bluuebunny/crossref_metadata_2025 huggingface dataset:
Rule-Based Systems for Medical Diagnosis
Authors: Akula V. S. Giridhar
Published: March 2015

A rule-based system is a set of “if-then” statements that uses a set of assertions, to which rules on how to act upon those assertions are created. Rule-based expert systems have played an important role in modern intelligent systems and their applications in strategic goal setting, planning, design, scheduling, fault monitoring, diagnosis, and so on. The theory of decision support system is explained in detail. This chapter explains how the concepts of fuzzy logic are used for forward and backward chaining. Patient data is analyzed with the help of inference rules.
Hybrid Approach for Analyzing Acute Spots of Clinical Speech Data Using Fuzzy Inference System
Authors: Bharathi C. R. , Shanthi V.
Published: March 2015

Acoustical measures of vocal functions are used in the assessments of voice disorders and monitoring the subject's improvement with speech therapy. In this chapter, a hybrid approach is proposed to identify the acute spots in pathological speech signals. These spots represents where the speech disorder occurs. The speech training for that specific portion of speech in particular could be given for enhancing the speeches. Dimensionality reduction is done using Principal Component Analysis (PCA) on Mel Frequency Cepstrum Coefficients (MFCC) extracted. By statistical method it is proved that overall 91.60% of the words were classified correctly. The features were trained using Support Vector Machines (SVM) for categorizing normally and abnormally pronounced words. The peaks found by Fast Fourier Transform (FFT) in abnormal words is made use of in the Fuzzy Inference System (FIS) for finding the acute spots in which the aberration has occurred in the word. This hybrid approach was found to have around 98% accuracy.
Knowledge Representation Using Fuzzy XML Rules in Web-Based Expert System for Medical Diagnosis
Authors: Sajja Priti Srinivas
Published: March 2015

The Web is a huge repository of information for large spectrum of decision making and advise. To effectively utilise it, there is a need for knowledge-based techniques. This chapter proposes a novel technique of knowledge representation using a fuzzy eXtensible Markup Language (XML). XML is an efficient tool to represent content; however, it lacks management of uncertainty and vagueness. The proposed technique serves dual advantages such as making the application Web-enabled and imparting benefits of uncertainty and intelligence. This chapter presents the general structure of fuzzy XML rule, DTD model, and the generic architecture of Web-based expert systems using fuzzy XML knowledge base for a variety of applications in different areas. To demonstrate the architecture proposed, an abdomen pain diagnosing system for appendicitis is discussed with sample rules along with a decision tree for the case.
Synechism in the Video Games Design
Authors: Cipolla-Ficarra Francisco V. , Alma Jacqueline , Quiroga Alejandra
Published: March 2015

The authors present an analysis of the first set of elements belonging to the interactive design categories: layout (naturalness of metaphor) and content (storytelling), which make up synechism in video game design. In addition, they examine the evolution of the notion of the video game in relation to the advance of the software and hardware. Finally, the authors include in that analysis the changes in storytelling, due to the greater or lesser presence of the dynamic means and the static means of hypermedia communication.
Improved Interaction for Mid-Air Projection Screen Technology
Authors: Palovuori Karri , Rakkolainen Ismo
Published: March 2015

Mid-air, walk-through fogscreens are frequently used in trade shows, theme parks, museums, concerts, etc. They enhance many kinds of entertainment experiences and are captivating for the audience. Currently, they are usually employed only as non-responsive, passive screens for “immaterial” walk-through special effects. Suitable sensors can turn fogscreens into interactive touch screens or walk-through virtual reality screens. Several interactive systems have been implemented. However, the cost and other features of 2D and 3D tracking sensors have been prohibitive for wider commercial adoption. This chapter presents a Microsoft Kinect-based 2D and 3D tracking for mid-air projection screens. Kinect cannot track through the fogscreen due to disturbances caused by fog. In addition to robust tracking and lower cost, the custom Kinect tracking also brings along other advantages such as possibilities for projector's hotspot removal, ballistic tracking, multi-user, multi-touch, and virtual reality setups, and novel user interfaces.
Efficient Prefix Scan for the GPU-Based Implementation of Random Forest
Authors: Novak Bojan
Published: March 2015

The random forest ensemble learning with the Graphics Processing Unit (GPU) version of prefix scan method is presented. The efficiency of the implementation of the random forest algorithm depends critically on the scan (prefix sum) algorithm. The prefix scan is used in the depth-first implementation of optimal split point computation. Described are different implementations of the prefix scan algorithms. The speeds of the algorithms depend on three factors: the algorithm itself, which could be improved, the programming skills, and the compiler. In parallel environments, things are even more complicated and depend on the programmer´s knowledge of the Central Processing Unit (CPU) or the GPU architecture. An efficient parallel scan algorithm that avoids bank conflicts is crucial for the prefix scan implementation. In our tests, multicore CPU and GPU implementation based on NVIDIA´s CUDA is compared.
Ubiquitous Learning Supporting Systems
Authors: Durán Elena B. , Álvarez Margarita
Published: March 2015

