A Study of Agriculture Value Added Percentage of Gross Domestic Product for Selected Asian Countries

Agriculture sector is considered most important sector our of primary sectors in any country. The basic needs of human being are to eat, salter and water. For hunger not just human being but all animal on planet is depend on agriculture sector so it is important to know that the growth of agriculture sector in the country. In this study Asian countries have been selected based on area on the earth. The selection of samples is considered as Russian which considered as highest area coverage on Asia after that China, India, Kazakhstan, Saudi Arabia, Indonesia and Iran selected for analysis purpose. The time period from 2006 to 2021 considered for the study. the major findings of the study was Russian , Kazakhstan and Saudi Arabia saw on an average constant trend of value added towards agriculture of GDP. Chine indicated decreasing trend whereas Iran in saw increasing trend of agriculture value added towards GDP. India is highest contributor of agriculture value added of GDP out of selected countries and Indonesia is on second position

Enhance Inverted Index Using in Information Retrieval

This paper proposes a method to represent the first step in information retrieval (IR) (that prepare the document set (preprocessing), In Information retrieval systems, tokenization is an integral part whose prime objective is to identify the token and their count. In this paper, an effective tokenization approach which is based on proposed new method called enhance inverted index (EII). The result shows that efficiency/ effectiveness of the proposed algorithm. Tokenization on documents helps to satisfy user’s information need more precisely and reduced search sharply, believed to be a part of information retrieval. Pre-processing of input document is an integral part of Tokenization, which involves preprocessing of documents and generates its respective tokens, which is the basis of these tokens. Probabilistic IR generates its scoring and gives reduced search space. The comparative analysis based on the two parameters; reduce the time of search space, Pre-processing tim

A Meta-Model to Predict and Detect Malicious Activities in 6G-Structured Wireless Communication Networks

Data Availability Statement: NSL_KDD, and UNSW_NB15 Dataset free downloaded from the link: http://www.di.uniba.it/~andresini/datasets.html, accessed on 18 February 2022. CICIDS2017 Dataset free downloaded from the link: http://205.174.165.80/CICDataset/CIC-IDS-2017/Dataset/, accessed on 24 June 2022, and SCE_CIC_IDS18Dataset free downloaded from the link: https://www.unb.ca/cic/datasets/ids-2018.html, accessed on 12 January 2022.Copyright © 2023 by the authors. The rapid leap in wireless communication systems incorporated a plethora of new features and challenges that accompany the era of 6G and beyond being investigated and developed. Recently, machine learning techniques were widely deployed in many fields, especially wireless communications. It was used to improve network traffic performance regarding resource management, frequency spectrum optimization, latency, and security. The studies of modern wireless communications and anticipated features of ultra-densified ubiquitous wireless networks exposed a risky vulnerability and showed a necessity for developing a trustworthy intrusion detection system (IDS) with certain efficiency/standards that have not yet been achieved by current systems. IDSs lack acceptable immunity against repetitive, updatable, and intelligent attacks on wireless communication networks, significantly concerning the modern infrastructure of 6G communications, resulting in low accuracies/detection rates and high false-alarm/false-negative rates. For this objective principle, IDS system complexity was reduced by applying a unique meta-machine learning model for anomaly detection networks was developed in this paper. The five main stages of the proposed meta-model are as follows: the accumulated datasets (NSL KDD, UNSW NB15, CIC IDS17, and SCE CIC IDS18) comprise the initial stage. The second stage is preprocessing and feature selection, where preprocessing involves replacing missing values and eliminating duplicate values, leading to dimensionality minimization. The best-affected subset feature from datasets is selected using feature selection (i.e., Chi-Square). The third step is represented by the meta-model. In the training dataset, many classifiers are utilized (i.e., random forest, AdaBoosting, GradientBoost, XGBoost, CATBoost, and LightGBM). All the classifiers undergo the meta-model classifier (i.e., decision tree as the voting technique classifier) to select the best-predicted result. Finally, the classification and evaluation stage involves the experimental results of testing the meta-model on different datasets using binary-class and multi-class forms for classification. The results proved the proposed work’s high efficiency and outperformance compared to existing IDSs.This research received no external funding

Simulation of adaptive gain control via 2-D lookup table for isolated hybrid micro-grid system

This paper presented a smartness 2-D lookup table (2-DLT) control by means of adaptation gain to develop a frequency controller and facilitate the power-sharing requirements in an isolated micro-grid system. This intelligence of an expert controller adopts the scale of adaptation gain for estimating control design. Synchronous power generators are commonly used to provide power to distant and isolated regions where grid expansion is expensive due to economic and technical constraints. Load frequency control (LFC) technology challenges to guarantee the reliability and stability regarding the system. It is known that conventional control methods are unreliable due to frequency variation and sudden changes in the load or failure generation. Traditional control and criteria may not be appropriate for the new structural networks, such as micro-grid. In this work, the performance of the proposed 2-DLT controller is examined and compared to the classical proportional integral (PI) controller and artificial neural network (ANN). The simulation system is implemented and tested using MATLAB/Simulink. © 2022, Institute of Advanced Engineering and Science

