Meganathan Padmanaban, Sasi Chinnathambi, P. Parthasarathy, Nammalvar Pachaivannan
To moderate global warming, conventional fossil fuels are depleted. As the population increased with the rising standard of living and industrial growth, the global environment is affected and cause the greenhouse gases occurrence, which are frequently increased by unlimited use of fossil fuels. The generation of electric power loads increases the power demand on the basics of modern power technology development. Several benefits can be attained by installing the distribution generation with the quality and reliability of power delivered. However, the global energy problem can be resolved by renewable energy sources as an alternative energy generation. Technological developments in the last decade have increased the use of renewable energy sources. In worldwide, several renewable energy sources are used to attain their own power demand. The photovoltaic (PV) generation is the essential renewable energy source to serve the increasing electrical loads. The fastest-growing PV system has the naturally available energy sources of robust evolution with elegant benefits. The foremost objective of this paper is to examine the performance of the PV system with various Maximum Power Point Tracking (MPPT) algorithms. The solar irradiance and temperature make it complex to track the MPPT of PV systems. This review is about various MPPT algorithms like online, offline, and hybrid methods. The selected algorithms from each discussion are simulated in MATLAB/Simulink environment to match their performance in footings of the dynamic response and efficiency of the PV system under the variations of solar irradiance and temperature. An explanation and discussion of the PV system are achieved with the study of different types of MPPT algorithms of PV systems.
{"title":"An Extensive Study on Online, Offline and Hybrid MPPT Algorithms for Photovoltaic Systems","authors":"Meganathan Padmanaban, Sasi Chinnathambi, P. Parthasarathy, Nammalvar Pachaivannan","doi":"10.52547/mjee.15.3.1","DOIUrl":"https://doi.org/10.52547/mjee.15.3.1","url":null,"abstract":"To moderate global warming, conventional fossil fuels are depleted. As the population increased with the rising standard of living and industrial growth, the global environment is affected and cause the greenhouse gases occurrence, which are frequently increased by unlimited use of fossil fuels. The generation of electric power loads increases the power demand on the basics of modern power technology development. Several benefits can be attained by installing the distribution generation with the quality and reliability of power delivered. However, the global energy problem can be resolved by renewable energy sources as an alternative energy generation. Technological developments in the last decade have increased the use of renewable energy sources. In worldwide, several renewable energy sources are used to attain their own power demand. The photovoltaic (PV) generation is the essential renewable energy source to serve the increasing electrical loads. The fastest-growing PV system has the naturally available energy sources of robust evolution with elegant benefits. The foremost objective of this paper is to examine the performance of the PV system with various Maximum Power Point Tracking (MPPT) algorithms. The solar irradiance and temperature make it complex to track the MPPT of PV systems. This review is about various MPPT algorithms like online, offline, and hybrid methods. The selected algorithms from each discussion are simulated in MATLAB/Simulink environment to match their performance in footings of the dynamic response and efficiency of the PV system under the variations of solar irradiance and temperature. An explanation and discussion of the PV system are achieved with the study of different types of MPPT algorithms of PV systems.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42619460","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Cloud computing in the field of high-performance distributed computing has emerged as a new development in which the demand for access to resources via the Internet is presented in distributed servers that dynamically scale are acceptable. One of the important research issues that must be considered to achieve efficient performance is fault tolerance. Fault tolerance is a way to find faults and failures in a system. Predicting and reducing errors play an important role in increasing the performance and popularity of cloud computing. In this study, an adaptive workflow scheduling approach is presented to increase fault tolerance in cloud computing. The present approach calculates the probability of failure for each resource according to the execution time of tasks on the resources. In the present method, a deadline is set for each of the tasks. If the task is not completed within the specified time, the probability of failure in the source increases and subsequent tasks are not sent to the desired source. The simulation results of the proposed method show that the proposed idea can work well on workflows and improve service quality factors.
