bluuebunny/crossref_metadata_2025 huggingface dataset:
A Fuzzy Model with Thermodynamic Based Consequents and a Niching Swarm-Based Supervisor to Capture the Uncertainties of Damavand Power System
Authors: Mozaffari Ahmad , Mohammadpour Moein , Fathi Alireza , Gorji-Bandpy Mofid
Published: July 2017

In this investigation, a novel fuzzy mathematical program based on thermodynamic principles is implemented to capture the uncertainties of a practical power system, known as Damavand power plant. The proposed intelligent machine takes the advantages of a niching bio-inspired learning mechanism to be reconciled to the requirements of the problem at hand. The aim of the bio-inspired fuzzy based intelligent system is to yield a model capable of recognizing different operating parameters of Damavand power system under different operating conditions. To justify the privileges of using a niching metaheuristic over gradient descend methods, the authors use the data, derived through data acquisition, together with a machine learning based approach to estimate the multi-modality associated with the training of the proposed fuzzy model. Moreover, the niching bio-inspired metaheuristic, niching particle swarm optimization (NPSO), is compared to canonical PSO (CPSO), stochastic social PSO (SSPSO), unified PSO (UPSO), comprehensive learning PSO (CLPSO), PSO with constriction factor (PSOCF) and fully informed PSO (FIPSO). Through experiments and analysis of the characteristics of the problem being optimized, it is proved that NPSO is not only able to tackle the deficiencies of the learning process, but also can effectively adjust the fuzzy approach to conduct the identification process with a high degree of robustness and accuracy.
Design of a Hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) Controller for Position and Angle Control of Inverted Pendulum (IP) Systems
Authors: Kharola Ashwani
Published: July 2017

This paper illustrates a comparison study of Fuzzy and ANFIS Controller for Inverted Pendulum systems. IP belongs to a class of highly non-linear, unstable and multi-variable systems which act as a testing bed for many complex systems. Initially, a Matlab-Simulink model of IP system was proposed. Secondly, a Fuzzy logic controller was designed using Mamdani inference system for control of proposed model. The data sets from fuzzy controller was used for development of a Hybrid Sugeno ANFIS controller. The results shows that ANFIS controller provides better results in terms of Performance parameters including Settling time(sec), maximum overshoot(degree) and steady state error.
PSK Method for Solving Type-1 and Type-3 Fuzzy Transportation Problems
Authors: Kumar P. Senthil
Published: July 2017

In conventional transportation problem (TP), supplies, demands and costs are always certain. In this paper, the author tried to categories the TP under the mixture of certain and uncertain environment and formulates the problem and utilizes the crisp numbers, triangular fuzzy numbers (TFNs) and trapezoidal fuzzy numbers (TrFNs) to solve the TP. The existing ranking procedure of Liou and Wang is used to transform the type-1 and type-3 fuzzy transportation problem (FTP) into a crisp one so that the conventional method may be applied to solve the TP. The solution procedure differs from TP to type-1 and type-3 FTP in allocation step only. Therefore, the new method called PSK method and new multiplication operation on TrFN is proposed to find the mixed optimal solution in terms of crisp numbers, TFNs and TrFNs. The main advantage of this method is computationally very simple, easy to understand and also the optimum objective value obtained by our method is physically meaningful. The effectiveness of the proposed method is illustrated by means of a numerical example.
Fuzzy Expert System to Diagnose Diabetes Using S Weights for S Fuzzy Assessment Methodology
Authors: Kumar A. V. Senthil , Kalpana M.
Published: July 2017

In the field of medicine decision making it is very important to deal with uncertainties, knowledge, and information. Decision making depends upon the experience, capability, and the observation of doctors. In the case of complex situations, it is very tough to give a correct decision. So computer-based procedure is very much essential. Fuzzy Expert System is used for decision making in the field of medicine. Fuzzy expert system consists of the following elements, fuzzification interface, S Fuzzy Assessment Methodology, and defuzzification. S Fuzzy Assessment Methodology uses the K Ratio to find overlap between membership function. To measure the similarity between fuzzy set, fuzzy number, and fuzzy rule, T Fuzzy similarity is used. Similar fuzzy sets are merged to form a common set; a new methodology was framed to identify the similarity between fuzzy rules with fuzzy numbers, and S Weights are to manage uncertainty in rules. S Weights use consequent and antecedent part of each rule. The efficiency of the proposed algorithm was implemented using MATLAB Fuzzy Logic tool box to construct a fuzzy expert system to diagnose diabetes.
Hybrid Fuzzy Neural Search Retrieval System
Authors: Ghnemat Rawan , Shaout Adnan
Published: July 2017

