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Über dieses Buch

This volume presents the selected papers of the First International Conference on Fundamental Research in Electrical Engineering, held at Khwarazmi University, Tehran, Iran in July, 2017. The selected papers cover the whole spectrum of the main four fields of Electrical Engineering (Electronic, Telecommunications, Control, and Power Engineering).

Inhaltsverzeichnis

Frontmatter

Biomedical Engineering

Frontmatter

Bioelectrical Signals: A Novel Approach Towards Human Authentication

Human authentication based on electrical bio-signals, or bioelectrical signals, is a rapidly growing research area due to increasing demand for establishing the identity of a person, with high confidence, in a number of applications in our vastly interconnected society. Studies show that bioelectrical signals can be not only employed for diagnostic purposes in medicine, but also used in human authentication since they have unique features among individuals. This article reviews examples of up-to-date researches that have applied bioelectrical signals like Electrocardiogram (ECG), Electroencephalogram (EEG) and Electrooculogram (EOG) in human authentication. Utilizing bioelectrical signals provides a novel approach to user authentication that contains all the crucial attributes of previous traditional authentication. The most significant reasons for deployment of electrical bio-signals in user authentication include their measurability, uniqueness, universality and resistance to spoofing, while other conventional biometrics like face shape, hand shape, fingerprint and voice can be artificially generated.

Hamed Aghili

Recognition of Speech Isolated Words Based on Pyramid Phonetic Bag of Words Model Display and Kernel-Based Support Vector Machine Classifier Model

This study aimed to improve the classification of individual (isolated) words, and specifically, the numbers from one to twenty. In this study, a strong model was suggested to gain a unified view of voice. It is based on the idea of phonetic bag for voice that has been developed into a pyramid state. The pyramid idea can model temporal relationships. One of the problems of Support Vector Machine to classify words is its inability to model temporal relationships unlike hidden Markov models. Using the BOW-based pyramid idea in the extraction of the display containing temporal information of voice, the SVM can be given the capability of considering the time relationships of speech frames. One of the main advantages of Support Vector Machine model is its fewer parameters than the hidden Markov model. As the experiments’ results have shown, it has much higher accuracy than the hidden Markov model in applications such as the recognition of single words, where the data set volume is limited. Using the pyramid BOW idea, the accuracy of SVM-based method can be increased as 20% compared to previous methods.

Sodabeh Salehi Rekavandi, Hamidreza Ghaffary, Maryam Davodpour

A Novel Improved Method of RMSHE-Based Technique for Mammography Images Enhancement

Contrast improvement is one of the most important steps in medical image enhancement procedures such as mammography. In this paper, a combination of best features related to direct and indirect histogram equalization techniques is proposed in a two dimensional workspace. Using different advantages of these methods, while the proposed algorithm is able to improve the contrast and brightness of mammography images, it could decrease different effects of noises, too. On the other hand, in order to reduce undesirable effects of traditional histogram equalization techniques, an improvement of recursive mean-separate histogram equalization using a fusion of contrast-limited adaptive histogram equalization is proposed, too. Evaluation results using four effective measurement techniques e.g. peak signal-to-noise ratio, mean squared error, absolute mean brightness error and effective measure of enhancement, shows that the suggested method has significant results in contrast enhancement.

Younes Mousania, Salman Karimi

Contrast Improvement of Ultrasound Images of Focal Liver Lesions Using a New Histogram Equalization

Contrast improvement is an important issue in the processing of medical images. Due to the difficulty of detecting liver lesions in conventional ultrasound imaging and the low contrast of these images, we tried to provide an indirect optimization technique on the ultrasound images of Focal Liver Lesions database in the space of two-dimensional histogram to improve the quality and the contrast of these images. To prevent undesirable effects due to the adjustment of the histogram images, two techniques are used: CLAHE and RMSHE. By using four effective measurement techniques metrics of EME, PSNR, MSE and AMBE, shows that the proposed method has significant consequences. Furthermore; results of the study revealed that improved outcomes are obtained when the proposed technique is utilized on other standard ultrasound and medical images like mammography.

Younes Mousania, Salman Karimi

An Unequal Clustering-Based Topology Control Algorithm in Wireless Sensor Networks Using Learning Automata

Clustering is an efficient method in saving nodes’ consumption of energy within wireless sensor networks. In the majority of clustering methods, the sizes of clusters are equal to each other. This feature will lead to a rise in consumption of energy in clusters which are close to the sink node. For this purpose, a new method has been presented based on the learning automata for the unequal clustering of nodes in wireless sensor network. In this method, upon reduction of the distance between the clusters and the sink hole, the size of clusters also shrinks. This feature in addition to optimization of consumption of energy in the network, will also be efficient in a rise in the number of packages delivered toward the sink hole. The effectiveness of the proposed method has been assessed based on its implementation in a simulated environment, while the corresponding results have been compared with previous approaches. The results show that the proposed method acts better than previous methods in reduction of consumption of energy and a rise in the number of delivered packages.

Elahe Nouri

Using an Active Learning Semi-supervision Algorithm for Classifying of ECG Signals and Diagnosing Heart Diseases

Diagnosis of various heart defects and arrhythmias based on the ECG signals recorded from the patient has greatly appealed to the medical community. Biological signal processing performed by experts in the field has involved many challenges to be able to present a precise model of the recorded signals and to analyze and diagnose defects and arrhythmias based on the extracted features and to classify them into the normal and abnormal classes. It is an issue that has appealed to researcher for years to make the process of precisely diagnosing heart diseases intelligent. An efficient classification method with active and semi-supervised learning for classification of the ECG signal based on the mRMR feature selection method has been used in this research. The extracted features include the temporal features, AR, and wavelet coefficients. Finally, the indicators of validity, precision, and sensitivity for this set of selected features have also been evaluated through application of the proposed classifier. The results of simulations in the Matlab software environment suggest that the proposed system has 98.64% validity for diagnosis of 6 class types of ECG. Comparison between the obtained precision and that of the previous research demonstrates the proper performance of the proposed method.

Javad Kebriaee, Hadi Chahkandi Nejad, Sadegh Seynali

Automatic Clustering Using Metaheuristic Algorithms for Content Based Image Retrieval

Development of internet networks and mobile phone tools with image capturing capabilities and network connectivity within the recent years have led to defining new services and applications, using such tools. In this article, automatic clustering method using evolutionary and metaheuristic algorithms used in order to identify and categorize various kinds of digital images. For this purpose, a database of images prepared, and then k-means clustering method using evolutionary algorithms and optimization applied on these images. The results of retrieval indicate that automatic clustering using particle swarm optimization (PSO) algorithm has higher average retrieval accuracy in comparison with other methods.

Javad Azarakhsh, Zobeir Raisi

A Robust Blind Audio Watermarking Scheme Based on DCT-DWT-SVD

In this paper, Watermarking hybrid sound algorithm is presented to protect the copyright of audio files, which, in addition to the clarity and consistency of the audio signal, has increased the strength and strength. To this end, a hybrid algorithm for voice signal cryptography is presented in the three domain parser transforms, discrete cosine transform, and discrete wavelet transforms. So, after discrete cosine transformation (DCT) on the host signal, by selecting the sub-band of low frequency, which contains the highest signal energy, two discrete wavelet transform (DWT) with a random wavelet filter on the low-frequency coefficients of conversion A discrete cosine applies, after selecting the approximation coefficients, the resulting one-dimensional matrix is converted to a two-dimensional matrix, and finally the resulting matrix is applied to a single value decomposition (SVD), which results in the formation of a The diameter matrix is that the watermark bits are embedded in the first layer of the dipole matrix, so that the two bits with value S (1,1), S (2,2) of the matrix The diameter S is chosen, first compares the first and second intersections of the diameter matrix S, which is multiplied by the coefficient θ multiplied by the obtained two bits and is used as a fixed value in the embedding formula and The title of the new watermark is embedded in S (1,1). The results of the implementation show that the proposed algorithm succeeded not only in achieving transparency and resistance to general audio processing attacks, such as Gaussian white noise, quantization rates, decreasing and increasing the rate of sampling, compression and low pass filtering. But has achieved better results than other similar algorithms.

Azadeh Rezaei, Mehdi Khalili

A New Method to Copy-Move Forgery Detection in Digital Images Using Gabor Filter

Copy-move forgery is one of the types of image manipulation which is widely used due to simplicity and effectiveness. In this method, part of the original image is copied and pasted to the desired location in the same image. The goal of detecting copy-move forgery is to find areas of the image that are identical or very similar. One of the important issues that some of the earlier algorithms suffer from is that the forged area is rotated or resized after attachment. In this research, a new approach is presented to detect copy-move forgery in digital images based on discrete wavelet decomposition along with multiple features extracted by Gabor filter to improve the function of detecting similar areas of the image. Experiments have shown that this algorithm recognizes similar areas with relatively good accuracy and is resistant to rotation and change in the scale of the forged area.

