bluuebunny/crossref_metadata_2025 huggingface dataset:
A Hyperspectral Subspace Target Detection Method Based on AMUSE
Authors: Hou Yani , Zhu Wenzhong , Wang Erli , Zhang Ying
Published: January 2019

Target detection is an important research topic in hyperspectral image processing, and has been the focus of research of many scholars. Compared with many target detection methods, the subspace target detection method is superior. This paper proposes a hyperspectral subspace target detection method LBSE-AMUSE based on the Local Background Subspace Estimation (LBSE) method and the AMUSE algorithm (Algorithm for Multiple Signals Extraction). HyMap airborne hyperspectral remote sensing data is used as the data source, and the performance between the LBSE and LBSE-AMUSE methods is compared by using quantitative indicators such as false alarm rate, detection rate and ROC curve. The experimental results show that the LBSE-AMUSE method has a simple structure, short running time and low false alarm rate compared with the LBSE method, which can suppress the background highlighting target to some extent.
Quasi-local mass at axially symmetric null infinity
Authors: Chen Po-Ning , Wang Mu-Tao , Wang Ye-Kai , Yau Shing-Tung
Published: January 2019

We give a brief review of the definition of the Wang–Yau quasi-local mass and discuss the evaluation of this quantity on surfaces of unit size at null infinity of an axisymmetric spacetime in Bondi–van der Burg–Metzner coordinates.
DECODING OF SIMPLE AND COMPOUND LIMB MOTOR IMAGERY MOVEMENTS BY FRACTAL ANALYSIS OF ELECTROENCEPHALOGRAM (EEG) SIGNAL
Authors: NAMAZI HAMIDREZA , ALA TIRDAD SEIFI
Published: January 2019

One of the major attempts in rehabilitation science is to decode different movements of human using physiological signals. Since human movements are mainly controlled by the brain, decoding of movements by analysis of the brain activity has great importance. In this paper, we apply fractal analysis to Electroencephalogram (EEG) signal in order to decode simple and compound limb motor imagery movements. The fractal dimension of EEG signal is analyzed in case of left hand, right hand, both hands, feet, left hand combined with right foot, and right hand combined with left foot movements. Based on the obtained results, EEG signal experiences the lowest and greatest fractal dimension in case of both hands movement, and feet movement, respectively. Besides obtaining different fractal dimension for EEG signal in case of different movements, no significant difference was observed in fractal dimension of EEG signal between different movements. The method of analysis employed in this research can be widely applied to analysis of EEG signal for decoding of different movements of human.
DECODING OF SIMPLE HAND MOVEMENTS BY FRACTAL ANALYSIS OF ELECTROMYOGRAPHY (EMG) SIGNAL
Authors: NAMAZI HAMIDREZA , JAFARI SAJAD
Published: January 2019

Analysis of body movement is the most important aspect of rehabilitation science. Hand movement as one of the major movements of humans has aroused the attention of many researchers. For this purpose, decoding of movements by analysis of the related bio signals is very important. In this research, complexity analysis of Electromyography (EMG) signal that was recorded due to simple hand movements is done. For this purpose, we employ fractal dimension as the indicator of complexity of signal in this research. The EMG signal was recorded from subjects while they did six simple hand movements and accordingly we applied fractal analysis on the signal. The result of our analysis showed that the EMG signal has the greatest and lowest fractal dimension in case of lateral (for holding thin, flat objects) and hook (for supporting a heavy load) hand movements. The capability seen in this research can be applied to the analysis of other types of bio signals in order to investigate the reaction of humans to different types of stimuli.
STRUCTURAL, FERROELECTRIC AND ENERGY-STORAGE PROPERTIES OF LEAD-FREE Zr-DOPED Bi0.5(Na0.80K0.20)0.5TiO3 FILMS
Authors: QUAN NGO DUC , HUONG CHU T. THANH , PHUONG NGUYEN T. HONG , HONG NGUYEN VAN , HUNG VU NGOC , NGUYEN MINH-DUC
Published: January 2019

Perovskite-type lead-free Bi[Formula: see text](Na[Formula: see text]K[Formula: see text](Ti[Formula: see text]Zrx)O3 (BNKT-[Formula: see text]Zr) ferroelectric films (with [Formula: see text] from 0.00 to 0.05) were synthesized on Pt/Ti/SiO2/Si substrates via chemical solution deposition. The influence of Zr[Formula: see text] concentration on the microstructures, ferroelectric and energy-storage properties of the prepared films was investigated in detail. It showed that the BNKT-[Formula: see text]Zr films possessed rhombohedral and tetragonal symmetries in morphotropic phase boundary when a small amount of Zr[Formula: see text] was added. Ferroelectric and energy-storage properties of the films investigated at an applied electric field of 600[Formula: see text]kV/cm were significantly enhanced with appropriate Zr[Formula: see text] concentration. The remnant polarization ([Formula: see text]), maximum polarization ([Formula: see text]) and [Formula: see text]–[Formula: see text] values at [Formula: see text] reached the highest values of 18.1[Formula: see text][Formula: see text]C/cm2, 42.0[Formula: see text][Formula: see text]C/cm2 and 24.0[Formula: see text][Formula: see text]C/cm2, respectively. Thanks to the strong enhancement in [Formula: see text] and the large [Formula: see text]–[Formula: see text] value, the highest recoverable energy-storage density gets the value of 4.6[Formula: see text]J/cm3 for the 2[Formula: see text]mol.% Zr[Formula: see text]-doped BNKT film. These obtained results indicate that the appropriate Zr[Formula: see text]-doped BNKT films have many application potentials in the advanced capacitors.
Application Specific Performance Evaluation of Vertical Handoff in UMTS-WLAN Network
Authors: JAIN AABHA , TOKEKAR SANJIV
Published: January 2019