Advanced Techniques in Harmonic Suppression via Active Power Filter: A Review

This paper intends to present the recent development of artificial intelligence (AI) applications in active power filter (APF). As a result of the development in power electronic technology, (APF) continues to attract ample attention. Compared with the traditional reactive LC filter, active power filter is considered to be more effective in compensating harmonic current generated by nonlinear loads.APF, can correct the power quality and improve the reliability and stability on power utility. A brief explanation of some important areas in AI and a comprehensive survey of the literature along the main categories of AI is presented to introduce the readers into the wide-ranging topics that AI encompasses. Plenty of relevant literatures have been selected in the review, mostly emphasized on better accuracy, robustness, efficiency, stability and tracking ability of the system

Performance Analysis of Active Power Filter for Harmonic Compensation using PI-PSO

In the recent decades, the world has seen an expansion in the use of non-linear loads. These loads draw harmonic non-sinusoidal currents and voltages in the connection point with the utility and distribute them through it. A Shunt Active power filters (SAPF) have been proposed as efficient tools for power quality improvement and reactive power compensation. The simulated system is a three phase balanced voltage system with nonlinear load .A particle swarm optimization (PSO) is implemented to optimize the gains of a proportional-integral (PI) algorithm to control the SAPF. The control of the DC voltage of the APF is of great importance. The DC voltage passes by a transient after load variation. This transient is a function of the controller parameters and the load variation. The aim of this work is to determine if the control schemes will be able to adapt to the changing conditions. Different studied for SAPF are implemented in MATLAB\Simulink and results are tabulated and discussed. Results show that the proposed filter can effectively reduce harmonics while keeping its DC-link balanced

High-Penetration, without Storage, PV Solar-Diesel Generator In Isolated System

The aim of this paper is to reduce the cost of supplying electricity in remote area and to get optimal operation of the distribution network including renewable energy sources. In actual power system operations, the load is changing continuously and randomly, as the ability of the generation to track the changing load is limited due to physical/technical considerations, to maintain the desired active output power of a generator matching with the changing load, there results an imbalance between the actual and the scheduled generation quantities. In recent years, many facilities all over the world the move towards renewable energy uses. For example, wind or photovoltaic power (PV) is an alternative, a source of clean energy and sustainable electricity production. PV certainly does not need to be tall and strong tower, as well as lacking of any vibration or noise, and does not need to be refrigerated. On the other hand volatility and rising fuel prices with considerations of greenhouse gas emission, and carbon footprint reduction therefore, certain features make PV generation worthwhile to consider in planning and electricity network operations now and in the future. The simulation system model and tested using MATLAB/ Simulink and the results are presented

Shunt active power filter based on particle swarm optimization-wavelet transform and zero crossing controller

One of the serious problems with modern electrical loads is harmonics, which is generated from nonlinear loads. Harmonics can lead to excessive heat and noise in the loads and create large amount of energy losses either in transmission systems or distribution systems. Compensation of these harmonics substantially improves the power factor and reduces the total harmonic distortion index (THD). This means that the system can transfer more active power without having to increase the capacity. Traditionally, passive filters have been used to remove harmonics but for their intrinsic downsides, they have been replaced by active power filter (APF). APF has superior filtering characteristics and dynamic response compared to passive filters. Over the past decades, there has been a significant increase in interest of APFs and its control methods. There are three factors that drives the research in this thesis; (1) although many studies has proven that zero crossing information is crucial in many control signal, there have been no attempt on incorporating zero crossing controller (ZCC) in APF DC link voltage regulation, (2) Particle swarm optimization (PSO) has been adapted for DC link voltage regulation in APF, but there is lack of evidences of dynamic performance investigation for such techniques, and (3) Synchronous Reference Frame (SRF) has been widely adopted for harmonics extraction in APF, although it has been found out to have a slow response. Discrete Wavelet Transform (DWT) on the other hand, is a good candidate for harmonics extraction, but have not received enough attention in the literature due to its relatively high complexity. This study attempts to tackle these gaps by introducing ZCC, PSO and DWT as a new fusion of controller for APF. The new controller is thoroughly developed and rigorously simulated in MATLAB-Simulink environment. The harmonics source is a 5.5 kW nonlinear load mimicking a real-life load from previous practical studies. The test cases ranges from steady state, various loads, dynamic loads and unbalance voltage. The results show that DWT outperforms SRF in all test cases with average 53% improvement. It is also found out that the combination of PSO and DWT yield better results in general. It is a superior controller as compared to traditional Zeigler-Nichols tuned Proportional Integral (PIZN) controller and Fuzzy Logic Controller (FLC). However, ZCC-DWT consistently yields better performance than all other controller in one of the test case; the unbalance voltage. As conclusion, DWT is a better candidate for harmonics extraction in APF, as compared with SRF. Together with DWT, PSO and ZCC perform very well in different test cases. This new combination of controller is a good candidate to be widely accepted as a new controller in modern APF