Ubiquitous learning features intuitive ways of identifying appropriate learning collaborators and right learning contents and services at the right place and at the right time. Consequently, there are many aspects that must be considered in designing computing applications that support this kind of learning. In this chapter, ubiquitous learning is introduced and characterized, the challenges that must be faced by those in charge of designing and developing such applications are reviewed, and the state of the art of this recently initiated line of research at the Informatics and Information System Research Institute of the National University of Santiago del Estero are presented. The developments achieved to date as well as the future guidelines are also shown.
Quality Analysis of VoIP in Real-Time Interactive Systems over Lossy Networks
Authors: Mouasher Maha Z. , Khalifeh Ala' F.
Published: March 2015

Voice over Internet Protocol (VoIP) systems have been spreading massively during the recent years. However, many challenges are still facing this technology among which is the lossy behavior and the uncontrolled network impairments of the Internet. In this chapter, the authors design and implement a VoIP test-bed utilizing the Adobe Real-Time Media Flow Protocol (RTMFP) that can be used for many voice interactive applications. The test-bed was used to study the effect of changing some voice parameters, mainly the encoding rate and the number of frames per packet as function of the network packet loss. Several experiments were conducted on several voice files over different packet losses, concluding in the best combination of parameters in low, moderate, and high packet loss conditions to improve the performance of voice packets measured by the Perceptual Evaluation of Speech Quality (PESQ) values.
E-Commerce for Italian Textile Manufacturers
Authors: Cipolla-Ficarra Francisco V.
Published: March 2015

In the current chapter, the authors intend to present the strengths and the weaknesses from the standpoint of graphic computing, managing and productive computing, and the human factors that prevent boosting on-line sales. They analyze the reality of several businesses or industries, which are gathered under the word “group” and belong to the textile sector with high profits because of the high volume of invoicing, a hundred-year-old tradition, with important customers of the European, American, and Asian international fashion, etc. in a northern Italian region known as Lombardy. Paradoxically, the textile sector in that region, like others in Europe, is one of the environments where computing and the breakthroughs and the advantages in new technologies are difficult to introduce these days. The human factor is the main cause because of organizational structures of a vertical and/or family type.
Demystifying the Delphi Method
Authors: Shelton Kaye , Creghan Kathleen Adair
Published: March 2015

The Delphi research method was specifically designed as a forecasting tool for the Rand Corporation in the 1950s. However, in the last several decades, Delphi research has been more frequently used for facilitating group communication for decision making and planning. Because of the Delphi Method's increased use, more information is needed for researchers to understand how to best utilize the method to precisely complete a Delphi study with rigor. This chapter explores the Delphi Method's origin, provides an explanation of the methodology, acknowledges the types and variations in Delphi studies, discusses the advantages and limitations, and provides clear, step-by-step guidelines for employing a successful research study.
Algorithms and Methods Inspired from Nature for Solving Supply Chain and Logistics Optimization Problems
Authors: Dounias Georgios , Vassiliadis Vassilios
Published: March 2015

The current work surveys 245 papers and research reports related to algorithms and methods inspired from nature for solving supply chain and logistics optimization problems. Nature Inspired Intelligence (NII) is a challenging new subfield of artificial intelligence (AI) particularly capable of dealing with complex optimization problems. Related approaches are used either as stand-alone algorithms, or as hybrid schemes i.e. in combination to other AI techniques. Ant Colony Optimization (ACO), Particle Swarm Optimization, Artificial Bee Colonies, Artificial Immune Systems and DNA Computing are some of the most popular approaches belonging to nature inspired intelligence. On the other hand, supply chain management represents an interesting domain of OR applications, including a variety of hard optimization problems such as vehicle routing (VRP), travelling salesman (TSP), team orienteering, inventory, knapsack, supply network problems, etc. Nature inspired intelligent algorithms prove capable of identifying near optimal solutions for instances of those problems with high degree of complexity in a reasonable amount of time. Survey findings indicate that NII can cope successfully with almost any kind of supply chain optimization problem and tends to become a standard in related scientific literature during the last five years.
Discount Focus Subgroup Method
Authors: Halaweh Mohanad
Published: March 2015

This chapter develops an innovative focus group method—the Discount Focus Subgroup (DFSG)—through its application in research aimed at identifying the ethical and social concerns of using an emerging technology, called near field communication, for mobile payments. The DFSG method was needed to address the challenges encountered when this research was conducted, such as limited financial research resources, the emergent nature of the research topic, and the challenges of gathering and analyzing qualitative data. This chapter illustrates when and how to use the DFSG method. It provides the methodological steps for its application, which can be followed while researching emerging topics in the Information Systems (IS) field. The chapter also discusses why DFSG is an innovative method and reflects on its application.
Technology-Enhanced Learning
Authors: O'Donnell Eileen , O'Donnell Liam
Published: March 2015