The next generation of wireless system is expected to provide multimedia, multi class services any time anywhere with seamless mobility and Quality of Service (QoS). In such environment, vertical handoff management plays an important and challenging role. Some of the main functions of vertical handoff management are: to implement appropriate vertical handoff decision to minimize number of unnecessary handoff, to maintain minimum vertical handoff latency for seamless mobility and to provide guaranteed acceptable QoS required for user satisfaction. Thus, in this paper to avoid unnecessary handoff in integrated heterogeneous network we have proposed that the vertical handoff decision depends on coverage area of the network and the speed of the Mobile Node. Application specific cut-off speed for particular coverage range of network during which handoff is beneficial has been determined. Real time applications like HDTV, MPEG-4, and H.261 are considered in integrated heterogeneous network of UMTS (Universal Mobile Telecommunication System) and WLAN. Vertical handoff latency is analyzed for varied network traffic load, types of application and varied speed of Mobile Node. Effect of Mobile Node speed on packet loss is also analyzed. Finally, to satisfy user with acceptable end to end QoS, especially in the presence of heterogeneous integrated networks where every network has individual QoS, an end to end QoS mapping scheme between UMTS and WLAN integrated network has been proposed. The simulation is performed using Network Simulator NS-2 with NIST (National Institute of Standards and Technology) add on module.
Inverse scattering for a random potential
Authors: Caro Pedro , Helin Tapio , Lassas Matti
Published: January 2019

In this paper, we consider an inverse problem for the [Formula: see text]-dimensional random Schrödinger equation [Formula: see text]. We study the scattering of plane waves in the presence of a potential [Formula: see text] which is assumed to be a Gaussian random function such that its covariance is described by a pseudodifferential operator. Our main result is as follows: given the backscattered far field, obtained from a single realization of the random potential [Formula: see text], we uniquely determine the principal symbol of the covariance operator of [Formula: see text]. Especially, for [Formula: see text] this result is obtained for the full nonlinear inverse backscattering problem. Finally, we present a physical scaling regime where the method is of practical importance.
Synthesis, Characterization and Dielectric Properties of BaTiO3 Nanoparticles
Authors: Haroon Azra , Rai Prabhakar , Uddin Imran
Published: January 2019

Barium titanate (BaTiO[Formula: see text] nanoparticles having small tetragonality were prepared via sol–gel technique followed by post-calcinations at 800∘C. The tetragonal phase was confirmed by XRD and TEM measurements. The obtained nanoparticles were quasi-spherical in shape with particle size lying between 30[Formula: see text]nm and 35[Formula: see text]nm, as obtained by TEM. The prepared sample was further characterized by TGA, DSC, FTIR, UV-Vis and PL spectroscopy. The low tetragonality of the obtained nanoparticles accounts for the absence of endothermic–exothermic peak in the DSC curve. The UV-Vis spectrum reveals band gap narrowing and the PL spectrum shows a broad band covering a large part of the visible spectra with the PL intensity maximum at 568[Formula: see text]nm. The dielectric and electrical properties were studied using LCR and Two probe method, and it shows a decrease in the permittivity as well as the tetragonal to cubic phase transition temperature.
Protein tertiary structure prediction using hidden Markov model based on lattice
Authors: Peyravi Farzad , Latif Alimohammad , Moshtaghioun Seyed Mohammad
Published: January 2019

The prediction of protein structure from its amino acid sequence is one of the most prominent problems in computational biology. The biological function of a protein depends on its tertiary structure which is determined by its amino acid sequence via the process of protein folding. We propose a novel fold recognition method for protein tertiary structure prediction based on a hidden Markov model and 3D coordinates of amino acid residues. The method introduces states based on the basis vectors in Bravais cubic lattices to learn the path of amino acids of the proteins of each fold. Three hidden Markov models are considered based on simple cubic, body-centered cubic (BCC) and face-centered cubic (FCC) lattices. A 10-fold cross validation was performed on a set of 42 fold SCOP dataset. The proposed composite methodology is compared to fold recognition methods which have HMM as base of their algorithms having approaches on only amino acid sequence or secondary structure. The accuracy of proposed model based on face-centered cubic lattices is quite better in comparison with SAM, 3-HMM optimized and Markov chain optimized in overall experiment. The huge data of 3D space help the model to have greater performance in comparison to methods which use only primary structures or only secondary structures.
Numerical Model of Time-Dependent Gas Flows Through Bed of Granular Phase Change Material
Authors: Lutsenko Nickolay A. , Fetsov Sergey S.
Published: January 2019