Mostafa Mokhtari Ardakan, Masoud Yerokh, Mostafa Akhavan Saffar

Temporal and Spatial Features for Visual Speech Recognition

Speech recognition from visual data is in important step towards communication when audio is not available. This paper considers several hand crafted features including HOG, MBH, DCT, LBP, MTC, and their combinations for recognizing speech from a sequence of images. Several classifiers including SVM, decision trees, K-nearest neighbor algorithm and the sub-space K-nearest algorithm were tested feature evaluation. Further, the application of PCA for dimensionality reduction was considered in this study. Two sets of tests were carried out in this study: lip pose recognition and recognition of isolated words. For evaluation, the MIRACL-VC1 data set was considered. Self-dependent tests reached an accuracy of over 95% while in the self-independent tests, the maximum accuracy of recognition was about 52%.

Ali Jafari Sheshpoli, Ali Nadian-Ghomsheh

The Application of Wavelet Transform in Diagnosing and Grading of Varicocele in Thermal Images

Varicocele is the abnormal dilation and tortuosity of venous plexus (venous) above the testicles. The pattern of abnormal heat distribution in the scrotum can be diagnosed by the help of thermal imaging. Thermal Imaging is a distant, non-contact, and non-invasive method. Thermal imaging was conducted on 50 patients who referred to the hospital 501 (AJA). It was implemented by non-contact infrared camera VISIR 640. Capabilities of thermography method was then evaluated. In order to evaluate and diagnose the varicocele, thermal asymmetry and Haar wavelet techniques were used based on thermal imaging. In two methods, with the help of heat distribution, varicocele can be detected using a thermal camera; one of these two methods includes thermal asymmetry and increased temperature in venous plexus (pampiniform) with no thermal increase in the testicle of the same side (It is grade II of varicocele with a temperature difference of about 1 °C), and the other includes the increased temperature of venous plexus (pampiniform) with increased temperature of the testicle in the same side(It is grade III of varicocele with a temperature difference of about 1.5 °C). The accuracy of the recognition of thermography is 76% in different grades of varicocele. According to the results of the study, thermography is a useful method for the initial screening process. In addition, it can be applied as a supplement to other diagnostic techniques due to lack of exposure, low cost and its exact diagnostic capacity in varicocele.

Hossein Ghayoumi Zadeh, Hamidreza Jamshidi, Farshad Namdari, Bijan Rezakhaniha

A Review of Feature Selection Methods with the Applications in Pattern Recognition in the Last Decade

The present study is a review of recently-done research (in the past 10 years) on the feature selection methods and a set of the applications in pattern recognition. The study aimed to introduce the latest research on the feature selection methods and applications. The study findings can be the basis for further and more practical research in this field. Significant advances have been made in the last decade. Particularly in recent years, the evolutionary algorithms related to random methods were widely used to solve feature selection problems.

Najme Ghanbari

A Review of Research Studies on the Recognition of Farsi Alphabetic and Numeric Characters in the Last Decade

The present paper is a review of research on the recognition of Persian alphabetic and numeric characters in the last ten years. The goal is to provide researchers with the latest research findings for further research after discovering the gaps that still exist in this field, i.e. Optical Character Recognition (OCR) in the Farsi language. However, there has been a dramatic improvement in this field in the last decade as it will be discussed. Although the researchers have achieved very good results, there is still a gap due to the lack of commercial and functional software.

Najme Ghanbari

A New Model for Iris Recognition by Using Artificial Neural Networks

Today, with advances in the science of machine vision, wide dimensions have been opened in the field of identity identification (biometric) in people’s lives. With the increase in inspection, surveillance and security centers, biometric systems are more crucial than ever. Iris recognition is one of the main biometric identification approaches in human’s identity recognition which has become a very functional and attractive subject in the research and practical applications. Due to the unique features of the iris, this kind of recognition is highly effective to identify a person. In literature, many researches have been done with regard to locating, image description and iris recognition. In this paper, a solution is provided for extracting features of iris that generated datasets can be analyzed. Given that the neural network uses this data set, iris patterns classification is done. Adaptive learning strategy is used to train the neural network. The simulation results show that the proposed system of identification of individuals can offer 95% accuracy in normal conditions and 88% in noisy conditions.

Mina Mamdouhi, Manouchehr Kazemi, Alireza Amoabedini

Designing a Fuzzy Expert Decision Support System Based on Decreased Rules to Specify Depression

Depression is a psychological disorder, if it doesn’t be diagnosed and cured in time, can effect on quality of humans’ life in wide dimensions. Thus, diagnosis easily and quickly is necessary need of sociality’s generally healthy. The aim of this paper is designing an fuzzy decision support system to implement BDI-II. Questions for BDI-II are grouped into multiple factors. In medical sciences, disorders, and diseases that lack high confidence and complexity in diagnosis, intelligent systems have better confidence capacity in diagnosis. In this investment, the structure is designed in form of two factors and five factors. The results show that designed system with two factors compared to five factors structure with 94.2% diagnostic power has implementations train data of BDI-II. Hence, in future, the psychologist can use this system as a decision support system of decision support in clinical and hospital diagnoses.

Hamed Movaghari, Rouhollah Maghsoudi, Abolfazl Mohammadi

Control Engineering

Frontmatter

Self-tuning PD2-PID Controller Design by Using Fuzzy Logic for Ball and Beam System

Nowadays, the science of aircraft equipment has made remarkable progress. However, due to the heavy costs and sensitivity, study on a laboratory scale for this equipment is impossible. Therefore, equivalent systems are used. The ball and beam is one of the systems which is used to simulate the aviation sciences. This system is composed of one motor, one ball and one beam. The purpose of this system is controlling and balancing the ball position on the beam at a desired value. There are several challenges like sensors noise and servo motor nonlinearities in the controlling this system. To solve these problems, a new control method is presented in this paper. This approach is made from the combination of two different methods consist of PD2-PID and fuzzy logic controller. The main purpose of the presented approach is realizing the best performance of the system and locating the ball position in desired value in the lowest time, steady state error and overshot. The obtained simulation results indicate the proposed method has better performance in controlling the ball and beam system compared to the other techniques like traditional PD2-PID.

Milad Ahmadi, Hamed Khodadadi

Design of Automatic Gain Control (AGC) Circuit for Using in a Laboratory Military Submarine Sonar Systems Based on Native Knowledge

Some of the applications of submarine communication are collecting the oceanography data, marine contaminations control, marine studies, military systems like relations between submarines and ships, and identification of submarine targets and torpedo. The principle of operation in submarine communication is based on sound acoustic emission which is utilized in a military sonar system in this paper. AGC is one of the most important parts of a sonar receiver. In this paper, designation of a circuit (based on a new topology) high quality separate automatic gain control (AGC) in a sonar receiver system is proposed and the results are compared with the previously designed circuits for RF and acoustic systems. The most important use of this circuit is in military industry, submarine communication, and ships.

Davood Jowkar, Mohammad Reza Bahmani, Mohammad Bagher Jowkar, Ali Shourvarzi, Ameneh Jowkar

Control of Robot Manipulators with a Model for Backlash Nonlinearity in Gears

This paper presents a model for backlash nonlinearity in gears based on torque input-output equation. By combining the robot dynamic model with backlash, a stable sliding mode controller is developed and the asymptotic stability of the closed-loop system is shown using Lyapunov method and Barbalat’s Lemma. The proposed method is produced no chattering in the control torques and the tracking performance is desirable. Effectiveness of the controller is verified by comparative studies with numerical simulation. Finally, experimental results are presented to demonstrate the efficiency and capability of the proposed controller in dealing with backlash nonlinearities in gears of a five-bar manipulator.

Soheil Ahangarian Abhari, Farzad Hashemzadeh, Mehdi Baradaran-nia, Hamed Kharrati

Designing an Automatic and Self-adjusting Leg Prosthesis

Throughout the whole human history, loss of limbs has been an important issue, such that extensive research has been conducted in designing and controlling above-knee prostheses, which have a long history of application by humans. Over time, with advances in medical sciences and engineering, this auxiliary tool evolved and has always been improving. Nevertheless, some challenges have remained. Therefore, proper and optimal design of knee mechanism for those who are not able to move can be very useful. In this research, first the human motion will be simulated and then prosthesis will be controlled. Received data from the rehabilitation center will be transferred through PLC to micro-prosthesis section. In the processing section, microcontroller will be calculated the information received and will be applied to the ankle and knee actuators. Using sensors embedded in different parts of the prosthesis, the prosthesis will be detected the actual position of the prosthesis and will be controlled the movement of the prosthesis.

Vahid Noei, Mehrdad Javadi

Electronic Engineering

Frontmatter

Implement Deep SARSA in Grid World with Changing Obstacles and Testing Against New Environment

In this paper, the Deep SARSA method is used to find the path of the robot on 5 × 5 environment with the presence of moving obstacles. This problem is known as Grid world with changing obstacles (GWCO). In GWCO problem, obstacles move on specific paths. Due to a permanent change in the location of obstacles, this can be considered as a dynamic problem. In dynamic problem, the environment is constantly changing. In this paper, we first refer to the applications of Deep learning and Reinforcement learning (RL), then to the details of Grid World and GWCO. Then it is discussed about the Deep SARSA algorithm and the results show that the agent could well find the optimal path and receive the highest reward. After learning the agent, we change the environment and add a new obstacle in the agent’s path. The results show that the agent has been able to quickly propose a new path. Simulation of this paper is done with the Python software and Tensorflow.