There are many elements to an individual's life. Each individual engages in a variety of different activities which all require different types or forms of supports. Through family, friends, and colleagues, supports are available for many of the activities in which we engage. But, for students conducting research, specific types of support are necessary that can only be provided by supervisors and peers. This chapter reviews the supports necessary to learn how to effectively undertake research and how these supports could satisfactorily be provided through an e-learning portal or an e-learning platform. An e-learning module could be used to facilitate collaboration amongst student learners and researchers who share similar research interests. Students should be encouraged to develop a community of practice with fellow researchers as this relationship could provide beneficial peer support for as long as their research interests evolve and endure.
Research E-Journaling to Enhance Qualitative and Mixed Methods Research
Authors: Hai-Jew Shalin
Published: March 2015

In qualitative and mixed methods research, the researcher and/or research team are critical elements in the research. Given perceptual, cognitive, and memory limitations, human researchers can often bring these shortcomings to their research and decision-making. To combat such tendencies, researcher reflection, self-awareness, and self-critique are seen as some research controls, as are various standardizations in research to control for bias and to provide for multiple points-of-view. One tool that has long been used for researcher reflection to promote research quality has been the research journal. Research journals are field texts created by the researcher or a research team to make sense of the research work; these are professional forms of narrative analyses or narrative inquiries to enhance researcher self-consciousness of their work, their reasoning, their decision-making, and their conclusions. A contemporaneous electronic version of the qualitative or mixed methods research journal is multimedia-based (including visuals, audio, and video) and may be built in data management software programs, shared cloud-based work sites, or simple folders or digital objects. Guided research e-journals may be structured for the elicitation and capture of specific information to ensure researcher attentiveness, awareness, mindfulness, and thoroughness. Guided electronic journaling (used prior to, during, and post-research) may be used to enhance research quality. This chapter proposes a partial typology of guided structures for research journaling and suggests channels for publishing and distributing research e-journals.
Multi-Objective Optimization Design of Control Devices to Suppress Tall Buildings Vibrations against Earthquake Excitations Using Fuzzy Logic and Genetic Algorithms
Authors: Pourzeynali Saeid , Salimi Shide
Published: March 2015

The main objective of this chapter is to find the optimal values of the parameters of the base isolation systems and that of the semi-active viscous dampers using genetic algorithms (GAs) and fuzzy logic in order to simultaneously minimize the buildings' selected responses such as displacement of the top story, base shear, and so on. In this study, performance of base isolation systems, and semi-active viscous dampers are studied separately as different vibration control strategies. In order to simultaneously minimize the objective functions, a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) approach is used to find a set of Pareto-optimal solution. To study the performance of semi-active viscous dampers, the torsional effects exist in the building due to irregularities, and unsymmetrical placement of the dampers is taken into account through 3D modeling of the building.
Experiences in Applying Mixed-Methods Approach in Information Systems Research
Authors: Peng Guo Chao , Annansingh Fenio
Published: March 2015

Mixed-methods research, which comprises both quantitative and qualitative components, is widely perceived as a means to resolve the inherent limitations of traditional single method designs and is thus expected to yield richer and more holistic findings. Despite such distinctive benefits and continuous advocacy from Information Systems (IS) researchers, the use of mixed-methods approaches in the IS field has not been high. This chapter discusses some of the key reasons that led to this low application rate of mixed-methods design in the IS field, ranging from misunderstanding the term with multiple-methods research to practical difficulties for design and implementation. Two previous IS studies are used as examples to illustrate the discussion. The chapter concludes by recommending that in order to apply mixed-methods design successfully, IS researchers need to plan and consider thoroughly how the quantitative and qualitative components (i.e. from data collection to data analysis to reporting of findings) can be genuinely integrated together and supplement one another, in relation to the predefined research questions and the specific research contexts.
Bangla User Adaptive Word Speech Recognition
Authors: Firoze Adnan , Arifin Md Shamsul , Rahman Rashedur M.
Published: March 2015

