2020 International Electronics Symposium (IES)最新文献_第5页

Risk Diagnosis and Mitigation System of COVID-19 Using Expert System and Web Scraping 基于专家系统和Web抓取的新型冠状病毒肺炎风险诊断与缓解系统

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/IES50839.2020.9231619

M. Mufid, A. Basofi, Saniyatul Mawaddah, K. Khotimah, N. Fuad

{"title":"Risk Diagnosis and Mitigation System of COVID-19 Using Expert System and Web Scraping","authors":"M. Mufid, A. Basofi, Saniyatul Mawaddah, K. Khotimah, N. Fuad","doi":"10.1109/IES50839.2020.9231619","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231619","url":null,"abstract":"The Novel Coronavirus that just appeared at the end of 2019 was named SARS-COV-2 which caused a pandemic of a respiratory disease known as COVID-19. In Indonesia itself, there was a case of COVID-19 first announced on March 2, 2020. The spread of COVID-19 in Indonesia is so fast because of one factor namely the lack of knowledge about COVID-19 prevention and early detection. This study will discuss the system to provide the latest information about the development of the COVID-19 case in Indonesia and help the community to conduct an independent detection of COVID-19 using an expert system. Information that will later be displayed on this application is obtained by web scraping techniques from the official website of the task force for the acceleration of handling COVID-19 in Indonesia. This system also has an early detection feature using the rule base method expert system. The results of this system are obtained from the responses of respondents and the results of respondents interested in this application with a percentage of 95.12%, and testing about the validation of the results of the expert system is the same as expected.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131153882","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: 9

Reverse Engineering WSPR on VHF Frequency Band VHF频段反向工程WSPR

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/IES50839.2020.9231786

Fikri Paramadina, T. Dutono, T. Santoso

引用次数: 2

Mobile-based Smart Parking Reservation System with Rate Display Occupancy Using Heuristic Algorithm and Haversine Formula 基于启发式算法和Haversine公式的基于率显示占用的移动智能车位预约系统

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/IES50839.2020.9231654

Rizka Safitri, Aries Pratiarso, Ahmad Zainudin

{"title":"Mobile-based Smart Parking Reservation System with Rate Display Occupancy Using Heuristic Algorithm and Haversine Formula","authors":"Rizka Safitri, Aries Pratiarso, Ahmad Zainudin","doi":"10.1109/IES50839.2020.9231654","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231654","url":null,"abstract":"Nowadays, the number of private vehicles increase significantly and cause the congestion. And as the result, almost all of the people have the same problem in failing to get a vacant parking slot People usually need to take time for about 30 minutes just to obtain a vacant parking slot. In this paper, we tackle this urgent issue and propose a Smart Parking Reservation System with Rate Display Occupancy denoted as SORAY. Our system uses simulated annealing based heuristic algorithm to optimize the queue method by considering three parameters such as the driver status (member or non-member), distance, and parking duration. This system also uses the Haversine formula to calculate the distance from the current position of the vehicle to the parking lot at the time of sending the reservation request. As the proof of reservation verification process, SORAY uses Quick Response Code. This SORAY system is also equipped with a secure member registration process by implementing SHA-256 algorithm to generate random OTP. The graph of the occupancy rate is displayed to predict the density of vehicles in the parking lot. Results show that this system successfully decreases the time needed to make a reservation process by almost 20 times faster than the conventional method for searching parking slots. For the simulation results, the heuristic method works and got the smallest cost: 1.97 with the condition of driver who makes a reservation was a member and has an hour parking duration with 5.4 kilometers distance. The results show that the average time to compute the SHA-256 java code for generating random OTP is 4.10 seconds.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130285746","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

Potato Leaf Disease Classification Using Deep Learning Approach 马铃薯叶病分类的深度学习方法

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/IES50839.2020.9231784

Rizqi Amaliatus Sholihati, I. A. Sulistijono, Anhar Risnumawan, Eny Kusumawati

引用次数: 46

Keynote Speakers 主旨发言人

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/ies50839.2020.9231783

Abel Bliss

{"title":"Keynote Speakers","authors":"Abel Bliss","doi":"10.1109/ies50839.2020.9231783","DOIUrl":"https://doi.org/10.1109/ies50839.2020.9231783","url":null,"abstract":"The real-world big data are largely unstructured, interconnected, and dynamic, in the form of natural language text. It is highly desirable to transform such massive unstructured data into structured knowledge. Many researchers rely on labor-intensive labeling and curation to extract knowledge from such data. However, such approaches may not be scalable, especially considering that a lot of text corpora are highly dynamic and domain-specific. On the other hand, massive text data itself may disclose a large body of hidden patterns, structures, and knowledge. Equipped with domain-independent and domain-dependent knowledge-bases, we should explore the power of massive data itself for turning unstructured data into structured knowledge. By organizing massive text documents into multidimensional text cubes, structured knowledge can be extracted and used effectively. In this talk, we introduce a set of methods developed recently in our group for such an exploration, including mining quality phrases, entity recognition and typing, multi-faceted taxonomy construction, and construction and exploration of multi-dimensional text cubes. We show that data-driven approach could be a promising direction at transforming massive text data into structured knowledge. Biography Jiawei Han is Abel Bliss Professor in the Department of Computer Science, University of Illinois at UrbanaChampaign. He has been researching into data mining, information network analysis, database systems, and data warehousing, with over 900 journal and conference publications. He has chaired or served on many program committees of international conferences in most data mining and database conferences. He also served as the founding Editor-In-Chief of ACM Transactions on Knowledge Discovery from Data and the Director of Information","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126999110","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

