bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ranking of Sensitive Positions using Statistical and Correlational Analysis
Authors: Verma Nishchal K. , Sevakula Rahul K. , Dixit Sonal , Salour Al 
Published: November 2017

Abstract
Condition Based Monitoring of a machine refers to the checking of various parameters and signatures of the machine and then predicting the machine’s current health status. The slight changes in the machine operating condition are carefully analyzed to know if the machine is having any fault. For monitoring the changes, we acquire acoustic data i.e. generated while machine is running. In order to collect acoustic data, a number of sensors are placed near various positions of the machine surface. Acquiring data from large number of sensor positions is not economically viable. It would always be preferable to have a monitoring system that acquires data quickly and efficiently, without compromising on the robustness of the system. Therefore there is a need to locate some special positions on the machine, termed as “sensitive positions”, which are expected to exhibit the fault characteristics in a much better way than others. This paper presents a novel method for ranking sensitive positions for a machine based on statistical parameters analysis. While the final list of required number of sensitive positions is generated, the cross-correlation amongst the positions is also taken into consideration to avoid redundancy. Furthermore, a standalone application for implementing the same has been developed on Android platform. The proposed scheme and application can be used for variety of other applications that work on similar principle of acquiring data from multiple sensors.
Smartphone Application for Fault Recognition
Authors: Verma Nishchal K. , Sevakula Rahul K. , Gupta Jayesh K. , Singh Sumanik , Dixit Sonal , Salour Al 
Published: November 2017

Abstract
Smart-phones have become an essential tool for many in daily life. Smart-phone Application development has grown rapidly to fulfill the demands of increasingly diverse usage. This paper presents an application based on a fault recognition model that can be used for recognizing different acoustic patterns. The application is made to detect various faulty conditions of an industrial air compressor based on the sound generated by the machine. The application has been tested in real time and is found to perform very well with classification accuracies above 94.75%. We propose that similar applications and recognition models with some modified specifications could be used for acoustic pattern recognition in a wide range of areas.
Electrocardiogram for Biometrics by using Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ): Integrating Feature Extraction and Classification
Authors: Imah Elly Matul , Jatmiko Wisnu , Basaruddin T. 
Published: November 2017

Abstract
Electrocardiogram (ECG) signal for human identity recognition is a new area on biometrics research. The ECG is a vital signal of human body, unique, robustness to attack, universality and permanence, difference to others traditional biometrics technic. This study also proposes Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ), that integrating feature extraction and classification method. The experiments shown that AMGLVQ can improve the accuracy of classification better than SVM or back-propagation NN and also able to handle some problems of heartbeat classification: imbalanced data set, inconsistency between feature extraction and classification and detecting unknown data on testing phase.
Applying Merging Convetional Marker and Backpropagation Neural Network in QR Code Augmented Reality Tracking
Authors: Agusta Gia M. , Hulliyah Khodijah , Arini  , Bahaweres Rizal Broer 
Published: November 2017

Abstract
Usability of QR Code in Augmented Reality system has been used for digital content accessible publicly. However, QR Code in AR system still has imprecision tracking. In this article we propose merging QR Code within conventional marker and backpropagation neural network (BPNN) algorithm to recognizing QR Code Finder Pattern. The method which our chosen to approaching conventional marker. The result of BPNN testing, QRFP detected in perspective distortion with ID-encoded character length 78, 53 and 32. The result has accuracy of 6DOF ±10.65° pitching, ±15.03° yawing and ±408.07 surging, marker stability has 97.625% and computation time runs at 35.41 fps.
Capacity Enhancement of Messages Concealment in Image and Audio Steganography
Authors: Jasril  , Marzuki Ismail , Rahmat Faisal 
Published: November 2017