The paper presents Bangla word speech recognition using two novel approaches with a comprehensive analysis. The first approach is based on spectral analysis and fuzzy logic and the second one uses Mel-Frequency Cepstral Coefficients (MFCC) analysis and feed-forward back-propagation neural networks. As human speech is imprecise and ambiguous, fuzzy logic – the base of which is indeed linguistic ambiguity, could serve as a precise tool for analyzing and recognizing human speech. The authors' systems revolve around the visual representations of voiced signals – the Fourier energy spectrum and the MFCC. The essences of a Fourier energy spectrum and the MFCC are matrices that include information about properties of a sound by storing energy and frequency in discrete time. The decision making process of their systems is based on fuzzy logic and neural networks. Experimental results demonstrate that their fuzzy logic based system is 86% accurate whereas the Artificial Neural Networks (ANN) based system is 90% accurate compared to a commercial Hidden Markov Model (HMM) based speech recognizer that shows 73% accuracy on an average. Moreover, the authors' research derives that, even though ANN gives a better recognition accuracy than the fuzzy logic based system, the fuzzy logic based system is more accurate when it comes to “more difficult” or “polysyllabic” words. In terms of runtime performance, the fuzzy logic based system outperforms the ANN based Bangla speech recognition system.
Assessment of Fuzzy Logic Radioisotopic Pattern Identifier on Gamma-Ray Signals with Application to Security
Authors: Alamaniotis Miltiadis , Young Jason , Tsoukalas Lefteri H.
Published: March 2015

Analysis of acquired nuclear detector gamma-ray signals for recognition of present radioisotopic signatures is crucial to national security and security applications. Identification algorithms must be accurate and rapid. Artificial intelligence is a scientific field with a variety of tools suitable to implement automated processing of nuclear signals. The use of low resolution portable detectors to measure gamma-ray signals has found a wide use in security and safeguards applications. In this paper, the fuzzy logic based analysis methodology that has been previously developed is applied and assessed on a variety of nuclear signals obtained with a low resolution scintillation detector, and more particularly a sodium iodide (NaI) detector. Various types of fuzzy membership functions are employed and their performance is assessed with regard to the number of positive detections, misses, and false alarms. Furthermore, recorded results from the set of low resolution gamma ray signals are used to estimate the detection sensitivity for each membership function. Results demonstrate the overall effectiveness of the fuzzy logic based identifier, and consist of the main course for the assessment of each membership function. Furthermore, comparison of results designates the triangular membership function as the best membership shape for this type of detector signals.
Hybrid Evolutionary Optimization Algorithms
Authors: Vasant Pandian
Published: March 2015

The novel industrial manufacturing sector inevitably faces problems of uncertainty in various aspects such as raw material availability, human resource availability, processing capability and constraints and limitations imposed by the marketing department. These problems have to be solved by a methodology which takes care of such unexpected information. As the analyst faces this man made chaotic and due to natural disaster problems, the decision maker and the implementer have to work collaboratively with the analyst for taking up a decision on an innovative strategy for implementation. Such complex problems of vagueness and uncertainty can be handled by the hybrid evolutionary intelligence algorithms. In this chapter, a new hybrid evolutionary optimization based methodology using a specific non-linear membership function, named as modified S-curve membership function, is proposed. The modified S-curve membership function is first formulated and its flexibility in taking up vagueness in parameters is established by an analytical approach. This membership function is applied for its useful performance through industrial production problems by employing hybrid evolutionary optimization algorithms. The novelty and the originality of this non-linear S-curve membership function are further established using a real life industrial production planning of an industrial manufacturing sector. The unit produces 8 products using 8 raw materials, mixed in various proportions by 9 different processes under 29 constraints. This complex problem has a cubic non-linear objective function. Comprehensive solutions to a non-linear real world objective function are achieved thus establishing the usefulness of the realistic membership function for decision making in industrial production planning.
Statistical Based Analysis of Electrooculogram (EOG) Signals
Authors: D'Souza Sandra , Sriraam N.
Published: March 2015

The use of Electrooculogram (EOG) signals for developing Human-Computer Interfaces is increasing in the recent times. Several advantages including ease and flexibility in acquiring EOG signals have encouraged insight into EOG based research. In order to identify optimal features for EOG signals for rehabilitation applications, it is necessary to apply the statistical basis to decide the selection of best feature. This paper suggests a pilot study on non-parametric statistical based approach for analyzing EOG signals. This paper considers the detailed statistical analysis of Electrooculogram (EOG) signals. The EOG signals are acquired by considering the horizontal and vertical movements of the eye. The recording includes subjects with identified age groups with different activities. Power spectral densities based on Welch, Yule-Walker, Burg methods are estimated from the acquired EOG signals. Then non-parametric based statistical analysis is performed to show whether the gender or age of the subject influences the EOG signal obtained for different activities. The experimental results based on statistical analysis show that the raw data did not hold any significance to categorize male-female or age wise grouping. However, some features extracted set from the raw data provides useful statistical information which will be of great importance when used for selective rehabilitation.
Analysing the Performance of a Fuzzy Lane Changing Model Using Data Mining
Authors: Moridpour Sara
Published: March 2015