Mohammad Hasan Olyaei, Hasan Jalali, Ali Olyaei, Amin Noori

A New 1 GS/s Sampling Rate and 400 μV Resolution with Reliable Power Consumption Dynamic Latched Type Comparator

A new high-speed dynamic latched type comparator with reliable resolution is presented in this paper. The proposed paper presents a 1 GS/s sampling rate in presence of 8 mV input offset, and it can detect the very low voltage differences such as ±200 µV at the output nodes, reliably. The power consumption and delay time of the proposed circuit are 750 µw and 257 ps with the power supply of 1.8 V, respectively. Furthermore, the proposed structure is the suitable candidate for high-speed SAR ADC, as well. Simulation results of the suggested circuit are performed using the BSIM3 model of a 0.18 µm CMOS process with the power supply of 1.8 V at all process corners along with the different temperatures in the region −50 to +50 °C, reliably.

Sina Mahdavi, Maryam Poreh, Shadi Ataei, Mahsa Jafarzadeh, Faeze Noruzpur

Improved Ring-Based Photonic Crystal Raman Amplifier Using Optofluidic Materials

Ring-based photonic crystal (PhC) structure for Raman amplifier is investigating in this article. Then using optofluidic materials in the holes on the sides of the signal path, pump and signal group velocity reducing that cause Raman gain increase. In order to achieve bigger Raman gain, we use two-ring structure. The time evolution and propagation of picosecond signal pulses and dispersion inside the device are analyzed and Raman gain, Raman bandwidth and bit rate are studied in one-ring and two-ring structures. Maxwell equations are solved by finite difference time domain (FDTD) method and considering the optical nonlinear parameters of two photon absorption, free carrier absorption, Kerr effect and self-phase modulation in PhC structure. From a structure with a length of 100 μm, Raman gain of 19.01 dB and bit rate of 0.6493 × 1012 pulse/sec are achieved.

Amire Seyedfaraji

Considering Factors Affecting the Prediction of Time Series by Improving Sine-Cosine Algorithm for Selecting the Best Samples in Neural Network Multiple Training Model

As stock exchange is complex and there is a high volume of information to process, no good prediction results are obtained using a simple system. Therefore, researchers have presented combined model to propose a system with lower sophistication and higher accuracy. System only uses information of one index for predicting in most prediction models but a two-level system of multi-layer perceptron neural network is proposed in this model and several indices are used to prediction and sine-cosine algorithm is also used to select the best samples after neural network training in order to train the neural network better and consequently gain better results. Results show that the proposed model is able to perform with lower prediction error compared with other models.

Hamid Rahimi

Advantages of Using Cloud Computing in Software Architecture

In recent years, various software architectures have emerged. Service oriented architecture and model driven architecture are two examples of this architecture. Service-oriented architecture (SOA) has disadvantages, such as: the need for further development, precise design, and the creation of a service infrastructure. According to Exforsys research, SOA is used in some cases, such as single-user applications that do not have distributed properties, a uniform connection of the asynchronous type is required, but there is no need for interconnection between the components; programs that are short-lived and in A short run is run, programs whose function is more dependent on the GUI. Model-based architecture also has some disadvantages, such as: ignoring some of the aspects and features of the system, including quality requirements, because of the model’s model, the inadequacy of the small software projects and the complexity of the software to The reason for the lack of a comprehensive definition of requirements. On the other hand, cloud computing has many benefits that access is based on the demand and the widespread use of networks and shared resources of these benefits. In this article, we are trying to provide a newer and more advanced architecture with the use of cloud computing and the development of software architecture. In cloud computing, the user designs his own cloud for his cloud and receives cloud services from the cloud without even coding a line or designing his own software at a great cost. Cloud architecture is very effective in designing small and large software, and even the user can add objects as services to the reference cloud. Finally, other benefits of the new architecture are expressed.

Alireza Mohseni, Mehrpooya Ahmadalinejad

Designing and Implementation a Simple Algorithm Considering the Maximum Audio Frequency of Persian Vocabulary in Order to Robot Speech Control Based on Arduino

Based on the definition, speech process is known as the audio signals Conversion process as an input for checking systems by computer algorithms. The importance of this field is for many applications such as aerospace. Automatic translation, providing news texts from lectures, home intelligent automation, Computer games. Serving the blinds and low—power people, collecting and organizing different information resources like books, websites and also facilitate and expedite in educational services. This study has done with the purpose of introducing and testing a simple algorithm for Persian vocabulary and implementation of a robot structure based on the Arduino. The important point of this study is using audio signals in Persian language which has a history less than two decades. Although some attempts such as Nevisa and speech to text conversion software has been made, but based on researcher’s investigation, there was not found a controllable product based on Persian vocabulary. Creating relevant response with the highest audio frequency based on three Persian terms, “right”, “left” and “straight” is the purpose which has considered in this article. In this article, Sound is received by the microphone and through Matlab software by getting and processing maximum received signal frequency, the higher frequency of receiving sound will be determined and transferred to the Arduino board existence on robot through serial communication which leads to a movement reaction based on the definition of this number by a robot. The way of sampling is totally free considering the kind of microphone and distance, and results of this study in the review of three words, “left”, “right” and “straight” is an indicator of the efficiency of the suggested algorithm with the success rate of 73 and 24% failure at the first repetition and with the success rate of 86 and 14% failure at the second repetition.

Ata Jahangir Moshayedi, Abolfazl Moradian Agda, Morteza Arabzadeh

Simulation of Bayard Alpert Ionization Vacuum Gauge with COMSOL

In this paper, the Bayard Alpert ionization vacuum gauge has been simulated using COMSOL. Employing Charged Particle Tracing (CPT) tool in COMSOL, the sensitivity coefficient of the gauge has been calculated from simulation results. Based on the results, the average measured value of sensitivity is 30, which shows compatibility with theoretical value of 28. It must be mentioned that a unique method is used in this article to calculate the sensitivity coefficient and the coefficient diagrams for sensitivity of different vacuum pressures have been obtained through these simulations. This paper also presents a method for obtaining electron velocity and energy and their diagrams.

Sadegh Mohammadzadeh Bazarchi, Ebrahim Abaspour Sani

Room Temperature Acetone Sensing Based on ZnO Nanowire/Graphene Nanocomposite

In this paper we report the preparation of a hybrid material by combination of graphene and ZnO nanowire for acetone sensing applications. The ZnO thin films and ZnO NWs were prepared by sol-gel and hydrothermal methods, respectively. The morphological analyses of the obtained material have been performed by means of scanning electron microscopy. These sensors exhibited an enhanced response to acetone concentration as low as 100 ppm at room temperature. The gas sensing analysis of the hybrid material showed that the structure can be used for fabrication of practical sensors.

Maryam Tabibi, Zahra Rafiee, Mohammad Hossein Sheikhi

Application of Learning Methods for QoS Provisioning of Multimedia Traffic in IEEE802.11e

In recent years, with increasing demands of real-time multimedia service, a lot of attention has been given to quality of service(QoS) support in wireless network. To maintain QoS of multimedia services we need to control packet loss, delay and packet delivery ratio. But it is difficult to guarantee QoS especially when the network is overloaded. The proposed scheduler algorithm called EQQ (Enhanced QoS with Q-Learning)guarantees QoS by using the kind of reinforcement learning with changing suitably service intervals and transmission opportunities. Simulation result show that the EQQ is superior to the older algorithm in parameter of delay and packet loss and packet delivery ratio.

Hajar Ghazanfar, Razieh Taheri, Samad Nejatian

LUT Design with Automated Built-in Self-test Functionality

Nowadays, FPGAs play a significant role in industrial applications. Therefore, ensuring their proper performance is of great importance. In this paper, an automatic Built-in self-test core has been designed in the LUT to test and investigate errors. In order to verify this method, powerful software H-Spice with 45 nm precision in transistor level has been used. The advantages of this method include being automatic, detecting various errors, preserving initial information, and reducing hardware overhead compared to the previous methods.

Hanieh Karam, Hadi Jahanirad

A Framework for Effective Exception Handling in Software Requirements Phase

The exception handling structure allows software developers to reduce software maintenance cost through preventing faults, errors, and failures that may occur after exception arising. Forecasting possible exceptions and presenting powerful exception handling structures are noticeable in decreasing software modification workload and maintenance costs. But most of the developers neglect proper exception handling (EH) in early software development phases which make difficulty in software maintenance, indeed they underestimate EH. Since Focusing on EH only in the last phases of software life cycle is not a good policy, so we propose a framework, including principles, components, and metrics to present EH at the software requirement phase just while system scenarios are written. The proposed framework is a means for early exception discovery and leads to improve in software metrics: reliability, robustness, and maintainability. Applying the components of the framework: exception classification, scenario dependency graph and etc. and measuring proposed metrics in relation with exceptions allows to select proper EH strategies. At the end of the research, we present guidelines for the software tester to test all parts of the software according to the framework as a facility for verifying and correcting EH structures and discovering new possible exceptions.