Abstract
Basically, a steganography indicates two of the principal requirements such the messages and the carrier file. Besides, it should have three aspects: capacity, imperceptibility, and robustness. This paper will show how to enhance the capacity of two types of carrier files for embedding message. By using Least Significant Bit method and modifying the four last bits of carrier files, bitmap and wav files could show the increasing of message size to be inserted to the carrier than only modifying the last 1 bit of carrier files. Particularly bitmap file which still had good quality visual showed PSNR value in 31.5460 dB, but wav file was only 3.8929 dB.
Real Time Steam Temperature Regulation using Self-Tuning Fuzzy PID Controller on Hydrodiffusion Essential Oil Extraction System
Authors: Yusoff Zakiah Mohd , Muhammad Zuraida , Hezri Mohd , Rahiman Fazalul , Taib Mohd Nasir 
Published: November 2017

Abstract
The essential oil is mostly depends on the temperature. The temperature will influence the final product of the extraction process. The existing steam distillation processes are giving less intention on this issue. This work implemented the robust self-tuning fuzzy PID (STFPID) controller to monitor the steam temperature in the hydro-diffusion essential oil extraction system. The hydrodiffusion system is built to overcome some weakness of existing systems. The effectiveness of the STFPID using 25 rules and PID controller is measured by using performance indices of settling time, rise time, percentage overshoot (%OS) and root mean square error. The step responses analysis and robustness test show that STFPID and PID controller are able to drive the steam temperature to the desired set point However, the analysis shows that STFPID produces better performances based on set point tracking and adoption of load disturbance.
Mobility of IP based Wireless Sensor Nodes in Sensor-Grid infrastructure
Authors: Bhunia Suman Sankar , Roy Sarbani , Mukherjee Nandini 
Published: November 2017

Abstract
As the world is moving towards the “Internet of Things” [1], Internet Protocol enabled wireless sensor network is becoming an important research area. In order to make it possible and to facilitate transmission of IPv6 packets over low powered networks, 6Lowpan [2,3] has been introduced. Since the IP- WSN application domain is expanded to real-time applications such as health-care [17] and surveillance systems, a fast and seamless handover becomes an important criterion for supporting mobility in 6LoWPAN [21]. In this paper, we have studied mobility characteristics along with design issues under different mobility scenarios. We propose a scheme to manage the mobility of nodes. The 6LoWPAN based wireless sensor network will be integrated with grid computing establishing a Sensor-grid which may also be used widely in various applications.
Cluster-based Routing Performance Optimization Constraint of Energy, Delay and Connectivity Metrics in Wireless Sensor Network
Authors: Cao Ting , Wang Yuhao , Xiong Xinmin , Hao Yan 
Published: November 2017

Abstract
This paper aims to propose a framework for optimizing performance in cluster-based wireless sensor networks (WSNs) with constrains of energy consumption, delay and connectivity. For the limitation of energy storage being discussed a lot, many researches try to find more solutions to improve it. But, the other index of wireless sensor networks may be deteriorated by many routings which are dedicated to optimizing energy consumption. Thereby, multi-objectives optimization is one of significant issues in WSNs. The model of isolation nodes probability for connectivity in the clusterbased networks is adopted for the issue. Not only will the performance of Leach and existing multiobjectives optimization methods be compared under the proposed framework, but also will the performance of networks in different size of scenarios be analyzed. Simulation results show that the proposed framework combining NSGA can provide an effective sensing in terms of energy consumption, delay and connectivity in the cluster-based networks.
Spectrum Sensing Algorithm Based on ATSC DTV Signal Structure
Authors: Cong Yuliang , Xing Lijuan , Bi Jiaxing 
Published: November 2017

Abstract
In order to improve spectrum utilization rate, people need a method to sense the spectrum hole. This article puts forward a spectrum sensing algorithm, which uses ATSC DTV signal structural characteristics. First, we should sample the input signal based on structural characteristics. Second, these signal samples should be separated into different sets and accumulate these samples. Third, we execute the correlation operation to accumulation result and synchronization. Finally, decision can be got by comparing the test statistics with threshold. According to the simulation result, we can get the conclusion that signal structural characteristics based on spectrum sensing method can realize spectrum sensing well enough.
Research on Longitudinal Control Algorithm for Flying Wing UAV Based on LQR Technology
Authors: Li Yibo , Chen Chao , Chen Wei 
Published: November 2017