{"title":"Adaptive Workflow Scheduling to Increase Fault Tolerance in Cloud Computing","authors":"Abdolreza Pirhoseinlo, Nafiseh Osati Eraghi, Javad Akbari Torkestani","doi":"10.52547/mjee.15.3.25","DOIUrl":"https://doi.org/10.52547/mjee.15.3.25","url":null,"abstract":": Cloud computing in the field of high-performance distributed computing has emerged as a new development in which the demand for access to resources via the Internet is presented in distributed servers that dynamically scale are acceptable. One of the important research issues that must be considered to achieve efficient performance is fault tolerance. Fault tolerance is a way to find faults and failures in a system. Predicting and reducing errors play an important role in increasing the performance and popularity of cloud computing. In this study, an adaptive workflow scheduling approach is presented to increase fault tolerance in cloud computing. The present approach calculates the probability of failure for each resource according to the execution time of tasks on the resources. In the present method, a deadline is set for each of the tasks. If the task is not completed within the specified time, the probability of failure in the source increases and subsequent tasks are not sent to the desired source. The simulation results of the proposed method show that the proposed idea can work well on workflows and improve service quality factors.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43033160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Moslehi, Hossei Ebrahimpor-Komleh, Salman Goli, Reza Taji
: In recent years, exponential growth of communication devices in Internet of Things (IoT) has become an emerging technology which facilitates heterogeneous devices to connect with each other in heterogeneous networks. This communication requires different level of Quality-of-Service (QoS) and policies depending on the device type and location. To provide a specific level of QoS, we can utilize emerging new technological concepts in IoT infrastructure, Software-Defined Network (SDN) and, machine learning algorithms. We use deep reinforcement learning in the process of resource management and allocation in control plane. We present an algorithm that aims to optimize resource allocation. Simulation results show that the proposed algorithm improved network performances in terms of QoS parameters, including delay and throughput compared to Random and Round Robin methods. Compared to similar methods, the performance of the proposed method is also as good as the fuzzy and predictive methods.
近年来，物联网(Internet of Things, IoT)通信设备呈指数级增长，已成为一种新兴技术，使异构设备能够在异构网络中相互连接。这种通信需要不同级别的服务质量(QoS)和策略，具体取决于设备类型和位置。为了提供特定级别的QoS，我们可以利用物联网基础设施、软件定义网络(SDN)和机器学习算法中新兴的新技术概念。我们在控制面的资源管理和分配过程中使用了深度强化学习。提出了一种优化资源分配的算法。仿真结果表明，与随机和轮循方法相比，该算法在QoS参数方面提高了网络性能，包括延迟和吞吐量。与同类方法相比，该方法的性能与模糊方法和预测方法相当。
{"title":"A QoS Optimization Technique with Deep Reinforcement Learning in SDN-Based IoT","authors":"M. Moslehi, Hossei Ebrahimpor-Komleh, Salman Goli, Reza Taji","doi":"10.52547/mjee.15.3.105","DOIUrl":"https://doi.org/10.52547/mjee.15.3.105","url":null,"abstract":": In recent years, exponential growth of communication devices in Internet of Things (IoT) has become an emerging technology which facilitates heterogeneous devices to connect with each other in heterogeneous networks. This communication requires different level of Quality-of-Service (QoS) and policies depending on the device type and location. To provide a specific level of QoS, we can utilize emerging new technological concepts in IoT infrastructure, Software-Defined Network (SDN) and, machine learning algorithms. We use deep reinforcement learning in the process of resource management and allocation in control plane. We present an algorithm that aims to optimize resource allocation. Simulation results show that the proposed algorithm improved network performances in terms of QoS parameters, including delay and throughput compared to Random and Round Robin methods. Compared to similar methods, the performance of the proposed method is also as good as the fuzzy and predictive methods.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48193672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Analyzes of electric discharge are sometimes tedious and relatively expensive. To overcome this problem, some scientists are working on variance analysis projects. The article presents the results of an electric discharge experiment performed on silicone, porcelain and heat tempered glass insulators at Triple Junction (TJ). The objective of this study is to develop a polynomial and Gaussian simple regression model (Polynomial Simple Linear Regression (SLR) model and Gaussian simple nonlinear regression model) considering different parameters by analyzing the observed quantitative data. The dependent variable or variable to be explained (discharge current) is a function of four independent variables (explanatory variables): voltage application time ( t ), solid insulator surface condition: net surface ( t’ ), worn rubbed surface with sandpaper ( t’’ ) and active electrode diameter ( diam ). Indeed, this study sets up precise prediction models generating good estimates of the studied variables values. A polynomial SLR model is proposed capable of predicting electric discharge with an adjusted coefficient of determination ( R 2 adj ) of 0.9774 for t and t’ , 0.9773 for t" and 0.9945 for diam . While ( R 2 adj ) for the Gaussian model reaches 0.9989 for t and t’ , 0.9998 for t’’ . By considering this, these models are strongly recommended to better understand and characterize the discharge and contribute to the improvement of the insulation and its design for better optimization and high performance.