A novel mathematical model and original numerical method for investigating time-dependent gas flows through a bed of granular phase change material (PCM) are proposed and described in detail. Such material is modeled as a porous medium, and continua mechanics method are used for constructing the mathematical model. The numerical method is based on a combination of explicit and implicit finite-difference schemes. Comparison of calculation results with known experimental data demonstrates a very good coincidence. The results of the study can be applied in modeling the thermal energy storage with granular PCM in advanced adiabatic compressed air energy storage and other heat storage devices.
A BIonic model for exchanging waves between water and DNA
Authors: Fioranelli Massimo , Roccia Maria Grazia
Published: January 2019

Recently, the quantum spectrum of black BIons has been considered and their entropies have been calculated. Generalizing this model to a tube of water which interacts with DNA waves, its quantum spectrum and entropy could be obtained. A DNA can emit two types of waves, including electromagnetic waves (EMS) and topoisomerase-like ones. EMS carry messages of a DNA and help it to communicate with other DNAs and also pure water. Topoisomerase-like waves open packings of a DNA and copy its genetic information. Both of these waves could interact with pure water and change its entropy and quantum spectrum.
Critical Resistance Affecting Sub- to Super-Critical Transition Flow by Vegetation
Authors: Pasha Ghufran Ahmed , Tanaka Norio
Published: January 2019

In order to design a vegetation structure to mitigate floods resulting from extreme events like tsunamis, vegetation density and thickness (width) are important parameters. Flow passing through vegetation faces great resistance, which results in a backwater rise on upstream (U/S) vegetation, increases the water slope inside the vegetation, and for some cases, forms a hydraulic jump downstream (D/S) of the vegetation, thus transforming a subcritical flow to supercritical [Pasha, G. A. and Tanaka, N. [2017] “Undular hydraulic jump formation and energy loss in a flow through emergent vegetation of varying thickness and density,” Ocean Eng. 141, 308–325.]. Like the concepts of critical velocity and critical slope, this paper introduces the concept of “critical resistance of vegetation,” which is defined as “resistance offered by vegetation that transforms a subcritical flow to supercritical.” An analytical approach to find the water depths U/S, inside, and D/S of vegetation is introduced and validated well by laboratory experiments. Critical resistance was determined against vegetation of variable densities ([Formula: see text], where [Formula: see text] of each cylinder in the cross-stream direction, [Formula: see text] of the cylinder), thicknesses (dn, where [Formula: see text] of a cylinder and [Formula: see text] of cylinders in a stream-wise direction per unit of cross-stream width), and the initial Froude number (Fro). A subcritical flow ([Formula: see text], without vegetation) was transformed to a supercritical flow (D/S vegetation) with a range of Froude numbers of 1.6–1.9, 1.1–1.2, and 0.85–0.98 against [Formula: see text] ratios of 0.25, 1.09, and 2.13, respectively, thus defining [Formula: see text] as the critical resistance. However, altering vegetation thickness did not change the results.
Some properties of sequences in gradual normed spaces
Authors: Ettefagh Mina , Etemad Sina , Azari Farnaz Y.
Published: January 2019

In this paper, we investigate some properties of sequences in a gradual normed space. We define some new notions such as gradual convergent sequences, gradual Cauchy sequences, etc., and then we state some theorems about these notions. Finally, in the last section, we bring some illustrative examples.
Impact of Blockchain on China’s Cyber Statecraft: Opportunities and Risks
Authors: LIU Bojian
Published: January 2019

Since 2016, China has officially regarded blockchain technology as a subversive innovation that will fundamentally transform major industries. Current blockchain projects in China are dominated by private or consortium blockchains that have their accessibility firmly controlled; for public blockchains such as Bitcoin and Ethereum, access is free for all. Not surprisingly, by weakening state control of digital data, public blockchains may neutralise China’s decades of efforts in building internet filtering systems. The existing development trajectory of private and consortium blockchains is likely to advance steadfastly, and citizens and companies in China may be required to use state-controlled blockchains.
The National Supervisory Commission from Xi Jinping’s Anti-corruption Campaign
Authors: ZHOU Na
Published: January 2019

China’s 13th National People’s Congress revised the state constitution and set up a new national institution, the National Supervisory Commission. This institution aims to prevent corruption and ensure the integrity of public officials. It has institutionalised Xi Jinping’s anti-corruption efforts in his first five-year term. It is also an important and effective instrument for Xi to consolidate his power despite the many challenges.
A Study on Thermal Characteristics Affected by Air Distribution System Installed in Indoor Ice Rink Arena
Authors: Kwon Yong-Il
Published: January 2019

