Recent Advances in Electrical & Electronic Engineering - Volume 13, Issue 6, 2020

Background: Microstrip antenna has gained significant attention for a large number of communication systems due to its adaptable features and compatibility. Objective: The major objective of this manuscript is to assess the microstrip antenna technology for structure adaptability, the feature based performance capabilities, design and versatility. Methods: The major reviews conducted in every decade on antenna technology highlighted the significance of microstrip antenna technology. Moreover, a review of the articles on microstrip antenna published in ‘IEEE Transaction on Antenna and Propagation’ revealed that these antennas can primarily be used instead of other types of antennas. The available presentation of microstrip antennas includes features, such as small size, flatness (low profiles), wide-ranging impedance bandwidth, high gain, and circular polarization. A chronological assessment of the major endeavors in the microstrip antenna study conducted during the last four decades, is highlighted. Results: This manuscript focuses on the cutting-edge developments in the microstrip antenna technology and facilitates various modern designated extents, which provide the readers an insight into the tractability presented by microstrip antennas and their prospective benefits as compared to different types of other antennas like lens antenna, dish antenna, horn antenna, etc. The recent advancements in manufacturing techniques of microstrip antenna are reviewed. A large number of publications on the applications of microstrip antennas, such as communication, sensing, energy harvesting, biomedical relevance etc. are also included to show their importance at present. Conclusion: This article presents a state of the art evaluation of the research carried out on microstrip antennas from the time of their inception to till date. It consolidates the information for the researchers working in this field and will be helpful in enhancing the efforts for the research.

Background: The Open Cloud Computing Alliance (OCCA) strives for more Cloud Computing Service Providers (CCSP) to join the alliance. OCCA only requires CCSP to provide virtual computing resources and does not care about the methods of the underlying implementation, which leads the open-source cloud computing to a larger scale and more efficient. Due to the differences in service modes and service categories, the cloud computing platforms formed by CCSP are heterogeneous. How to implement tasks across platforms and ensure the quality of migration are the key issue for sharing the OCCA platform. Methods: The Mobile Agent technology based on a domain is introduced. User tasks are encapsulated into Mobile agent packets by domain client, which realizes the migration of user tasks from one platform to another, and makes it possible to interoperate between OCCA virtual machines. To ensure the service quality of OCCA better, a five-layer logical model of R-OCCA with high commercial availability is proposed, which defines the service content of each layer and gives the setting of key parameters. This paper introduces the architectural composition and operational mechanism of the model, which carries out a qualitative analysis of the model, and establishes an experimental prototype to verify the feasibility of the model on the virtual machine platform. Results: Experiments show that it is feasible to implement Cloud Computing Alliance among cloud computing platforms through Mobile Agent under the existing technical conditions. Conclusion: To better guarantee the quality of OCCA service, a five-level R-OCCA logic model with strong commercial availability is proposed. The service content of each level is defined and the key parameters are given. From the CCSP income, the rationality of the model set is explained. The feasibility of the model was analyzed. The architectural composition and operational mechanisms of the model are introduced. The performance of the model was also analyzed.

The Vector control scheme widely used for control purposes of PMSM drives requires rotor position information. Generally, sensors are used for this purpose, which increases the cost, size, and complexity of the system and also reduces the efficiency of drives. Therefore, it has become essential to avoid the use of these sensors and go for sensorless drives. In this paper, different types of speed and position estimation techniques are reviewed for sensorless control with their recent developments and their inherent advantages and disadvantages.

Background: Winding deformation is one of the most common faults in power transformers, which seriously threatens the safe operation of transformers. In order to discover the hidden trouble of transformer in time, it is of great significance to actively carry out the research of transformer winding deformation detection technology. Methods: In this paper, several methods of winding deformation detection with on-line detection prospects are summarized. The principles and characteristics of each method are analyzed, and the advantages and disadvantages of each method as well as the future research directions are expounded. Finally, aiming at the existing problems, the development direction of detection method for winding deformation in the future is prospected. Results: The on-line frequency response analysis method is still immature, and the vibration detection method is still in the theoretical research stage. Conclusion: The ΔV − I1 locus method provides a new direction for on-line detection of transformer winding deformation faults, which has certain application prospects and practical engineering value.

