title: Texture mapping progressive meshes

abstract: Given an arbitrary mesh, we present a method to construct a progressive mesh (PM) such that all meshes in the PM sequence share a common texture parametrization. Our method considers two important goals simultaneously. It minimizes texture stretch (small texture distances mapped onto large surface distances) to balance sampling rates over all locations and directions on the surface. It also minimizes texture deviation (“slippage” error based on parametric correspondence) to obtain accurate textured mesh approximations. The method begins by partitioning the mesh into charts using planarity and compactness heuristics. It creates a stretch-minimizing parametrization within each chart, and resizes the charts based on the resulting stretch. Next, it simplifies the mesh while respecting the chart boundaries. The parametrization is re-optimized to reduce both stretch and deviation over the whole PM sequence. Finally, the charts are packed into a texture atlas. We demonstrate using such atlases to sample color and normal maps over several models.


title: Tuning Methods of PID Controller for DC Motor Speed Control

abstract: The traditional PID controllers are used for a long time to control the DC motor for many industrial processes, that because of the simplicity, flexibility, and satisfactory performance of this type of controller. This paper discusses the basic PID tuning method (Ziegler-Nichols) and its modification (Chien-Hrones-Reswick). Also, analysis the speed control DC motor response using the PID controller parameters that result from the tuning methods mentioned earlier. Moreover, explain the advantage and disadvantage of each formula of these methods. GUL/MATLAB windows used to implementing both methods to create more comfortable and friendly environment for better understanding of the PID controller tuning methods formula for engineering students and practicing engineers.


title: Classification of Human Brain Waves Using Self-Organizing Maps

abstract: This chapter presents a method for the classification of EEG spectra by means of Kohonen’s self-organizing map. We use EEG data recorded by 19 electrodes (channels), sampled at 128 Hz. Data vectors are extracted at intervals of half a second with a duration of one second each, resulting in vectors overlapping half a second. Before the training of the map, the sample vectors were compressed by either the Fast-Fourier-Transform or the Wavelet-Transform. Data preprocessed by the Fourier-Transform result in short-time power spectra. These spectra are filtered by butterworth filters that meet the EEG frequency bands of the delta-, theta-, alpha-, beta- and gamma-rhythms. Data preprocessed by the Wavelet-Transform result in wavelet coefficients that are combined and averaged. The preprocessed vectors form “clusters” on the trained self-organizing map that are related to specific EEG patterns.


title: Factors Influencing Cosmetics Purchase Intention in Thailand: A Study on the Relationship of Credibility and Reputation with in Persuasive Capabilities of Beauty Bloggers.

abstract: The purpose of this study is to examine the factors affecting beauty bloggers’ credibility and how credibility itself influences cosmetic purchase intentions of Thai people. As identified by Ohanian (1990), three variables impacting one’s decision-making process (trustworthiness, expertise and attractiveness) are considered along with two additional variables determined by this researcher through focus group interviews to fit with and complement them. These are reputation and persuasive capabilities. Demographic factors of the respondents (age, gender, etc) were investigated as part as understanding differences, if any, in the cosmetic purchase intentions of Thai people. The Pearson Correlation analysis indicates that all independent variables have a positive relationship with purchase intention. Moreover, the results from the one-way ANOVA analysis show that the demographic factors variously affect the purchase intention of cosmetics of respondents.


title: Natrium : Use of FPGA embedded processors for real-time data compression

abstract: We present test results and characterization of a data compression system for the readout of the NA62 liquid krypton calorimeter trigger processor. The Level-0 electromagnetic calorimeter trigger processor of the NA62 experiment at CERN receives digitized data from the calorimeter main readout board. These data are stored on an on-board DDR2 RAM memory and read out upon reception of a Level-0 accept signal. The maximum raw data throughput from the trigger front-end cards is 2.6 Gbps. To readout these data over two Gbit Ethernet interfaces we investigated different implementations of a data compression system based on the Rice-Golomb coding: one is implemented in the FPGA as a custom block and one is implemented on the FPGA embedded processor running a C code. The two implementations are tested on a set of sample events and compared with respect to achievable readout bandwidth.


title: Electric Power System Anomaly Detection Using Neural Networks

abstract: The aim of this work is to propose an approach to monitor and protect Electric Power System by learning normal system behaviour at substations level, and raising an alarm signal when an abnormal status is detected; the problem is addressed by the use of autoassociative neural networks, reading substation measures. Experimental results show that, through the proposed approach, neural networks can be used to learn parameters underlaying system behaviour, and their output processed to detecting anomalies due to hijacking of measures, changes in the power network topology (i.e. transmission lines breaking) and unexpected power demand trend.


title: A realisation of ethical concerns with smartphone personal health monitoring apps

abstract: The pervasiveness of smartphones has facilitated a new way in which owners of devices can monitor their health using applications (apps) that are installed on their smartphones. Smartphone personal health monitoring (SPHM) collects and stores health related data of the user either locally or in a third party storing mechanism. They are also capable of giving feedback to the user of the app in response to conditions that are provided to the app therefore empowering the user to actively make decisions to adjust their lifestyle. Regardless of the benefits that this new innovative technology offers to its users, there are some ethical concerns to the user of SPHM apps. These ethical concerns are in some way connected to the features of SPHM apps. From a literature survey, this paper attempts to recognize ethical issues with personal health monitoring apps on smartphones, viewed in light of general ethics of ubiquitous computing. The paper argues that there are ethical concerns with the use of SPHM apps regardless of the benefits that the technology offers to users due to SPHM apps' ubiquity leaving them open to known and emerging ethical concerns. The paper then propose a need for further empirical research to validate the claim.


title: Substrate-Integrated Waveguide Vertical Interconnects for 3-D Integrated Circuits

abstract: This paper presents and demonstrates a class of 3-D integration platforms of substrate-integrated waveguide (SIW). The proposed right angle E-plane corner based on SIW technology enables the implementation of various 3-D architectures of planar circuits with the printed circuit board and other similar processes. This design scheme brings up attractive advantages in terms of cost, flexibility, and integration. Two circuit prototypes with both 0- and 45° vertical rotated arms are demonstrated. The straight version of the prototypes shows 0.5 dB of insertion loss from 30 to 40 GHz, while the rotated version gives 0.7 dB over the same frequency range. With this H-to-E-plane interconnect, a T-junction is studied and designed. Simulated results show 20-dB return loss over 19.25% of bandwidth. Measured results suggest an excellent performance within the experimental frequency range of 32-37.4 GHz, with 10-dB return loss and less than ±4° phase imbalance. An optimized wideband magic-T structure is demonstrated and fabricated. Both simulated and measured results show a very promising performance with very good isolation and power equality. With two 45° vertical rotated arm bends, two antennas are used to build up a dual polarization system. An isolation of 20 dB is shown over 32-40 GHz and the radiation patterns of the antenna are also given.


title: Martin Luther's Body: The “Stout Doctor” and His Biographers

abstract: PERHAPS THE MOST DISCONCERTING monument to the Reformation is the double statue of Martin Luther and Philipp Melanchthon in the city market at Wittenberg. There they stand, their feet locked onto grandiose Schinkel pedestals, and can do no other, as they gaze grimly out from under their neo-Gothic baldachins. Melanchthon was an afterthought: Luther’s statue was unveiled in 1821, and Melanchthon’s followed a generation later in 1865, the monumental design of the first dictating the form for the second.1 The two Reformation heroes tower over the meat stands and vegetable stalls like two caged giants. But the effect of their being seen side by side like this, even with the nineteenth-century attempts to minimize the difference, is disastrous: the stout Luther confronts the cadaverous Melanchthon. In the contemporary double portraits by Heinrich Aldegrever and the Cranach workshop, it is even worse: Luther and Melanchthon are twinned like Laurel and Hardy.2 This dilemma takes us to the heart of the representational problem: Luther was stoutly built. Saints and pious clerics tend, on the whole, to come in Melanchthonian shape, their thinness underlining their indifference to the temptations of the flesh. In the history of Western Christianity, Aquinas aside, there were few spiritual figures who were corpulent. From Lucas Cranach the Elder’s painting of the bulky Luther of 1529 to the jowly, double-chinned head of Luther that looks out at us from the iconic woodcut of Lucas Cranach the Younger of 1546, Luther was large.3 After


title: Algorithmic Accountability: Journalistic investigation of computational power structures

abstract: Every day automated algorithms make decisions that can amplify the power of businesses and governments. Yet as algorithms come to regulate more aspects of our lives, the contours of their power can remain difficult to grasp. This paper studies the notion of algorithmic accountability reporting as a mechanism for elucidating and articulating the power structures, biases, and influences that computational artifacts exercise in society. A framework for algorithmic power based on autonomous decision-making is proffered and motivates specific questions about algorithmic influence. Five cases of algorithmic accountability reporting involving the use of reverse engineering methods in journalism are then studied and analyzed to provide insight into the method and its application in a journalism context. The applicability of transparency policies for algorithms is discussed alongside challenges to implementing algorithmic accountability as a broadly viable investigative method.


title: 3D Face Hallucination from a Single Depth Frame

abstract: We present an algorithm that takes a single frame of a person's face from a depth camera, e.g., Kinect, and produces a high-resolution 3D mesh of the input face. We leverage a dataset of 3D face meshes of 1204 distinct individuals ranging from age 3 to 40, captured in a neutral expression. We divide the input depth frame into semantically significant regions (eyes, nose, mouth, cheeks) and search the database for the best matching shape per region. We further combine the input depth frame with the matched database shapes into a single mesh that results in a high resolution shape of the input person. Our system is fully automatic and uses only depth data for matching, making it invariant to imaging conditions. We evaluate our results using ground truth shapes, as well as compare to state-of the-art shape estimation methods. We demonstrate the robustness of our local matching approach with high-quality reconstruction of faces that fall outside of the dataset span, e.g., Faces older than 40 years old, facial expressions, and different ethnicities.


title: Isolating Operating System Components with Intel SGX

abstract: In this paper, we present a novel approach on isolating operating system components with Intel SGX. Although SGX has not been designed to work in kernel mode, we found a way of wrapping Linux kernel functionality within SGX enclaves by moving parts of it to user space. Kernel components are strictly isolated from each other such that a vulnerability in one kernel module cannot escalate into compromising the entire kernel. We provide a proof-of-concept implementation which protects an exemplary kernel function, namely full disk encryption, using an Intel SGX enclave. Besides integrity of the disk encryption, our implementation ensures that the confidentiality of the disk encryption key is protected against all software level attacks as well as physical attacks. In addition to the user password, we use a second authentication factor for deriving the encryption key which is stored sealed and bound to the platform. Thus, stealing the hard drive and sniffing the user password is insufficient for an attacker to break disk encryption. Instead, the two factor authentication scheme requires an attacker to additionally obtain the actual machine to be able to break encryption.