{"title":"An Experimental Study Followed by a Development and a Comparison of Regression Models for Predicting TJ Electric Discharge in Insulators","authors":"Nabila Saim, F. Bitam-Megherbi","doi":"10.52547/mjee.15.3.45","DOIUrl":"https://doi.org/10.52547/mjee.15.3.45","url":null,"abstract":": Analyzes of electric discharge are sometimes tedious and relatively expensive. To overcome this problem, some scientists are working on variance analysis projects. The article presents the results of an electric discharge experiment performed on silicone, porcelain and heat tempered glass insulators at Triple Junction (TJ). The objective of this study is to develop a polynomial and Gaussian simple regression model (Polynomial Simple Linear Regression (SLR) model and Gaussian simple nonlinear regression model) considering different parameters by analyzing the observed quantitative data. The dependent variable or variable to be explained (discharge current) is a function of four independent variables (explanatory variables): voltage application time ( t ), solid insulator surface condition: net surface ( t’ ), worn rubbed surface with sandpaper ( t’’ ) and active electrode diameter ( diam ). Indeed, this study sets up precise prediction models generating good estimates of the studied variables values. A polynomial SLR model is proposed capable of predicting electric discharge with an adjusted coefficient of determination ( R 2 adj ) of 0.9774 for t and t’ , 0.9773 for t\" and 0.9945 for diam . While ( R 2 adj ) for the Gaussian model reaches 0.9989 for t and t’ , 0.9998 for t’’ . By considering this, these models are strongly recommended to better understand and characterize the discharge and contribute to the improvement of the insulation and its design for better optimization and high performance.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48566020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: DGs and capacitor banks are installed to optimize the performance of many distribution networks. Typically, the problem of optimizing the overall performance of the distribution network is examined with multi-objective purposes. Network optimization purposes are usually varied and sometimes contradictory. Therefore, the problem search space is very large due to the variety of purposes. This paper presents a modified Pareto local search function for optimal placement of DGs and capacitor banks. To limit the search space and find Pareto points, a new combination method including Pareto chart and a weight function has been used. The optimal operation of the distribution network is performed by three single objective functions related to the voltage stability index, voltage profile of buses and power loss. In this method, a modified per-unit system is presented to align single objective functions and their weighting coefficients. The network is studied with three different loads. So that, the network is examined in the final stage by increasing the load and reaching bus voltage stability margins. The particle swarm optimization method is applied to solving placement problems. In addition, locating and sizing DG and capacitor banks, tap setting of on load tap changer transformer is adjusted by the proposed method. To show the effectiveness of the purposed method, simulations are applied to 69 bus radial system. The results indicated the favorable advantage of the proposed method to improve the overall performance of the distribution network.
{"title":"Pareto Local Search Function for Optimal Placement of DG and Capacitors Banks in Distribution Systems","authors":"A. Sadighmanesh, M. Sabahi, M. Zavvari","doi":"10.52547/mjee.15.3.81","DOIUrl":"https://doi.org/10.52547/mjee.15.3.81","url":null,"abstract":": DGs and capacitor banks are installed to optimize the performance of many distribution networks. Typically, the problem of optimizing the overall performance of the distribution network is examined with multi-objective purposes. Network optimization purposes are usually varied and sometimes contradictory. Therefore, the problem search space is very large due to the variety of purposes. This paper presents a modified Pareto local search function for optimal placement of DGs and capacitor banks. To limit the search space and find Pareto points, a new combination method including Pareto chart and a weight function has been used. The optimal operation of the distribution network is performed by three single objective functions related to the voltage stability index, voltage profile of buses and power loss. In this method, a modified per-unit system is presented to align single objective functions and their weighting coefficients. The network is studied with three different loads. So that, the network is examined in the final stage by increasing the load and reaching bus voltage stability margins. The particle swarm optimization method is applied to solving placement problems. In addition, locating and sizing DG and capacitor banks, tap setting of on load tap changer transformer is adjusted by the proposed method. To show the effectiveness of the purposed method, simulations are applied to 69 bus radial system. The results indicated the favorable advantage of the proposed method to improve the overall performance of the distribution network.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47611757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Amongst the approaches proposed to estimate parameters of a chirp signal sequentially, i.e., the central frequency and the chirp rate, algorithms, such as Discrete Polynomial-Phase Transform (DPT) and promoted DPT, exhibit acceptable estimation accuracy. Algorithms intended to estimate phase parameters sequentially, diminish the order of polynomials in complex exponential power to lower-order polynomials, and then estimate these two parameters using the NLS method in a given single exponential mode. The NLS method, which uses FFT to decrease the computational load of frequency domain search, encounters predicaments. In this work, we assessed the bias of algorithms intended for estimating of phase parameters sequentially using the RBF method. The results of investigating the bias of estimators indicated the improved accuracy of the DPT and promoted DPT algorithms in estimation using the RBF method instead of NLS and also than DCFT method.