Search engines are crucial for information gathering systems (IGS). New challenges face search engines concerning automatic learning from user requests. In this paper, a new hybrid intelligent system is proposed to enhance the search process. Based on a Multilayer Fuzzy Inference System (MFIS), the first step is to implement a scalable system to relay logical rules in order to produce three classifications for search behavior, user profiles, and query characteristics from analysis of navigation log files. These three outputs from the MFIS are used as inputs for the second step, an Adaptive Neuro-Fuzzy Inference System (ANFIS). The training process of the ANFIS replaced the rules by adjusting the weights in order to find the most relevant result for the search query. This proposed system, called MFIS-ANFIS, is implemented as an experimental system. The system performance is evaluated using quantitative and comparative analysis. MFIS-ANFIS aimed to be the core of intelligent and reliable search process.
A Multi-Objective Fuzzy Ant Colony Optimization Algorithm for Virtual Machine Placement
Authors: Perumal Boominathan , M. Aramudhan
Published: July 2017

In cloud computing, the most important challenge is to enforce proper utilization of physical resources. To accomplish the mentioned challenge, the cloud providers need to take care of optimal mapping of virtual machines to a set of physical machines. In this paper, the authors address the mapping problem as a multi-objective virtual machine placement problem (VMP) and propose to apply multi-objective fuzzy ant colony optimization (F-ACO) technique for optimal placing of virtual machines in the physical servers. VMP-F-ACO is a combination of fuzzy logic and ACO, where we use fuzzy transition probability rule to simulate the behaviour of the ants and the authors apply the same for virtual machine placement problem. The results of fuzzy ACO techniques are compared with five variants of classical ACO, three bin packing heuristics and two evolutionary algorithms. The results show that the fuzzy ACO techniques are better than the other optimization and heuristic techniques considered.
A Two-Level Fuzzy Value-Based Replica Replacement Algorithm in Data Grids
Authors: Saadat Nazanin , Rahmani Amir Masoud
Published: July 2017

One of the challenges of data grid is to access widely distributed data fast and efficiently and providing maximum data availability with minimum latency. Data replication is an efficient way used to address this challenge by replicating and storing replicas, making it possible to access similar data in different locations of the data grid and can shorten the time of getting the files. However, as the number and storage size of grid sites is limited and restricted, an optimized and effective replacement algorithm is needed to improve the efficiency of replication. In this paper, the authors propose a novel two-level replacement algorithm which uses Fuzzy Replica Preserving Value Evaluator System (FRPVES) for evaluating the value of each replica. The algorithm was tested using a grid simulator, OptorSim developed by European Data Grid projects. Results from simulation procedure show that the authors' proposed algorithm has better performance in comparison with other algorithms in terms of job execution time, total number of replications and effective network usage.
A Fuzzy Expert System for Star Classification Based on Photometry
Authors: Pakniyat Aida , Hosseini Rahil , Mazinai Mahdi
Published: July 2017

The application of fuzzy systems is emerging in science where experts' knowledge plays a vital role. This paper utilizes the capability of fuzzy set theory for managing uncertainty associated to star classification problem. The fuzzy classifies uses a dataset of stars obtained from Harvard classification. This paper, for the first time, presents fuzzy starts classification based on photometry. For performance evaluation, an ROC analysis was performed. The results reveal a classifier with an accuracy of 83.5% and with the 72% area under the ROC curve. The mean square error (MSE) was ?3.77*10?^(-5) which reveals superiority of the proposed fuzzy expert system compared to the other classification methods.
Movie Recommendation System Based on Fuzzy Inference System and Adaptive Neuro Fuzzy Inference System
Authors: Siddiquee Mahfuzur Rahman , Haider Naimul , Rahman Rashedur M.
Published: July 2017

One of most prominent features that social networks or e-commerce sites now provide is recommendation of items. However, the recommendation task is challenging as high degree of accuracy is required. This paper analyzes the improvement in recommendation of movies using Fuzzy Inference System (FIS) and Adaptive Neuro Fuzzy Inference System (ANFIS). Two similarity measures have been used: one by taking account similar users' choice and the other by matching genres of similar movies rated by the user. For similarity calculation, four different techniques, namely Euclidean Distance, Manhattan Distance, Pearson Coefficient and Cosine Similarity are used. FIS and ANFIS system are used in decision making. The experiments have been carried out on Movie Lens dataset and a comparative performance analysis has been reported. Experimental results demonstrate that ANFIS outperforms FIS in most of the cases when Pearson Correlation metric is used for similarity calculation.
Including Client Opinion and Employee Engagement in the Strategic Human Resource Management
Authors: Belhaj Rachid , Tkiouat Mohamed
Published: July 2017

The trend in the Human Resources Management is to enhance it to the strategic level, this paper intends to provide an advanced decision making tool in the field of the Strategic Human Resources Management applying a combination of an augmented SWOT analysis approach to evaluate and to rank strategies and a Fuzzy Inference System (FIS) to eliminate the vagueness in the expressed opinions. The version of SWOT utilized here includes the client opinion and employee engagement besides to the traditional experts' assessment, while the FIS is an instrument that treats the data coming from SWOT analysis with the goal of avoiding the uncertainty that may come from the opinions expressed in the SWOT analysis and so to improve the ranking of the strategies. The results show improvements in prioritization of strategies in the way that besides knowing the decision to make for each, the model shows us also what to do regarding every strategy (what to maximize and what to minimize while talking about strengths, weaknesses, opportunities and threat).The proposed model can be applied for strategies prioritization and decision making problems in all fields.
A Fuzzy-Based Calorie Burn Calculator for a Gamified Walking Activity Using Treadmill
Authors: Subramaniam Prabhakar Rontala , Venugopal Chitra , Sangaiah Arun Kumar
Published: July 2017