The Republic of Korea held the Winter Olympics in February 2018 and built several indoor ice rinks. Recently, the population of viewing and enjoying winter sports in indoor ice rink arenas is increasing and it is expected that the demand for building new indoor ice rink arenas will increase in the future. These indoor ice rinks generally should have an adequate dehumidification and heating system to provide optimal indoor air condition for users (spectators and athletes) under the required heat and humidity conditions. In addition, HVAC system designers should take steps to prevent fogging from condensation on the ice surface and to prevent condensation on the walls. This study was carried out to evaluate the formation of fog near the ice surface by using two air distribution systems applicable to the indoor ice rink arena. It was confirmed that the mixed ventilation method did not cause fog near ice surface, and that there is a great difference in the composition of the indoor thermal environment of the ice rink arena according to the type of ventilation system.
Multiple Quadrotors Formation Flying Control Design and Experimental Verification
Authors: Wang Jianan , Zhou Zhengyang , Wang Chunyan , Shan Jiayuan
Published: January 2019

The formation control problem in multi-quadrotor systems is studied in this paper. Each quadrotor has limited access to its neighbors’ information due to communication constraint. First, the dynamics model of the quadrotor is linearized using Newton–Euler method. The distributed formation control law is then designed and the stability analysis is provided. An experimental platform is built with three Parrot Bebop drones and an indoor motion capture system. Numerical and experimental results are provided to show the effectiveness of the proposed algorithms.
Recovering the Principle of Relativity from the Cosmic Fabric Model of Space
Authors: Tenev T. G. , Horstemeyer M. F.
Published: January 2019

We extend the descriptive power of the Cosmic Fabric model of space developed by Tenev and Horstemeyer [Int. J. Mod. Phys. D 27 (2018) 1850083] to include moving observers by demonstrating that all reference frames are phenomenologically equivalent with one another and transform between each other via the Lorentz transformations. Our approach is similar to that of Lorentz [Versl. Kon. Akad. Wetensch 1 (1892) 74], which was used to explain the negative outcome of the Michelson–Morley æther detection experiment [A. A. Michelson and E. W. Morley, Am. J. Sci. s3–34 (1887) 333], except that we deduce the notions of length contraction and time dilation from the postulates of the Cosmic Fabric model. Our result is valid for the continuum length scale at which, by definition, the cosmic fabric can be described mathematically as a continuum. Herein, we also discuss the length scale-dependent nature of the Cosmic Fabric model as a possible way to relate gravitational and quantum theories.
Time Varying Loads and White Noise on an SDOF System with Bouc Hysteresis Using Gaussian Closure
Authors: Waubke Holger , Kasess Christian
Published: January 2019

In a recent publication [H. Waubke and C. Kasess, Gaussian closure technique applied to the hysteretic Bouc model with nonzero mean white noise excitation, J. Sound Vibr. 382 (2016) 258–273], the response of a single-degree-of-freedom (SDOF) system under Gaussian white noise and a constant dead load is presented. The system has a hysteresis described by Bouc [R. Bouc, Forced vibration of mechanical systems with hysteresis, in Proc. Fourth Conference on Nonlinear Oscillation (Prague, 1967), p. 315]. New is the usage of a slowly time-varying deterministic load added to the Gaussian white noise process. The transient solution is calculated using the Gaussian closure technique together with an explicit time step procedure. All moments in the Gaussian closure technique are evaluated analytically. The results of the Gaussian closure technique are in good agreement with the results from the Monte-Carlo method.
An assessment of KIR channel function in human cerebral arteries
Authors: Sancho Maria , Gao Yuan , Hald Bjorn O. , Yin Hao , Boulton Melfort , Steven David A. , MacDougall Keith W. , Parrent Andrew G. , Pickering J. Geoffrey , Welsh Donald G.
Published: January 2019

In the rodent cerebral circulation, inward rectifying K+ (KIR) channels set resting tone and the distance over which electrical phenomena spread along the arterial wall. The present study sought to translate these observations into human cerebral arteries obtained from resected brain tissue. Computational modeling and a conduction assay first defined the impact of KIR channels on electrical communication; patch-clamp electrophysiology, quantitative PCR, and immunohistochemistry then characterized KIR2.x channel expression/activity. In keeping with rodent observations, computer modeling highlighted that KIR blockade should constrict cerebral arteries and attenuate electrical communication if functionally expressed. Surprisingly, Ba2+ (a KIR channel inhibitor) had no effect on human cerebral arterial tone or intercellular conduction. In alignment with these observations, immunohistochemistry and patch-clamp electrophysiology revealed minimal KIR channel expression/activity in both smooth muscle and endothelial cells. This absence may be reflective of chronic stress as dysphormic neurons, leukocyte infiltrate, and glial fibrillary acidic protein expression was notable in the epileptic cortex. In closing, KIR2.x channel expression is limited in human cerebral arteries from patients with epilepsy and thus has little impact on resting tone or the spread of vasomotor responses.