{"title":"Investigating Bias of DCFT, DPT and Promoted DPT Methods in terms of Phase Parameters Estimation of Chirp Signal","authors":"Nooshin Rabiee, Hamid Aazad, N. Parhizgar","doi":"10.52547/mjee.15.3.35","DOIUrl":"https://doi.org/10.52547/mjee.15.3.35","url":null,"abstract":": Amongst the approaches proposed to estimate parameters of a chirp signal sequentially, i.e., the central frequency and the chirp rate, algorithms, such as Discrete Polynomial-Phase Transform (DPT) and promoted DPT, exhibit acceptable estimation accuracy. Algorithms intended to estimate phase parameters sequentially, diminish the order of polynomials in complex exponential power to lower-order polynomials, and then estimate these two parameters using the NLS method in a given single exponential mode. The NLS method, which uses FFT to decrease the computational load of frequency domain search, encounters predicaments. In this work, we assessed the bias of algorithms intended for estimating of phase parameters sequentially using the RBF method. The results of investigating the bias of estimators indicated the improved accuracy of the DPT and promoted DPT algorithms in estimation using the RBF method instead of NLS and also than DCFT method.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48789574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mojgan Mirzaei Hotkani, S. Seyedin, Jean-François Bousquet
Matched Field Processing (MFP) is one of the most famous algorithms for source detection and underwater localization. Traditional MFP relies on a match between the received signal at the hydrophone array and a replica signal, which is constructed using Green’s Function, then by scanning the space in range and depth to provide an estimation of source position in shallow water and deep water. Different environment models relying on Green’s function exist for constructing the replica signal; this includes normal modes in a shallow water waveguide, the Lloyd-Mirror Pattern, and the Image model. Using the proposed estimation algorithm, here, an analytical Lloyd-Mirror model is developed based on the reflection from the target surface for a case where a target is located in the source signal propagation path. So, in this paper, a new underwater acoustic target localization algorithm using the generalized Lloyd-Mirror Pattern is presented. This idea is verified using an acoustic data from a 2019 underwater communication trial in Grand Passage, Nova Scotia, Canada.