Gamification can be viewed as a process design which encapsulates competition, achievements, status and self-expression. Gamification is used as a tool for improving physical fitness. In this chapter the physical activity using treadmill walking is considered. Calorie burn calculation plays a vital role in the gamification design. In treadmill calorie burn calculation, traditional and fuzzy based methods are compared for effective gamification. In the traditional calorie burn calculation method different equations are used for different incline levels. In the fuzzy logic method fuzzy reasoning technique is applied to calculate the calorie burn for different incline levels. It is identified that fuzzy based calorie calculation enhances physical activity and supports Gamification. Fuzzy based calorie burn calculation methods produces approximate values and supports the players to choose higher incline levels instead of lower incline levels and thereby burning more calories.
Application of Fuzzy Logic for Mapping the Agro-Ecological Zones
Authors: Simanjuntak Bistok Hasiholan , Prasetyo Sri Yulianto Joko , Hartomo Kristoko Dwi , Purnomo Hindriyanto Dwi
Published: July 2017

The mapping of agro-ecological zone, which is integrated with the suitability of land evaluation, will determine the ideal farming system. The ideal farming system including sustainable land management will support the food security scenario of a region. In this chapter, the implementation of fuzzy logic for mapping the agro-ecological zone is discussed. The agro-ecological zone in Boyolali is used as case study in which the mapping considers its physiographic characteristics and climate. Two physiographic characteristics are involved: slope of the land and elevation. Rainfall is used as representative of climate. The experiment results reveal that simple membership function with the Mamdani inferences system could help decision makers to classify the agricultural land in Boyolali.
Enhancement of Turbo-Generators Phase Backup Protection Using Adaptive Neuro Fuzzy Inference System
Authors: Abdel Aziz Mohamed Salah El-Din Ahmed , Elsamahy Mohamed , Hassan Mohamed A. Moustafa , Bendary Fahmy M. A.
Published: July 2017

This research work presents an advanced solution for the problem due to the current setting of Relay (21). This problem arises when it is set to provide thermal backup protection for the generator during two common system disturbances, namely a system fault and a sudden application of a large system load. These investigations are carried out using Adaptive Neuro Fuzzy Inference System (ANFIS). The results of the investigations have shown that the ANFIS has a promising tool when applied for turbo-generators phase backup protection. The effect of this tool varies according to the type of input data used for ANFIS testing and validation. The proposed method in this paper proposes the use of two different sets of inputs to the ANFIS, these inputs are the generator terminal impedance measurements (R and X) and the generator three phase terminal voltages and currents (V and I). The dynamic simulations of a test benchmark have been conducted using the PSCAD/EMTDC software. The results obtained from the ANFIS scheme are encouraging.
Rule-Based Systems for Medical Diagnosis
Authors: Akula V. S. Giridhar
Published: July 2017

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.
Application of Fuzzy Expert System in Medical Treatment
Authors: Ghosal Kajal , Haldar Partha , Sutradhar Goutam
Published: July 2017

The incidence of breast cancer is increasing day by day. Emotional significance of females for the fear of removal of breast demands attention and carries a particular terror. Fuzzy logic-based expert system is a powerful tool that is used in this chapter to get the benefits of soft computing in modern medical science. This chapter deals with reasoning for medical implementation in breast cancer diagnosis. The motto of this expert system using MATLAB software is to make the people of the world healthier, free from breast cancer and its metastasis through the power of information. Special revolutionary screening technology and a few (cancer markers) blood tests enable breast cancer diagnosis, configuration, and control, and prompt necessary decisions for treatment. Thus, this system provides healthier living, better healthcare outcomes, and helps to lower the overall cost of the healthcare system.
Vague Correlation Coefficient of Interval Vague Sets and its Applications to Topsis in MADM Problems
Authors: P. John Robinson , E. C. Henry Amirtharaj
Published: July 2017

Various attempts are made by researchers on the study of vagueness of data through Intuitionistic Fuzzy sets and Vague sets, and also it is shown that Vague sets are Intuitionistic Fuzzy sets. However, there are algebraic and graphical differences between Vague sets and Intuitionistic Fuzzy sets. In this chapter, an attempt is made to define the correlation coefficient of Interval Vague sets lying in the interval [0,1], and a new method for computing the correlation coefficient of interval Vague sets lying in the interval [-1,1] using a-cuts over the vague degrees through statistical confidence intervals is also presented by an example. The new method proposed in this work produces a correlation coefficient in the form of an interval. The proposed method produces a correlation coefficient in the form of an interval from a trapezoidal shaped fuzzy number derived from the vague degrees. This chapter also aims to develop a new method based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to solve MADM problems for Interval Vague Sets (IVSs). A TOPSIS algorithm is constructed on the basis of the concepts of the relative-closeness coefficient computed from the correlation coefficient of IVSs. This novel method also identifies the positive and negative ideal solutions using the correlation coefficient of IVSs. A numerical illustration explains the proposed algorithms and comparisons are made with some existing methods.
A Fuzzy-Based Approach to Support Decision Making in Complex Military Environments
Authors: Hanratty Timothy P. , Newcomb E. Allison , Hammell II Robert J. , Richardson John T. , Mittrick Mark R.
Published: July 2017