NEW & NOTEWORTHY KIR2.x channels are expressed in rodent cerebral arterial smooth muscle and endothelial cells. As they are critical to setting membrane potential and the distance signals conduct, we sought to translate this work into humans. Surprisingly, KIR2.x channel activity/expression was limited in human cerebral arteries, a paucity tied to chronic brain stress in the epileptic cortex. Without substantive expression, KIR2.x channels were unable to govern arterial tone or conduction.
Host Immunity Following Near-Infrared Photoimmunotherapy Is Enhanced with PD-1 Checkpoint Blockade to Eradicate Established Antigenic Tumors
Authors: Nagaya Tadanobu , Friedman Jay , Maruoka Yasuhiro , Ogata Fusa , Okuyama Shuhei , Clavijo Paul E. , Choyke Peter L. , Allen Clint , Kobayashi Hisataka
Published: January 2019

Near-infrared photoimmunotherapy (NIR-PIT) induces immunogenic cell death but has mostly failed to induce durable antitumor responses in syngenic tumor mouse models. We hypothesized that adaptive immune resistance could be limiting durable responses after treatmemt with NIR-PIT. We investigated the effects of combining NIR-PIT targeting cell-surface CD44 and PD-1 blockade in multiple syngeneic tumor models. In two of three models, NIR-PIT monotherapy halted tumor growth, enhanced dendritic cell tumor infiltration, and induced de novo tumor antigen–specific T-cell responses absent at baseline. The addition of PD-1 blockade reversed adaptive immune resistance, resulting in both enhanced preexisting tumor antigen–specific T-cell responses and enhanced de novo T-cell responses induced by NIR-PIT. Enhanced immune responses correlated with shared tumor antigen expression, suggesting that antigenicity is a major determinant of response to combination NIR-PIT and PD-1 blockade. Combination treatment induced complete rejection of MC38 tumors treated with NIR-PIT, as well as untreated, distant tumors. Accordingly, tumor antigen–specific T-cell responses were measured in both treated and untreated tumors, validating the development of systemic antitumor immunity. Mice that cleared tumors resisted subsequent tumor challenge, indicating the presence of systemic immune memory. Cumulatively, these results demonstrate reversal of adaptive immune resistance following induction of innate and adaptive immunity by NIR-PIT, resulting in high rates of tumor rejection and/or significant tumor growth control in antigenic syngeneic models of cancer.
GENCO Optimal Bidding Strategy and Profit based Unit Commitment using Evolutionary Particle Swarm Optimization Illustrating the Effect of GENCO Market Power
Authors: Bikeri Adline , Muriithi Christopher , Kihato Peter
Published: January 2019

In deregulated electricity markets, generation companies (GENCOs) make unit commitment (UC) decisions based on a profit maximization objective in what is termed profit based unit commitment (PBUC). PBUC is done for the GENCOs demand which is a summation of its bilateral demand and allocations from the spot energy market. While the bilateral demand is known, allocations from the spot energy market depend on the GENCOs bidding strategy. A GENCO thus requires an optimal bidding strategy (OBS) which when combined with a PBUC approach would maximize operating profits. In this paper, a solution of the combined OBS-PBUC problem is presented. An evolutionary particle swarm optimization (EPSO) algorithm is implemented for solving the optimization problem. Simulation results carried out for a test power system with GENCOs of differing market strengths show that the optimal bidding strategy depends on the GENCOs market power. Larger GENCOs with significant market power would typically bid higher to raise market clearing prices while smaller GENCOs would typically bid lower to capture a larger portion of the spot market demand. It is also illustrated that the proposed EPSO algorithm has a better performance in terms of solution quality than the classical PSO algorithm.
Conceptual Sentiment Analysis Model
Authors: Ghag Kranti Vithal , Shah Ketan
Published: January 2019

Bag-of-words approach is popularly used for Sentiment analysis. It maps the terms in the reviews to term-document vectors and thus disrupts the syntactic structure of sentences in the reviews. Association among the terms or the semantic structure of sentences is also not preserved. This research work focuses on classifying the sentiments by considering the syntactic and semantic structure of the sentences in the review. To improve accuracy, sentiment classifiers based on relative frequency, average frequency and term frequency inverse document frequency were proposed. To handle terms with apostrophe, preprocessing techniques were extended. To focus on opinionated contents, subjectivity extraction was performed at phrase level. Experiments were performed on Pang & Lees, Kaggle’s and UCI’s dataset. Classifiers were also evaluated on the UCI’s Product and Restaurant dataset. Sentiment Classification accuracy improved from 67.9% for a comparable term weighing technique, DeltaTFIDF, up to 77.2% for proposed classifiers. Inception of the proposed concept based approach, subjectivity extraction and extensions to preprocessing techniques, improved the accuracy to 93.9%.
Real-Time Video Processing using Contour Numbers and Angles for Non-urban Road Marker Classification
Authors: Sani Zamani Md , Ghani Hadhrami Abd , Besar Rosli , Azizan Azizul , Abas Hafiza
Published: January 2019

Road users make vital decisions to safely maneuver their vehicles based on the road markers, which need to be correctly classified. The road markers classification is significantly important especially for the autonomous car technology. The current problems of extensive processing time and relatively lower average accuracy when classifying up to five types of road markers are addressed in this paper. Two novel real time video processing methods are proposed by extracting two formulated features namely the contour number, , and angle, 𝜃 to classify the road markers. Initially, the camera position is calibrated to obtain the best Field of View (FOV) for identifying a customized Region of Interest (ROI). An adaptive smoothing algorithm is performed on the ROI before the contours of the road markers and the corresponding two features are determined. It is observed that the achievable accuracy of the proposed methods at several non-urban road scenarios is approximately 96% and the processing time per frame is significantly reduced when the video resolution increases as compared to that of the existing approach.
OFCS: Optimized Framework of Compressive Sensing for Medical Images in Bottleneck Network Condition
Authors: M Lakshminarayana , Sarvagya Mrinal
Published: January 2019

