2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)最新文献_第5页

Performance Evaluation of Data Center Network with Network Micro-segmentation 基于网络微分段的数据中心网络性能评估

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271749

Muhammad Mujib, R. F. Sari

{"title":"Performance Evaluation of Data Center Network with Network Micro-segmentation","authors":"Muhammad Mujib, R. F. Sari","doi":"10.1109/ICITEE49829.2020.9271749","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271749","url":null,"abstract":"Research on the design of data center infrastructure is increasing, both from academia and industry, due to the rapid development of cloud-based applications such as search engines, social networks, and large-scale computing. On a large scale, data centers can consist of hundreds to thousands of servers that require systems with high-performance requirements and low downtime. To meet the network's needs in a dynamic data center, infrastructure of applications and services are growing. It takes a process of designing a network topology so that it can guarantee availability and security. One way to surmount this is by implementing the zero trust security model based on micro-segmentation. Zero trust is a security idea based on the principle of \"never trust, always verify\" in which no concepts of trust and untrust in network traffic. The zero trust security model implemented network traffic in the form of untrust. Micro-segmentation is a way to achieve zero trust by dividing a network into smaller logical segments to restrict the traffic. In this research, data center network performance based on software-defined networking with zero trust security model using micro-segmentation has been evaluated using a testbed simulation of Cisco Application Centric Infrastructure by measuring the round trip time, jitter, and packet loss during experiments. Performance evaluation results show that micro-segmentation adds an average round trip time of 4 μs and jitter of 11 μs without packet loss so that the security can be improved without significantly affecting network performance on the data center.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131201394","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: 5

Radiation Performances of Side Reduced Terahertz Dielectric Silicon Lens Antenna 侧减太赫兹介质硅透镜天线的辐射性能

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271706

C. Apriono, Farida Ulfah

{"title":"Radiation Performances of Side Reduced Terahertz Dielectric Silicon Lens Antenna","authors":"C. Apriono, Farida Ulfah","doi":"10.1109/ICITEE49829.2020.9271706","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271706","url":null,"abstract":"Although the use of a dielectric lens has shown the gain improvement, the hemispherical shape gives other considerations, which are an effective function of the whole lens, and occupied size just for one sensor. This research proposes a size reduction technique to reduce lens size. The reduced size consideration is necessary to provide an as small as possible sensor of a planar crossed bowtie feeding antenna at a working frequency of 1 THz that radiates THz wave radiation and then collimated by a hemispherical dielectric silicon lens. The initially considered lens diameter and the extended dielectric thickness are 3000 µm and 1000 µm, respectively. This research conducts those investigations by using CST Microwave Studio. The results show that reduced performances of gain and radiation efficiency. However, the gain decreasing slowly at the beginning of the substrate reduction means that the expected gain remains to obtain. The gain still can be achieved at around 30 dB when the extension is about 1000 µm. This technique offers more suppressed side lobe levels and reduced the volume use of dielectric materials. The research can contribute to farther research to develop a compact THz wave sensor device based on a planar antenna and a quasi-optical dielectric lens.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128315622","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

Assessing Short Answers in Indonesian Using Semantic Text Similarity Method and Dynamic Corpus 基于语义文本相似度和动态语料库的印尼语短文答案评价

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271696

U. Hasanah, Bambang Pilu Hartato

{"title":"Assessing Short Answers in Indonesian Using Semantic Text Similarity Method and Dynamic Corpus","authors":"U. Hasanah, Bambang Pilu Hartato","doi":"10.1109/ICITEE49829.2020.9271696","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271696","url":null,"abstract":"Automatic assessment of short answers is one of the Computer Assisted Test works that can assess answers in natural language. Several methods have been used to create a system capable of assessing short answers that are close to human markings. In Indonesian, it might be easy to use string-based similarity methods by matching keywords, as has been done in previous studies. However, short answers have characteristics that focus on content, question type, and answer length, which cannot be accommodated only by string-based methods. This study aims to implement a hybrid method using corpus and string-based similarities. The Semantic Text Similarity (STS) method was used in this study to assess short answers in Indonesian. The STS method consists of three combinations of similarity methods, namely Normalized and Modified Longest Common Subsequence, Second Order Co-occurrence Pointwise Mutual Information, and Common Word Order Similarity. We also use a dynamic corpus with the advantage of being relatively small and adaptable to the learning domain. The Gensim Module is used to generate a dynamic corpus. The dynamic corpus uses the top five answers from students obtained from the Gensim module. The STS method is compared with the Cosine Similarity method since Cosine Similarity is the most commonly used method to assess answers in Indonesian. The results show that the STS method can outperform the Cosine Similarity method based on the Mean Absolute Error value, but still not outperformed in terms of correlation.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134544338","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: 2