Hamid Maleki, Ayob Jamshidi, Maryam Mohammadi

HMFA: A Hybrid Mutation-Base Firefly Algorithm for Travelling Salesman Problem

The Travelling Salesman Problem (TSP) is one of the major problems in graph theory and also is NP-Hard Problem. In this work, by improving the firefly algorithm (MFA), we introduced a new method for solving TSP. The result of the proposed method has compared with the other algorithms such as Firefly algorithm, GA and PSO. The Proposed Method out performs of other algorithms.

Mohammad Saraei, Parvaneh Mansouri

IGBT Devices, Thermal Modeling Using FEM

Thermal control and modeling of transistor devices, and especially IGBT transistors, are of interest to many researchers today. Managing thermal devices These transistors can have a significant impact on energy consumption. Considering the importance of the subject, in this research, the FEM method is used to model the thermal devices of IGBT transistors. By simulating the proposed method in this study, it was observed that the proposed method significantly improved the aspects of wasted energy during switching on and off IGBT transistors at different temperatures.

Sonia Hosseinpour, Mahmoud Samiei Moghaddam

Power Engineering

Frontmatter

An Overview on the Probabilistic Safety Assessment (PSA), the Loss of External Power Source Connected to the Nuclear Power Plant

Loss of Offsite Power source connected to the nuclear power plant (LOOP) as the starter event and consequently the probability Station Blackout (SBO) are among accidents that are considered in the Probabilistic Safety Assessment (PSA) and have a significant impact on the melting frequency of the reactor core. Thus, in this paper, the Probabilistic Safety Assessment (PSA), the loss of the external power source in the nuclear power plant is investigated.

Mohsen Ahmadnia, Farshid Kiomarsi

Optimization of the Fuel Consumption for the Vehicle by Increasing the Efficiency of the Electrical Transmission System

The author studies the method of improving the fuel efficiency parameters of automobile power installation with electromechanical transmission. He also carries out the calculating research of the power installation balance during the movement of an automobile according to the NEDC—new European drive cycle. The fuel efficiency of automotive internal combustion engines remain the main indicators of his work. Among these indices, nominal and effective efficiency of the engine at a particular operating mode (often nominal), the corresponding specific fuel consumption, hourly fuel consumption in this mode, the fuel consumption on 100 km of run of the car or operational fuel consumption. Among these indicators is the most informative, operational fuel consumption, since it reflects the fuel efficiency of the power train of a car taking into account the distribution of the modes of operation of the installation in real operation conditions.

Mohsen Ahmadnia

Improve the Reliability and Increased Lifetime of Comb Drive Structure in RF MEMS Switch

This paper presents a novel electrostatic comb-drive RF MEMS switches for the purpose of increasing reliability of micro-electromechanical switches, some new designs analyzed for elimination of adhesion, friction and dielectric charging in non-contact switches, targeted to decrease electrostatic force and applied voltage in the comb driven structure. The reason of this choice is simple manufacturing process (1 or 3 masking) compared to the other MEMS structures, ability to build with more material, linear functioning without static spring fingers, wide applications in addition to switches, such as Resonators, micro-filters, gyroscopes, accelerometers etc.

Faraz Delijani, Azim Fard

Comparing the Efficiency of Proposed Protocol with Leach Protocol, in Terms of Network Lifetime

The wireless sensor network is a collection which consists of large number of sensor nodes, with small dimensions, and limit communication and calculation capabilities, that in it, energy consumption is very important, and neural network of self-organizing plan (SOM) is an uncontrolled neural network, and creates by neuronal neurons, in a regular grid structure with a low dimension. Also, clustering is performed by using the K-means algorithm, which divides the data set into k subsets, and uses from three important factors to select the cluster header as follows: The sensor which has the highest energy level, the nearest sensor, to the basis station, and the center of the cluster gravity. Additionally, for estimating the cost, the above three criteria used to select the cluster header, plus a new benchmark, namely the number of cluster nodes, and sending data in this method, is similar to sending data step, in CDDA protocol, which in there, after selecting the cluster head, through the mentioned methods, each cluster node distributes its data to other cluster nodes.

Javad NikAfshar

Voltage Stability Enhancement Along with Line Congestion Reduction Using UPFC and Wind Farm Allocation and Sizing by Two Different Evolutionary Algorithms

Due to the growing demand of electricity, adding the new power lines for compensating the demand is not possible. Connecting the renewable energy sources, as a favourable alternative source of energy, to the power grid makes some new challenges. In this paper, allocating and sizing the UPFC along with wind farms is covered. The most important purpose of this study is to mitigate the congestion of the power transmission line along with improving the voltage stability margin. For this objective, two important evolutionary algorithms, namely Genetic Algorithm and Particle Swarm Optimization are utilized for finding the optimum size and place of the UPFC and wind farm. An IEEE 24 bus RTS system is simulated. Load data is selected according to IEEE database and mimic the real load situation. The wind data is collected from Manjil, a city in north of Iran, and the output power of the wind farms is simulated. At the end, the optimum place and size for UPFC and wind farm is presented in order to have the minimum congestion for transmission line along with maximum voltage stability margin, system load ability.

S. Ehsan Razavi, Mohsen Ghodsi, Hamed Khodadadi

Analysis of a Multilevel Inverter Topology

Nowadays multilevel inverters have become more popular in electric high power application and the connection of renewable energy such as solar and wind energy to the power grid is an interesting subject. Many topologies and control methods have already been suggested. In this paper, first of all, gives a brief survey of the three prevalently used multilevel inverter systems. Then, in continue there will be examined and compared the most usual multilevel topologies and finally, a short review is presented to verify the control methods for power converters.

Shahrouz Ebrahimpanah, Qihong Chen, Liyan Zhang

Control Scheme of Micro Grid for Intentional Islanding Operation

The cluster of multiple distributed generators (DGs) such as renewable energy sources that supply electrical energy are defined as micro grid. The DG is a voltage source inverter with an output low pass filter supplying the load. The connection of micro grid is in parallel with the main grid. When micro grid is isolated from the remainder of the utility system, it is said to be in intentional islanding mode. In this mode, DG inverter system operates in voltage control mode to provide constant voltage to the local load. During grid connected mode, the micro grid operates in constant current control mode to supply preset power to the main grid. An intentional islanding detection algorithm responsible for switching between current control and voltage control is developed using logical operations. The satisfactory performance of the micro grid with the proposed controllers and algorithms is analyzed by conducting simulation on dynamic model using MATLAB.

Ronak Jahanshahi Bavandpour, Mohammad Masoudi

Quasi-3D Analytical Prediction for Open Circuit Magnetic Field of Axial Flux Permanent-Magnet Machine

Precise simulation of magnetic field in the air gap is necessary to Predict of electromagnetic performance of permanent magnet machines. In this paper an analytical approach is proposed to calculate the magnetic field of slot-less Axial flux permanent magnet machine. Finite element method is the most precise method for magnetic calculation in the air gap although because of its low speed calculation is not appropriate for parametric and optimization studies. In this paper, an efficient analytical method is used to parametric studies on magnetic field in the air gap in case of no-load operation. By applying above mentioned method with high analytical speed, flux density in the middle of air gap is predicted and then induced voltage is calculated. Result of proposed analytical method is compared with 3-D FEM simulations that are reached from Ansys-Electronics software. These results are in the form of Quasi-3D.

Amir Hossein Sharifi, Seyed Mehdi Seyedi, Amin Saeidi Mobarakeh

The Improvement of Voltage Reference Below 1 V with Low Temperature Dependence and Resistant to Variations of Power Supply in CMOS Technology

In this article, the objective is designing a linear voltage reference based on CMOS technology and a structure which is insensitive to variations of temperature and supply power. In such a case, accuracy of circuit output will be optimal under different conditions. Among such sensitivities, one could point to variation of output in relation to temperature, variation due to output performance of the structure and currents, noises and turbulence. First, different voltage references, their structures and advantages and disadvantages will be reviewed individually. Then, output startup method will be explained through bulk transistor and parallel combination of transistors in output for control of output leakage current. This is followed by elaboration of reference building designed based on this method. Consequently, intended structure will designed by taking above-mentioned objectives into account. The circuit simulation and circuit layout will be done through H-Spice Software and Cadence applications respectively. The pre-layout and post-layout results signify improved results and resistance of suggested circuit against substrate noise and noise of power supply. Simulations will be done through 0.18 um CMOS technology.