Compressive sensing is one of teh cost effective solution towards performing compression of heavier form of signals. We reviewed the existing research contribution towards compressive sensing to find that existing system doesnt offer any form of optimization for which reason the signal are superiorly compressed but at the cost of enough resources. Therefore, we introduce a framework that optimizes the performance of the compressive sensing by introducing 4 sequential algorithms for performing Random Sampling, Lossless Compression for region-of-interest, Compressive Sensing using transform-based scheme, and optimization. The contribution of proposed paper is a good balance between computational efficiency and quality of reconstructed medical image when transmitted over network with low channel capacity. The study outcome shows that proposed system offers maximum signal quality and lower algorithm processing time in contrast to existing compression techniuqes on medical images.
Initial Optimal Parameters of Artificial Neural Network and Support Vector Regression
Authors: Fradinata Edy , Suthummanon Sakesun , Suntiamorntut Wannarat
Published: January 2019

This paper presents architecture of backpropagation Artificial Neural Network (ANN) and Support Vector Regression (SVR) models in supervised learning process for cement demand dataset. This study aims to identify the effectiveness of each parameter of mean square error (MSE) indicators for time series dataset. The study varies different random sample in each demand parameter in the network of ANN and support vector function as well. The variations of percent datasets from activation function, learning rate of sigmoid and purelin, hidden layer, neurons, and training function should be applied for ANN. Furthermore, SVR is varied in kernel function, lost function and insensitivity to obtain the best result from its simulation. The best results of this study for ANN activation function is Sigmoid. The amount of data input is 100% or 96 of data, 150 learning rates, one hidden layer, trinlm training function, 15 neurons and 3 total layers. The best results for SVR are six variables that run in optimal condition, kernel function is linear, loss function is ౬-insensitive, and insensitivity was 1. The better results for both methods are six variables. The contribution of this study is to obtain the optimal parameters for specific variables of ANN and SVR.
Novel Approach for Evaluating Video Transmission using Combined Scalable Video Coding over Wireless Broadband Network
Authors: Rantelobo Kalvein , Ramli Kalamullah , Wirawan Wirawan
Published: January 2019

One of the main problems in video transmission is the bandwidth fluctuation in wireless channel. Therefore, there is an urgent need to find an efficient bandwidth utilization and method. This research utilizes the Combined Scalable Video Coding (CSVC) which comes from Joint Scalable Video Model (JSVM). In the combined scalable video coding, we implement Coarse Grain Scalability (CGS) and Medium Grain Scalability (MGS). We propose a new scheme in which it can be implemented on Network Simulator II (NS-2) over wireless broadband network. The advantages of this new scheme over the other schemes are more realistic and based on open source program. The result shows that CSVC implementation on MGS mode outperforms CGS mode.
Design Study of a Miniaturized Multi-layered Antenna-in-package for 2.4 GHZ Wireless Communication
Authors: Naghar Jalal , Aghzout Otman , Naghar Azzeddin
Published: January 2019

This paper proposes a novel miniaturization technique to enhance the radiation properties of small multi-layer patch antenna used in packaged circuits. The multilayered antenna design is composed of three layers with different shapes. An enhancement on the radiation properties has been obtained by optimizing the geometry of the radiated element and the parasitic conductor of the middle layer. The whole design has been implemented on the FR4 substrate with dielectric constant of 4.4, thickness of 1.6 mm and Copper thickness of 5 μm. The first layer is a driven element while second and the third layer are parasitic patch elements. The optimized multilayer antenna has a very small size of 12×6×5 mm^3. Considering the small size of the antenna, a detailed study of the parameter affecting the radiation has been considered to force the antenna to operate at 2.4 GHz band. Miniaturization techniques based on the current distribution have been also taken into account to shift down the resonant frequency and reduces more and more the antenna size at the designed operating frequency. The miniaturized antenna maintains performant radiation characteristics in terms of reflexion coefficient, bandwidth and directivity. All developed antennas are simulated using the commercial Electromagnetic CST Microwave Studio software. Achieved results demonstrate a good performance with low cost and compact size.
Markovian Queueing Model for Throughput Maximization in D2D-Enabled Cellular Networks
Authors: Gbenga-ilori Abiodun , Sanusi Olufunmilayo
Published: January 2019