Data for military intelligence operations are increasing at astronomical rates. As a result, significant cognitive and temporal resources are required to determine which information is relevant to a particular situation. Soft computing techniques, such as fuzzy logic, have recently been applied toward decision support systems to support military intelligence analysts in selecting relevant and reliable data within the military decision making process. This article examines the development of one such system and its evaluation using a constructive simulation and human performance model to provided critical understanding of how this conceptual information system might interact with personnel, organizational, and system architectures. In addition, similarities between military intelligence analysts and cyber intelligence analysts are detailed along with a plan for transitioning the current fuzzy-based system to the cyber security domain.
Fuzzy Logic-Based Intelligent Control System for Active Ankle Foot Orthosis
Authors: Kanthi M.
Published: July 2017

The Ankle Foot Orthosis (AFO) is an orthotic device intended to assist or to restore the movements of the ankle foot complex in the case of pathological gait. Active AFO consists of sensor, controller, and actuator. The controller used in the conventional AFO to control the actuator does not use the property of synchronization of the feet. This chapter deals with development of a fuzzy-based intelligent control unit for an AFO using property of symmetry in the foot movements. The control system developed in LabVIEW provides real-time control of the defective foot by continuously monitoring the gait patterns. The input signals for the control system are generated by the sensor system having gyroscope. DC motor is used as an actuator. The data acquisition for Gait Analysis is done using National Instrument's data acquisition system DAQ6221 interfaced with a gyro-sensor.
Knowledge Representation Using Fuzzy XML Rules in Web-Based Expert System for Medical Diagnosis
Authors: Sajja Priti Srinivas
Published: July 2017

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.
Bio-Inspired Computing through Artificial Neural Network
Authors: Dash Nilamadhab , Priyadarshini Rojalina , Mishra Brojo Kishore , Misra Rachita
Published: July 2017

Developing suitable mathematical or algorithmic model to solve real life complex problems is one of the major challenges faced by the researchers especially those involved in the computer science field. To a large extent Computational intelligence has been found to be effective in designing such models. Bio inspired computing is the technique which makes the machines intelligent by adapting the behavior and methods exhibited by the human beings and other living organisms while forming intelligent systems. These intelligent models include the intelligent techniques such as Artificial Neural Network (ANN), evolutionary computation, swarm intelligence, fuzzy system, artificial immune system accompanied by fuzzy logic, expert system, deductive reasoning. All these together form the area of Bio inspired computing. The chapter deals with various bio inspired technique, giving emphasis on issues, development, advances and practical implementations of ANN.
Trust Calculation Using Fuzzy Logic in Cloud Computing
Authors: Chahal Rajanpreet Kaur , Singh Sarbjeet
Published: July 2017

Cloud Computing is the latest rage in the world of technology. It has vast potential that can be tapped to the advantage of mankind. But there are some challenges which need to be resolved in order to fully utilise its potential. One of these challenges is trust evaluation. Since services are provided by service providers to clients, there has to be some notion of trust between them. This chapter first provides the basic introduction to cloud computing and fuzzy logic. On the basis of extensive literature survey, this chapter discusses trust and its need, in addition to use of fuzzy logic for the purpose of trust calculation in distributed environments and cloud computing till now. Trust calculation using fuzzy logic has been explained through the use of various models. At the end, the difficulties and applications of using fuzzy logic for trust evaluation are discussed along with research directions for future.
Fuzzy Decision Support System for Coronary Artery Disease Diagnosis Based on Rough Set Theory
Authors: Setiawan Noor Akhmad
Published: July 2017

The objective of this research is to develop an evidence based fuzzy decision support system for the diagnosis of coronary artery disease. The development of decision support system is implemented based on three processing stages: rule generation, rule selection and rule fuzzification. Rough Set Theory (RST) is used to generate the classification rules from training data set. The training data are obtained from University California Irvine (UCI) data repository. Rule selection is conducted by transforming the rules into a decision table based on unseen data set. Furthermore, RST attributes reduction is proposed and applied to select the most important rules. The selected rules are transformed into fuzzy rules based on discretization cuts of numerical input attributes and simple triangular and trapezoidal membership functions. Fuzzy rules weighing is also proposed and applied based on rules support on the training data. The system is validated using UCI heart disease data sets collected from the U.S., Switzerland and Hungary and data set from Ipoh Specialist Hospital Malaysia. The system is verified by three cardiologists. The results show that the system is able to give the approximate possibility of coronary artery blocking.
Artificial Intelligent Approaches for Prediction of Longitudinal Wave Velocity in Rocks
Authors: Verma A. K. , Singh T. N. , Maheshwar Sachin
Published: July 2017