Amirreza Piri

Micro—Electromechanical Switches Application in Smart Grids for Improving Their Performance

Wireless sensor networks are as series sensor node in very small dimensions with the capability of sensing the surrounding environments, processing the data which is sensed; and, sharing the data between each other in wireless form. Despite numerous capabilities of these nodes, as their energy is supplied by batteries with limited power, they have limited life. In fact, the restrictions in the energy of nodes and the life span of a network poses as one of the important challenges in (using) these networks. The sensor nodes shall have the characteristics of low consumption capability; thus, in designing the nodes hardware, one must try to use designs and parts with low consumption. Furthermore, providing the sleep mode for the whole node or each section separately is highly important. Therefore, we suggest a combo-switch in which, the Micro—Electromechanical switch is used as a MOSFET switch functions as a gate MOSFET driver with the applicability of energy collection systems. The Power Administration Circuits which use combo-switch have the capacity of very low loss and no leakage, autonomous property and high current transmission capability. The measurements show solar energy collection circuits that use combo-switches collect energy without any power supply sources and voltage source, they charge the battery or drive resistive load. The current leakage during energy collection is very low; therefore, power administration which uses the proposed combo switch could serve as an ideal solution for autonomy of wireless sensor nodes in smart grid systems.

Shariati Alireza, Olamaei Javad

Phase Balancing in Distribution Network Using Harmony Search Algorithm and Re-phasing Technique

A large part of the power losses is generated in the distribution network, partly due to the load unbalance in the network. Often, the number of splits is not the same in different phases, and even in the case of equilibrium, due to the difference in the behaviour of the consumers, the unbalance in the network phases are observed and for this reason the distribution network is generally an unbalanced network. The unbalance of the distribution network and the flow of the current in the neutral wire will result in various consequences such as increased power losses, voltage drop, unbalance of three-phase voltages and ultimately consumer dissatisfaction. To reduce this unbalance, various methods and algorithms are presented. In this paper, the re-phasing method using the Harmony Search Algorithm is used to balance the phases in the distribution network. In addition, the proper method of load flow in unbalanced distribution networks is expressed, the selection of the objective function in the re-phasing process is examined and the most appropriate objective function is introduced. In order to demonstrate the efficiency of this method, the simulation for the unbalanced 25-bus network is implemented and compared with the results of other proposed methods. The results show that the proposed method has a very good performance.

Saeid Eftekhari, Mahmoud Oukati Sadegh

Study on Performance of MPPT Methods in WRSG-Based Wind Turbines Utilized in Islanded Micro Grid

Wind energy systems are progressively used in different micro grids. Maximum power point tracking (MPPT) plays a critical role to improve the efficiency of wind energy conversion system (WECS). This Paper provides a comparison between common MPPT methods, including power curve, tip speed ratio (TSR) and optimal torque control (OTC). Then their effects on behavior of an islanded micro grid during and after overload has been investigated. The results indicate that OTC has better behavior than other methods. The studied system is a micro grid with high share of renewable energy resources containing a WECS driven by wound rotor synchronous generator (WRSG), a synchronous diesel unit and some active and reactive loads.

Arash Khoshkalam, Seyed Mohammad Mahdi Moosavi

Evaluation of Harmonic Effect on Capacity and Location of Optimal Capacitors in Distribution Network Using HBB-BC Algorithm

In this paper, the locating and determining the optimal capacity of capacitor banks were studied in the 15-Bus standard distribution network and considering the harmonic effect. The aim was to find the location and capacity of capacitor banks with a loss reduction approach and improve the voltage profile of the network. Constraints such as capacity of capacitor banks, voltage limitation and harmonic distortion limitation were considered in the optimization. Due to the nonlinear nature of the issue of the capacity location in the distribution network, non-linear methods were used. For this purpose, a Hybrid Big Bang-Big Crunch (HBB-BC) algorithm has been used. In simulations, firstly, using the power loss indicator on the slacks, the locations of the banks was determined to estimate the proper capacity of the banks by HBB-BC algorithm. Studies were repeated in two scenarios. In the first scenario, it was assumed that there was no harmonic in the network, and in the second scenario, studies were conducted in the presence of harmonic loads. The results indicated that considering the harmonics in the problem of capacity location will have a great effect on the characteristics of the network and should be considered in studies.

Vahid Asgari

Performance Evaluation of Indicators Effective in Improving Air Cooler Output by Linear Programming

The air conditioning unit requires water and electricity. It has household appliances and facilities, and has many manufacturing benefits, including the simplicity of technology and low cost of production. This unit in addition to cooling the environment, it also provides moisture. The purpose of this paper is to examine different solutions for reengineering the production process in order to identify effective indicators for optimizing production costs, outlet air temperature and water and power consumption efficiency of this device.

Amir Khayeri Dastgerdi

Determining the Parameters of Insulation Model by Using Dielectric Response Function

The identification of electrical insulation of power grid’s equipment is so important due to increasing the reliability of these networks. To do this, internal insulation of equipment should be accessible. Procedures for conducting such experiments are often costly, time-consuming and impossible. Today using modern methods such as polarization and depolarization current technique (PDC), insulation model can be obtained with an easier way. Insulation’s dissipation factor could be calculated using model parameters and plotted at different frequencies. Insulation condition could be observed partially by comparing the dissipation factor curve with its initial curves. Notably, the interpolation of these curves needs enough sciences and skills. In this paper using the curve fitting, Genetic and PSO algorithm the insulation models parameters have been determined by PDC technique. Depolarization current have been calculated by these models parameters and compared with experimental data to modeling validation. Then insulation dissipation factor have been plotted using different models data.

Seyed Amidedin Mousavi, Arsalan Hekmati

Modeling Electrical Arc Furnace (EAF) and Simulating STATCOM Devices for Adjusting Network Power Quality

Electrical arc furnace is considered as great and intricate load in power systems. It is unbalanced, non-linear with time variable properties and consumes active and reactive power with a lot of oscillations. Meanwhile, one basic attempt to neutralize its undesired effects on the network is to model it accompanied by compensating network power quality. This paper studies the effect of STATCOM on EAF performance. In this article, a real model modeling random and chaotic properties of EAFs is used. All parameters of this model are modeled based on a real model of a 28.2 MW EAF. It is a dynamic model of EAF developed in MATLAB/SIMULINK environment. Moreover, a real STATCOM system model is simulated in MATLAB separately as the necessary reactive power compensator for this model. It is perceived from simulation results that the transient performance of EAF voltage is better when the line equipped with STATCOM than when it is without compensating devices.

Behrang Sakhaee, Davood Fanaie Sheilkholeslami, Mohammad Esmailee, Davood Nazeri

Distributed Generation Optimization Strategy Based on Random Determination of Electric Vehicle Power

In this paper, an optimal strategy is presented for the participation of distributed generations in the energy market, considering the effect of uncertainty in the generation of wind turbines, uncertainty in market prices and uncertainty in the demand for electric vehicles. Virtual power plant is a collection of distributed generations that are co-located in order to participate in the market. The uncertainties make planning difficult for a virtual power plant. Four strategies have been proposed for participation in the energy market for the virtual power plant and the optimization problem has been solved with the help of the learning and training algorithm. In this strategy, the problem is solved by the probabilistic estimation method which has both an acceptable profit and needs a little time to perform calculations confirmed by the Monte Carlo method.

Mohammad Ali Tamayol, Hamid Reza Abbasi, Sina Salmanipour

An Improved Harmony Search Algorithm to Solve Dynamic Economic Load Dispatch Problem in Presence of FACTS Devices

One of the important optimization problems in power systems operation is Dynamic Economic Load Dispatch (DELD). Economic load dispatch for a time interval of few hours is done considering the constraints related to maximum rate of change of active power generated by units and other system constraints such as prohibited operating zones and the valve effect. These constraints cause the optimization problem to be non-smooth and non-convex. An improved Harmony Search Algorithm (HSA) is presented in this paper to solve the DELD problem in the presence of Flexible AC Transmission System (FACTS) devices considering the above mentioned constraints. The FACTS devices considered in this paper are Static VAR Compensator (SVC) and Thyristor Controlled Series Compensator (TCSC). The proposed algorithm is evaluated on IEEE 30-Bus Test System. Results show high strength of the proposed method for solving the DELD problem.

Panteha Hashemi, Navid Eghtedarpour

Coordinated Operation of Wind Farm, Pumped-Storage Power Stations, and Combined Heat and Power Considering Uncertainties

One approach to increase the economic efficiency of renewable power generation units is to use combined projects. The supplied energy from these renewable resources is unpredictable because the wind speed and the amount of production in wind farms is not certain. Thus, to increase the reliability, maximize the profits, and supply the load demands of these wind farms and storage systems they must be considered much more than the supply amount. By combining two or more resources, in combined systems, with the capability of predicting production, the controllable production increases; in fact, these resources cover each other`s shortcomings. Here the wind farms, pumped storage, and combined heat and power (CHP) are used in a coordinated way to supply the load demands. Determining independent and coordinated operation strategy of power generation units in the IEEE 30-bus standard System shows that the proposed method is efficient and appropriate.

