Serbian Journal of Electrical Engineering最新文献_第2页

Optimal siting of capacitors in distribution grids considering electric vehicle load growth using improved flower pollination algorithm 考虑电动汽车负荷增长的配电网电容器优化配置的改进授粉算法

Serbian Journal of Electrical Engineering Pub Date : 2022-01-01 DOI: 10.2298/sjee2203329j

Varaprasad Janamala

{"title":"Optimal siting of capacitors in distribution grids considering electric vehicle load growth using improved flower pollination algorithm","authors":"Varaprasad Janamala","doi":"10.2298/sjee2203329j","DOIUrl":"https://doi.org/10.2298/sjee2203329j","url":null,"abstract":"The optimal VAr compensation using capacitor banks (CBs) in radial distribution networks (RDNs) is solved in this paper while taking the growth of the load from electric vehicles (EVs) into consideration. This is accomplished by adapting an improved variant of the flower pollination algorithm (IFPA) with an enhanced local search capability. The primary objective of determining the locations and sizes of CBs is to minimize the distribution losses in the operation and control of RDNs. Additionally, the effect of CBs is shown by the increased net savings, greater voltage stability, and improved voltage profile. A voltage stability index (VSI) was used in the optimization process to determine the predefined search space for CB locations, and a double-direction learning strategy (DLS) was then considered to optimize the locations and sizes while maintaining a balance between the exploration and exploitation phases. Three IEEE RDNs were used to simulate various EV load increase scenarios as well as typical loading situations. According to a comparison with the literature, the IPFA produced global optimum results, and the proposed CBs allocation approach demonstrated enhanced performance in RDNs under all scenarios of EV load growth.","PeriodicalId":37704,"journal":{"name":"Serbian Journal of Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68755461","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}

引用次数: 0

Tumor detection using brain MRI and low-dimension co-occurrence feature approach 脑MRI与低维共现特征方法的肿瘤检测

Serbian Journal of Electrical Engineering Pub Date : 2022-01-01 DOI: 10.2298/sjee2203273m

Marta Mirkov, A. Gavrovska

{"title":"Tumor detection using brain MRI and low-dimension co-occurrence feature approach","authors":"Marta Mirkov, A. Gavrovska","doi":"10.2298/sjee2203273m","DOIUrl":"https://doi.org/10.2298/sjee2203273m","url":null,"abstract":"Research in medical imaging focuses on methods useful in computer-aided diagnosis systems. In modern times, these systems often have automatic detection of regions of interest, and imaging technologies offer numerous advantages, like the possibility of developing reliable assisting algorithms. Magnetic Resonance Imaging (MRI) provides compelling features for brain tumor detection due to good soft tissue contrast and has important clinical value. To help clinicians in making diagnoses, current algorithms for processing and medical image classification may depend on intricate deep learning designs that demand large hardware resources and lengthy execution times. This is with no doubt helpful in understanding disease mechanisms and in labeling difficult instances for brain tumor identification. On the other hand, statistical low-dimension feature sets including co-occurrence-based ones could be useful in dealing with tumor detection avoiding possible complexity. In this paper, statistical approaches for feature extraction and reduction are analyzed for MRI brain tumor classification, and the evaluation of the results is presented on one of the publicly available brain tumor detection database commonly used for machine learning tasks. Bayes and kNN classifiers are applied for the analysis, as well as four distance metrics, and two methods for feature reduction. The results seem promising in developing a simple and less hardware-demanding procedure.","PeriodicalId":37704,"journal":{"name":"Serbian Journal of Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68755375","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}

引用次数: 0

New catalysts for formic acid fuel cells 甲酸燃料电池的新型催化剂

Serbian Journal of Electrical Engineering Pub Date : 2022-01-01 DOI: 10.2298/sjee2203387s

Milica Spasojevic-Savkovic, Zoran Kićanović, P. Spasojevic, Milentije Luković

引用次数: 0

Snort ids system visualization interface for alert analysis 用于警报分析的Snort id系统可视化界面

Serbian Journal of Electrical Engineering Pub Date : 2022-01-01 DOI: 10.2298/sjee2201067g

Nadja Gavrilovic, V. Ciric, Nikola Lozo

{"title":"Snort ids system visualization interface for alert analysis","authors":"Nadja Gavrilovic, V. Ciric, Nikola Lozo","doi":"10.2298/sjee2201067g","DOIUrl":"https://doi.org/10.2298/sjee2201067g","url":null,"abstract":"Over the past decades, the rapid Internet development and the growth in the number of its users have raised various security issues. Therefore, it is of great importance to ensure the security of the network in order to enable the safe exchange of confidential data, as well as their integrity. One of the most important components of network attack detection is an Intrusion Detection System (IDS). Snort IDS is a widely used intrusion detection system, which logs alerts after detecting potentially dangerous network packets. A major challenge in network monitoring is the high volume of generated IDS alerts. A necessary step in successful network protection is the analysis of the great amount of logged alerts in search of deviations from normal traffic that may indicate an intrusion. The goal of this paper is to design and implement a visualization interface for IDS alert analysis, which graphically presents alerts generated by Snort IDS. Also, the proposed system classifies the alerts according to the most important attack parameters, and allows the users to understand evolving network situations and easily detect possible traffic irregularities. An environment in which the system has been tested in real-time is described, and the results of attack detection and classification are given. One of the detected attacks is analyzed in detail, as well as the method of its detection and its possible consequences.","PeriodicalId":37704,"journal":{"name":"Serbian Journal of Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68754862","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}