Heavy vehicles have substantial impact on traffic flow particularly during heavy traffic conditions. Large amount of heavy vehicle lane changing manoeuvres may increase the number of traffic accidents and therefore reduce the freeway safety. Improving road capacity and enhancing traffic safety on freeways has been the motivation to establish heavy vehicle lane restriction strategies to reduce the interaction between heavy vehicles and passenger cars. In previous studies, different heavy vehicle lane restriction strategies have been evaluated using microscopic traffic simulation packages. Microscopic traffic simulation packages generally use a common model to estimate the lane changing of heavy vehicles and passenger cars. The common lane changing models ignore the differences exist in the lane changing behaviour of heavy vehicle and passenger car drivers. An exclusive fuzzy lane changing model for heavy vehicles is developed and presented in this chapter. This fuzzy model can increase the accuracy of simulation models in estimating the macroscopic and microscopic traffic characteristics. The results of this chapter shows that using an exclusive lane changing model for heavy vehicles, results in more reliable evaluation of lane restriction strategies.
Intelligent Computation for Manufacturing
Authors: Afify Ashraf
Published: March 2015

Intelligent computation refers to intelligence artificially realised through computation. This chapter reviews six intelligent computation techniques. They are: knowledge-based systems, fuzzy logic, inductive learning, neural networks, genetic algorithms, and swarm intelligent techniques. All of these tools have found many practical applications. Examples of applications in manufacturing are given in the chapter.
Comparative Study on Multi-Objective Genetic Algorithms for Seismic Response Controls of Structures
Authors: Cha Young-Jin , Kim Yeesock
Published: March 2015

This chapter introduces three new multi-objective genetic algorithms (MOGAs) for minimum distributions of both actuators and sensors within seismically excited large-scale civil structures such that the structural responses are also minimized. The first MOGA is developed through the integration of Implicit Redundant Representation (IRR), Genetic Algorithm (GA), and Non-dominated sorting GA 2 (NSGA2): NS2-IRR GA. The second one is proposed by combining the best features of both IRR GA and Strength Pareto Evolutionary Algorithm (SPEA2): SP2-IRR GA. Lastly, Gene Manipulation GA (GMGA) is developed based on novel recombination and mutation mechanism. To demonstrate the effectiveness of the proposed three algorithms, two full-scale twenty-story buildings under seismic excitations are investigated. The performances of the three new algorithms are compared with the ones of the ASCE benchmark control system while the uncontrolled structural responses are used as a baseline. It is shown that the performances of the proposed algorithms are slightly better than those of the benchmark control system. In addition, GMGA outperforms the other genetic algorithms.
An Efficient Evolutionary Algorithm for Strict Strong Graph Coloring Problem
Authors: Bensouyad Meriem , Guidoum Nousseiba , Saïdouni Djamel-Eddine
Published: March 2015

A very promising approach for combinatorial optimization is evolutionary algorithms. As an application, this paper deals with the strict strong graph coloring problem defined by Haddad and Kheddouci (2009) where the authors have proposed an exact polynomial time algorithm for trees. The aim of this paper is to introduce a new evolutionary algorithm for solving this problem for general graphs. It combines an original crossover and a powerful correction operator. Experiments of this new approach are carried out on large Dimacs Challenge benchmark graphs. Results show very competitive with and even better than those of state of the art algorithms. To the best of the author's knowledge, it is the first time that an evolutionary algorithm is proposed to solve the strict strong graph coloring problem.
Quantitative Structure-Activity/Property/Toxicity Relationships through Conceptual Density Functional Theory-Based Reactivity Descriptors
Authors: Pan Sudip , Gupta Ashutosh , Subramanian Venkatesan , Chattaraj Pratim K.
Published: March 2015

Developing effective structure-activity/property/toxicity relationships (QSAR/QSPR/QSTR) is very helpful in predicting biological activity, property, and toxicity of a given set of molecules. Regular change in these properties with the structural alteration is the main reason to obtain QSAR/QSPR/QSTR models. The advancement in making different QSAR/QSPR/QSTR models to describe activity, property, and toxicity of various groups of molecules is reviewed in this chapter. The successful implementation of Conceptual Density Functional Theory (CDFT)-based global as well as local reactivity descriptors in modeling effective QSAR/QSPR/QSTR is highlighted.
A High Torque Magnetorheological Brake for Gait Rehabilitation Robot
Authors: Wang Juan , Li Jun Qiang , Zhu Song Song , Shi Chao
Published: March 2015

A new structure magnetorheological brake (MR brake) with three effective areas was designed, two end surfaces and the cylindrical surface of the rotor work as effective areas, then the effective area was increased with the same volume of the rotor. Finite element model of the MR brake was built, the electromagnetic field analysis was performed, then magnetic field quantities of the damper model were got. With the results of the magnetic analysis and the relation between the yield stress and the magnetic field strength of the magnetorheological fluid (MR fluid), the performance simulation of the magnetorheological damper was realized. According to the requirements of the gait rehabilitation robot to the yield torque of the MR brake, the current driver was designed. On these bases, the mechanical performance test system of the MR brake were developed, the mechanical performance of the brake was researched used the test system, the brake’s properties: torque vs. speed and yield torque vs. current were obtained.
A Method of Robotic Remote Operation Based on an Electromagnetic Tracking System
Authors: Luo Yuan Yuan , Li Si Kan , Li Dong Xu , Fan Cai Zhi
Published: March 2015