Evaluating the WordsEye Text-to-Scene System: Imaginative and Realistic Sentences.


The Hitchhiker’s Guide to Testing Statistical Significance in Natural Language Processing


title: Experimenting with docker: Linux container and base OS attack surfaces

abstract: Linux containers showed great superiority when compared to virtual machines and hypervisors in terms of networking, disk and memory management, start-up and compilation speed, and overall processing performance. In this research, we are questioning whether it is more secure to run services inside Linux containers than running them directly on a host base operating system or not. We used Docker v1.10 to conduct a series of experiments to assess the attack surface of hosts running services inside Docker containers compared to hosts running the same services on the base operating system represented in our paper as Debian Jessie. Our vulnerability assessment shows that using Docker containers increase the attack surface of a given host, not the other way around.


title: Ordinal Regression Analysis: Using Generalized Ordinal Logistic Regression Models to Estimate Educational Data

abstract: The proportional odds (PO) assumption for ordinal regression analysis is often violated because it is strongly affected by sample size and the number of covariate patterns. To address this issue, the partial proportional odds (PPO) model and the generalized ordinal logit model were developed. However, these models are not typically used in research. One likely reason for this is the restriction of current statistical software packages: SPSS cannot perform the generalized ordinal logit model analysis and SAS requires data restructuring. This article illustrates the use of generalized ordinal logistic regression models to predict mathematics proficiency levels using Stata and compares the results from fitting PO models and generalized ordinal logistic regression models.


title: UCNN: Exploiting Computational Reuse in Deep Neural Networks via Weight Repetition

abstract: Convolutional Neural Networks (CNNs) have begun to permeate all corners of electronic society (from voice recognition to scene generation) due to their high accuracy and machine efficiency per operation. At their core, CNN computations are made up of multi-dimensional dot products between weight and input vectors. This paper studies how weight repetition ---when the same weight occurs multiple times in or across weight vectors--- can be exploited to save energy and improve performance during CNN inference. This generalizes a popular line of work to improve efficiency from CNN weight sparsity, as reducing computation due to repeated zero weights is a special case of reducing computation due to repeated weights. To exploit weight repetition, this paper proposes a new CNN accelerator called the Unique Weight CNN Accelerator (UCNN). UCNN uses weight repetition to reuse CNN sub-computations (e.g., dot products) and to reduce CNN model size when stored in off-chip DRAM ---both of which save energy. UCNN further improves performance by exploiting sparsity in weights. We evaluate UCNN with an accelerator-level cycle and energy model and with an RTL implementation of the UCNN processing element. On three contemporary CNNs, UCNN improves throughput-normalized energy consumption by 1.2x - 4x, relative to a similarly provisioned baseline accelerator that uses Eyeriss-style sparsity optimizations. At the same time, the UCNN processing element adds only 17-24% area overhead relative to the same baseline.


title: A network perspective of the stock market

abstract: Complex networks are constructed to study correlations between the closing prices for all US stocks that were traded over two periods of time (from July 2005 to August 2007; and from June 2007 to May 2009). The nodes are the stocks, and the connections are determined by cross correlations of the variations of the stock prices, price returns and trading volumes within a chosen period of time. Specifically, a winner-take-all approach is used to determine if two nodes are connected by an edge. So far, no previous work has attempted to construct a full network of US stock prices that gives full information about their interdependence. We report that all networks based on connecting stocks of highly correlated stock prices, price returns and trading volumes, display a scalefree degree distribution. The results from this work clearly suggest that the variation of stock prices are strongly influenced by a relatively small number of stocks. We propose a new approach for selecting stocks for inclusion in a stock index and compare it with existing indexes. From the composition of the highly connected stocks, it can be concluded that the market is heavily dominated by stocks in the financial sector.


title: Acoustic assessment of flow patterns in unsaturated soil

abstract: Abstract Acoustic wavelengths in soils range from meters to millimeters, depending on their frequencies. The spatial and temporal scales of pulse transmission through soils are well suited to investigate transient and presumably heterogeneous water infiltration into and redistribution within soils. Acoustic pulses were transmitted through a column of an undisturbed and partially water-saturated loess soil with height and diameter of 0.8 and 0.3 m, respectively. The maximum frequency of the arriving pulses was 10 kHz, which corresponds to a wavelength of about 50 mm. Both travel velocities and absorption of the acoustic waves reacted in the expected ways on soil moisture variations; however, the two temporal reaction patterns differed considerably. Brutsaert's [J. Geophys. Res. 69 (1964) 243] model was successfully applied to the data. Dye tracers visualized the patterns of water distribution. Their scale compares well with theoretical considerations on the flow paths and the results from the acoustic investigations.


title: Excision of the piggyBac transposable element in vitro is a precise event that is enhanced by the expression of its encoded transposase

abstract: The piggyBac Lepidopteran transposable element moves from the cellular genome into infecting baculovirus genomes during passage of the virus in cultured TN-368 cells. We have constructed genetically tagged piggyBac elements that permit analysis of excision when transiently introduced on plasmids into the piggyBac-deficient Spodoptera frugiperda IPLB-SF21AE cell line. Precise excision of the element from these plasmids occurs at a higher frequency in the presence of a helper plasmid that presumably supplies the piggyBac transposase. The results suggest that the piggyBac transposon encodes a protein that functions to facilitate not only insertion, but precise excision as well. This is the first demonstration of piggyBac mobility from plasmid sources in uninfected Lepidopteran cells.


title: Access Control in Internet of Things: A Survey

abstract: Cheating is a real problem in the Internet of Things. The fundamental question that needs to be answered is how we can trust the validity of the data being generated in the first place. The problem, however, is not inherent in whether or not to embrace the idea of an open platform and open-source software, but to establish a methodology to verify the trustworthiness and control any access. This paper focuses on building an access control model and system based on trust computing. This is a new field of access control techniques which includes Access Control, Trust Computing, Internet of Things, network attacks, and cheating technologies. Nevertheless, the target access control systems can be very complex to manage. This paper presents an overview of the existing work on trust computing, access control models and systems in IoT. It not only summarizes the latest research progress, but also provides an understanding of the limitations and open issues of the existing work. It is expected to provide useful guidelines for future research.


title: Image Steganography Using a Dynamic Symmetric Key

abstract: Steganography is the art of concealing one digital media within another digital media and retrieving the information afterwards. There are many examples of usage: image into image, text into image, video into voice, voice into video, etc. This paper concentrates on a method used for hiding text into image using Least Significant Bit (LSB), and using a symmetric key between sender and receiver to choose which bits are needed to be embeded the text to minimize the resolution between the original image and the stego-image. Further this paper also explains about the security issues to the stego-image. Also the comparision of the performance of the algorithms (PSNR) have been discussed.


title: An Origami-Inspired Approach to Worm Robots

abstract: This paper presents an origami-inspired technique which allows the application of 2-D fabrication methods to build 3-D robotic systems. The ability to design robots as origami structures introduces a fast and low-cost fabrication method to modern, real-world robotic applications. We employ laser-machined origami patterns to build a new class of robotic systems for mobility and manipulation. Origami robots use only a flat sheet as the base structure for building complicated bodies. An arbitrarily complex folding pattern can be used to yield an array of functionalities, in the form of actuated hinges or active spring elements. For actuation, we use compact NiTi coil actuators placed on the body to move parts of the structure on-demand. We demonstrate, as a proof-of-concept case study, the end-to-end fabrication and assembly of a simple mobile robot that can undergo worm-like peristaltic locomotion.


title: Maestoso: an intelligent educational sketching tool for learning music theory

abstract: Learning music theory not only has practical benefits for musicians to write, perform, understand, and express music better, but also for both non-musicians to improve critical thinking, math analytical skills, and music appreciation. However, current external tools applicable for learning music theory through writing when human instruction is unavailable are either limited in feedback, lacking a written modality, or assuming already strong familiarity of music theory concepts. In this paper, we describe Maestoso, an educational tool for novice learners to learn music theory through sketching practice of quizzed music structures. Maestoso first automatically recognizes students' sketched input of quizzed concepts, then relies on existing sketch and gesture recognition techniques to automatically recognize the input, and finally generates instructor-emulated feedback. From our evaluations, we demonstrate that Maestoso performs reasonably well on recognizing music structure elements and that novice students can comfortably grasp introductory music theory in a single session.


title: A CMOS analog front-end IC for portable EEG/ECG monitoring applications

abstract: A new digital programmable CMOS analog front-end (AFE) IC for measuring electroencephalograph or electrocardiogram signals in a portable instrumentation design approach is presented. This includes a new high-performance rail-to-rail instrumentation amplifier (IA) dedicated to the low-power AFE IC. The measurement results have shown that the proposed biomedical AFE IC, with a die size of 4.81 mm/sup 2/, achieves a maximum stable ac gain of 10 000 V/V, input-referred noise of 0.86 /spl mu/ V/sub rms/ (0.3 Hz-150 Hz), common-mode rejection ratio of at least 115 dB (0-1 kHz), input-referred dc offset of less than 60 /spl mu/V, input common mode range from -1.5 V to 1.3 V, and current drain of 485 /spl mu/A (excluding the power dissipation of external clock oscillator) at a /spl plusmn/1.5-V supply using a standard 0.5-/spl mu/m CMOS process technology.