引用次数: 1

Feasibility test of activity index summary metric in human hand activity recognition 活动指标汇总度量在手部活动识别中的可行性检验

Serbian Journal of Electrical Engineering Pub Date : 2022-01-01 DOI: 10.2298/sjee2202225m

Jelena Medarevic, Marija M. Novičić, Marko Marković

{"title":"Feasibility test of activity index summary metric in human hand activity recognition","authors":"Jelena Medarevic, Marija M. Novičić, Marko Marković","doi":"10.2298/sjee2202225m","DOIUrl":"https://doi.org/10.2298/sjee2202225m","url":null,"abstract":"Activity monitoring is a technique for assessing the physical activity that a person undertakes over some time. Activity Index (AI) is a metric that summarizes the raw measurements from tri-axial accelerometers, often used for measuring physical activity. Our research compared the Activity Index for different activity groups and hand usage [1]. We also tested this metric as a classification feature, and how different data acquisition and segmentation parameter configurations influence classification accuracy. Data acquisition was done with a previously developed system that includes a smartwatch on each wrist and a smartphone placed in the subject?s pocket; raw data from smartwatch accelerometers was used for the analysis. We calculated the Activity Index for labeled data segments and used ANOVA1 statistical test with Bonferroni correction. Significant differences were found between cases of hand usage (left, right, none, both). In the next analysis phase, the Activity Index was used as the classification feature with three supervised machine learning algorithms-Support Vector Machine, k-Nearest Neighbors, and Random Forest. The best accuracy (measured by F1 score) of classifying hand usage was achieved by using the Random Forest algorithm, 50 Hz sampling frequency, and a window of 10 s without overlap for AI calculation, and it was 97%. On the other hand, the classification of activity groups had a low accuracy, which indicated that a specific activity group can?t be identified by using only one simple feature.","PeriodicalId":37704,"journal":{"name":"Serbian Journal of Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68755606","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}

引用次数: 0

Circularly polarized quasi-rectangular patch UWB antenna for GPR applications 探地雷达用圆极化准矩形贴片超宽带天线

Serbian Journal of Electrical Engineering Pub Date : 2022-01-01 DOI: 10.2298/sjee2203261c

A. Chaabane, M. Guerroui, Djelloul Aissaoui

引用次数: 1

Modeling and practical implementation of the optimal wireless security gateway for the industrial automation network 工业自动化网络最优无线安全网关的建模与实际实现

Serbian Journal of Electrical Engineering Pub Date : 2022-01-01 DOI: 10.2298/sjee2203303n

I. Nevliudov, S. Novoselov, O. Sychova

引用次数: 0

Data augmentation methods for semantic segmentation-based mobile robot perception system 基于语义分割的移动机器人感知系统的数据增强方法

Serbian Journal of Electrical Engineering Pub Date : 2022-01-01 DOI: 10.2298/sjee2203291j

Aleksandar Jokic, Lazar Djokic, Milica Petrović, Z. Miljković

引用次数: 0

C-V and I-V characterisation of CdS/CdTe thin film solar cell using defect density model 用缺陷密度模型表征CdS/CdTe薄膜太阳能电池的C-V和I-V特性

Serbian Journal of Electrical Engineering Pub Date : 2021-06-30 DOI: 10.2298/sjee2102255p

D. Pal, Soumee Das

引用次数: 4

Video coding and constant quality evaluation using 4k aomenc-AV1 and rav1e-AV1 formats 使用4k aomenc-AV1和rav1e-AV1格式的视频编码和恒定质量评估

Serbian Journal of Electrical Engineering Pub Date : 2021-06-30 DOI: 10.2298/sjee2102139m

M. Milivojević, D. Dujković, A. Gavrovska

{"title":"Video coding and constant quality evaluation using 4k aomenc-AV1 and rav1e-AV1 formats","authors":"M. Milivojević, D. Dujković, A. Gavrovska","doi":"10.2298/sjee2102139m","DOIUrl":"https://doi.org/10.2298/sjee2102139m","url":null,"abstract":"It is much expected from the relatively novel, open, royalty-free AV1\u0000 (Alliance for Open Media (AOMedia) Video 1) standard. At this moment, there\u0000 are many new variants of AV1 format. It is designed for efficient video\u0000 internet delivery and high-quality video transmission. AV1 is recognized as\u0000 Google?s VP9 format successor. One of the reference tools used so far for\u0000 testing AV1 is libaom- AV1. Nevertheless, due to its time-consuming\u0000 performance, there are now different available standalone solutions for\u0000 experimental analysis. Here, one such solution AOMedia?s standalone aomenc\u0000 (aomenc-AV1) is tested in order to analyze quality assessment based on\u0000 constant quality constraint factor. Three different metrics are calculated\u0000 for various 4k video content of the same frame rate. Moreover, rav1e\u0000 implementation was tested for the same visual data, where rav1e-AV1 also\u0000 represents an AV1 video encoder, which is considered reliable and suitable\u0000 in most cases, where libaom is not applicable. In this paper, the comparison\u0000 results between aomenc-AV1 and rav1e-AV1 are shown.","PeriodicalId":37704,"journal":{"name":"Serbian Journal of Electrical Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46510439","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}

引用次数: 0