Robotic remote operation has become a new research hotspot in many fields, experiments on remote operated manipulator doing surgeries for the patients have been carried out in medical science. This paper takes the manipulator of four degrees of freedom capturing the target object as the study background and comes up with a new method of remote control for a robotic arm based on an electromagnetic tracking system which serves as the signal acquisition device. Thus the arm movement can be the input of the robot arm control loop and guides the motion of the robot arm. Firstly, the paper builds the kinematics model of the experimental robotic arm. Secondly, based on the analysis of human arm structure, the paper proposes an appropriate experimental program. Finally, experiments on remote operation have been carried out, the results of which prove the effectiveness of the method above.
Automation Control System of the Pressure Pulse Testing Rig
Authors: Zhu Zhi Hui , Gong Yu Jie , Liu Xin Fu
Published: March 2015

With the development of industrial automation, people are increasingly demanding high product quality. Especially in automotive and aerospace fields, the fatigue quality of components determines the merits of the whole vehicle. Therefore fatigue performance testing has good prospects. Pressure pulse testing rig is a automatic control system. The system uses the solution which combines the virtual instrument technology with PLC controller technology. It has the ability to get the function of signal acquisition, signal analyzing, data processing and automatic control together. It enables the system to run automatically in accordance with setting commands and avoids the problem that the CNC system lacks of real-time capability and the disadvantage that the whole PLC driver control system can not meet the requirement of data acquisition and data processing. At the same time, it has both the advantages in the open CNC system and advantages in the controller system and can realize the highly efficient control.
Development of Automatic CAN Gateway Test System
Authors: Yang Tian Yue , Luo Feng , Liu Chu
Published: March 2015

In order to solve the problem of hardship and complexity in manual vehicle gateway tests, an Automatic CAN Gateway Test System was developed. The test system integrated IPC, CAN tools and network control module. It supports 2-4 channels gateways, and it also supports complex gateways with signal routing, network status management and other complicated functions. When the test is executed, the text system can simulate all the nodes which are required for DUT in normal communication to construct realistic bus environment. It can also construct relevant message status, signal status and network status to execute tests. The system, which is highly automatic, improves the accuracy and efficiency of CAN gateway test.
The Construction of Remote Online Access to PLC Laboratory Based on Internet
Authors: Ruan You De
Published: March 2015

This paper describes the construction of remote online access to PLC Laboratory based on Internet .The Laboratory apply industrial communication modules, relay on the powerful ommunications capabilities of Siemens PLC , transfer data by the Internet. The PLC of the Laboratory can be accessed by remote PC. The remote PC possible upload and download PLC program, online diagnosis, online monitoring, etc; and directly observed action of PLC by video, determine equipment movement is whether correct or error. The paper introduces the network topology, various functions and data security communication method of the system.
Design of Control Net Based on CAN Bus
Authors: Zhang Xiu Hong
Published: March 2015

Discussed the structure feature, working principle, communication protocol and design of hardware and software of the intelligent measurement and control device based on CAN bus in this paper.
Model Identification and Controller Design for Piezoelectric Ceramic Actuator
Authors: Li Yi Bo , Liu Zhao Hui , Liu Yan Mei
Published: March 2015

Piezoelectric ceramics are widely used in precision measurement and precision positioning, but its nonlinear characteristics seriously affected its application. Thus, firstly input voltage and output displacement data of piezoelectric ceramics are collected by the experiment, the nonlinear characteristics of piezoelectric ceramics is analyzed. Then a piezoelectric ceramic linear model is established using recursive least squares algorithm based on input and output signal. The identification results show that the algorithm is effective. Finally PID controller is designed and the controller has better control effect.
Research of Tornambe Control in the Speed Regulation of Induction Motor System
Authors: Zhao Jun Mei , Zhang Zhi Jie , Ren Yi Feng
Published: March 2015

Induction motor (IM) is a complex controlled object that is difficult to drive and control. In this paper, direct torque control strategy (DTC) is adopted to drive IM. In order to overcome drawbacks of the bad low speed performance of DTC system, Tornambe control (TC) is used to replace the traditional speed regulator to improve system performance. The results show that TC strategy overcomes the disadvantage of the low speed performance declined and improves the response speed of DTC system, and effectively solves the contradiction between the system response speed and overshoot.
Autocorrelation Phase Measurement of Spread Spectrum Signal for High Precision Indoor Microwave Positioning
Authors: Cai Wen Yang , Luo Gao Yong
Published: March 2015