Airflow-Restricting Mask Reduces Acute Performance in Resistance Exercise


title: Story Cloze Ending Selection Baselines and Data Examination

abstract: This paper describes two supervised baseline systems for the Story Cloze Test Shared Task (Mostafazadeh et al. 2016). We first build a classifier using features based on word embeddings and semantic similarity computation. We further implement a neural LSTM system with different encoding strategies that try to model the relation between the story and the provided endings. Our experiments show that a model using representation features based on average word embedding vectors over the given story words and the candidate ending sentences words, joint with similarity features between the story and candidate ending representations performed better than the neural models. Our best model achieves an accuracy of 72.42, ranking 3rd in the official evaluation.


title: Development of a New High Speed Dual-Channel Impulse Ground Penetrating Radar

abstract: This paper presents the development of a dual channel, air coupled Ultra-Wideband (UWB) Ground Penetrating Radar (GPR) targeting highway pavements and bridge deck inspections. Compared to most existing GPRs with a single channel and low survey speeds, our GPR possesses competitive features, including wide area coverage, high spatial resolution and operating capability at normal highway driving speed (up to 60 mph). The system has a two-channel microwave front end, a high speed (8 Gsps) real time data acquisition unit, a high throughput multithread data transmission and storage module, and a customized low-cost control element developed in a field-programmable gate array (FPGA). Experiments with different steel reinforcing bars establish GPR system performance.


title: Bilateral Normal Filtering for Mesh Denoising

abstract: Decoupling local geometric features from the spatial location of a mesh is crucial for feature-preserving mesh denoising. This paper focuses on first order features, i.e., facet normals, and presents a simple yet effective anisotropic mesh denoising framework via normal field denoising. Unlike previous denoising methods based on normal filtering, which process normals defined on the Gauss sphere, our method considers normals as a surface signal defined over the original mesh. This allows the design of a novel bilateral normal filter that depends on both spatial distance and signal distance. Our bilateral filter is a more natural extension of the elegant bilateral filter for image denoising than those used in previous bilateral mesh denoising methods. Besides applying this bilateral normal filter in a local, iterative scheme, as common in most of previous works, we present for the first time a global, noniterative scheme for an isotropic denoising. We show that the former scheme is faster and more effective for denoising extremely noisy meshes while the latter scheme is more robust to irregular surface sampling. We demonstrate that both our feature-preserving schemes generally produce visually and numerically better denoising results than previous methods, especially at challenging regions with sharp features or irregular sampling.


title: Deep Exploration via Randomized Value Functions

abstract: We study the use of randomized value functions to guide deep exploration in reinforcement learning. This offers an elegant means for synthesizing statistically and computationally efficient exploration with common practical approaches to value function learning. We present several reinforcement learning algorithms that leverage randomized value functions and demonstrate their efficacy through computational studies. We also prove a regret bound that establishes statistical efficiency with a tabular representation.


title: Automatic arabic number plate recognition

abstract: This paper presents a license plate recognition system for the Egyptian plates introduced in 2008. The proposed system is composed of three main stages; localization & skew correction stage, segmentation stage, and recognition stage. The localization stage uses the main feature of the plate where high contrast text-background is tagged with colored or gray area, to find the plate candidates in the image and to measure the skew angle. In segmentation stage, connected component analysis is applied to find objects belong to license number. The objects will be analyzed to attach diacritic and over segmented objects to each other to form a group of recognizable objects. The final objects will be split to digits and letter groups. In recognition stage, an adapted template match technique is introduced to recognize the digits and letter groups separately after normalizing them. The system is tested against a real video of two hours and the accuracy was 81% and average time per frame was 24 msec/frame.


title: Development of instructional package with video clips on problem solving steps in mathematics of sixth-grade students in Bhutan

abstract: This study developed an instructional package with video clips on problem solving steps in mathematics for sixth-grade students in Bhutan. The instructional package composed of four components: content, lesson process, video, and evaluation. The purposive sampling technique was used for selecting 28 sixth-grade students of Khamdang Lower Secondary School, Trashi Yangtse, eastern Bhutan to study Unit 4: measurement. The success of the instructional package depended on the students' academic achievement and their satisfaction. To measure these, achievement tests were administered before (pre-test) and after (post-test) the experimental phase, and a satisfaction questionnaire was administered one time, after the experimental phase. The achievement test was analyzed using the paired sample t-test, and it revealed that achievement test was statistically significant p(0.000)


Does LeTID occur in c-Si even without a firing step?


title: Intelligent and Adaptive Headlight with Electronic Controlled Power Steering System (IAEPS)

abstract: According to traffic accident data, the maximum of server road accidents occurs at night vision. Therefore of great importance to use available technology to contribute to road safety by increase the visual conditions provided by vehicle headlights. In order to provide improved night time safety measures, this work aims to design & build a prototype of Intelligent and Adaptive Headlight with Electric Power Steering System. This prototype model is focus to achieve active and passive safety system. In this an intelligent and adaptive system is active safety system where as EPS is passive system. This idea gives more advantages for automobile. It gives the advantages such as low level of steering torque during static steering, increase fuel efficiency or economy, low weight of vehicle because of using EPS system, flexibility in steering system and more space for driver and front passenger.


title: Reliability and validity of a weight-bearing measure of ankle dorsiflexion range of motion.

abstract: PURPOSE ::: To examine reliability and validity of the Lunge Test (LT) of dorsiflexion range of motion and determine the impact of different approaches to obtain a score on these parameters. ::: ::: ::: METHODS ::: Fifty-three patients with ankle injury/dysfunction provided initial assessment data for cross-sectional convergent and known-groups validity analysis with the Pearson coefficient (r) and paired t-test, respectively; data after 4-8 weeks of treatment for longitudinal validity analysis with coefficient r; and data 3 days later for test-retest reliability using the intra-class correlation coefficient (ICC) and minimal detectable change (MDC). LT scores were determined for the affected leg only (LTAff) and for the difference between the two limbs (LTDiff). Two strategies were used to calculate LT scores: a single series and the mean of three series of lunges. LTs were correlated with the Lower Extremity Functional Scale and Global Foot and Ankle Scale. ::: ::: ::: RESULTS ::: Reliability coefficients were high (ICC=0.93-0.99). The MDC=1.0/1.5 cm, LTAff/LTDiff, respectively. Cross-sectional validity was confirmed for LTDiff (r=-0.40 to -0.50). Between-limb differences (p<0.05) supported known-groups validity. Longitudinal validity was supported for both LT change scores (r=0.39-0.63). The number of series of lunges used did not impact results. ::: ::: ::: CONCLUSIONS ::: A single series of lunges produces a reliable LT score. From a validity perspective, clinicians should use LTDiff on initial assessment and either LT to assess change.


title: Mutual Coupling Reduction in Millimeter-Wave MIMO Antenna Array Using a Metamaterial Polarization-Rotator Wall

abstract: An effective technique for reducing the mutual coupling between millimeter-wave dielectric resonator antennas (DRAs) using a novel metamaterial polarization-rotator (MPR) wall is investigated and presented. The mutual coupling is reduced by embedding an MPR wall between two DRAs, which are placed in the H-plane. Using this MPR wall, the TE modes of the antennas become orthogonal, which reduces the mutual coupling between the two DRAs. The proposed MPR wall is composed of 1 × 7 unit cells along the E-plane. The mutual coupling is reduced by more than 16 dB on average (8 dB at 57 GHz, 22 dB at 60 GHz, 14 dB at 62 GHz) when the MPR wall is placed between the antennas. The proposed MPR wall nearly has no effect on the antenna characteristics in terms of input impedance and radiation pattern. The radiation pattern is almost unchanged compared to a DRA multiple-input-multiple-output (MIMO) antenna array without MPR wall. The MIMO antenna array with MPR wall is fabricated and measured. The results give a low correlation coefficient (<;0.1e-6). This is due to the fact that the MPR wall makes the two antennas orthogonal in terms of mutual coupling. The measured and simulated results show a good agreement.


title: Neural Person Search Machines

abstract: We investigate the problem of person search in the wild in this work. Instead of comparing the query against all candidate regions generated in a query-blind manner, we propose to recursively shrink the search area from the whole image till achieving precise localization of the target person, by fully exploiting information from the query and contextual cues in every recursive search step. We develop the Neural Person Search Machines (NPSM) to implement such recursive localization for person search. Benefiting from its neural search mechanism, NPSM is able to selectively shrink its focus from a loose region to a tighter one containing the target automatically. In this process, NPSM employs an internal primitive memory component to memorize the query representation which modulates the attention and augments its robustness to other distracting regions. Evaluations on two benchmark datasets, CUHK-SYSU Person Search dataset and PRW dataset, have demonstrated that our method can outperform current state-of-the-arts in both mAP and top-1 evaluation protocols.


title: SGXIO: Generic Trusted I/O Path for Intel SGX

abstract: Application security traditionally strongly relies upon security of the underlying operating system. However, operating systems often fall victim to software attacks, compromising security of applications as well. To overcome this dependency, Intel SGX allows to protect application code against a subverted or malicious OS by running it in a hardware-protected enclave. However, SGX lacks support for generic trusted I/O paths to protect user input and output between enclaves and I/O devices. This work presents SGXIO, a generic trusted path architecture for SGX, allowing user applications to run securely on top of an untrusted OS, while at the same time supporting trusted paths to generic I/O devices. To achieve this, SGXIO combines the benefits of SGX's easy programming model with traditional hypervisor-based trusted path architectures. Moreover, SGXIO can tweak insecure debug enclaves to behave like secure production enclaves. SGXIO surpasses traditional use cases in cloud computing and digital rights management and makes SGX technology usable for protecting user-centric, local applications against kernel-level keyloggers and likewise. It is compatible to unmodified operating systems and works on a modern commodity notebook out of the box. Hence, SGXIO is particularly promising for the broad x86 community to which SGX is readily available.


title: A Large Coverage Verb Taxonomy for Arabic.

abstract: In this article I present a lexicon for Arabic verbs which exploits Levin’s verb-classes (Levin, 1993) and the basic development procedure used by (Schuler, 2005). The verb lexicon in its current state has 173 classes which contain 4392 verbs and 498 frames providing information about verb root, the deverbal form of the verb, the participle, thematic roles, subcategorisation frames and syntactic and semantic descriptions of each verb. The taxonomy is available in XML format. It can be ported to MYSQL, YAML or JSON and accessed either in Arabic characters or in the Buckwalter transliteration.