匹配场处理(matching Field Processing, MFP)是目前最著名的声源检测和水下定位算法之一。传统的MFP依赖于水听器阵列接收到的信号与使用格林函数构造的复制信号之间的匹配，然后通过扫描距离和深度的空间来估计浅水和深水中的源位置。基于格林函数构建复制信号存在不同的环境模型;这包括在浅水波导的正常模式，劳埃德-镜子模式，和图像模型。利用所提出的估计算法，针对目标位于源信号传播路径的情况，建立了基于目标表面反射的解析Lloyd-Mirror模型。为此，本文提出了一种基于广义Lloyd-Mirror方向图的水声目标定位算法。利用2019年在加拿大新斯科舍省Grand Passage进行的水下通信试验的声学数据验证了这一想法。
{"title":"Underwater Target Localization using the Generalized Lloyd-Mirror Pattern","authors":"Mojgan Mirzaei Hotkani, S. Seyedin, Jean-François Bousquet","doi":"10.52547/mjee.15.3.17","DOIUrl":"https://doi.org/10.52547/mjee.15.3.17","url":null,"abstract":"Matched Field Processing (MFP) is one of the most famous algorithms for source detection and underwater localization. Traditional MFP relies on a match between the received signal at the hydrophone array and a replica signal, which is constructed using Green’s Function, then by scanning the space in range and depth to provide an estimation of source position in shallow water and deep water. Different environment models relying on Green’s function exist for constructing the replica signal; this includes normal modes in a shallow water waveguide, the Lloyd-Mirror Pattern, and the Image model. Using the proposed estimation algorithm, here, an analytical Lloyd-Mirror model is developed based on the reflection from the target surface for a case where a target is located in the source signal propagation path. So, in this paper, a new underwater acoustic target localization algorithm using the generalized Lloyd-Mirror Pattern is presented. This idea is verified using an acoustic data from a 2019 underwater communication trial in Grand Passage, Nova Scotia, Canada.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47446285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
: Today, due to the advent of the powerful photo editing software packages, it has become relatively easy to create forgery images. Recognizing the correctness of digital images becomes important when those images are used as evidence in legal, forensic, industrial, and military applications. One of the most common ways to forge images is copy move forgery, in which one part of the image is copied and pasted in another part of the same image. So far, various methods have been proposed for detecting copy move forgery, but these methods are not able to detect copy move forgery with different challenges of noise, rotation, scale, and detection of symmetrical images with high accuracy. In this paper, an enhanced hybrid method based on local and frequency feature extraction is presented for image copy move forgery detection, which has a very high resistance to above challenges, both individually and simultaneously and has provided good identification accuracy. In this method, the combination of Discrete Wavelet Transform, Scale Invariant Feature Transform and Local Binary Pattern are used simultaneously. The forged area is chosen in such a way that at least both methods used in this proposed method have consensus about the forgery of that area. Various experiments and analyses on the MICC database show that the proposed methods, despite the above challenges, have reached the accuracy of 98.81% both separately and simultaneously, which shows significant improvement compared to other methods used in this field.
{"title":"An Enhanced Hybrid Method based on Local and Frequency Feature Extraction for Image Copy Move Forgery Detection","authors":"Shirin Nayerdinzadeh, M. R. Yousefi","doi":"10.52547/mjee.15.3.69","DOIUrl":"https://doi.org/10.52547/mjee.15.3.69","url":null,"abstract":": Today, due to the advent of the powerful photo editing software packages, it has become relatively easy to create forgery images. Recognizing the correctness of digital images becomes important when those images are used as evidence in legal, forensic, industrial, and military applications. One of the most common ways to forge images is copy move forgery, in which one part of the image is copied and pasted in another part of the same image. So far, various methods have been proposed for detecting copy move forgery, but these methods are not able to detect copy move forgery with different challenges of noise, rotation, scale, and detection of symmetrical images with high accuracy. In this paper, an enhanced hybrid method based on local and frequency feature extraction is presented for image copy move forgery detection, which has a very high resistance to above challenges, both individually and simultaneously and has provided good identification accuracy. In this method, the combination of Discrete Wavelet Transform, Scale Invariant Feature Transform and Local Binary Pattern are used simultaneously. The forged area is chosen in such a way that at least both methods used in this proposed method have consensus about the forgery of that area. Various experiments and analyses on the MICC database show that the proposed methods, despite the above challenges, have reached the accuracy of 98.81% both separately and simultaneously, which shows significant improvement compared to other methods used in this field.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46421826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Water Distribution and the Impact of Relative Humidity in a PEMFC Energy System using Macroscopic Energy Representation by Inversion Control","authors":"Farid Saadaoui, Khaled Mammar, Abdaldjabar Hazzab","doi":"10.52547/mjee.15.3.57","DOIUrl":"https://doi.org/10.52547/mjee.15.3.57","url":null,"abstract":"","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47144188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mohsen Mojahed, Amir Sabbagh Molahossein, Azadeh Alsadat Emrani Zarandi
: The 4-moduli set residue number system (RNS), {2 𝑛 + 3,2 𝑛 − 3,2 𝑛 + 1, 2 𝑛 − 1} , with a wide dynamic range, has recently been proposed as a balanced 4-moduli set for utilizing the cases that demand fast calculations such as deep learning and implementation of asymmetric cryptographic algorithms. Up to now, only an unsigned reverse converter has been designed for this moduli set. Thus, there is a need for two separate units, a sign detection circuit, and a comparator to use this set in cases requiring sign and comparison. Nevertheless, the existence of these components demands high hardware that makes the implementation of the RNS impractical. Therefore, this paper presents the design of a sign detection circuit and a signed reverse converter that can overcome this problem by reusing the hardware. To achieve an integrated hardware design, first, we optimized the previous unsigned reverse converter for this 4-moduli set and next, we derived an approach from the structure of the reverse convertor for detecting signs and recognizing comparators. Finally, using the sign signals extracted from the reverse converter, we change reverse convertor into a unit that perform sign detection and comparison. The simulation has been conducted using ISE Design Suite 14.7 tool and the Spartan6 family technology. Empirical results show that, the proposed multifunctional unit has an approximately identical performance with respect to delay and area compared to the previous reverse converter. Besides, the proposed signed reverse converter relies on a 46% and 28% reduction in area and delay compared to the previous unsigned reverse converter which uses a comparator and also a multiplexer to detect a sign in the output.