The increasing demand for high precision indoor positioning in many public services has urged research to implement cost-effective systems for a rising number of applications. However, current systems with either short-range positioning technology based on wireless local area networks (WLAN) and ZigBee achieving meter-level accuracy, or ultra-wide band (UWB) and 60 GHz communication technology achieving high precision but with high cost required, could not meet the need of indoor wireless positioning. This paper presents a new method of high precision indoor positioning by autocorrelation phase measurement of spread spectrum signal utilizing carrier frequency lower than 1 GHz, thereby decreasing power emission and hardware cost. The phase measurement is more sensitive to the distance of microwave transmission than timing, thus achieving higher positioning accuracy. Simulation results demonstrate that the proposed positioning method can achieve high precision of less than 1 centimeter decreasing when various noise and interference added.
Study on Traveling Wave Signal Anti-Interference and a New Detection Method
Authors: Li Yi , Wu Zheng Qiu , Li Jian Qi , Luo Xiang Ci
Published: March 2015

Traveling wave in transit, wave head is easy to produce distortion and affected by environmental interference, so accurately measuring the head of traveling wave singularity occurrence time become extremely difficult. The key to improve the precision of traveling wave detection is to accurately capture the happening time of wave head of singular points. Recently, traveling wave singularity detection usually use wavelet, EMD-HHT transform technique, but both have mixing phenomenon, affecting the accuracy of detection. In this paper, we propose a new method that use Duffing chaotic oscillator to suppress traveling wave interference signal. By Matlab simulation and it is proved that this method can effectively suppress noise singular point. Meanwhile, we propose an anti-mixing EEMD-HHT wave head detection technology. Through simulation experiment and field test, it is proved that, compared with EMD, EEMD can more accurately identify the traveling wave arrival time, detection accuracy increasing by 1.52%.
Implementation of Power Load Forecasting Based on the Improved Neural Network Model
Authors: Xu Yang
Published: March 2015

This paper introduces the importance of power load forecasting, and makes forecasting based on the power load values collected in Botou City within a week. The conclusion shows that the accuracy of PSO - ELMAN network forecasting results is much higher than that of PSO - BP network forecasting results.
Research of the Algorithms for Service Restoration Reconfiguration in Distribution Network
Authors: Wang Jun Feng
Published: March 2015

The purpose of this paper is to propose a mixed integer programming model of service restoration reconfiguration considering the minimum switching frequency and power losses. The recovery after the service failure of distribution network is a multi-objective optimization problem with constraints. This paper also discusses the reconfiguration algorithms for power restoration and load balancing in the real-time operation environment of distribution network, which can make the problem solving easy to handle and control. The methods and measures for service auto restoration in distribution automation system are analyzed by examples.
Research on the Optimization Model of Flights Alternate Based on Linear Programming
Authors: Cao Xing Wu
Published: March 2015

Currently, flight alternate is becoming a growing serious problem in large hub airports due to temporary emergencies such as adverse weather, equipment outages, runway collisions, terrorism threats, and others. Therefore it becomes more and more pressing to study alternate strategy for arriving flights in large hub airports. By taking the minimum total diverted time as the optimization objective in this paper, an optimization model based on linear programming is proposed to solve the allocation alternative airports problem for arriving flights. Then it is verified by real operational data of the capital airport under bad weather. Experiments show that the whole flights diversion time is reduced by 9.7% after optimization, which proves that the model is effective.
Aluminum Plate Surface Defects Classification Based on the BP Neural Network
Authors: Li Qing Hua , Liu Di
Published: March 2015

The aluminum plate surface defects recognition method of BP neural network is studied based on target detection .In order to detect the defects, the target image is binaried by adaptive threshold method. After binarizing the target image, three kinds of image feature, including geometric feature, grayscale feature and shape feature, are extracted from the target image and its corresponding binary image. The defects classification model based on back-propagation neural network utilizes three layers neural network structure model and the hyperbolic tangent function of S function as the activation function, the number of neurons in hidden layer is confirmed by experiments. The experimental results show that the classification accuracy of BP neural network classification model as high as 94%, this can meet our requirements.
Face Recognition by PCA and Improved LBP Fusion Algorithm
Authors: Dong En Zeng , Fu Yan Hong , Tong Ji Gang
Published: March 2015

This paper proposed a theoretically efficient approach for face recognition based on principal component analysis (PCA) and rotation invariant uniform local binary pattern texture features in order to weaken the effects of varying illumination conditions and facial expressions. Firstly, the rotation invariant uniform LBP operator was adopted to extract the local texture feature of the face images. Then PCA method was used to reduce the dimensionality of the extracted feature and get the eigenfaces. Finally, the nearest distance classification was used to distinguish each face. The method has been accessed on Yale and ATR-Jaffe face databases. Results demonstrate that the proposed method is superior to standard PCA and its recognition rate is higher than the traditional PCA. And the proposed algorithm has strong robustness against the illumination changes, pose, rotation and expressions.
Image Recognition Based on High-Dimensional Information Geometry
Authors: Chen Peng , Liu Ning
Published: March 2015