Intelligent techniques are quickly gaining importance in the field of geophysics, mining and geology. In this chapter the significance of intelligent techniques like ANN and ANFIS for prediction of longitudinal wave velocity and its advantages over other conventional methods of computing have been discussed. Longitudinal wave measurement is an indicator of peak particle velocity during blasting in a mine and it is a significant factor to be predicted to minimize the damage caused by ground vibrations. Wave velocity measurements have wide applications in the different fields of geophysics, mining and geology. In this chapter, ANN and ANFIS models are designed to predict the longitudinal wave velocity of different rocks and correlation have been developed with fracture properties. The fracture roughness coefficient and physico-mechanical properties are taken as input parameters and longitudinal wave velocity as output parameters. The mean absolute percentage error for the Longitudinal wave velocity predicted by Adaptive Neuro Fuzzy Inference System has been found to be the least.
An Adaptive Path Planning Based on Improved Fuzzy Neural Network for Multi-Robot Systems
Authors: Shi Zhiguo , Zhang Huan , Zhou Jingyun , Wei Junming
Published: July 2017

The fuzzy neural network (FNN) is the combination of fuzzy theory with neural network, which has advantages of validity and adaptability in robot path planning. However, the path planning based on the FNN is not optimal because of the limitations of the subjective experience and motion mutation and the dead-zone. In this paper, FNN is improved by using A* graph search algorithm to guarantee an optimal path, providing the rationality and the feasibility, in which the grid map is divided into two stages, including the A* algorithm in the first stage and FNN in the second stage. In addition, a neural network based on adaptive control strategy is introduced to compensate the sensor failure and ensures the stability, which is caused by the loss of data and information uncertainty. The simulation results show that the approach is with effective performance in the robot path planning.
Information Systems on Hesitant Fuzzy Sets
Authors: D. Deepak , John Sunil Jacob
Published: July 2017

Knowledge extraction from information systems is one of the most significant problems in artificial intelligence. This paper attempts to study information systems in the hesitant fuzzy domain. It studies information systems which has a set of possible membership values. Illustration of a case is provided where the hesitant membership values are arrived at from attribute values whose membership values are a family of sets. The membership value here would turn out to be a subset of the power set of membership values from the usual information system. Although it does not mean that it is arrived at from usual information systems. Reduct, core, relative reduct, relative core and the corresponding indiscernibility matrices are also studied. Apart from these, paper also discusses the homomorphisms between hesitant information systems. For two homomorphic information systems the reduct and core of one information system are the corresponding images of the reduct and core of the other information system under this homomorphism.
Contrasting Correlation Coefficient with Distance Measure in Interval Valued Intuitionistic Trapezoidal Fuzzy MAGDM Problems
Authors: Robinson John P.
Published: July 2017

In this paper, Multiple Attribute Group Decision Making (MAGDM) problems in which the data is of the form of Interval Valued Intuitionistic Trapezoidal Fuzzy Numbers (IVITzFNs) is presented. Some operational laws of IVITzFNs are introduced. Then some new aggregation operators including interval valued Intuitionistic Trapezoidal Fuzzy Weighted Averaging (IVITzFWA) operator, interval valued Intuitionistic Trapezoidal Fuzzy Ordered Weighted Averaging (IVITzFOWA) operator and Interval Intuitionistic Trapezoidal Fuzzy Hybrid Averaging (IVITzFHA) operator, are proposed and some desirable properties of these operators are studied, such as Commutativity, Idempotency and Monotonicity. A new distance function and correlation coefficient are proposed for IVITzFNs which will be utilized for ranking the alternatives in MAGDM problems. Finally, numerical illustrations are given to verify the developed approach and to demonstrate its practicality and effectiveness.
Modeling Conflict Dynamics
Authors: Usenik Janez , Turnsek Tit
Published: July 2017

This chapter touches the question of how to model conflict. The discussion is limited to inter- and intra- organizational conflicts. The focus is on the behavior of the conflict in time. A working definition of conflict, named starting theory, is given. The presented models are constructed by means of system dynamics tools. A short explanation of system dynamics tools is given. Moreover, fuzzy logic and fuzzy system are introduced. Fuzzy system models human reasoning and decision making, and is integrated in the model of isolated conflict. Three models are presented, namely: the qualitative model, the model of isolated conflict, and, finally, the generic model of isolated conflict with fuzzy system. At the end, the results of a few simulation runs illustrate the use of the model.
Adjust Fuzzy Model Parameters for Head Election in Wireless Sensor Network Protocols
Authors: Afifi Walaa Abd el Aal , Hefny Hesham Ahmed
Published: July 2017

The clustering routing protocols attract many research papers that result from their well topology control, less demand resources, and less energy dissipation. The cluster routing protocols consist of single hop communication and multi hop communication. Single hop is applied between sensor node and its related cluster head. Multi hop is applied between cluster heads to base station. The previous two communication modes depend on the cluster head election. Appropriate cluster-head election can drastically reduce the energy consumption and enhance the lifetime of the network. The fuzzy models are used frequently for cluster head election. The fuzzy models can be built either expert's knowledge or numerical data. The authors propose fuzzy model using adaptive Takagi-Sugeno for wireless sensor network protocol (FATSN). The FATSN protocol is implemented by modified merging algorithm of fuzzy clustering with expected value (MCFEV). The FATSN protocol compares with the famous cluster routing protocol LEACH, EEUC, CHEF, and FCM protocols. The results show that FATSN protocol is efficiency
MAGDM-Miner
Authors: Robinson John P. , Amirtharaj Henry E.C.
Published: July 2017