Device-to-Device (D2D) communication has been considered a key enabling technology that can facilitate spectrum sharing in 4G and 5G cellular networks. In order to meet the high data rate demands of these new generation cellular networks, this paper considers the optimization of available spectrum resource through dynamic spectrum access. The utilization of continuous-time Markov chain (CTMC) model for efficient spectrum access in D2D-enabled cellular networks is investigated for the purpose of determining the impact of this model on the capacity improvement of cellular networks. The paper considers the use of CTMC model with both queueing and non-queueing cases called 13-Q CTMC and 6-NQ CTMC respectively with the aim of improving the overall capacity of the cellular network under a fairness constraint among all users. The proposed strategy consequently ensures that spectrum access for cellular and D2D users is optimally coordinated by designing optimal spectrum access probabilities. Numerical simulations are performed to observe the impact of the proposed Markovian queueing model on spectrum access and consequently on the capacity of D2D-enabled cellular networks. Results showed that the proposed 13-Q CTMC provide a more spectrum-efficient sharing scheme, thereby enabling better network performances and larger capabilities to accommodate more users.
Performance Analysis of Data Mining Methods for Sexually Transmitted Disease Classification
Authors: Yuliastuti Gusti E. , Alfiyatin Adyan N. , Rizki Agung M. , Hamdianah A. , Taufiq H. , Mahmudy W. F.
Published: January 2019

According to health reports of Malang city, many people are exposed to sexually transmitted diseases and most sufferers are not aware of the symptoms. Malang city being known as a city of education so that every year the population number increases, it is at risk of increasing the spread of sexually transmitted diseases virus. This problem is important to be solved to treat earlier sufferers sexually transmitted diseases virus in order to reduce the burden of patient spending. In this research, authors conduct data mining methods to classifying sexually transmitted diseases. From the experiment result shows that K-NN is the best method for solve this problem with 90% accuracy.
Strategy for Foreground Movement Identification Adaptive to Background Variations
Authors: Anuradha K. , Raajan N.R.
Published: January 2019

Video processing has gained a lot of significance because of its applications in various areas of research. This includes monitoring movements in public places for surveillance. Video sequences from various standard datasets such as I2R, CAVIAR and UCSD are often referred for video processing applications and research. Identification of actors as well as the movements in video sequences should be accomplished with the static and dynamic background. The significance of research in video processing lies in identifying the foreground movement of actors and objects in video sequences. Foreground identification can be done with a static or dynamic background. This type of identification becomes complex while detecting the movements in video sequences with a dynamic background. For identification of foreground movement in video sequences with dynamic background, two algorithms are proposed in this article. The algorithms are termed as Frame Difference between Neighboring Frames using Hue, Saturation and Value (FDNF-HSV) and Frame Difference between Neighboring Frames using Greyscale (FDNF-G). With regard to F-measure, recall and precision, the proposed algorithms are evaluated with state-of-art techniques. Results of evaluation show that, the proposed algorithms have shown enhanced performance.
Caching on Named Data Network: a Survey and Future Research
Authors: Yovita Leanna Vidya , Syambas Nana Rachmana
Published: January 2019

The IP-based system cause inefficient content delivery process. This inefficiency was attempted to be solved with the Content Distribution Network. A replica server is located in a particular location, usually on the edge router that is closest to the user. The user’s request will be served from that replica server. However, caching on Content Distribution Network is inflexible. This system is difficult to support mobility and conditions of dynamic content demand from consumers. We need to shift the paradigm to content-centric. In Named Data Network, data can be placed on the content store on routersthat are closest to the consumer. Caching on Named Data Network must be able to store content dynamically. It should be selectively select content that is eligible to be stored or deleted from the content storage based on certain considerations, e.g. the popularity of content in the local area. This survey paper explains the development of caching techniques on Named Data Network that are classified into main points. The brief explanation of advantages and disadvantages are presented to make it easy to understand. Finally, proposed the open challenge related to the caching mechanism to improve NDN performance.
PORM: Predictive Optimization of Risk Management to control Uncertainty Problems in Software Engineering
Authors: Firdose Salma , Rao L. Manjunath
Published: January 2019

Irrespective of different research-based approaches toward risk management, developing a precise model towards risk management is found to be a computationally challenging task owing to critical and vague definition of the origination of the problems. This research work introduces a model called as PROM i.e. Predictive Optimization of Risk Management with the perspective of software engineering. The significant contribution of PORM is to offer a reliable computation of risk analysis by considering generalized practical scenario of software development practices in Information Technology (IT) industry. The proposed PORM system is also designed and equipped with better risk factor assessment with an aid of machine learning approach without having more involvement of iteration. The study outcome shows that PORM system offers computationally cost effective analysis of risk factor as assessed with respect to different quality standards of object oriented system involved in every software projects.
Comparison Analysis of Gait Classification For Human Motion Identification Using Embedded Computer
Authors: Jati Agung Nugroho , Novianty Astri , Septiana Nanda , Nasution Leni Widia
Published: January 2019

In this paper, it will be discussed about comparison between two kinds of classification methods in order to improve security system based of human gait. Gait is one of biometric methods which can be used to identify person. K-Nearest Neighbour has parallelly implemented with Support Vector Machine for classifying human gait in same basic system. Generally, system has been built using Histogram and Principal Component Analysis for gait detection and its feature extraction. Then, the result of the simulation showed that K-Nearest Neighbour is slower in processing and less accurate than Support Vector Machine in gait classification.
Bidirectional Underwater Visible Light Communication
Authors: Darlis Arsyad Ramadhan , Widura Andre , Andrian Muhamad Rifan
Published: January 2019