Bringing Ethics into Focus: How Regulatory Focus and Risk Preferences Influence (Un)ethical Behavior


Deep Learning-based Poetry Generation Given Visual Input


title: Learning Facial Expressions with 3D Mesh Convolutional Neural Network

abstract: Making machines understand human expressions enables various useful applications in human-machine interaction. In this article, we present a novel facial expression recognition approach with 3D Mesh Convolutional Neural Networks (3DMCNN) and a visual analytics-guided 3DMCNN design and optimization scheme. From an RGBD camera, we first reconstruct a 3D face model of a subject with facial expressions and then compute the geometric properties of the surface. Instead of using regular Convolutional Neural Networks (CNNs) to learn intensities of the facial images, we convolve the geometric properties on the surface of the 3D model using 3DMCNN. We design a geodesic distance-based convolution method to overcome the difficulties raised from the irregular sampling of the face surface mesh. We further present interactive visual analytics for the purpose of designing and modifying the networks to analyze the learned features and cluster similar nodes in 3DMCNN. By removing low-activity nodes in the network, the performance of the network is greatly improved. We compare our method with the regular CNN-based method by interactively visualizing each layer of the networks and analyze the effectiveness of our method by studying representative cases. Testing on public datasets, our method achieves a higher recognition accuracy than traditional image-based CNN and other 3D CNNs. The proposed framework, including 3DMCNN and interactive visual analytics of the CNN, can be extended to other applications.


title: Categorical Frameworks for Graph Transformation and HLR Systems Based on the DPO Approach

abstract: Several variants of high-level replacement (HLR) and adhesive categories have been introduced in the literature as categorical frameworks for graph transformation and HLR systems based on the double pushout (DPO) approach. In addition to HLR, adhesive, and adhesive HLR categories several weak variants, especially weak adhesive HLR with horizontal and vertical variants, as well as partial variants, including partial map adhesive and partial VK square adhesive categories are reviewed and related to each other. We propose as weakest version the class of vertical weak adhesive HLR categories, shortM-adhesive categories, which are still sufficient to obtain most of the main results for graph transformation and HLR systems. The results in this paper are summarized in Fig. 1 showing a hierarchy of all these variants of adhesive, adhesive HLR, andM-adhesive categories, which can be considered as different categorical frameworks for graph transformation and HLR systems.


Generating Paraphrases from DBPedia using Deep Learning.


E.: An Injection Island GA for Flywheel Design Optimization


title: Recommending Eco-Friendly Route Plans

abstract: As personal transportation is one of the greatest contributors of CO2 emissions, means able to assist travelers in reducing their ecological impact are urgently needed. In this work we focus on travel recommenders that encourage green transportation habits among travelers who have a preexisting interest in taking action to lessen their impact on the environment. We aim to provide urban travelers with a personalized travel recommender that will nudge them to plan routes while considering the environmentally friendliest travel modes. We present a novel, ecologically-aware approach for travel recommender systems and propose a system architecture that incorporates dimensions of recommendation information elements and prole matching methods.


title: Simulated Attack on DNP3 Protocol in SCADA System

abstract: Supervisory Control and Data Acquisition (SCADA) system monitors and controls industrial process in physical critical Infrastructures. It is thus of vital importance that any vulnerabilities of SCADA system must be identified and mitigated. DNP3 is and open SCADA network protocol that is mainly used in electrical utilities. However, the security mechanisms of DNP3 were neglected at its design stage. For example, the coverage of DNP3 Secure Authentication is limited to itself only. In our experiments, we have successfully performed a number of attacks to DNP3 on a small-scale testbed. Hence, this paper will not only discuss our experimental results but also propose a novel hybrid method that can enhance the security of existing DNP3 protocol by combining both encryption and authentication techniques.


title: Cooperative Nonlinear Output Regulation of Multi-agent Systems with Uncertain Leader*

abstract: In this work, we investigate the cooperative output regulation problem of multi-agent uncertain nonlinear systems in lower triangular form with unknown leader. The cooperative output regulator construction is done based on a nonlinear internal model approach. Specifically, nonlinear internal models are first constructed, converting the cooperative output regulation problem into a cooperative stabilization problem of the augmented system, and then an integral input-to-state stable (iISS) based approach is proposed to solve the latter cooperative stabilization. It finally gives rise to a constructive state feedback design for cooperative nonlinear output regulation problem.


title: Different approaches for probability of common cause failure on demand calculations for safety integrity systems

abstract: The common cause failures (ccf) are the biggest part when calculating the probability of failure for redundant safety integrity systems. A ccf can occur, when a random hardware failure leads to a failure of several components. There are several methods to calculate the probability of ccf. Three models will be shown in this paper, with the help of which the beta-factor will be calculated. The ccf ratio for the calculation of the overall probability of failure is defined with the beta-factor.


title: Virtual Reality: Opportunities and Challenges

abstract: Virtual Reality systems have drawn much attention by researchers and companies in the last few years. Virtual Reality is a term that applies to computer-simulated environments that can simulate physical presence in places in the real world, as well as in imaginary worlds. Interactivity and its captivating power, contribute to the feeling of being the part of the action on the virtual safe environment, without any real danger. So, Virtual Reality has been a promising technology applicable in various domains of application such as training simulators, medical and health care, education, scientific visualization, and entertainment industry. Virtual reality can lead to state of the art technologies like Second Life, too. Like many advantageous technologies, beside opportunities of Virtual Reality and Second Life, inevitable challenges appear, too. This paper is a technical brief on Virtual Reality technology and its opportunities and challenges in different areas.


title: A new two-stage Op-Amp using hybrid cascode compensation, bulk-driven, and positive feedback techniques

abstract: In this paper a 0.9V high gain, high speed two-stage Op-Amp is designed and simulated in a 0.18µm CMOS technology. Using both bulk-driven and positive feedback techniques, the dc gain of this Op-Amp is increased about 18.5dB without consuming more power. In addition, the frequency response of the proposed Op-Amp is investigated. Compared to the conventional Op-Amp structure, it is shown that in the proposed Op-Amp, in spite of the decrease of the first pole, the other poles and zeros are not changed. In other words, while the UGBW and phase margin are identical for both conventional and proposed Op-Amps, in the proposed Op-Amp, the pole splitting is performed better than its conventional counterpart. The simulation results show a dc gain of 94dB, unity gain frequency of 549MHz and phase margin of 68°. The slew rate is 200V/µs and the Op-Amp dissipates about 2.73mW from a 0.9V supply voltage.


Integrating Web 2.0 Technologies into Face-to-Face PBL to Support Producing, Storing, and Sharing Content in a Higher Education Course


Analyzing Framing through the Casts of Characters in the News


title: Depression and postoperative complications: an overview

abstract: The interaction of depression and anesthesia and surgery may result in significant increases in morbidity and mortality of patients. Major depressive disorder is a frequent complication of surgery, which may lead to further morbidity and mortality. Several electronic data bases, including PubMed, were searched pairing “depression” with surgery, postoperative complications, postoperative cognitive impairment, cognition disorder, intensive care unit, mild cognitive impairment and Alzheimer’s disease. The suppression of the immune system in depressive disorders may expose the patients to increased rates of postoperative infections and increased mortality from cancer. Depression is commonly associated with cognitive impairment, which may be exacerbated postoperatively. There is evidence that acute postoperative pain causes depression and depression lowers the threshold for pain. Depression is also a strong predictor and correlate of chronic post-surgical pain. Many studies have identified depression as an independent risk factor for development of postoperative delirium, which may be a cause for a long and incomplete recovery after surgery. Depression is also frequent in intensive care unit patients and is associated with a lower health-related quality of life and increased mortality. Depression and anxiety have been widely reported soon after coronary artery bypass surgery and remain evident one year after surgery. They may increase the likelihood for new coronary artery events, further hospitalizations and increased mortality. Morbidly obese patients who undergo bariatric surgery have an increased risk of depression. Postoperative depression may also be associated with less weight loss at one year and longer. The extent of preoperative depression in patients scheduled for lumbar discectomy is a predictor of functional outcome and patient’s dissatisfaction, especially after revision surgery. General postoperative mortality is increased. Depression is a frequent cause of morbidity in surgery patients suffering from a wide range of conditions. Depression may be identified through the use of Patient Health Questionnaire-9 or similar instruments. Counseling interventions may be useful in ameliorating depression, but should be subject to clinical trials.