Introduction: Incomplete data sets containing some missing attributes is a prevailing problem in many research areas. The reasons for the lack of missing attributes may be several; human error in tabulating/recording the data, machine failure, errors in data acquisition or refusal of a patient/customer to answer few questions in a questionnaire or survey. Further, clustering of such data sets becomes a challenge. Objective: In this paper, we presented a critical review of various methodologies proposed for handling missing data in clustering. The focus of this paper is the comparison of various imputation techniques based FCM clustering and the four clustering strategies proposed by Hathway and Bezdek. Methods: In this paper, we imputed the missing values in incomplete datasets by various imputation/ non-imputation techniques to complete the data set and then conventional fuzzy clustering algorithm is applied to get the clustering results. Results: Experiments on various synthetic data sets and real data sets from UCI repository are carried out. To evaluate the performance of the various imputation/ non-imputation based FCM clustering algorithm, several performance criteria and statistical tests are considered. Experimental results on various data sets show that the linear interpolation based FCM clustering performs significantly better than other imputation as well as non-imputation techniques. Conclusion: It is concluded that the clustering algorithm is data specific, no clustering technique can give good results on all data sets. It depends upon both the data type and the percentage of missing attributes in the dataset. Through this study, we have shown that the linear interpolation based FCM clustering algorithm can be used effectively for clustering of incomplete data set.

Background: Ventricular Arrhythmias, one of the fatal heart diseases, requires timely recognition. The nonlinear and random nature of heart rate makes the diagnosis challenging. Introduction: The research work in this paper is divided into three phases. In the first phase, classification of some of the ventricular arrhythmias is done in four classes as Premature Ventricular Contraction (PVC), Left Bundle Branch Block (LBBB) and Right Bundle Branch Block (RBBB) with some Normal (N) samples and the analysis of classifying algorithms to improve the classifiers accuracy. A Support Vector Machine (SVM), Random Forest, Artificial Neural Network (ANN), and K Nearest Neighbor (KNN) algorithms were used to train and test the classifier, with the help of online available MIT-BIH Arrhythmia Database. Then, in the second phase, the variance analysis of the data is carried out using Principle Component Analysis (PCA) to improve the classifier performance. In the last phase, the whole process is repeated after including Quadratic features with the best performing classifier only. Methods: Signal processing, generation of Heart Rate Variability (HRV) signals from the available Electrocardiogram (ECG) signals and training, testing of ANN classifier was done in MATLAB environment, and the training and testing of SVM, and Random Forest classifier was done in R project software. Results: Random Forest shows the best result among all classifiers with 86.11% accuracy, 87.1% after applying PCA with top 16 features, and 91.4% after including quadratic features with top 28 features. Conclusion: The present study envisages helping ECG and HRV data analyses while selecting the AI techniques for classification purposes according to data.

Background: The Remote Terminal Units (RTUs) in the Distribution Automation System (DAS) are widely used in the field in recent years. It is lack of sample data in different operation status that makes the RTU maintenance improper. The weight allocation for the monitoring indicators in the health status evaluation needs to be identified efficiently and properly. Methods: A systematic health status assessment indicator system is constructed firstly. Then, a hybrid indicator weight allocation algorithm based on the Attribute Hierarchy Model (AHM) and grey relational degree (GRA) is proposed to identify the elementary item in the weight allocation under small sample condition. The final indicator weight would be dynamically adjusted according to the equilibrium coefficient, which is determined by the indicator condition parameter. Results: The simulation results show that the weight allocation can be effectively and reasonably adjusted according to the indicator value even under small sample condition. Conclusion: The expert experience and objective data laws are combined and used in our proposed dynamic weight allocation method. It can be used to assess the health status of RTU in the electrical power distribution network.

Background: This paper presents the comparative study of power dissipation, delay and power delay product (PDP) of different full adders and multiplier designs. Methods: Full adder is the fundamental operation for any processors, DSP architectures and VLSI systems. Here ten different full adder structures were analyzed for their best performance using a Mentor Graphics tool with 180nm technology. Results: From the analysis result high performance full adder is extracted for further higher level designs. 8T full adder exhibits high speed, low power delay and low power delay product and hence it is considered to construct four different multiplier designs, such as Array multiplier, Baugh Wooley multiplier, Braun multiplier and Wallace Tree multiplier. These different structures of multipliers were designed using 8T full adder and simulated using Mentor Graphics tool in a constant W/L aspect ratio. Conclusion: From the analysis, it is concluded that Wallace Tree multiplier is the high speed multiplier but dissipates comparatively high power. Baugh Wooley multiplier dissipates less power but exhibits more time delay and low PDP.