In this article, the authors propose a new framework called the MAGDM-Miner, for mining correlation rules from trapezoidal intuitionistic fuzzy data efficiently. In the MAGDM-Miner, the raw data from a Multiple Attribute Group Decision Making (MAGDM) problem with trapezoidal intuitionistic fuzzy data are first pre-processed using some arithmetic aggregation operators. The aggregated data in turn are processed for efficient data selection through fuzzy correlation rule mining where the unwanted or less important decision variables are pruned from the decision making system. Using this MAGDM-Miner, a decision-maker can overcome the drawbacks in the conventional methods of Decision Support Systems (DSS) especially when dealing with large data-set. The algorithm is also presented, in which the technique of Fuzzy Correlation Rule Mining (FCRM) is fused into the MAGDM problem, in order to enhance the efficiency and accuracy in decision making environment. A numerical illustration is presented to show the effectiveness and accuracy of the newly developed MAGDM-Miner algorithm.
Finite Element Method and Analytical Studies on Fiber-Metal Laminates under Multiaxial Loadings
Authors: Kvam David J. , Duan Yi Yu , Donnelly Erica , Restrepo Alicia
Published: July 2017

Fiber-metal laminates (FMLs) are composites materials that are commonly used in areas such as aircraft industry. They are composed of ductile metal layers with high strength fiber reinforced polymer layers. So far, however, only uniaxial tests have been used to characterize the quasistatic mechanical properties, which cannot reflect the real loading situation of the FML applications. In this work biaxial tensile behavior of FMLs with glass and Kevlar fibers based on aluminum alloy is studied with finite element method simulation. The simulation is run to find the stress-strain relationship for FMLs at the off-axis angles of 0˚ and 45˚ for glass and Kevlar fibers. The “composites layups” are constructed for the 3D FML part. Two different elements C3D8R (8-node linear) and C3D20R (20-node quadratic) are used to carry out the simulation. The results show that C3D20R shows major advantages. Analytical solutions based on the classical laminate theory are obtained to compare with the finite element method (FEM) solutions. The results show good consistency.
Study and Analysis of Mechanical Behavior between Rigid and Dynamic Fixation Systems Analyzed by the Finite Element Method
Authors: Zahaf Samir , Kebdani Said
Published: July 2017

Orthopedic fixation devices are widely used in treatment of spinal diseases. It is expected that application of dynamic stabilization confers valuable movement possibility besides its main role of load bearing. Comparative investigation between pedicle screw model rigid fixation and (B Dyne, Elaspine, Bioflex, Coflexe rivet) models dynamic fixation systems may elucidate the efficacy of each design. The goal of the present study is to evaluate the efficacy of five fixation systems mounted on L4-L5 motion segment. In this numerical study, a 3D precious model of L4, L5 and their intervertebral disc has been employed based on CT images. five fixation devices have been also implanted internally to the motion segment. Finite element method was used to evaluate stress distribution in the disc and determine the overall displacement of the segment as a measure of movement possibility. The results show that The Coflex rivet implantation can provide stability in all motions and reduce disc annulus stress at the surgical segment (L4-L5), on the other hand, Maximum stress in the disc has been observed in dynamic systems but within the safe range. The greater movement of the motion segment has been also appeared in dynamic fixations. Existence of the fixation systems reduced the stress on the intervertebral disc which might be exerted in intact cases. Use of the fixation devices can considerably reduce the load on the discs and prepare conditions for healing of the injured ones. Furthermore, dynamic modes of fixation confer possibility of movement to the motion segments in order to facilitate the spinal activities.
Adaptive Epileptic Seizure Prediction Based on EEG Synchronization
Authors: Ibrahim Sutrisno , Majzoub Sohaib
Published: July 2017

Epilepsy is type of neurological disorder characterized by recurrent seizures that may cause injury to self and others. The ability to predict seizure before its occurrence, so that counter measures are considered, would improve the quality of life of epileptic patients. This research work proposes an adaptive seizure prediction approach based on electroencephalography (EEG) signals analysis. We use cross-correlation to estimate synchronization between EEG channels. Abnormal synchronization between brain regions may reveal brain condition and functionality. Two EEG synchronization baselines, normal and pre-seizure, are used to continuously monitor sliding windows of EEG recording to predict the upcoming seizure. The two baselines are continuously updated using distance-based method based on the most recent prediction outcome. Up to 570 hours continuous EEG recording taken from CHB-MIT dataset is used for validating the proposed method. An overall of 84% sensitivity (46 out of 55 seizures are correctly predicted) and 63% specificity are achieved with one hour prediction horizon. The proposed method is suitable to be implemented in mobile or embedded device which has limited processing resources due to its simplicity.
Annealing Temperature Dependence of Optical Properties of Sol-Gel ZnO Thin Films with Different Sol Aging Time
Authors: Li Ji Tao , Yang Ding Yu , Zhu Xing Hua
Published: July 2017