Hamid Jafari, Ehsan Jafari, Reza Sharifian

Optimization of Exponential Double-Diode Model for Photovoltaic Solar Cells Using GA-PSO Algorithm

In this paper, an equivalent electrical circuit based on the photovoltaic effect (PV) is presented with studies on the simulation of the solar energy system. This model consists of exponential double diodes illustrates how solar cells behave in order to generate electricity. By using the MATLAB software, we performed simulations. Our goal is to calculate the minimum error value for the unknown parameters of the model, which is attained by using root mean square of errors (RMSE). Regarding to the offered model, which we intend to investigate with the suggested GA-PSO algorithm, we obtain the minimum error value (RMSE) after achieving unknown parameters and then we will compare the results with other methods. Therefore, it can be shown that the proposed algorithm with a RMSE value of 2.02 provides an optimal result. According to the computed calculations, the runtime of this algorithm for each calculation is approximately 1 min and 30 s, while the total time of the algorithm will be figured according to the parameter values and the frequency of repetition. With the progress of the calculation process this time comes out to 3 min and 30 s.

Vahdat Nazerian, Sogand Babaei

Telecommunication Engineering

Frontmatter

Hierarchical Routing in Large Wireless Sensor Networks Using a Combination of LPA * and Fuzzy Algorithms

This paper presents a new routing method that increases the network life by combining the fuzzy approach with the A-star algorithm. This algorithm determines the optimal path from source to destination based on maximum battery energy, minimum number of jumps and minimum traffic loads. Due to the limitations of network-aware algorithms for storing the entire grid data in each node’s memory, a new clustering strategy has been used. This clustering method identifies the paths that have more densities of the nodes, and we consider them as spinal cords, and so we call it the backbone of the network, and we select the cluster selection based on its proximity to the spine. For comparison, the LPA algorithm without clustering and Patil (a clustering method based on the weight distribution criterion that includes node-level parameters, distance to node neighbors, node speed, and time spent) and Mounir (a new clustering combination with Using LEACH and MTE protocols). The simulation results show that the shelf life of the network created by the proposed method can be increased by extending the network and increasing the number of node.

Farhad Mousazadeh, Sayyed Majid Mazinani

Improving Security Using Blow Fish Algorithm on Deduplication Cloud Storage

Nowadays, most of the commercial processes have been digitized. Data mostly is of great value, thus any damage or loss of it can be a great disaster for its owner. Large enterprises want to store information in a place with maximum security and low cost. One of the information-storing place is cloud that the world moving toward it. The providers of storage space are trying to improve security in the cloud. To decrypt of data in cloud storage server 64-bits secret-key block cipher called Blowfish algorithm is used. The blowfish algorithm has improved in point of security and performance comparing DES, 3DES, AES. In this paper we assume a deduplication storage server and set the blowfish. At 20 Mb block size the time of blowfish algorithm was (1.7 t) comparing with other algorithms. Also, failure time of blowfish was 60 t that it was less than DES, AES, and 3DES failure time. The results are shown with blowfish algorithm the security of storage data improved. In addition, this algorithm was implemented on the deduplication server. The Winhex output has shown all data in the encrypted format that confirmed the attacker couldn’t access to the original data.

Hamed Aghili

Increased Rate of Packets in Cognitive Radio Wireless ad hoc Network with Considering Link Capacity

Cognitive radio is a new method helps to utilize a very valuable and natural limited resource which is named frequency spectrum. This method can learn it’s surrounding, make a decision and to adapt itself with environmental conditions. One of the most important goals of the cognitive radio is to use the spectrum efficiently. In cognitive radio networks, spectrum bands between primary users (licensed users) and cognitive radio users (secondary or unlicensed users) are shared prioritized. By studying the frequency allocation in these networks, you can understand that almost all of the usable parts of this frequency bands are allocated to the primary users and apparently we are faced with a lack of bandwidth, whereas if we review the used frequency spectrum, we realize that some parts of the spectrum are unused mostly. In this article, a determination of link capacity method for intelligent radio networks is used. The proposed method helps to improve the acceptance capacity of intelligent radio networks by channel determination. The mechanism of proposed channel determination reduces the number of spectrum hand-offs which significantly improves the efficiency and the capacity of the network.

Seyedeh Rezvan Sajadi

Deadlock Detection in Routing of Interconnection Networks Using Blocked Channel Fuzzy Method and Traffic Average in Input and Output Channels

One of the most important issues in parallel processing is routing message from a source node to destination that is done by routing nodes. Deadlock in routing is a damaging factor that arises because of dependence of buffers and routing channel dependency cycles as insoluble one. Many routing algorithms to confronting deadlocks use prevent methods and deadlock avoidance. In these methods sources aren’t used in optimal forms, because in these methods there are some limitations in routing and using sources. But in many algorithms of routing the method of deadlock detection and deadlock recovery is used because of in appropriate use of sources in prevention method. In this paper deadlock detection method is indicated based on traffic average in input and output channels in each node and using fuzzy techniques. And it tries reducing the messages that are introduced wrongly as deadlock involving messages and as much as possible in real deadlock, less messages as involving deadlock been introduced to deadlock recovery.

Maryam Poornajaf

Optimizing of Deadlock Detection Methods in Routing of Multicomputer Networks by Fuzzy Here Techniques

One of the most important issues in parallel processing is routing message from a source node to destination that is done by routing nodes. Deadlock in routing is a damaging phenomenon that arises because of dependency of buffers and routing channels as insoluble dependency cycle. Therefor routing algorithms, which are inevitability different phenomenon, costs are incurred. Many routing algorithms to confronting deadlocks use prevention methods and deadlock avoidance. In these methods sources aren’t used in optimal forms, because in these methods there are some limitations in routing and using sources. But in many algorithms of routing the method of deadlock detection and deadlock recovery is used because of inappropriate use of sources in prevention method. In this paper, a new method to detect deadlocks using fuzzy techniques is proposed that this method is combination of deadlock detection methods. And it tries reducing the messages that are introduced wrongly as deadlock involving messages.

Maryam Poornajaf

Occupancy Overload Control by Q-learning

Session Initiation Protocol (SIP) is considered as a signaling protocol for IP multimedia subsystem (IMS). IMS is introduced by 3rd generation partnership project (3GPP) as signaling foundation in next generation networks (NGN). Despite having the features such as: text based, IP based, independent of the data transmission, support for mobility and end-to-end, the SIP protocol has not suitable mechanism to deal with overload. Therefore, many mechanisms are proposed to control overload in SIP networks. One of their most famous is occupancy CPU (OCC) that is used in many researches. In traditional OCC, the value of parameters is indicated and they are used in subsequent documents. In this paper, optimal parameters value is obtained by Q-learning algorithm. Because modeling a large SIP network is impossible by mathematical relationships and it is a heuristic problem, Q-learning is the best method to compute the parameters. The simulation results demonstrate that the Q-learning output is comparable with traditional OCC.

Mehdi Khazaei

Mobile Smart Systems to Detect Balance Motion in Rehabilitation

In the present paper, a mobile smart system is introduced to assess the individual’s balance in remote rehabilitation. Gyroscope sensor is used in order to analyze the individual’s balance during the remote rehabilitation for five movement activities. The data acquired from the sensor are transmitted via edge layer and SDN controllers to the server database leading to reduction of costs, control of network traffic, and mitigation of delay. The transmitted raw data are analyzed using unsupervised K Means algorithm. The respective algorithm performed the best separation with K values equal to 5 and 8. In fact, accuracy of this method for the 5 movement activities is equal to 0.7 and 0.8 for k = 5 and k = 8, respectively.

Saedeh Abbaspour, Faranak Fotouhi Ghazvini

A Novel Algorithm Developed with Integrated Metrics for Dynamic and Smart Credit Rating of Bank Customers

There are a wide variety of algorithms for bank customer credit rating. Over-allocation or under-allocation of credit arises from weakness in algorithms and lack of software programs involving efficient metrics. This in turn gives rise to legal and criminal issues between banks and customers, poor utilization of customer capabilities, and inappropriate provision of banking services. This study intended to propose qualitative metrics to identify the best customer credit rating model with a focus on financial transitions. Instead of focusing on customer credit, this study employed a concept known as discredit derived from the concepts concerning system quality assurance. The new model was validated through efficiently developed software including metric information and customer data. Over the past four years, the account information about 56,000 customers of an international bank branch was studied to determine the criteria and metrics of their credits using different modeling techniques. The developed software was used to define, analyze, and statistically test multiple financial metrics for the financial information of an international bank branch, while fitting the best metrics in a dynamic model for discredit detection. The best coefficients for combination of financial metric were calculated by weighting based on time, while extracting and validating appropriate equations for the newly proposed model. More specifically, the current year account balance was correlated with discredit, whereas the previous year account balances were not correlated. In addition, the discredit data involved a somewhat greater regression than the numerical discredit data.