Background: Due to the openness of wireless fading channel, it is easy to be disturbed by other transmission signals and noises. Encryption and decryption can guarantee the security of signals, and Physical Layer Security (PLS) which uses the features of fading channels itself to ensure the security of signal transmission has also been widely concerned. In addition, considering the wide applications of Κ-μ shadowed distribution model and the advantages of Multiple-Input Multiple- Output (MIMO) technology, the confidentiality over Single-Input Multiple-Output (SIMO) independent Κ-μ shadowed model has been studied. Objective: To introduce the factors affecting the confidentiality on SIMO independent Κ-μ shadowed model. Methods: Novel representations of the lower bound on SPSC and SOP are deduced over independent Κ-μ shadowed model. The method of moment matching to deal with infinite series is adopted. Results: Through theoretical simulation and statistical simulation, the validity of our analysis is verified. We also get the curves for SOP and SPSC when the parameters of the channel change. Conclusion: Under the condition of larger P, large L , large μD , large mD and small kD can improve the secrecy performance on independent Κ-μ shadowed network.

Background: This paper presents an optimal power delivery system for a hybrid microgrid consisting of a solar PV, wind farm, battery storage and diesel generator. The fuzzy logicbased control approach is used to match the generation and consumers’ demand. Methods: The load demand is assumed to vary hourly in a day and season to season in a year. The frequency of AC (alternating current) bus may deviate from standard frequency due to supplydemand imbalance and thus make the system unstable. Results: To overcome the situation, the controller actuates a control signal to maintain system frequency. Frequency deviation is an indication of the load change and battery voltage (state of charge) is taken as input. In case of excessive generation, the extra power will be absorbed in the dump load for an isolated system. Conclusion: Whereas, for a grid-connected system, the surplus generation is fed into the grid. This cost-effective control method ensures the balance between generation and load demand at all times.

Background: The MEMS scanning mirror prototype is a spatial scanning device, which has advantages such as light mass, low drive voltage, large scanning and high angular measurement accuracy. Methods: The MEMS scanning mirror prototype uses the piezoelectric driving principle to drive the micro-structure to realize two-axis scanning. The corner of the MEMS scanning mirror is measured by using a piezoelectric resistance sensor. In the paper, the damping properties of MEMS scanning mirrors have been studied, which deduce the damping force formula of MEMS scanning mirrors. Moreover, the influence of different sizes and structures of MEMS scanning mirrors on the damping force and the amplitude of scanning mirror angles are analyzed, and a structural optimization design method to reduce the driving voltage of MEMS scanning mirrors is proposed. Results: The theoretical analysis, design and testing of piezoelectric driven MEMS scanning microscopes have been carried out. Conclusion: Through related experiments, it is verified that the maximum scanning range and the precision index of angle measurement meet the requirements of the index.

Background: This article studies the issue of adaptive neural dynamic surface control for the chaotic permanent magnet synchronous motor system with constrained output, external disturbances and parameter perturbations. Methods: Firstly, a virtual controller and two practical controllers are created based on the backstepping framework. In the process of creating controllers, adaptive technique and radial basis function neural networks are used to handle unknown parameters and nonlinearities, respectively. The nonlinear damping items are applied to overcome external disturbances. The barrier Lyapunov function is used to prevent the violation of system output constraint. Meanwhile, the first-order filter to eliminate the “explosion of complexity” of traditional back stepping has been introduced. Then, it is proved that all the closed-loop signals are uniform ultimate asymptotic stability and the tracking error converges to a small set of origin. Results: The effectiveness and robustness of the developed approach are illustrated by numerical simulations. Conclusion: The raised control scheme is a useful tool for enhancing the performance of the chaotic PMSM system with external disturbances, constrained output and parameter perturbations.

Background: Remote area electrification is a social responsibility that needs to be catered by research fraternity. One of the most viable technology as a solution is the Renewable Energy Source (RES) based power generation. However, RES is intermittent and thus, mostly ineffective without an energy storage device. Energy storage device comes at increased cost and may not be a cost-effective solution to the problem. Introduction: One solution that has been frequently proposed to reduce the intermittency of RES is hybridization. Hybridization of RES such as Wind Energy Conversion System (WECS) with Solar Energy Conversion System (SECS) is the most basic solution offered owing to their complementary nature. Therefore, this paper sees SECS in the role of supporting WECS in regions with highly intermittent wind conditions. In this paper, a novel technique of hybridization of WECS with SECS has been proposed. Methods: The basic idea of the paper is to control the dc-link voltage from the generation side by regulating the power generated by RES as per load demand using minimum components. The underlined principle is the relative lower time constant of solar panel and battery system in comparison to a wind turbine. Results: The experimental results on the proposed system shows that the SECS supports the WECS at higher wind turbulence and low wind conditions. Conclusion: This unique feature of the proposed system enables a WECS supported by a small rated SECS to attain high power reliability and thus, suitable for application such as remote area electrification.