title: Effects of Coconut Oil on Human Health

abstract: Coconut oil (CO) has generated discussions about its possible effects on health, especially for being an oil rich in saturated fat, which is known to contribute to the development of atherosclerosis and cardiovascular diseases. On the other hand, CO contains high levels of lauric acid that is directly absorbed by enterocytes and may prevent the fat deposition in blood vessels. In addition, flavonoids and polyphenols present in CO may be beneficial in reducing the oxidative stress involved in the etiology of various diseases, for instance, cardiovascular diseases and cancer. This article aimed to review the likely benefits of CO and its effects related to oxidative stress, hyperlipidemia and chronicle diseases in humans.


title: You are what you eat? Vegetarianism, health and identity.

abstract: This paper examines the views of 'health vegetarians' through a qualitative study of an online vegetarian message board. The researcher participated in discussions on the board, gathered responses to questions from 33 participants, and conducted follow-up e-mail interviews with 18 of these participants. Respondents were predominantly from the United States, Canada and the UK. Seventy per cent were female, and ages ranged from 14 to 53 years, with a median of 26 years. These data are interrogated within a theoretical framework that asks, 'what can a vegetarian body do?' and explores the physical, psychic, social and conceptual relations of participants. This provides insights into the identities of participants, and how diet and identity interact. It is concluded that vegetarianism is both a diet and a bodily practice with consequences for identity formation and stabilisation.


title: Algebraic Multigrid Preconditioning of High-Order Spectral Elements for Elliptic Problems on a Simplicial Mesh

abstract: Algebraic multigrid is investigated as a solver for linear systems that arise from high-order spectral element discretizations. An algorithm is introduced that utilizes the efficiency of low-order finite elements to precondition the high-order method in a multilevel setting. In particular, the efficacy of this approach is highlighted on simplexes in two and three dimensions with nodal spectral elements up to order $n=11$. Additionally, a hybrid preconditioner is also developed for use with discontinuous spectral element methods. The latter approach is verified for the discontinuous Galerkin method on elliptic problems.


title: Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groups

abstract: Background. Qualitative research explores complex phenomena encountered by clinicians, health care providers, policy makers and consumers. Although partial checklists are available, no consolidated reporting framework exists for any type of qualitative design. Objective. To develop a checklist for explicit and comprehensive reporting of qualitative studies (indepth interviews and focus groups). Methods. We performed a comprehensive search in Cochrane and Campbell Protocols, Medline, CINAHL, systematic reviews of qualitative studies, author or reviewer guidelines of major medical journals and reference lists of relevant publications for existing checklists used to assess qualitative studies. Seventy-six items from 22 checklists were compiled into a comprehensive list. All items were grouped into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. Duplicate items and those that were ambiguous, too broadly defined and impractical to assess were removed. Results. Items most frequently included in the checklists related to sampling method, setting for data collection, method of data collection, respondent validation of findings, method of recording data, description of the derivation of themes and inclusion of supporting quotations. We grouped all items into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. Conclusions. The criteria included in COREQ, a 32-item checklist, can help researchers to report important aspects of the research team, study methods, context of the study, findings, analysis and interpretations.


title: Life course transitions and racial and ethnic differences in smoking prevalence.

abstract: This study aims to: (1) describe trajectories in the likelihood of smoking by racial or ethnic group across the transition to adulthood, (2) identify the influence of achieved socioeconomic status (SES) and the nature and timing of adult role transitions, and (3) determine the extent to which achieved SES and adult roles mediate the effects of race and ethnicity on smoking. The analyses use U.S. longitudinal data from the National Longitudinal Study of Adolescent Health (Add Health), which follows a representative national sample over four waves and from ages 11–17 in 1994/95 to 26–34 in 2007/08. Growth curve models compare trajectories of smoking likelihood for white, black, Hispanic, Asian/Pacific Islander, and American Indian/Alaska Native individuals. While whites have higher rates of smoking than blacks and Hispanics during their teen years and 20s, blacks and Hispanics lose their advantage relative to whites as they approach and enter their 30s. American Indian/Alaska Natives show high rates of smoking at earlier ages and an increasing likelihood to smoke. Although life course transitions are influential for smoking prevalence in the overall U.S. population, SES and the nature and timing of adult role transitions account for little of the gap between whites and black, Hispanic, and American Indian/Alaska Native individuals. Racial and ethnic disparities in adult smoking are independent of SES and life transitions, pointing to explanations such as culturally specific normative environments or experiences of discrimination.


title: Minutia Cylinder-Code: A New Representation and Matching Technique for Fingerprint Recognition

abstract: In this paper, we introduce the Minutia Cylinder-Code (MCC): a novel representation based on 3D data structures (called cylinders), built from minutiae distances and angles. The cylinders can be created starting from a subset of the mandatory features (minutiae position and direction) defined by standards like ISO/IEC 19794-2 (2005). Thanks to the cylinder invariance, fixed-length, and bit-oriented coding, some simple but very effective metrics can be defined to compute local similarities and to consolidate them into a global score. Extensive experiments over FVC2006 databases prove the superiority of MCC with respect to three well-known techniques and demonstrate the feasibility of obtaining a very effective (and interoperable) fingerprint recognition implementation for light architectures.


title: Super Resolution Image Generation Using Wavelet Domain Interpolation With Edge Extraction via a Sparse Representation

abstract: This letter addresses the problem of generating a super-resolution (SR) image from a single low-resolution (LR) input image in the wavelet domain. To achieve a sharper image, an intermediate stage for estimating the high-frequency (HF) subbands has been proposed. This stage includes an edge preservation procedure and mutual interpolation between the input LR image and the HF subband images, as performed via the discrete wavelet transform (DWT). Sparse mixing weights are calculated over blocks of coefficients in an image, which provides a sparse signal representation in the LR image. All of the subband images are used to generate the new high-resolution image using the inverse DWT. Experimental results indicated that the proposed approach outperforms existing methods in terms of objective criteria and subjective perception improving the image resolution.


title: Detection of non-flat ground surfaces using V-Disparity images

abstract: Ground plane detection plays an important role in stereo vision based obstacle detection methods. Recently, V-Disparity image has been widely used for ground plane detection. The existing approach based on V-Disparity image can detect flat ground successfully but have difficulty in detecting non-flat ground. In this paper, we discuss the representation of non-flat ground in V-Disparity image, based on which we propose a method to detect non-flat ground using V-Disparity image.


title: A computational analysis of poetic style Imagism and its influence on modern professional and amateur poetry

abstract: How do standards of poetic beauty change as a function of time and expertise? Here we use computational methods to compare the stylistic features of 359 English poems written by 19th century professional poets, Imagist poets, contemporary professional poets, and contemporary amateur poets. Building upon techniques designed to analyze style and sentiment in texts, we examine elements of poetic craft such as imagery, sound devices, emotive language, and diction. We find that contemporary professional poets use significantly more concrete words than 19th century poets, fewer emotional words, and more complex sound devices. These changes are consistent with the tenets of Imagism, an early 20thcentury literary movement. Further analyses show that contemporary amateur poems resemble 19th century professional poems more than contemporary professional poems on several dimensions. The stylistic similarities between contemporary amateur poems and 19th century professional poems suggest that elite standards of poetic beauty in the past “trickled down” to influence amateur works in the present. Our


title: Reporting intellectual capital in annual reports: evidence from Ireland

abstract: Examines the extent to which 11 knowledge‐based Irish listed companies are adopting methodologies for reporting of intellectual capital in their annual reports. Their market and book values were compared and a content analysis of the annual reports of the 11 listed companies was conducted. With the exception of two of the 11 listed companies, significant differences in market and book values were found, suggesting that knowledge‐based Irish listed companies have a substantial level of non‐physical, intangible, intellectual capital assets. The level of disclosure of intellectual capital attributes by the 11 listed companies studied was low.


title: SMS flood alert system

abstract: Flood disaster is considered a norm for Malaysians since Malaysia is located near the Equator. Flood disaster usually happens due to improper irrigation method in a housing area or the sudden increase of water volume in a river. Flood disaster often causes lost of property, damages and life. Since this disaster is considered dangerous to human life, an efficient countermeasure or alert system must be implemented in order to notify people in the early stage so that safety precautions can be taken to avoid any mishaps. This paper presents a remote water level alarm system developed by applying liquid sensors and GSM technology. System focuses on monitoring water level remotely and utilizes Global System of Mobile Connections (GSM) and Short Message Service (SMS) to convey data from sensors to the respective users through their mobile phone. The hardware of the system includes Micro Controller Unit (MCU) PIC18F452, three (3) liquid sensors, Inverter and Easygate GSM Module. Software used for the system is C compiler thru (ATtention) AT commands. It is hoped that this project would be beneficial to the community and would act as a precautionary measure in case of flood disaster at any flood prone area. By having early detection, users could take swift action such as evacuation so that cases of loss of lives could be minimized.


title: Opinion Mining In Hindi Language: A Survey

abstract: Opinions are very important in the life of human beings. These Opinions helped the humans to carry out the decisions. As the impact of the Web is increasing day by day, Web documents can be seen as a new source of opinion for human beings. Web contains a huge amount of information generated by the users through blogs, forum entries, and social networking websites and so on To analyze this large amount of information it is required to develop a method that automatically classifies the information available on the Web. This domain is called Sentiment Analysis and Opinion Mining. Opinion Mining or Sentiment Analysis is a natural language processing task that mine information from various text forms such as reviews, news, and blogs and classify them on the basis of their polarity as positive, negative or neutral. But, from the last few years, enormous increase has been seen in Hindi language on the Web. Research in opinion mining mostly carried out in English language but it is very important to perform the opinion mining in Hindi language also as large amount of information in Hindi is also available on the Web. This paper gives an overview of the work that has been done Hindi language.