Abstract
Linear Quadratic Regulator (LQR) is widely used in many practical engineering fields due to good stability margin and strong robustness. But there is little literature reports the technology that has been used to control the flying wing unmanned aerial vehicles (UAV). In this paper, aiming at the longitudinal static and dynamic characteristics of the flying wing UAV, LQR technology will be introduced to the flying wing UAV flight control. The longitudinal stability augmentation control law and longitudinal attitude control law are designed. The stability augmentation control law is designed by using output feedback linear quadratic method. It can not only increase the longitudinal static stability, but also improve the dynamic characteristics. The longitudinal attitude control law of the flying wing UAV is designed by using command tracking augmented LQR method. The controller can realize the control and maintain the flight attitude and velocity under the condition without breaking robustness of LQR. It solves the command tracking problems that conventional LQR beyond reach. Considering that some state variables of the system are difficult to obtain directly, a control method that called quasi-command tracking augmented LQR is designed by combing with the reduced order observer, it retains all the features of command tracking augmented LQR and more suitable for the application of practice engineering. Finally, the control laws are simulated under the environment of Matlab/Simulink. The results show that the longitudinal control laws of the flying wing UAV which are designed based on LQR can make the flying wing UAV achieve satisfactory longitudinal flying quality.
Design of Linear-Phase Filter Banks with Multiplier-Less Lattice Structures
Authors: Chen Li , Wang Xiyan , Peng Ronghua , Yang Fu 
Published: November 2017

Abstract
In this paper, a new multiplier-less algorithm is proposed for the design of perfectreconstruction linear-phase (PR LP) filter banks by using multiplier-less lattice structures. The coefficients in the multiplication operations have been replaced with limited number of additions and the computational complexity is reduced significantly. The property of perfection reconstruction, however, is preserved regardless the multiplier-less approximation of lattice structures in the factorization of polyphase matrix. The coefficients in the 2x2 rotation matrices of the lattice structures are expressed as sum-of-powers-of-two (SOPOT) coefficients in the parameterization processes. By using the multiplier-less rotation matrices, the unitary matrices are constructed for the lattice factorization of perfect-reconstruction linear-phase filter banks. Design examples of 5-channel and 8-channel multiplier-less linear-phase filter banks are included to validate the algorithm and implementation.
Analysis of Key Fuel Properties Inside Combination Electronic unit Pump Fuel Pipeline
Authors: Hayat Qaisar , Liyun Fan , Ma Xiuzhen , Bingqi Tian , Farouk Naeim 
Published: November 2017

Abstract
Because of high pressure fluctuations in Combination Electronic Unit Pump (CEUP) system during fuel injection cycles, physical properties of diesel fuel including density, acoustic wave speed and bulk modulus also vary. These physical properties of fuel have significant importance in predicting the fuel injection behavior and its optimization. A 1D viscous damped mathematical model of wave equation has been developed in MATLAB not only to simulate the pressure fluctuations in fuel pipeline at various operating conditions of diesel engine but also to determine and analyze the variations in these physical properties of diesel fuel.
A Climbing Hold With an Integrated Three Dimensional Force Measurement and Wireless Data Acquisition
Authors: Lechner B. , Filzwieser I. , Lieschnegg M. , Sammer P. 
Published: November 2017

Abstract
A three dimensional force measurement system was integrated in a climbing hold. The force measurement system consisted of three orthogonally mounted platform load cells. Data acquisition and power supply of the load cells was performed by a wireless data acquisition system ViFDAQ. Data was transferred by ViFDAQ to a nearby laptop by a wireless Bluetooth connection. Measurements were done during a regional climbing competition. The instrumented climbing hold was mounted in one of the climbing routes. The forces the athletes exerted on the climbing hold to reach the top were measured. Force data was analyzed and compared to the actual ranking of the athlete in this competition.
A Study of X-Ray Machine Image Local Semantic Features Extraction Model based on bag-of-words for Airport Security
Authors: Zhang Ning , Zhu Jinfu 
Published: November 2017