Navid Hashemi Taba, Seyed Kamel Mahfoozi Mousavi, Ahdieh Sadat Khatavakhotan

Data Mining Based on Standard Analysis

Data investigation in any type of database or any smart systems intends for achieving sound and practical information, so that data analysis can be used for extracting defined models and patterns, which can be generalized and utilized, and such patterns and structures are discovered and perceived that can be used as instruction or application in similar structures. In fact, data mining is important because working process of a system can be perceived by analysis of data content, and useful and constructive information can be obtained by standard and expert analysis. Data mining can be defined at any smart system or interactive and communicative structure that has outcome and different results, and data analysis can help to develop performance of any system with any method and working purpose in interactive and competitive space. Utilizing data mining science is a factor for producing better content, performance improvement, and achievement of optimal outcome and result. Thus, standard analyses are able to provide sound information about activities because they can properly identify and investigate nature of the activity and data. This information are practical and security, quality, and quantity of data as well as performance can be improved using these information, new working patterns and models can be formed. Data mining actually based on standard analyses causes development of data-dependent processes.

Ali Saberi

Development of Software with Appropriate Applications in Smart Tools

Technology development has caused that smart tools to become part of interactions and communications, that is, the smart systems have developed along with the human activities. Thus, smart tools have become service providers by utilization of developed computer and electronic structure. Smart tools are composed of a hardware system. This hardware system, using an operating system or under several operating systems like Microsoft Windows, Android, Linux, IOS, Windows Phone, etc. develops a smart tool like cell phone, computer, and other smart tools. In order to promote the interaction between smart tool and user or to provide more facilities for the smart tool, certainly software appropriate to the operating system and smart tool is used. This process of change and advancement is crucially important in the current technological era, and the better the tool is able to communicate, it is considered as an advantage and superiority. Various software with different applications plays the major role in the superiority process. If the smart tool enjoys side facilities or suitable software, tendency to use it would be increased because of its usefulness and efficacy. Hence, developing practical software with healthy and effective contents is a major issue in software design and production, which would lead to more capabilities and facilities for the smart tools, and people, would be more tended to use them.

Ali Saberi

Investigating IPv6 Addressing Model with Security Approach and Compare It with IPv4 Model

Internet Protocol Version 6, or IPv6, is the latest version of the Internet Protocol which Internet connections formed based on it. This version is expected to replace version 4 of this protocol that is currently in use, therefore, in this study, the IPv6 addressing model has been utilized with a security method and compared with the IPv4 model, which is the reason of IPv6 features should be held as the benefits of IPv4, the disadvantages of it have been abandoned or diminished or added new features.

Asieh Dehvan, Amir Reza Estakhrian, Ahmad Changai

Design of Dual-Band Band-Pass Filters with Compact Resonators and Modern Feeding Structure for Wireless Communication Applications

In this paper two new planar dual-band band-pass filters (DBBPF), that each of them is designed using an exclusive type of feed structure and by planar technologies of microstrip have been presented. First DBBPF is implemented, using compact open-loop meandering resonators, and open stub-loaded feed-lines. The cause of introducing the transmission zeros near the pass-bands of the first filter is source/load coupling at stub-loaded feed structures. The longer resonators, which are fed by open-stub loaded feed-lines, independently control the lower pass-band and the shorter resonators which are magnetically coupled, independently control the higher pass-band. The second DBBPF are designed by using 0° feed structure and by combining of two types of resonators. The main resonators with diagonal feeding structure and similar to stepped-impedance resonators (SIR) construct the lower pass-band. The sub-resonators with double-spiral and inter-coupling, can be embedded in the structure of main-resonators and construct the higher pass-band. There is a cross-coupling between the four sub-resonators, that suppresses any harmonics and introduces the extra transmission zeros at each side of second pass-band. Both sets of DBBPFs are designed to miniaturize, improve the gain, decrease losses and are fabricated to apply to wireless communication applications. The obtained experimental results validate the simulation results.

Mohammadreza Zobeyri, Ahmadreza Eskandari

New Fuzzy Logic-Based Methods for the Data Reduction

The problem of finding effective data reduction algorithm was discussed in the paper. To improve the quality of initial data, the matrix and singular value decomposition and fuzzy reasoning were used, the method of selection of the most efficient reduction algorithm was proposed.

Reyhaneh Tati

A New Approach for Processing the Variable Density Log Signal Using Frequency-Time Analysis

Cementing is a common practice in drilling and completion of each well, and it is necessary to evaluate how to bonding the cement in this operation. So far, all the methods used to evaluate the extent and how to bonding the cement is eye-catching. Due to the fact that most of the signals are non-stationary, time-frequency analysis methods are among the best methods, the most important of which is the short-time Fourier transform and continuous wavelet transform. Due to the problem of the dispersion of the signal components in these two transformations, the conversion of synchrosqueezing by fixing this limit, it has achieved better results. In this paper, using these transformations, various modes of VDL sonic signaling, which is a criterion for evaluating the quality of cement bond, are investigated. The data used in this article is related to the South Yarran Field to a depth of 2294.5 m located in Ahvaz, Iran.

Esmat Mousavi, Yousef Seifi Kavian, Gholamreza Akbarizadeh

Detection of Malicious Node in Centralized Cognitive Radio Networks Based on MLP Neural Network

The cognitive radio network (CRNs) has been developed in recent years for the optimal use of Available vacuum in the frequency spectrum. In this network, Cooperate Spectrum Sensing (CSS) is used to combine the observations of all users. In CRNs, security is one of the most important problems spectrum sensing data falsification (SSDF) attack is one of major challenges for CSS in CRNs, in which Malicious user are among honest users trying to change the information sent to the fusion center and thus make the fusion center’s wrong decision. In this paper, a method for defense against SSDF attack is proposed using MLP-based neural network. In this scheme, the weights of secondary users were constantly updated and finally the sensing results were combined in the fusion center based on their trusted weights. Simulation results show that the proposed scheme can significantly reduce the effects of Spectrum Sensing Data Falsification (SSDF) attack even percentage of malicious users are more than trusted users.

Zeynab Sadat Seyed Marvasti, Omid Abedi

FIR Filter Realization Using New Algorithms in Order to Eliminate Power Line Interference from ECG Signal

Biomedical recordings are often contaminated by power line interference (PLI). Notch filtering is one of the most common filtering that suppresses the major PLI as well as its harmonics in the electrocardiographic recording. A finite impulse response (FIR) filter is one of the fascinating methods to filter interference so that obtain a relatively pure signal. In this paper, the authors focus on providing new algorithms (HSTAE, MPSO) for reducing the hardware complexity. Using these algorithms, in addition to reducing the hardware volume, the frequency response and quality of the output signal will be improved. The simulation results showed that the proposed algorithms remarkably reduce the hardware complexity of the FIR filter for eliminating PLI from the electrocardiogram (ECG) signal.

Akbar Farajdokht, Behbood Mashoufi

Providing a Proper Solution to Solve Problems Related to Banking Operations Through the ATM Machines to Help the Disabled, the Elderly and the Illiterate People

This article aims at solving the current problems of individuals with disabilities and illiteracy in using the ATM machines to carry out banking operations (e.g. paying and receiving payments or paying bills or any other operations that an ATM can do), so that these people, like other people, are able to do their banking operations without the involvement of another person.

Farhood Fathi Meresht

Presenting a New Clustering Algorithm by Combining Intelligent Bat and Chaotic Map Algorithms to Improve Energy Consumption in Wireless Sensor Network

One of the major challenges that wireless sensor networks face is the limited energy of nodes which reduces network’s life time. Clustering is a popular approach to overcome this problem. Also, it is a particular energy efficient mechanism within large scale wireless sensor networks. Most problems of the computer systems like wireless sensor network could not be solved by linear solutions and there is not any deterministic solution for most NP-hard problems and the result of such problems is always optimizing. To solve these problems, applying evolutionary algorithms is recommended. The bat algorithm could find the shortest path between member nodes of the cluster and cluster head. In this paper, to reduce the energy consumption in wireless sensor nodes and also select the suitable cluster heads, the capabilities of combining the evolutionary bat algorithm and chaotic map is used. Applying chaotic map instead of some particular and random parameters in the bat algorithm improves the clustering. The results obtained from the implementation of the proposed method in MATLAB and their comparison with the existing methods such as GA, GAPSO, LEACH and LEACH-T represent significant impact in energy consumption improvement, network lifetime increase and also the number of live nodes increase within different rounds of algorithm execution.

Masome Asadi, Seyyed Majid Mazinani

The Impact of Spatial Resolution on Reconstruction of Simple Pattern Through Multi Layer Perceptron Artificial Neural Network

This study investigates the effect of spatial resolution factor on prediction of symbol ‘I’, the first Roman number, from scatter pixel images of this symbol through multiple perceptron neural network with adjusted network training parameter. The corrupted images of this symbol with different spatial resolution and pixel size has applied to the feed forward neural network model. The results of modelling have revealed acceptable correlation coefficient values with low and high resolution desired images and low and high resolution predicted images. From other aspect, a very less difference between these correlation coefficients emphasize on insignificant consequence of pixel size variation over the symbol with simple geometry.