title: Optical based non invasive glucometer with IoT

abstract: Diabetes mellitus (DM) nicknamed as sugar is becoming one of incurable and critical challenge to medical field. Serious illness such as premature mortality even cause of death, which can be identified by continuous monitoring from a remote location. The traditional and conventional method such as finger pricking's demerits such as pain and damage to tissues that cause infection. Such type of infections can be overcome by non invasive technique. The objective of this paper is to monitor glucose level using non invasive technique by optical and IoT technology. The proposed sensor circuit consists of IR LED's of wavelength 650–2500nm for optical blood glucose measurement and NIR photodiodes (InGaAs) to receive the reflected light from body parts to determine the glucose level. The Beer-Lambert law is used for signal processing along with GSM based IoT real time information transmission. The project is implemented using Arduino IDE for finding the performance matrix of the system as well as various analytical studies.


title: Autoencoder With Invertible Functions for Dimension Reduction and Image Reconstruction

abstract: The extreme learning machine (ELM), which was originally proposed for “generalized” single-hidden layer feedforward neural networks, provides efficient unified learning solutions for the applications of regression and classification. Although, it provides promising performance and robustness and has been used for various applications, the single-layer architecture possibly lacks the effectiveness when applied for natural signals. In order to over come this shortcoming, the following work indicates a new architecture based on multilayer network framework. The significant contribution of this paper are as follows: 1) unlike existing multilayer ELM, in which hidden nodes are obtained randomly, in this paper all hidden layers with invertible functions are calculated by pulling the network output back and putting it into hidden layers. Thus, the feature learning is enriched by additional information, which results in better performance; 2) in contrast to the existing multilayer network methods, which are usually efficient for classification applications, the proposed architecture is implemented for dimension reduction and image reconstruction; and 3) unlike other iterative learning-based deep networks (DL), the hidden layers of the proposed method are obtained via four steps. Therefore, it has much better learning efficiency than DL. Experimental results on 33 datasets indicate that, in comparison to the other existing dimension reduction techniques, the proposed method performs competitively better with fast training speeds.


title: A Stress-Detection System Based on Physiological Signals and Fuzzy Logic

abstract: A stress-detection system is proposed based on physiological signals. Concretely, galvanic skin response (GSR) and heart rate (HR) are proposed to provide information on the state of mind of an individual, due to their nonintrusiveness and noninvasiveness. Furthermore, specific psychological experiments were designed to induce properly stress on individuals in order to acquire a database for training, validating, and testing the proposed system. Such system is based on fuzzy logic, and it described the behavior of an individual under stressing stimuli in terms of HR and GSR. The stress-detection accuracy obtained is 99.5% by acquiring HR and GSR during a period of 10 s, and what is more, rates over 90% of success are achieved by decreasing that acquisition period to 3-5 s. Finally, this paper comes up with a proposal that an accurate stress detection only requires two physiological signals, namely, HR and GSR, and the fact that the proposed stress-detection system is suitable for real-time applications.


title: The Development of Embodied Cognition: Six Lessons from Babies

abstract: The embodiment hypothesis is the idea that intelligence emerges in the interaction of an agent with an environment and as a result of sensorimotor activity. We offer six lessons for developing embodied intelligent agents suggested by research in developmental psychology. We argue that starting as a baby grounded in a physical, social, and linguistic world is crucial to the development of the flexible and inventive intelligence that characterizes humankind.


title: RE-irradiation of silver nanoparticles obtained by laser ablation in water and assessment of their antibacterial effect

abstract: Abstract The rapid evolution of resistant bacteria is a huge problem in medicine because makes the treatment of infections more and more difficult. The bactericidal properties of noble metal nanoparticles could be a solution. In this work silver nanoparticles were produced by using two nanosecond Nd:YVO4 lasers operating at 1064 and 532 nm respectively to ablate a silver target submerged in pure de-ionized water. Part of the resulting colloidal solution was injected as a fine stream by a compressed air system and re-irradiated one and three times with the same laser to resize and get uniform nanoparticles. The obtained nanoparticles by ablation and re-irradiation consisted of crystalline Ag nanoparticles with a bimodal size distribution. The particle size has been reduced by subsequent laser re-irradiation with both laser sources, reaching a 40% of mean size reduction. Inhibitory effects on the proliferation of Staphylococcus aureus was demonstrated on silver nanoparticles obtained after re-irradiation with the infrared laser.


title: Efficient Computation of G-Skyline Groups

abstract: The skyline of a data point set is made up of the best points in the set, and is very important for multi-criteria decision making. In these years, the skyline problem attracts more and more attention, and many variants of the traditional skyline emerge in the database field. One recent and important variant is group-based skyline, which aims to find the best groups of points in a given set. In this paper, we bring forward an efficient approach, called minimum dominance search (MDS), to solve the g-skyline problem, a latest group-based skyline problem. MDS consists of two steps: In the first step, we construct a novel g-skyline support structure, i.e., minimum dominance graph (MDG), which proves to be a minimum g-skyline support structure. In the second step, we search for g-skyline groups based on the MDG through two searching algorithms, and a skyline-combination based optimization strategy is employed to improve these two algorithms. We conduct comprehensive experiments on both synthetic and real-world data sets, and show that our algorithms are orders of magnitude faster than the state-of-the-art in most cases.


title: Multiple Bernoulli relevance models for image and video annotation

abstract: Retrieving images in response to textual queries requires some knowledge of the semantics of the picture. Here, we show how we can do both automatic image annotation and retrieval (using one word queries) from images and videos using a multiple Bernoulli relevance model. The model assumes that a training set of images or videos along with keyword annotations is provided. Multiple keywords are provided for an image and the specific correspondence between a keyword and an image is not provided. Each image is partitioned into a set of rectangular regions and a real-valued feature vector is computed over these regions. The relevance model is a joint probability distribution of the word annotations and the image feature vectors and is computed using the training set. The word probabilities are estimated using a multiple Bernoulli model and the image feature probabilities using a non-parametric kernel density estimate. The model is then used to annotate images in a test set. We show experiments on both images from a standard Corel data set and a set of video key frames from NIST's video tree. Comparative experiments show that the model performs better than a model based on estimating word probabilities using the popular multinomial distribution. The results also show that our model significantly outperforms previously reported results on the task of image and video annotation.


title: Lidar Remote Sensing of the Canopy Structure and Biophysical Properties of Douglas-Fir Western Hemlock Forests

abstract: 21 of biomass and an LAI of 12, with 90% and like conventional microwave and optical sensors, lidar 75% of variance explained, respectively. Furthermore, we sensors directly measure the distribution of vegetation were able to make accurate estimates of other stand material along the vertical axis and can be used to pro- structure attributes, including the mean and standard devide three-dimensional, or volumetric, characterizations viation of diameter at breast height, the number of stems of vegetation structure. Ecological applications of scan- greater than 100 cm in diameter, and independent estining lidar have hitherto used one-dimensional indices to mates of the basal area of Douglas-fir and western hemcharacterize canopy height. A novel three-dimensional lock. These measurements can be directly related to indianalysis of lidar waveforms was developed to character- ces of forest stand structural complexity, such as those ize the total volume and spatial organization of vegeta- developed for old-growth forest characterization. Indices tion material and empty space within the forest canopy. of canopy structure developed using the novel, threeThese aspects of the physical structure of canopies have dimensional analysis accounted for most of the variables been infrequently measured, from either field or remote used in predictive equations generated by the stepwise methods. We applied this analysis to 22 plots in Douglas- multiple regression. Published by Elsevier Science Inc. fir/western hemlock stands on the west slope of the Cascades Range in Oregon. Each plot had coincident lidar data and field measurements of stand structure. We com- INTRODUCTION pared results from the novel analysis to two earlier methCharacterization of structure in moderate to high bioods of canopy description. Using the indices of canopy mass forests is a major challenge in remote sensing. structure from all three methods of description as inde


title: Postnatal depression in first-time mothers: prevalence and relationships between functional and structural social support at 6 and 12 weeks postpartum.

abstract: Postnatal depression (PND) is a significant public health issue, with variable prevalence and a dearth of research on risk and protective factors. This quantitative longitudinal study of 512 first-time mothers identified the prevalence of PND and examined the relationships between functional and structural social support at 6 and 12 weeks postpartum. The prevalence of PND was 13.2% at 6 weeks and 9.8% at 12 weeks. At 6 and 12 weeks, the only social support dimension independently associated with PND was total functional social support. At-birth formal structural support and emotional functional support were independently predictive of PND at 12 weeks.


title: The research of DC traction power supply system and the DDL protection algorithm based on MATLAB/Simulink

abstract: This paper presents a simulation and protection algorithm of DDL in DC traction system based on MATLAB/Simulink. With the introduction of the operation of DC traction system, this paper developed different models and implemented the simulation and test separately for different feeding arrangement and operation condition of DC power supply system, analyzed the characteristics of the typical train starting current and remote short-circuit current based on simulation results. This paper proposed a DDL protection scheme and designed the algorithm logic of DDL protection scheme. This paper combined the Simulink simulation and MATLAB programming method, proved the effectiveness of the protection scheme.