ZnO thin films on glass substrates have been successfully fabricated by sol-gel method for various aging time and annealing temperature. X-ray diffraction (XRD) patterns showed the crystallites at (100), (002) and (101) plane of hexagonal wurtzite structure. Atomic force microscope (AFM) images were used to investigate the surface morphology. The transmittance, energy gap, Urbach energy and photoluminescence (PL) of samples were investigated to explore the effects of annealing temperature on optical properties of ZnO thin films under different sol aging time. The transmittance spectra of thin films aged for 24 hours and 48 hours revealed the enhanced transmittance in visible region as rising annealing temperature, also, the optical band gap of the samples increased and Urbach energy decreased. The photoluminescence (PL) spectra of samples aged for 24 hours and 48 hours were studied and found the increased ultraviolet emission at ~387 nm, and various decreased visible emissions with rising annealing temperature. Nevertheless, the excessive sol aging time for 72 hours deteriorated the optical characteristics of thin films, resulting in that transmittance, energy gap and ultraviolet emission declined, and visible emissions increased with rising annealing temperature. The optical performances of the ZnO films aged for different time have no the same dependence of annealing temperature.
Cutting Edge: CD3 ITAM Diversity Is Required for Optimal TCR Signaling and Thymocyte Development
Authors: Bettini Matthew L. , Chou Po-Chein , Guy Clifford S. , Lee Thomas , Vignali Kate M. , Vignali Dario A. A.
Published: July 2017

For the αβ or γδTCR chains to integrate extracellular stimuli into the appropriate intracellular cellular response, they must use the 10 ITAMs found within the CD3 subunits (CD3γε, CD3δε, and ζζ) of the TCR signaling complex. However, it remains unclear whether each specific ITAM sequence of the individual subunit (γεδζ) is required for thymocyte development or whether any particular CD3 ITAM motif is sufficient. In this article, we show that mice utilizing a single ITAM sequence (γ, ε, δ, ζa, ζb, or ζc) at each of the 10 ITAM locations exhibit a substantial reduction in thymic cellularity and limited CD4−CD8− (double-negative) to CD4+CD8+ (double-positive) maturation because of low TCR expression and signaling. Together, the data suggest that ITAM sequence diversity is required for optimal TCR signal transduction and subsequent T cell maturation.
Deconstructing the Lectin Pathway in the Pathogenesis of Experimental Inflammatory Arthritis: Essential Role of the Lectin Ficolin B and Mannose-Binding Protein–Associated Serine Protease 2
Authors: Banda Nirmal K. , Acharya Sumitra , Scheinman Robert I. , Mehta Gaurav , Takahashi Minoru , Endo Yuichi , Zhou Wuding , Farrar Conrad A. , Sacks Steven H. , Fujita Teizo , Sekine Hideharu , Holers V. Michael
Published: July 2017

Complement plays an important role in the pathogenesis of rheumatoid arthritis. Although the alternative pathway (AP) is known to play a key pathogenic role in models of rheumatoid arthritis, the importance of the lectin pathway (LP) pattern recognition molecules such as ficolin (FCN) A, FCN B, and collectin (CL)-11, as well as the activating enzyme mannose-binding lectin–associated serine protease-2 (MASP-2), are less well understood. We show in this article that FCN A−/− and CL-11−/− mice are fully susceptible to collagen Ab–induced arthritis (CAIA). In contrast, FCN B−/− and MASP-2−/−/sMAp−/− mice are substantially protected, with clinical disease activity decreased significantly (p < 0.05) by 47 and 70%, respectively. Histopathology scores, C3, factor D, FCN B deposition, and infiltration of synovial macrophages and neutrophils were similarly decreased in FCN B−/− and MASP-2−/−/sMAp−/− mice. Our data support that FCN B plays an important role in the development of CAIA, likely through ligand recognition in the joint and MASP activation, and that MASP-2 also contributes to the development of CAIA, likely in a C4-independent manner. Decreased AP activity in the sera from FCN B−/− and MASP-2−/−/sMAp−/− mice with arthritis on adherent anti-collagen Abs also support the hypothesis that pathogenic Abs, as well as additional inflammation-related ligands, are recognized by the LP and operate in vivo to activate complement. Finally, we also speculate that the residual disease seen in our studies is driven by the AP and/or the C2/C4 bypass pathway via the direct cleavage of C3 through an LP-dependent mechanism.
Zebrafish B Cell Development without a Pre–B Cell Stage, Revealed by CD79 Fluorescence Reporter Transgenes
Authors: Liu Xingjun , Li Yue-Sheng , Shinton Susan A. , Rhodes Jennifer , Tang Lingjuan , Feng Hui , Jette Cicely A. , Look A. Thomas , Hayakawa Kyoko , Hardy Richard R.
Published: July 2017