Pardis Jafari, Saeideh Sarmadi

Analysis of the Role of Cadastre in Empowerment of Informal Settlements (Case Study: Ahvaz City)

Ahvaz is the capital of the province and the second largest city in terms of size after Tehran and the 7th Iranian city in terms of population. In Ahwaz, the issue of marginalization is a function of the process of marginalization of the whole country. The purpose of this study is to analyze the role of cadastre in the empowerment of informal settlements in Ahvaz city. This paper addresses the socio-economic dimensions of eight marginal neighborhoods and the effect of cadastre on empowerment of its inhabitants. Among the various types of cadastre, we emphasize the civil-legal cadastre in this research. In order to investigate the role of cadastre in decision making and decision making, library resources and questionnaires and questionnaires were used to survey the statistical population and face to face interviews with relevant managers and experts at different levels. In the quantitative analysis of the questionnaires, statistical techniques such as correlation and regression were used in the SPSS software package that resulted in the following results: Using the correlation test, it was determined that between the security of capture and the incentive to invest in the housing sector as well as the motivation for participation People have a direct relationship with improvement plans and using regression it has been found out that secretive and perceived security has a greater impact on the security of legal seizure on the incentive to invest in the housing sector as well as the incentive for people to participate in improvement projects. Therefore, it can be concluded that in informal settlements, in addition to enhancing the legal dimension of seizure, with tools such as the implementation of civil-law cadastre and the consolidation of ownership and documentation of seizure, it should strengthen and increase the conventional and perceptual dimensions of security of seizure by measures such as increasing Sense of belonging to the environment and promoting the quality of urban, educational and social services. The collection of library resources, as well as interviews with managers and experts, resulted in the ignorance of informal settlements and the prevention of the granting of property, the method of dealing with and the prevention of the spread of these gatherings, as the effects of informal neighborhoods such as poverty and corruption, and Other social disruptions have a direct impact on the city.

Seyed Sajjad Ghoreyshi Madineh, Ramatullah Farhoudi, Hasan Roosta

Threats of Social Engineering Attacks Against Security of Internet of Things (IoT)

Internet of Things is a fast growing technology. Home appliances, clothes, traffic lights, cars, cameras, and more things used by human are prone to be connected to the IoT. Any new technology has its own challenges. Security is one of the greatest challenges of IoT. Security has been a challenge about the Internet, but in IoT domain, security is wider problem. For instance, manipulating the system of traffic lights will disrupt the security and public discipline. The daily life of human being is involved in the IoT, always and anytime is carried or controlled by users, therefore a vital role is going to be played in human interactions by IoT. Influencing the social interactions of individuals and their everyday lives can mean the penetration in the IoT and challenging the security. Social engineering is not a new concept; SE is an old category that is growing steadily with no end in its vision. SE is effective because human prefer to trust naturally. Social engineers target human factors and use the trust to thieve the purposed information. Generally, SE influences social interactions. Using SE against IoT and lack of knowledge among society will be able to cause a tragedy. SE is introduced in this paper and then security challenges of IoT will be discussed. People’s behaviors to keep their security will be discussed in this paper.

Mohsen Ghasemi, Mohammad Saadaat, Omid Ghollasi

Assessment and Modeling of Decision-Making Process for e-Commerce Trust Based on Machine Learning Algorithms

Decision-making on trust in an e-commerce environment is associated with several other elements such as security, risk, satisfaction, loyalty and reputation. The life cycle of e-trust in online Business to Consumer (B2C) transactions takes multiple stages from beginning to end. The first stage involves the complete unawareness of online shoppers about online sellers. Then, individual trust begins to develop, endure, recover and ultimately sustain or diminish. Since it is a complicated task to gain trust, there have been numerous solutions, methods and models proposed so far to create, maintain, measure, enhance and prevent loss of trust. One of the solutions that has long been adopted to determine trust level in B2C is a concentration on the history or background of online shoppers (customers) and online sellers (companies) so as to obtain reliable data or identify trust level. This paper attempted to adopt the machine learning algorithms to analyze decisions about the past and history of individuals/companies and trust in e-business/e-commerce (EC). Moreover, efforts were made to identify and assess the key contributing factors to decision-making. The results demonstrated that corporate factors and business models left the greatest impacts on customer decision-making in e-business trust or distrust during electronic transactions.

Issa Najafi

Three-Band, Flexible, Wearable Antenna with Circular Polarization

In this chapter, we show a circular polarization (CP), wearable antenna, with a flexible substrate for GPS, DCS, and PCS applications. The CP was created using different methods, for example, we truncated two opposite edges of a square patch, as well as using other methods. We used a coplanar waveguide for feeding and the substrate material antenna is Rogers RO4003. The dimensions of the proposed antenna is 76 × 76 mm, with a thickness of 0.8 mm, a relative permittivity of 3.55, and dielectric loss tangent of 0.0027. The chapter goes on to show that the CP, wearable antenna has a 3-dB axial ratio (AR) bandwidth of 520 MHz (26%), a return loss (RL) of 10 dB, and impedance bandwidth of 2.9 GHz (97%). The antenna was simulated by HFSS (High Frequency Electromagnetic Field) software.

Milad Najjariani, Pejman Rezaei

A Multi-objective Distribution Network Reconfiguration and Optimal Use of Distributed Generation Unites by Harmony Search Algorithm

In this paper, the method of network reconfiguration and simultaneous use of distributed generation resources (DG) in optimal location and capacity is analyzed in order to minimize losses and reach the optimum level of voltage stability and voltage profile. A new method for this purpose is proposed by use of the Harmonic Search Algorithm (HSA). To investigate the effectiveness of the proposed method, the capabilities of the MATLAB software and the DPL language linked to the DIGSILENT application is used. The 33-node distribution network of IEEE standard was selected for investigation. The simulation results shows that by using the proposed method, network losses were minimized and the voltage level and voltage profiles were improved correctly.

Mojtaba Mohammadpoor, Reza Ranjkeshan, Abbas Mehdizadeh

Multi-band Rectangular Monopole Microstrip Antenna with Modified Feed Junction for Microwave Wireless Applications

A multi-band microstrip antenna, based on a cheap FR-4 substrate and with thickness of 1.6 mm is proposed in this paper. A 50 O female SMA connector is welded to antenna and the antenna is fed by coaxial cable. The antenna has 8 bandwidths between 2.2 and 11 GHz frequency region. −68.04 dB return loss has been measured at 3.099 GHz in the second bandwidth. Finally, the antenna is used as array elements in 6 different linear and planar geometric arrangements. 17.2 dBi directivity is achieved at 7.9 GHz by 4 elements linear array antenna. The antenna has a simple structure and is suitable for microwave wireless applications such as energy harvesting. The voltage standing wave ratio (VSWR), return loss, radiation pattern and directivity are provided.

Mohammad Faridani, Ramezan Ali Sadeghzadeh

Electrostatic MEMS Switch with Vertical Beams and Body Biasing

One of the easiest and the most appropriate solution for fabricating MEMS switch is Electrostatic actuation. However, it requires large parallel plates which can take a large surface on the substrate wafer and thus an expensive fabrication cost. In this paper, an improved electrostatic MEMS switch is presented. The proposed design is carried out so that it minimizes the dimensions of the MEMS device. Simulation results are also done by COMSOL based on the proposed design.

Armin Bahmanyaran, Kian Jafari

Optimal Clustering of Nodes in Wireless Sensor Networks, Using a Gravitational Search Algorithm

Wireless sensors are among the most appropriate data collection solutions in the world. Information collected by sensors should be transmitted to a base station. In direct transmission, each sensor sends information directly to the center. Due to the high distance of the sensors from the center, they consume a lot of energy. In contrast, designs that create the shortest distance can prolong the life of the network. In these networks, sensor nodes are often confronted with limitations due to small size, such as processing power and limited power supply. These limitations have led researchers to carry out extensive studies in the design of these networks. The nodes are more distant than the nodes of the cluster, consuming more time and power to transmit data to the cluster. Therefore, better clustering of sensor nodes in wireless sensor networks to reduce the power consumption of sensor nodes through better connection of sensor nodes to cluster nodes using a gravitational search algorithm, and the results are optimized with artificial and optimal beehive algorithms. Particle swarm is compared.

Saeid Madadi barough, Ahmad Khademzadeh

A Bee Colony (Beehive) Based Approach for Data Replication in Cloud Environments

Cloud computing refers to applications and services which run on a distributed network, they also represent the ability of information technology as a service to network users. Data replication is an important way of managing mass data in a distributed manner; data replication is seen as one of the important issues in distributed systems which are usually undertaken for increasing the efficiency, availability, and security of information. Data replication’s core idea is developing methods for putting repetitions in different places, so that there are multiple iterations of the specific file in different sites. A key issue in data managing is the manner that system deals with duplicates. This included steps such as: which files are replicated, when is the data replication done and where in the system are they to be placed. In this study, the proposed method has been implemented using the MATLAB environment and the results have showed that the performing time of the proposed method is much lower as compared to previous methods and it had improved performance time compared to the previous methods.

Saedeh khalili azimi
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Globales Erdungssystem in urbanen Kabelnetzen

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