Aims: Two evolutionary algorithms consist of Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are being used for finding the best value of critical parameters in AGIDS which will affect the accuracy and efficiency of the algorithm. Background: Adaptive Group of Ink Drop Spread (AGIDS) is a powerful algorithm which was proposed in fuzzy domain based on Active Learning Method (ALM) algorithm. Objective: The effectiveness of AGIDS vs. artificial neural network and other soft-computing algorithms has been shown in classification, system modeling and regression problems. Methods: For solving a real-world problem a tradeoff should be taken between the needed accuracy and the available time and processing resources. Results: The simulation result shows that optimization approach will affect the accuracy of modelling being better, but its computation time is rather high. Conclusion: The simulation shows that AGIDS algorithm has a suitable efficacy in solving complex problems without using complex optimization algorithms. Other: The simulation shows that AGIDS algorithm has a suitable efficacy in solving complex problems without using complex optimization algorithms.

Background: A multifunctional power factor device based on the FFT algorithm has been designed. The digital panel can display power factor, voltage, current, frequency, phase angle, active power and reactive power. Objective: To solve the influence of the harmonic interference and the aperiodic component on the accuracy of power factor measurement. Methods: In this paper, by combining a fixed-point 256-point FFT algorithm and taking STM32 as the core microcontroller, the hardware circuit and the software program are designed respectively. The hardware circuit is tested and analyzed in practice. Among them, the hardware circuit mainly includes the main circuit design, STM32 control circuit design, EMI and second-order RC filter circuit design, sampling circuit design, and signal conditioning circuit design. The software program mainly includes the main program, AD conversion subroutine, voltage and current acquisition subroutine, LCD display subroutine and twirl factor array. FFT algorithm is achieved by the table look-up method. Results: Finally, the hardware circuit is built and the software program is debugged to test the designed device. The experimental results show that the designed power factor instrument meets the task requirements under the different types of loads. Conclusion: After processing and analyzing the measurement results, it can be concluded that: under the pure resistive load, the maximal relative error of electrical parameters is 4.49%; and under the resistive inductive load, the maximal relative error of electrical parameters is 2.86%. Both results meet the design requirements.

Background: High-Efficiency Video Coding (HEVC) is a recent video compression standard. It provides better compression performance compared to its predecessor, H.264/AVC. However, the computational complexity of the HEVC encoder is much higher than that of H.264/AVC encoder. This makes HEVC less attractive to be used in real-time applications and in devices with limited resources (e.g., low memory, low processing power, etc.). The increased computational complexity of HEVC is partly due to its use of a variable size Transform Unit (TU) selection algorithm which successively performs transform operations using transform units of different sizes before selecting the optimal transform unit size. In this paper, a fast transform unit size selection method is proposed to reduce the computational complexity of an HEVC encoder. Methods: Bayesian decision theory is used to predict the size of the TU during encoding. This is done by exploiting the TU size decisions at a previous temporal level and by modeling the relationship between the TU size and the Rate-Distortion (RD) cost values. Results: Simulation results show that the proposed method achieves a reduction of the encoding time of the latest HEVC encoder by 16.21% on average without incurring any noticeable compromise on its compression efficiency. The algorithm also reduces the number of transform operations by 44.98% on average. Conclusion: In this paper, a novel fast TU size selection scheme for HEVC is proposed. The proposed technique outperforms both the latest HEVC reference software, HM 16.0, as well as other state-of-the-art techniques in terms of time-complexity. The compression performance of the proposed technique is comparable to that of HM 16.0.

Background: With the development and innovation of digital information technologies and new-generation Internet information platforms, new types of information exchange methods have been spawned. It has broken the restriction of the traditional internet boundary, and integrated all round connections between people and objects. Methods: Based on the above progresses, digital multimedia contents distributed or published much more convenient on the internet than before and most of them without any copyright protection. The dishonest owner can easily copy and distribute digital multimedia content without reducing any perceptual quality. According to the relative concerns, watermark protocol networks play a very important role in the usage tracking and copyrights infringement authentication, etc. However, most of the watermark protocols always require a “fully trusted third party”, which has a potential risk to suffer conspiracy attack. Results: Therefore, in this paper, we focus on designing a watermark protocol with trustless third party via blockchain for protecting copyrights of owners that they want to publish or distribute on the internet. The proposed watermark protocol includes three sub-protocols which covers the negotiation process, transaction process and identification processes. Conclusion: In addition, this paper also provides a fully detail analysis that describes the benefits and weaknesses of current solution.