title: Optimal Mass Transport for Registration and Warping

abstract: Image registration is the process of establishing a common geometric reference frame between two or more image data sets possibly taken at different times. In this paper we present a method for computing elastic registration and warping maps based on the Monge–Kantorovich theory of optimal mass transport. This mass transport method has a number of important characteristics. First, it is parameter free. Moreover, it utilizes all of the grayscale data in both images, places the two images on equal footing and is symmetrical: the optimal mapping from image A to image B being the inverse of the optimal mapping from B to A. The method does not require that landmarks be specified, and the minimizer of the distance functional involved is uniques there are no other local minimizers. Finally, optimal transport naturally takes into account changes in density that result from changes in area or volume. Although the optimal transport method is certainly not appropriate for all registration and warping problems, this mass preservation property makes the Monge–Kantorovich approach quite useful for an interesting class of warping problems, as we show in this paper. Our method for finding the registration mapping is based on a partial differential equation approach to the minimization of the L2 Kantorovich–Wasserstein or “Earth Mover's Distance” under a mass preservation constraint. We show how this approach leads to practical algorithms, and demonstrate our method with a number of examples, including those from the medical field. We also extend this method to take into account changes in intensity, and show that it is well suited for applications such as image morphing.


title: Data-efficient Deep Reinforcement Learning for Dexterous Manipulation

abstract: Grasping an object and precisely stacking it on another is a difficult task for traditional robotic control or hand-engineered approaches. Here we examine the problem in simulation and provide techniques aimed at solving it via deep reinforcement learning. We introduce two straightforward extensions to the Deep Deterministic Policy Gradient algorithm (DDPG), which make it significantly more data-efficient and scalable. Our results show that by making extensive use of off-policy data and replay, it is possible to find high-performance control policies. Further, our results hint that it may soon be feasible to train successful stacking policies by collecting interactions on real robots.


title: Rhizosphere chemical dialogues: plant-microbe interactions.

abstract: Every organism on earth relies on associations with its neighbors to sustain life. For example, plants form associations with neighboring plants, microflora, and microfauna, while humans maintain symbiotic associations with intestinal microbial flora, which is indispensable for nutrient assimilation and development of the innate immune system. Most of these associations are facilitated by chemical cues exchanged between the host and the symbionts. In the rhizosphere, which includes plant roots and the surrounding area of soil influenced by the roots, plants exude chemicals to effectively communicate with their neighboring soil organisms. Here we review the current literature pertaining to the chemical communication that exists between plants and microorganisms and the biological processes they sustain.


title: Left atrial strain in patients with arterial hypertension early effects of arterial hypertension : left atrial deformation analysis by two-dimensional speckle tracking echocardiography

abstract: Background: Arterial hypertension (HTN) causes left ventricular (LV) cavity dysfunction even if ejection function (EF) remains preserved. Recent studies have shown that diastolic dysfunction and left atrial (LA) dilatation are also associated with myocardial dysfunction. The aim of the present study was to explore the nature of LA longitudinal function disturbances in hypertensive patients with normal LV and LA structure and conventional function parameters. Methods: Peak atrial longitudinal strain (PALS) was evaluated in 78 patients with systemic HTN and preserved EF (≥ 55%) divided in 41 patients with diastolic dysfunction but no hypertrophy (group HTNdd), and 37 patients with no diastolic dysfunction or hypertrophy (group eHTN). Results were compared with those from 38 age and gender-matched healthy controls. Results: Indexed LA area and indexed LA volume were within the normal range and not different between the two patient groups and controls. eHTN group had reduced global PALS (p < 0.001) and four-and two-chamber average PALS (p < 0.001 for both). Similar abnormalities were seen in HTNdd group but to a worse degree (P < 0.01 for both). LV EF was not different between the eHTN and HTNdd groups compared to controls. LV E/e’ ratio was the strongest predictor of reduced global PALS in both eHTN and HTNdd groups. Conclusion: Asymptomatic untreated HTN patients with preserved LVEF and normal diastolic function have compromised LA strain despite normal cavity size, consistent with preclinical LA myocardial dysfunction.


title: A text visualization method for cross-domain research topic mining

abstract: Cross-domain research topic mining can help users find relationships among related research domains and obtain a quick overview of these domains. This study investigates the evolution of cross-domain topics of three interdisciplinary research domains and uses a visual analytic approach to determine unique topics for each domain. This study also focuses on topic evolution over 10 years and on individual topics of cross domains. A hierarchical topic model is adopted to extract topics of three different domains and to correlate the extracted topics. A simple yet effective visualization interface is then designed, and certain interaction operations are provided to help users more deeply understand the visualization development trend and the correlation among the three domains. Finally, a case study is conducted to demonstrate the effectiveness of the proposed method.Graphical Abstract


title: Electronic cigarettes increase endothelial progenitor cells in the blood of healthy volunteers.

abstract: BACKGROUND AND AIMS ::: The use of electronic cigarettes is increasing dramatically on a global scale and its effects on human health remain uncertain. In the present study, we measured endothelial progenitor cells (EPCs) and microvesicles (MVs) in healthy young volunteers following short-term exposure to inhalation of e-cigarette vapor (ECV) to determine vascular changes. ::: ::: ::: METHODS ::: Sixteen healthy seldom smokers were randomized into two groups either exposed or not exposed to 10 puffs of ECV for 10 min, in a crossover design. Blood samples were obtained at baseline and 1, 4 and 24 h following exposure. EPCs (CD34 + CD309) and MVs were analyzed by flow cytometry. MVs were phenotyped according to origin (platelet (CD41), endothelial (CD144), leukocytes (CD45), monocytes (CD14)) and nuclear content (SYTO 13 dye). In addition, expression of inflammation markers such P-selectin (CD62P), E-selectin (CD62E), CD40-ligand (CD154) and HMGB1 was investigated. Fractional exhaled nitric oxide (FeNO) was also measured at baseline and after 24 h. ::: ::: ::: RESULTS ::: EPC levels in blood were significantly increased 1 h following exposure to ECV and returned to baseline values after 24 h. Only E-selectin positive MVs (endothelial origin) were slightly elevated (p < 0.038). FeNO was unaffected by exposure to ECV. ::: ::: ::: CONCLUSIONS ::: In healthy volunteers, ten puffs of e-cigarette vapor inhalation caused an increase in EPCs. This increase was of the same magnitude as following smoking of one traditional cigarette, as we previously demonstrated. Taken together, these results may represent signs of possible vascular changes after short e-cigarette inhalation. Further studies analyzing potential cardiovascular health effects are critical as the e-cigarette market continues to burgeon.


abstract: Content-based 3D shape retrieval is an important problem in computer vision. Traditional retrieval interfaces require a 2D sketch or a manually designed 3D model as the query, which is difficult to specify and thus not practical in real applications. With the recent advance in low-cost 3D sensors such as Microsoft Kinect and Intel Realsense, capturing depth images that carry 3D information is fairly simple, making shape retrieval more practical and user-friendly. In this paper, we study the problem of cross-domain 3D shape retrieval using a single depth image from low-cost sensors as the query to search for similar human designed CAD models. We propose a novel method using an ensemble of autoencoders in which each autoencoder is trained to learn a compressed representation of depth views synthesize d from each database object. By viewing each autoencoder as a probabilistic model, a likelihood score can be derived as a similarity measure. A domain adaptation layer is built on top of autoencoder outputs to explicitly address the cross-domain issue (between noisy sensory data and clean 3D models) by incorporating training data of sensor depth images and their category labels in a weakly supennsed learning formulation. Experiments using real-world depth images and a large-scale CAD dataset demonstrate the effectiveness of our approach, which offers significant improvements over state-of-the-art 3D shape retrieval methods.


title: Automatic Labelling of Topic Models

abstract: We propose a method for automatically labelling topics learned via LDA topic models. We generate our label candidate set from the top-ranking topic terms, titles of Wikipedia articles containing the top-ranking topic terms, and sub-phrases extracted from the Wikipedia article titles. We rank the label candidates using a combination of association measures and lexical features, optionally fed into a supervised ranking model. Our method is shown to perform strongly over four independent sets of topics, significantly better than a benchmark method.


title: Data Channel Design and Performance for LTE Narrowband IoT

abstract: In 3GPP Rel-13, a narrowband system based on Long Term Evolution (LTE) is being introduced to provide wide-area cellular connectivity for the Internet of Things. This system, named Narrowband Internet of Things (NB-IoT), can be deployed in three different operation modes - (1) stand-alone as a dedicated carrier, (2) in-band within the occupied bandwidth of a wideband LTE carrier, and (3) within the guard-band of an existing LTE carrier. The design targets of NB-IoT include low-cost devices, high coverage (20-dB improvement over GPRS), long device battery life (more than 10 years), and massive capacity. Latency is relaxed although a delay budget of 10 seconds is the target for exception reports. This paper discusses the design and performance of the downlink and uplink data channels. Although the design of these channels is based on LTE, there are some differences, particularly in the uplink, with the introduction of subcarrier-level transmission. The similarities have enabled rapid specification, while the enhancements in the design enable the achievement of the stated targets for NB-IoT.


title: Wideband Branch-Line Couplers With Single-Section Quarter-Wave Transformers for Arbitrary Coupling Levels

abstract: Wideband branch-line couplers with arbitrary coupling levels are demonstrated. By integrating single-section quarter-wave transformers at each port, wideband characteristic with excellent coupling flatness is achieved. Also, a method is demonstrated that introduces intentional mismatch for a further enhancement in bandwidth. Superior structural and design simplicity outperform previous wideband couplers. Branch-line couplers at 3 GHz are demonstrated experimentally that maintain the coupling level within 0.5 dB from the specified 10 dB in as much as a 50.9% bandwidth, with minimum return loss and isolation of 16.3 and 18.7 dB, respectively.


title: A very low-profile UWB phased array antenna design for supporting wide angle beam steering

abstract: This paper presents a design example of a low-profile UWB dual-polarization array antenna design based on tightly-coupled dipole elements. This supports array can support beam steering for more than 60° beam steering in both E- and H-plane with more than 2.5:1 impedance bandwidth, from 0.55 fc to 1.45fc where fc is the center frequency. An 18×18 array prototype was fabricated and measured to validate the performance of the proposed design.