CD79a and CD79b proteins associate with Ig receptors as integral signaling components of the B cell Ag receptor complex. To study B cell development in zebrafish, we isolated orthologs of these genes and performed in situ hybridization, finding that their expression colocalized with IgH-μ in the kidney, which is the site of B cell development. CD79 transgenic lines were made by linking the promoter and upstream regulatory segments of CD79a and CD79b to enhanced GFP to identify B cells, as demonstrated by PCR analysis of IgH-μ expression in sorted cells. We crossed these CD79-GFP lines to a recombination activating gene (Rag)2:mCherry transgenic line to identify B cell development stages in kidney marrow. Initiation of CD79:GFP expression in Rag2:mCherry+ cells and the timing of Ig H and L chain expression revealed simultaneous expression of both IgH-μ– and IgL-κ–chains, without progressing through the stage of IgH-μ–chain alone. Rag2:mCherry+ cells without CD79:GFP showed the highest Rag1 and Rag2 mRNAs compared with CD79a and CD79b:GFP+ B cells, which showed strongly reduced Rag mRNAs. Thus, B cell development in zebrafish does not go through a Raghi CD79+IgH-μ+ pre–B cell stage, different from mammals. After the generation of CD79:GFP+ B cells, decreased CD79 expression occurred upon differentiation to Ig secretion, as detected by alteration from membrane to secreted IgH-μ exon usage, similar to in mammals. This confirmed a conserved role for CD79 in B cell development and differentiation, without the requirement of a pre–B cell stage in zebrafish.
Evidence-Based Guidelines for Screening and Management of Strongyloidiasis in Non-Endemic Countries
Authors: Requena-Méndez Ana , Buonfrate Dora , Gomez-Junyent Joan , Zammarchi Lorenzo , Bisoffi Zeno , Muñoz José
Published: July 2017

Strongyloidiasis is an intestinal parasitic infection becoming increasingly important outside endemic areas, not only because of the high prevalence found in migrant populations, but also because immunosuppressed patients may suffer a potentially fatal disseminated disease. The aim of these guidelines is to provide evidence-based guidance for screening and treatment of strongyloidiasis in non-endemic areas. A panel of experts focused on three main clinical questions (who should be screened and how, how to treat), and reviewed pertinent literature available in international databases of medical literature and in documents released by relevant organizations/societies. A consensus of the experts’ opinion was sought when specific issues were not covered by evidence. In particular, six systematic reviews were retrieved and constituted the main support for this work. The evidence and consensus gathered led to recommendations addressing various aspects of the main questions. Grading of evidence and strength of recommendation were attributed to assess the quality of supporting evidence. The screening of individuals at risk of the infection should be performed before they develop any clinical complication. Moreover, in immunosuppressed patients, the screening should be mandatory. The screening is based on a simple and widely accessible technology and there is now a universally accepted treatment with a high efficacy rate. Therefore, the screening could be implemented as part of a screening program for migrants although further cost-effectiveness studies are required to better evaluate this strategy from a public health point of view.
The Subjective-Objective Disjunction in Psychometrically-Defined Schizotypy: What it is and Why it is Important?
Authors: Cohen Alex S. , Mitchell Kyle R. , Beck Melissa R. , Hicks Jason L.
Published: July 2017

An interesting set of findings has emerged from the literature regarding schizotypy. Individuals with psychometric schizotypy self-report pathology in certain neuropsychological, affective experiential, expressive and olfactory abilities and subjective quality of life at levels between one and two standard deviations more severe than their non-schizotypal peers; a level often similar to that seen in chronic schizophrenia. Objectively however, individuals with psychometric schizotypy do not show concomitant impairments in these domains. This “subjective-objective” disjunction is remarkable in that samples are largely drawn from college settings; thus likely reflecting the healthiest individuals within the schizophrenia-spectrum. We propose that this disjunction can be conceptualized as a “cognitive bias”, and that it reflects a dysfunction in the systems underlying reasoning and self-evaluation. In this article, we lay out evidence underlying the subjective-objective disjunction and discuss potential methodological and psychological issues that may explain this phenomenon.
Eye Movements Enhance Recollection of Re-Imagined Negative Words: A Link between EMDR and Sire?
Authors: Phaf R. Hans
Published: July 2017

Do eye movements primarily affect emotion, as in Eye-Movement Desensitization and Reprocessing therapy (EMDR), or memory retrieval, as in Saccade-Induced Retrieval Enhancement (SIRE)? Despite growing confidence in the effectiveness of the former, the latter memory effect is sometimes not replicated. I argue here that the memory enhancement due to eye movements can be obtained, when conditions are made more similar to EMDR: a) participants are explicitly instructed to retrieve and re-imagine the memories during the eye movements, and b) emotionally negative material is involved. An exploratory memory experiment is presented that compares horizontal eye-movement and eye-fixation conditions. Mixed lists of positive, neutral, and negative words were studied and explicitly recollected during the eye manipulation. Results showed evidence for enhanced recollection due to eye movements, with a large effect size specifically for negative words. The crosstalk between these different domains may not only be helpful for gaining a better understanding of SIRE but also for improving the effectiveness of EMDR.