Enhancement Methods of Brain MRI Images : A Review 脑MRI图像增强方法综述

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271785

Wirawan Setyo Prakoso, I. Soesanti, S. Wibirama

{"title":"Enhancement Methods of Brain MRI Images : A Review","authors":"Wirawan Setyo Prakoso, I. Soesanti, S. Wibirama","doi":"10.1109/ICITEE49829.2020.9271785","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271785","url":null,"abstract":"Image processing shows an important part of collecting information on brain images. Magnetic resonance imaging (MRI) technique provides important information for doctors to diagnose diseases. The image processing technique begins with image pre-processing to improve the quality of the original image. The procedures of images pre-processing cover artifact elimination, skull despoil, noise elimination, and image quality enhancement. Detecting tumors easily requires processed images. This study is a review of the current methods used in the process of enhancing the quality of brain MRI images. The study aims to review current methods for enhancing the quality of MRI images to identify the strengths and weaknesses of each method to proceed to the next stage in detecting tumors. The strengths and weaknesses of each method are considered in selecting the best method for handling a variety of different cases. The summary of each method is presented in a table followed by a brief explanation. This study reveals that the Average Intensity Reinstatement placed on Adaptive Histogram Equalization is the best pre-processing method for clinical datasets with the highest PSNR values of 87.370 and the Brainweb dataset shows that the combined Contrast Guided Interpolation and Iterative back-projection methods are the best pre-processing method with the highest PSNR values of 30.196. Meanwhile, Non-Local Means Filter is the best pre-processing method for the clinical dataset because it has the lowest MSE value of 0.025 compared to others.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114187136","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: 3

Modeling and Simulation to Improve 66 kV Overhead Transmission Lines Performance toward Lightning Strike 提高66千伏架空输电线路抗雷击性能的建模与仿真

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271667

A. Habibie, P. Pramana, A. S. Surya

引用次数: 1

An Efficient Hola Filter for Saliency Detection 一种用于显著性检测的高效Hola滤波器

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271690

Donyarut Kakanopas, K. Woraratpanya

引用次数: 3

Application of Ensemble Learning with Mean Shift Clustering for Output Profile Classification and Anomaly Detection in Energy Production of Grid-Tied Photovoltaic System 集成学习与均值移位聚类在并网光伏发电系统输出剖面分类与异常检测中的应用

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271699

Justin D. de Guia, Ronnie S. Concepcion, Hilario A. Calinao, Sandy C. Lauguico, E. Dadios, R. R. Vicerra

{"title":"Application of Ensemble Learning with Mean Shift Clustering for Output Profile Classification and Anomaly Detection in Energy Production of Grid-Tied Photovoltaic System","authors":"Justin D. de Guia, Ronnie S. Concepcion, Hilario A. Calinao, Sandy C. Lauguico, E. Dadios, R. R. Vicerra","doi":"10.1109/ICITEE49829.2020.9271699","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271699","url":null,"abstract":"Fault detection and monitoring system in photovoltaic (PV) energy management system is important in achieving its optimal performance. An effective diagnostic system involves correct analysis of electrical parameters of a PV array on a given weather condition. In the study, mean-shift clustering was applied for pre-classification and anomaly detection of time-series data of electrical parameters from grid-tied inverter, and solar-irradiance. Classification and anomaly detection applied is based in ensemble learning, where its base learners are based from multilayer perceptron. A stacking ensemble is used in classification of energy production profile while bagging ensemble is used detecting anomalous trend in time-series data. A stacking ensemble got a highest accuracy value of 94% compared to single classifiers which have accuracy value of 85.25%, 84.14%, and 63.4%, respectively. The bagging ensemble autoencoders have the lowest mean squared error during model reconstruction compared to single autoencoder. It has a fair performance in classifying anomaly points from normal datapoints, having an AUC value of 0.795 and F1-score of 0.71, given that the hyperparameter is 0.5. Overall, ensemble learners improve the performance in classification and detection tasks.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116762174","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: 7

Polynomial-Based Linear Programming Relaxation of Sensor Network Localization Problem 传感器网络定位问题的多项式线性规划松弛

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271716

T. Tamba, Y. Y. Nazaruddin

引用次数: 0

ICITEE 2020 TOC 这里2020 TOC

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/icitee49829.2020.9271689

引用次数: 0

Optimal Placement and Sizing Distributed Wind Generation Using Particle Swarm Optimization in Distribution System 基于粒子群算法的配电系统分布式风力发电布局优化

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271671

Muhammad Hasan Basri Paleba, Lesnanto Multa Putranto, S. P. Hadi

{"title":"Optimal Placement and Sizing Distributed Wind Generation Using Particle Swarm Optimization in Distribution System","authors":"Muhammad Hasan Basri Paleba, Lesnanto Multa Putranto, S. P. Hadi","doi":"10.1109/ICITEE49829.2020.9271671","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271671","url":null,"abstract":"Distributed Generation (DG) is a system of generating electricity from energy sources with small capacity, in this paper DG is generated from wind renewable energy source to reduce fossil fuel usage. DG has several functions such as power loss minimization and voltage profile improvement. In this study, location and size of wind-DG in the modified IEEE 33 bus test system were determined. Optimization procedure to minimize power loss and Voltage Deviation (VD) was formulated. There are two scenarios were simulated, there are one wind-DG and two wind-DG locations. The optimization was simulated using Particle Swarm Optimization (PSO) technique under MATLAB environment. The results were proven that the objective function satisfied. Furthermore, the total losses becomes 2.459 MWh in the first scenario and 2.209 MWh in the second scenario. Maximum VD value is on bus 18 with sample results in low load at 03:00 am and peak load at 07:00 pm, with a value 0.040 pu in the first scenario and 0.032 pu in the second scenario at 03:00 am. Then at 07:00 pm with a VD value 0.042 pu in the first scenario and 0.035 pu in second scenario.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124056460","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: 3