Abstract
The aviation security at the airport has been faced with increasingly severe situations since the 9-11 event. It’s of utmost importance to train airport X-ray machine screener’s image recognition competency. So they can prevent terrorists from bringing dangerous articles in their carry-on or checked bags. However, usually the luggages are placed in different positions and the density & volume of articles differ greatly. As a result, dangerous articles show a variety of X-ray image features. It’s easy for the confused screeners to miss or incorrectly detect dangerous articles. This has been a hidden danger for civil aviation safety. For image recognition improvement, the researcher analyzed the visual semantics of dangerous goods images and applied a local semantic features extraction method. After classification and summarization, the method was used to train the screeners for particular image recognition. The comparison showed the improved accuracy and efficiency of image recognition for the screeners and demonstrated a satisfactory effect.
Survey of Semantic Similarity Measures in Pervasive Computing
Authors: Guessoum Djamel , Miraoui Moeiz , Tadj Chakib 
Published: November 2017

Abstract
Semantic similarity measures usage is prevalent in pervasive computing with the following aims: 1) to compare the components of an application; 2) to recommend and rank services by degree of relevance; 3) to identify services by matching the description of a query with the available services; 5) to compare the current context with already known contexts. The existing works that apply semantic similarity measures to pervasive computing focus on one particular issue. Furthermore, surveys in this domain are limited to the recommendation or discovery of context-aware services. In this article, we therefore present a survey of context-aware semantic similarity measures used in various areas of pervasive computing.
Tracking of Moving Target Based on Video Motion Nuclear Algorithm
Authors: Xiaojun Wang , Feng Pan , Weihong Wang 
Published: November 2017

Abstract
Moving target detection and tracking algorithm research content is very broad and complex applications, without and different target features directly affects the detection of selected tracking algorithm. So far still does not exist a universal algorithm for perfect can be suitable for various applications, so the detection and tracking of moving targets is still a valuable research subject of. The research work in this paper is in the field, the moving target detection spatiotemporal correlation and difference contour tracking algorithm based on a fixed background. The algorithm in the background under the condition of fixed to pay a smaller time complexity, the target detection and tracking has a good effect, so it has higher application value. Based on solving the detection and location of moving target tracking in real-time and accuracy requirements, a new moving target detection spatiotemporal correlation and difference contour tracking scheme based on the practical implementation, at the same time analysis and the experimental results are given. In the moving target tracking, tracking method is mainly traditional correlation method target based on template matching. The matching process is time consuming, so the actual use of more of the improved algorithm of correlation method, the improved algorithm attempts to improve the efficiency of feature matching and search range, and also achieved a certain effect, the some excellent tracking algorithm. This paper presents an improved active contour model tracking algorithm, improve the tracking efficiency and quality, the algorithm first from the frame difference detection results to find the moving target coarse contour, and then the convergence of coarse contour by using improved Snake algorithm, the right edge to get the target in the course of the campaign, in order to achieve the tracking of moving objects.
Characterization of a Needle-Type Giant Magnetoresistance Sensor for Detection of Escherichia Coli’S Magnetic Marker
Authors: Shirzadfar Hamidreza , Nadi Mustapha , Kourtiche Djilali , Yamada Sotoshi , Shahabi Payman 
Published: November 2017

Abstract
In the recent years, the introduction and development of simple and portable sensors has been the focus of researchers in nearly all scientific domains, particularly in the biomedical settings. Giant magnetoresistance (GMR) provides a cutting-edge sensor technology. The GMR-based sensors are capable to affordably and sensitively detect and quantify micro- and nano-magnetic particles, even in very weak magnetic fields.
In this paper, we introduce a highly sensitive needle-type GMR-based sensor, designed for the identification and quantification of Escherichia coli O157:H7 bacteria covered by superparamagnetic beads, Dynabeads® MAX E.coli O157. The sensor characteristics, measurement system setup and the properties of the magnetic marker solution are discussed in detail.
Robust Visual Tracking Based on Support Vector Machine and Weighted Sampling Method
Authors: Xiaoxing Gao , Feng Liu 
Published: November 2017