This paper proposes a new method of image recognition based on the theory of high-dimensional information geometry. Firstly, we used the linear algebra to describe the high-dimensional information geometry and studied the effectiveness of included angle cosine in different dimensional spaces. Secondly, the image could be expressed as a vector and the cosine value of angle between two vectors was used as the discriminant conditions of classifier to identify images. Finally, a face recognition system extracting facial features based on a fast principal component analysis (PCA) was designed, using Euclidean distance and included angle cosine value to measure the nearest neighbor classifier respectively for comparision. The experiments results proved that the proposed method has a higher accuracy and better performance than a traditional recognition system.
Empirical Study on the Non-Periodic Cycles of Fractal Time Series: Examples of Indices of the Chinese Stock Market
Authors: Li Yang , Zhang Wei Yu , Wei Yong , Sun Jin Hui
Published: March 2015

By R/S analysis, non-periodic cycles of the SSE Composite Index and SZSE Composite Index are studied in this paper. With a different determinant method from the previous works about fractal behaviors of the Chinese stock market, the empirical results obtained in this study support the non-periodic cycle results but with different values. With more data available, the analysis shows that the two indices follow a biased random walk with two non-periodic cycles, one about 4.5 years and another about 9 years, which may be tied to the economic and politic cycles.
Research on Relay Protection of Distribution Network System with Distributed Generation
Authors: Liu Hui Hai , Zhang Xiao Li , Li Wei , Wang Xiao Yang , Zhang Yi Fan
Published: March 2015

Introduce the current development of distributed generation, the structure and protection configuration of existing distribution network, and the fault current insert of different kinds of distributed generation was introduced. Through the distribution network in different positions to join distributed generation, the influence of the join of distributed generation on the existing protection of distribution network was analyzed, which included the serious interference to the sensitivity and selectivity of the original protection, the refusal of line protection, the action error of non- fault line protection. The influence of distributed generation on automatic reclosing, and the effect between fuses was discussed, to some extent, and base on the discussion some appropriate countermeasures are proposed.
Design and Research of Trench-Isolated LAPS Sensor Array
Authors: Sun Ying , Guo Wei , Zhu Da Zhong
Published: March 2015

A new kind of SOI LAPS sensor array with trench and heavy doping structure was proposed. Photo current response, noise isolation and device performance were simulated with ISE-TCAD tools. The new structure LAPS sensor array effectively improves noise separation characteristics of adjacent array units. The SNR (signal-to-noise ratio) of LAPS array with trench-isolated structure is superior to that with only heavy doping regions. Trench isolation structure also improves the integration scales of LAPS array.
Obtainable P-Type ZnO Film Doped with Li by Sol-Gel Method
Authors: Wang Ting Ting , Dai Miao Miao , Yan Ya Jun , Zhang Hong , Yu Yi Min
Published: March 2015

A series of Li-doped zinc oxide ( ZnO ) thin films were deposited on quartz glass by sol-gel and spin coating method. Their p-type conductivities could be achieved by subsequently thermal annealing process, which were characterized by Hall effect measurement. An optimized result with resistivity of 46.8 Ω cm, Hall mobility of 1.35 cm2/V s, and hole concentration of 9.89×1016 cm-3 was achieved at the annealing temperature of 700 °C. The films exhibited highly (002) oriented growth in all the cases. Strong green emission centered at 510 nm was observed by photoluminescence spectra in Li-doped ZnO films at room temperature.
A Research of New Zero-Voltage Switching Equalization for Super-Capacitor Energy Storage System
Authors: Gao Han , Gao Zhi Gang
Published: March 2015

An expatiation to analyze and verification for zero-voltage-switching (ZVS) is proposed for cell voltage equalization control in a series connected super capacitors string. Resonant circuit was designed to achieve the ZVS to reduce the switching loss in equalization circuit. Analyze result indicates that the switching loss and equalization efficiency can be improved with the ZVS technology. The simulation and experimental results shows the ZVS equalization technology can achieve voltage equalization performance and reduce MOSFET switches power loss and increase the efficiency by 20% compared with the traditional equalizer.
Inhibition of Double PWM Welding Power Supply Voltage Fluctuation of the Intermediate Links
Authors: Zhang Ji Fang , Liu Wei , Sun Shi Wei
Published: March 2015

Double PWM welding power source can restrain the net side current harmonic. In order to suppress the transient when the intermediate DC link voltage fluctuation, generally adopt the method of increasing capacitor capacity, the disadvantages of this approach are: slow dynamic response, large volume, low service life, high cost of equipment. Therefore put forward a kind of double PWM welding power source based on feed-forward control power, using the power of feed-forward can effectively inhibit the intermediate DC link voltage fluctuation, based on the control method of the power system has a high power factor, good dynamic performance, simple and easy, good application prospect.