrate to an urban area for other profitable businesses, and they can't focus on agriculture. Innovation in farming is not new but IoT is set to push smart farming to next level Internet of things is a system consists of actuators or sensors or both provides connectivity to the internet directly or indirectly. This paper includes various features like detection of leaf disease, server based remote monitoring system, Humidity and temperature sensing, Soil the Moisture Sensing etc. It makes use of sensors networks for measurement of moisture, temperature, and humidity instead of manual check. Various Sensors are deployed in various locations of farms, to control all these sensors it has been used one controller called Raspberry PI (RPI). Leaf disease can be detected camera interfacing with RPI. Immediate status of a farm like a leaf disease and other environmental factors affecting crop like humidity, temperature and moisture is send using WIFI Server through RPI to the farmers. The paper presents the study of IOT techniques to engross the use of technology in Agriculture.


title: Factors that influence the cutaneous synthesis and dietary sources of vitamin D

abstract: The major sources of vitamin D for most humans are casual exposure of the skin to solar ultraviolet B (UVB;290–315 nm) radiation and from dietary intake. The cutaneous synthesis of vitamin D is a function of skin pigmentation and of the solar zenith angle which depends on latitude, season, and time of day. In order to mimic the natural environment of skin to sunlight exposure, we therefore measured serum 25-hydroxyvitamin D levels in volunteers with different skin types following repeated UV irradiation. Because melanin pigment in human skin competes for and absorbs the UVB photons responsible for the photolysis of 7-dehydrocholesterol to previtamin D3, we also studied the effect of skin pigmentation on previtamin D3 production in a human skin by exposing type II and type V skin samples to noon sunlight in June when the solar zenith angle is most acute. Vitamin D is rare in food. Among the vitamin D-rich food, oily fish are considered to be one of the best sources. Therefore, we analyzed the vitamin D content in several commonly consumed oily and non-oily fish. The data showed that farmed salmon had a mean content of vitamin D that was ~25% of the mean content found in wild caught salmon from Alaska, and that vitamin D2 was found in farmed salmon, but not in wild caught salmon. The results provide useful global guidelines for obtaining sufficient vitamin D3 by cutaneous synthesis and from dietary intake to prevent vitamin D deficiency and its health consequences.ensuing illness, especially, bone fractures in the elderly.