Abstract
Visual tracking algorithm based on binary classification has become the research hot issue. The tracking algorithm firstly constructs a binary classifier between object and background, then to determine the object’s location by the probability of the classifier. However, such binary classification may not fully handle the outliers, which may cause drifting. To improve the robustness of these tracking methods, a novel object tracking algorithm is proposed based on support vector machine (SVM) and weighted multi-sample sampling method. Our method constructs a classifier by sampling positive and negative samples and then to find the best candidate that has the largest response using SVM classifier. What’s more, the proposed method integrates weighted multi-instance sampling method, which can consider the sample importance by the different weights. The experimental results on many sequences show the robustness and accuracy of the improved method. The proposed target tracking algorithm in video target tracking with a variety of classic popular tracking algorithm, better able to achieve robust target tracking, but also in the infrared video, the infrared target tracking is also has the advantages of stable and accurate.
A Comprehensive Analysis on Sizing of Solar Energy Harvester Elements for Wireless Sensor Motes
Authors: Hemalatha R. , Ramaprabha R. , Radha S. 
Published: November 2017

Abstract
Wireless sensor networks (WSN) have limited lifetime due to on board battery. The lifetime can be improved by energy harvesting solutions. In this paper the solar energy harvester requirements for TelosB mote has been analyzed and calculated. Photovoltaic (PV) panel and battery sizing requirements are calculated by assuming that the mote follows SMAC and TDMA-MAC schedule for image communication. The calculations are validated by comparing it with the parameters calculated from the real time current consumption measurement of the mote. Lifetime has been predicted with the physical design of energy harvester. The analysis confirms that the lifetime of the network can be increased to a greater extent, by proper sizing of the harvester and efficient utilization of the available energy.
Review on Modeling and Controller Design of Hydraulic Actuator Systems
Authors: Salleh S. , Rahmat M.F. , Othman S.M. , Danapalasingam K. A. 
Published: November 2017

Abstract
The purpose of this paper is to review the literature on modeling and previous control strategies of the hydraulic actuator system proposed by most of the researchers around the world. Before comes to the main discussion, some background information related to hydraulic actuator will be presented. This review includes a short summary and conclusion for hydraulic actuator system. The repercussion of this review is for future inventions of a better and robust hydraulic actuator system.
Recommender Algorithms Based on Boosting Ensemble Learning
Authors: Lili Cheng 
Published: November 2017

Abstract
This article introduces ensemble learning algorithms in recommender systems, and in boosting algorithm framework of this article, shows how to filter the basic recommendation algorithm according to the characteristics of boosting algorithm. By comparing the rational choice of the two recommended boosting algorithm is applied to the frame. And then it determines the main parameters of the algorithm through the experiments, ultimately to obtain a more effective integration of the recommendation algorithm. Experimental results on Netflix validate the effectiveness of the proposed algorithm.
Iris-Face Fusion and Security Analysis Based on Fisher Discriminant
Authors: Wang Qihui , Zhu Bo , Liu Yu , Xie Lijun , Zheng Yao 
Published: November 2017

Abstract
With the development of society and science technology, the information security becomes more and more important for people and nation. In this paper, we focus on the technology of iris-face fusion in multi-mode sense in order to find an algorithm to get a better recognition performance. Firstly, we introduce the feature extraction of iris and face, and fusion the features using different algorithms. By simulation, we find out the recognition performance with different fusion methods, which provide some new conclusions. In order to improve the performance of recognition system, we classify these features with fisher discriminant analysis again. Then we analyze the security of recognition system from the aspect of influence of leak in biology features. Finally, experiments were designed to demonstrate the effectiveness of the proposed algorithms.