4模集剩数系统(RNS){2𝑛+ 3,2𝑛−3,2𝑛+ 1,2𝑛−1}，具有广泛的动态范围，最近被提出作为一个平衡的4模集，用于利用需要快速计算的情况，如深度学习和非对称密码算法的实现。到目前为止，针对这个模集只设计了一个无符号反向转换器。因此，需要两个独立的单元，一个符号检测电路和一个比较器，以便在需要符号和比较的情况下使用该集合。然而，这些组件的存在对硬件的要求很高，这使得RNS的实现不切实际。因此，本文设计了一种符号检测电路和一种符号反向转换器，通过硬件的复用来克服这一问题。为了实现集成硬件设计，首先，我们针对这个4模集优化了之前的无符号反向转换器，然后，我们从反向转换器的结构中推导出一种检测符号和识别比较器的方法。最后，利用从反向变换器中提取的符号信号，将反向变换器改造成一个进行符号检测和比较的单元。仿真使用ISE Design Suite 14.7工具和Spartan6系列技术进行。实验结果表明，与之前的反向变换器相比，所提出的多功能单元在延迟和面积方面具有大致相同的性能。此外，与之前使用比较器和多路复用器检测输出中的符号的无符号反向转换器相比，所提出的有符号反向转换器依赖于46%和28%的面积和延迟减少。
{"title":"Magnitude Comparison and Sign Detection based on the 4-Moduli Set {2n+1, 2n−1, 2n+3, 2n−3}","authors":"Mohsen Mojahed, Amir Sabbagh Molahossein, Azadeh Alsadat Emrani Zarandi","doi":"10.52547/mjee.15.3.93","DOIUrl":"https://doi.org/10.52547/mjee.15.3.93","url":null,"abstract":": The 4-moduli set residue number system (RNS), {2 𝑛 + 3,2 𝑛 − 3,2 𝑛 + 1, 2 𝑛 − 1} , with a wide dynamic range, has recently been proposed as a balanced 4-moduli set for utilizing the cases that demand fast calculations such as deep learning and implementation of asymmetric cryptographic algorithms. Up to now, only an unsigned reverse converter has been designed for this moduli set. Thus, there is a need for two separate units, a sign detection circuit, and a comparator to use this set in cases requiring sign and comparison. Nevertheless, the existence of these components demands high hardware that makes the implementation of the RNS impractical. Therefore, this paper presents the design of a sign detection circuit and a signed reverse converter that can overcome this problem by reusing the hardware. To achieve an integrated hardware design, first, we optimized the previous unsigned reverse converter for this 4-moduli set and next, we derived an approach from the structure of the reverse convertor for detecting signs and recognizing comparators. Finally, using the sign signals extracted from the reverse converter, we change reverse convertor into a unit that perform sign detection and comparison. The simulation has been conducted using ISE Design Suite 14.7 tool and the Spartan6 family technology. Empirical results show that, the proposed multifunctional unit has an approximately identical performance with respect to delay and area compared to the previous reverse converter. Besides, the proposed signed reverse converter relies on a 46% and 28% reduction in area and delay compared to the previous unsigned reverse converter which uses a comparator and also a multiplexer to detect a sign in the output.","PeriodicalId":37804,"journal":{"name":"Majlesi Journal of Electrical Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47040618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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