title: Distributed Event-Triggered Scheme for Economic Dispatch in Smart Grids

abstract: To reduce information exchange requirements in smart grids, an event-triggered communication-based distributed optimization is proposed for economic dispatch. In this work, the $\theta$ -logarithmic barrier-based method is employed to reformulate the economic dispatch problem, and the consensus-based approach is considered for developing fully distributed technology-enabled algorithms. Specifically, a novel distributed algorithm utilizes the minimum connected dominating set (CDS), which efficiently allocates the task of balancing supply and demand for the entire power network at the beginning of economic dispatch. Further, an event-triggered communication-based method for the incremental cost of each generator is able to reach a consensus, coinciding with the global optimality of the objective function. In addition, a fast gradient-based distributed optimization method is also designed to accelerate the convergence rate of the event-triggered distributed optimization. Simulations based on the IEEE 57-bus test system demonstrate the effectiveness and good performance of proposed algorithms.


title: Predicting Economic Indicators from Web Text Using Sentiment Composition

abstract: Of late there has been a significant amount of work on using sources of text data from the Web (such as Twitter or Google Trends) to predict financial and economic variables of interest. Much of this work has relied on some form or other of superficial sentiment analysis to represent the text. In this work we present a novel approach to predicting economic variables using sentiment composition over text streams of Web data. We treat each text stream as a separate sentiment source with its own predictive distribution. We then use a Bayesian classifier combination model to combine the separate predictions into a single optimal prediction for the Nonfarm Payroll index, a primary economic indicator. Our results show that we can achieve high predictive accuracy using sentiment over big text streams.


title: Towards domain-independent information extraction from web tables

abstract: Traditionally, information extraction from web tables has focused on small, more or less homogeneous corpora, often based on assumptions about the use of tags. A multitude of different HTML implementations of web tables make these approaches difficult to scale. In this paper, we approach the problem of domain-independent information extraction from web tables by shifting our attention from the tree-based representation of webpages to a variation of the two-dimensional visual box model used by web browsers to display the information on the screen. The there by obtained topological and style information allows us to fill the gap created by missing domain-specific knowledge about content and table templates. We believe that, in a future step, this approach can become the basis for a new way of large-scale knowledge acquisition from the current "Visual Web.


title: Overlapping cell nuclei segmentation in microscopic images using deep belief networks

abstract: This paper proposes a method for segmentation of nuclei of single/isolated and overlapping/touching immature white blood cells from microscopic images of B-Lineage acute lymphoblastic leukemia (ALL) prepared from peripheral blood and bone marrow aspirate. We propose deep belief network approach for the segmentation of these nuclei. Simulation results and comparison with some of the existing methods demonstrate the efficacy of the proposed method.


title: Model Reference Adaptive Control of Permanent Magnet Synchronous Motor

abstract: In this paper the classical theory of the direct Model Reference Adaptive Control is used to develop a control algorithm for Permanent Magnet Synchronous Motor (PMSM). A PMSM model widely used in electric drives community is considered as base for control system development. Conventionally used controllers are replaced by adaptive ones. The resulting control system adapts to changes in any of PMSM parameters.


title: Coronary vasomotor disorders during hypoxia-reoxygenation: do calcium channel blockers play a protective role?

abstract: During heart surgery, myocardial dysfunction may occasionally appear when extracorporeal circulation is discontinued, causing serious haemodynamic disorders. Many mechanisms are involved in this hypoxia-reoxygenation syndrome. The aim of this experimental study was to characterize the vasomotor disorders that take place in the isolated porcine coronary artery during in vitro hypoxia-reoxygenation and to analyse the effect of nifedipine on them. Rings of porcine coronary artery were placed in an organ chamber connected to a system that recorded isometric forces. The vascular rings were divided into two groups: control group (no nifedipine) and study group (nifedipine, 10−6 mol/l). The vascular rings were precontracted with 30 mmol/l KCl and then hypoxia-reoxygenation was induced. Control arterial rings showed important changes in coronary vasomotor tone: severe hypoxic contraction (from 14.48±1.16 g of stable contraction to 17.6±0.44 g after the imposition of hypoxia), and transient vasodilation during reoxygenation (69.9±10.1% of the maximum contraction achieved). The nifedipine group experienced a slow, progressive, vasodilation throughout the whole experiment (73±3.5% of the maximum contraction). Neither hypoxic vasospasm nor fluctuations of the coronary vascular tone occurred. Thus, at the end of the hypoxia, the control vessels presented a degree of contraction similar to the initial level. However, in the rings treated with nifedipine, the percentage of dilation was 73±3.5% (P<0.05). In the isolated porcine coronary artery with intact endothelium undergoing a situation of hypoxia-reoxygenation, we have detected transient vasoconstriction during the first period of hypoxia, followed by vasodilation during reoxygenation. The intracoronary administration of nifedipine prior to the imposition of hypoxia prevents hypoxic contraction, achieving a greater and more stable degree of coronary vasorelaxation during the complete process of hypoxia-reoxygenation.


title: State of the Art in Surface Reconstruction from Point Clouds

abstract: The area of surface reconstruction has seen substantial progress in the past two decades. The traditional problem addressed by surface reconstruction is to recover the digital representation of a physical shape that has been scanned, where the scanned data contains a wide variety of defects. While much of the earlier work has been focused on reconstructing a piece-wise smooth representation of the original shape, recent work has taken on more specialized priors to address significantly challenging data imperfections, where the reconstruction can take on different representations -- not necessarily the explicit geometry. This state-of-the-art report surveys the field of surface reconstruction, providing a categorization with respect to priors, data imperfections, and reconstruction output. By considering a holistic view of surface reconstruction, this report provides a detailed characterization of the field, highlights similarities between diverse reconstruction techniques, and provides directions for future work in surface reconstruction.


title: Vehicle model recognition using geometry and appearance of car emblems from rear view images

abstract: In this paper a novel vehicle model recognition approach is presented modelling the geometry and appearance of car emblems (model, trim level, etc.) from rear view images. The proposed system is assisted by LPR and VMR modules. Thus, a generic methodology is defined to build a hierarchical structure of car-make-dependent vehicle model classifiers. The emblems location, size and variations are firstly learnt. Then, the appearance of each badge is modelled using a linear SVM binary classifier with HOG (histogram of oriented gradients) features and the outputs of each individual classifier are converted to an estimate of posterior probabilities. A specific probability is computed for each hypothesis (model) integrating the posterior probabilities of all the emblems using the geometric mean. Inference about the most probable car model is finally carried out selecting the model with the maximum probability. The authors evaluate this approach on a dataset composed of 1,342 images (910/432 for training/test) corresponding to 8 different car makes and 28 different car models (52 considering generations) achieving an overall accuracy of 93.75%.


title: Cavity perturbation method for characterization of liquid crystals up to 35 GHz

abstract: Liquid Crystals (LCs) are very promising agile materials for tunable microwave components [Z]. Hence, precise microwave measurements are required. In this paper the measurement results of two LCs are presented using a cavity perturbation method with two cavities at 9GHz between -25°C and 45°C and at 3SGHz between -10/sl degC and 80sl degC. The cavities are rectangular waveguide resonators with two insertion holes for LC-filled FTFE-tubes. The complex permittivity as well as the complex permeability of these samples are extracted. The tunability of the LCs are measured by using an external magnetostatic field in order to orient the LC-molecules. Besides the quasi-standard LC K15, a novel mixture is investigated, having a higher tunability and lower losses compared to K1S at microwaves.


title: Three-component stereoselective synthesis of spirooxindole derivatives

abstract: A concise and efficient one-pot regio- and stereoselective synthesis of structurally diverse spirooxindoles was constructed by simply refluxing a mixture of different types of heterocyclic ketene aminals, isatins and ethyl trifluoroacetate using catalytic piperidine. The advantages of this method include high efficiency, mild reaction conditions and environmentally benign reagents. These spirooxindoles are promising candidates for drug discovery; consequently, a library of diverse spirooxindoles was rapidly constructed using the present protocol.


title: Reduction of Low Space Harmonics for the Fractional Slot Concentrated Windings Using a Novel Stator Design

abstract: Using magnetic flux barriers in the stator yoke of electric machines with fractional slots, tooth-concentrated winding, it is possible to reduce or even to cancel some space harmonics of low order in the air-gap flux density resulting in lower rotor losses induced by the armature reaction field. In this paper, this new technique is applied during the design and analysis of two permanent magnet machines with different 12-teeth/10-poles concentrated windings. Considering the main machine performances, such as the electromagnetic torque, machine losses, and also the field-weakening capability, the new stator design shows significant advantages over the conventional design. According to the new technique, a prototype machine is built and some measurement results are given.


title: Ka-band GaN power amplifier MMIC chipset for satellite and 5G cellular communications

abstract: Ka-band gallium nitride (GaN) power amplifier monolithic microwave integrated circuits (MMICs) with 2 W driver Amplifier (DRA) MMIC and 8 W high power amplifier (HPA) MMIC have been developed. These MMICs are demonstrated using a 0.15 um GaN high electron mobility transistor (HEMT) technology on silicon carbide (SiC) substrate. At 28 GHz, the three-stage DRA MMIC in-fixture exhibits 25.8 dB of small signal gain and 33.1 dBm of continuous wave (CW) output power, which is sufficient to drive a HPA MMIC. The three-stage HPA MMIC achieves 23.5 dB of small signal gain, a CW output power of 39 dBm, and power added efficiency (PAE) of 26.6% at 28 GHz. The chip areas of the DRA MMIC and HPA MMIC are 4.08 mm2 and 11.22 mm2, respectively.