In this paper, a novel bidirectional underwater visible light communication (BiUVLC) is proposed. The VLC transmitter transmits an information signal using the one of RGB LED through the water tank that represents an underwater environment and then is received by VLC receiver via a color filter. The color LEDs and color filters are utilized in bidirectional systems. The single link is created by a LED on the transmitter and the color filter on the receiver with the same color which represents a single wavelength. The performance of the proposed BiUVLC system was evaluated via implementations. The experimental result shows that the transmitted signal undergoes attenuation over the underwater optical channel and the pair of the blue wavelength in link 1 and the green wavelength in link 2 have the best performance than the other wavelength pair. In the crosstalk measurement, the red wavelength color is the worst in the underwater environment.
Smart database concept for Power Management in an electrical vehicle
Authors: Mahmoudi Chokri , Aymen Flah , Lassaad Sbita
Published: January 2019

As world population continues to grow and the limited amount of fossil fuels begin to diminish, it may not be possible to afford the needed amount of energy demanded by the world by only using fossil fuels. Meanwhile, the abundant nature of renewable energy sources brings new beginning for next generations. Greater penetration of electric vehicles will play an important role in building green and healthy world. The main remaining issue to make the switch from conventional to electric vehicle is performance cost; Efficient EVs that can drive for long distances, on single charge, are still expensive for ordinary consumer. To address this range problem, many attempts have been made during last decade. The goal was to conceive a power efficient electric vehicle, capable of managing its energy and reach longer distances. It depends on the electrical architectures and used algorithms.

This paper adds new perspective for power Management in EVs; The proposed methodology introduces a new power management architecture based on communication and car learning. The conventional software level in EV has been replaced with self readjustable software. EVs are connected through a database, and can upload or download adjustment parameters while software is running.

To take advantage of the new architecture, a new learning technique concept is introduced too, based on Cloud experience exchange between Electric Vehicles. This enhancement aims to build a better EV experience in power management through Cloud sharing and definitely cut with conventional architecture that may have reached its boundaries.
Performance identification of the asynchronous electric drives by the spectrum of rotor currents
Authors: Kodkin Vladimir L. , Anikin Aleksandr Sergeevich , Baldenkov Aleksandr A.
Published: January 2019

The efficiency of analyzing the rotor currents of asynchronous electric drives with frequency control is substantiated in the article. To assess the quality of torque generation in the engine it is suggested to use the spectral analysis of these currents and the fundamental harmonic, as the most accurate "conformity" of slip in an asynchronous motor. The proposed method showed that "sensorless vector" control leads to the appearance of high-frequency harmonics with significant amplitude. Because of these harmonics, a non-sinusoidal electromagnetic moment is created and the performance of the drive is decreased. The most effective method of torque generation is the frequency control with positive stator current feedback. This control is dominated by pronounced harmonic components, which indicates the proximity of this structure to linear and significantly better controllability of the drives, which makes promising their use in high-tech mechanisms, in particular, in industrial robots. Simulation and experiments confirm the proposed theoretical propositions.
Design and development of SEPIC DC-DC boost converter for photovoltaic application
Authors: Alhamrouni Ibrahim , K. Rahmat M. , A. Ismail F. , Salem Mohamed , Jusoh Awang , Sutikno T.
Published: January 2019

This study highlights a new construction of SEPIC DC-DC converter. The proposed converter aims for some features such as high voltage gain, continuous input current and reduce stress on the power switch. In addition, the circuit construction ensurs the simplicity in design along with signicant cost saving, since its components are readily available and smaller in size compared to the off-shelf components. This type of converter can adjust the DC voltage to maintain its output voltage to be constant. Typically, SEPIC operated in equipment that uses battery and also in wide range input voltage DC power supply. The converter is designed for renewable energy application where it is able to regulate the output voltage of the Photovoltaic (PV). The converter has been analysed based on different switching frequencies and duty cycle. Thus the outcome of the proposed converter can be achieved by using D=0.45 and fs=30 kHz. The proposed converter is supplied by 26V as an input voltage and produces 300V output and gives 94% of efficiency.
Eccentric operation of STATCOM using Predictive Controller
Authors: Varalakshmi K. , R.L. Narasimham , Ramdas G. Tulasi
Published: January 2019

The impact of multilevel converter STATCOM in transmission and distribution system is given high importance. Increment of number of switches in multi-level cascaded H-bridge converter, made it more vulnerable to open circuit and short circuit faults. To reduce the effect of faults on line voltage magnitude, in this paper an advanced improved predictive controller is used to generate PWM pulses for the power electronic devices. A Cascaded H-bridge STATCOM, interconnected to a distribution system with linear and non-linear loads. The feedback control structure of STATCOM has an advantage of reducing THD and controllable reactive power. A switch fault detection and elimination method is proposed with a bypass switch connected to each H-bridge to surpass the faulty  H-bridge. The complete analysis with all control structures is designed in MATLAB/Simulink representing dynamic graphs and feasibility of proposed method is verified.