Estimation State of Charge (SOC) of Ultracapacitor Based On Classical Equivalent Circuit Using Extended Kalman Filter 基于经典等效电路的扩展卡尔曼滤波超级电容器荷电状态估计

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/IES50839.2020.9231736

Achmad Afandi, B. Sumantri, N. Windarko

引用次数: 1

Surveillance System for Illegal Fishing Prevention on UAV Imagery Using Computer Vision 基于计算机视觉的无人机图像防非法捕捞监控系统

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/IES50839.2020.9231539

Agus Prayudi, I. A. Sulistijono, Anhar Risnumawan, Zaqiatud Darojah

{"title":"Surveillance System for Illegal Fishing Prevention on UAV Imagery Using Computer Vision","authors":"Agus Prayudi, I. A. Sulistijono, Anhar Risnumawan, Zaqiatud Darojah","doi":"10.1109/IES50839.2020.9231539","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231539","url":null,"abstract":"Indonesia has a vast ocean with an abundance of fishes with its natural environments. Those abundances have to be conserved to prevent further destruction of the environment, which can result in the extinction of the surrounding living things. The government had deployed a vessel monitoring system, but illegal fishing still hardly been controlled. In this paper, toward conserving the fishes and especially the environment, we present a surveillance system framework from aerial images using drones technology. We develop a surveillance system using only visual information from the camera installed on the UAV and the design of the convolutional layer for accurate detection. Parameters are learned automatically without manually hand-tuned parameters because the learning process is pure from visual data that learned, so that makes the surveillance and investigation process easier. Experiment show relatively well that the proposed method successfully reaches Average Precision (AP)=75.03%, and hull plate classification reaches Average Matching Precision (AMP)=96.44%, and we believe it could bring many benefits for the ministry of fisheries and marine affairs Indonesia for identifying the illegal vessels and reduce the number of illegal fishing.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131059631","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: 8

IES 2020 Cover Page IES 2020封面

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/ies50839.2020.9231885

引用次数: 0

Convolutional Neural Network for Automatic Pneumonia Detection in Chest Radiography 基于卷积神经网络的胸片肺炎自动检测

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/IES50839.2020.9231540

Septy Aminatul Khoiriyah, A. Basofi, A. Fariza

{"title":"Convolutional Neural Network for Automatic Pneumonia Detection in Chest Radiography","authors":"Septy Aminatul Khoiriyah, A. Basofi, A. Fariza","doi":"10.1109/IES50839.2020.9231540","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231540","url":null,"abstract":"X-ray imagery is a non-invasive method that involves exposure to small doses of ionizing radiation to parts of the body to help doctors diagnose diseases, including pneumonia. Detecting pneumonia on a chest X-ray image can be difficult for radiologists because X-ray images are often unclear, overlap with other diagnoses, and approach many other abnormalities. The automated method was developed as a decision support tool to help doctors diagnose pneumonia. This paper proposes different deep convolution neural network architectures with an augmentation strategy to classify the pneumonia detection from the chest X-ray images. We use three convolution layers and three classification layers (fully connected). Resize, flip, and rotation augmentation strategy to avoid overfitting. The experiment result shows that the augmentation strategy on the proposed CNN's architecture results in an accuracy value of 83,38% while on without augmentation result accuracy value 80,25%. The small difference between prediction results with the augmentation strategy and without the augmentation strategy shows that the proposed CNN's architecture can train small datasets.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116419933","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: 11

Detection and Prognosis Evaluation of Diabetic Retinopathy using Ensemble Deep Convolutional Neural Networks 基于集成深度卷积神经网络的糖尿病视网膜病变检测及预后评价

2020 International Electronics Symposium (IES) Pub Date : 2020-09-01 DOI: 10.1109/IES50839.2020.9231789

S. Sridhar, Sowmya Sanagavarapu

{"title":"Detection and Prognosis Evaluation of Diabetic Retinopathy using Ensemble Deep Convolutional Neural Networks","authors":"S. Sridhar, Sowmya Sanagavarapu","doi":"10.1109/IES50839.2020.9231789","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231789","url":null,"abstract":"Diabetic Retinopathy is a condition that occurs in the eye as a result of diabetes in patients. Due to uncontrolled blood sugar levels in patients, there would be a lack of blood flow and oxygen to the retina. This causes strain on blood vessels some extent without invasive treatment and when detected in its early stages. When the strain in the blood vessels increases, it may cause leakage of fluids from blood vessels and loss of proper vision in the eye. This system implements a deep learning model using ResNet to determine the performance for the detection of the various stages of the condition in individuals. Individual submodels are built using ResNet to detect the presence of Diabetic Retinopathy and are ensembled together using the AdaBoost Classifier. Multiclass classification ResNet models are built and stacked together to detect the prognosis of Diabetic Retinopathy. The implemented models showed a performance accuracy of 78.88% to detect the presence and 61.9% to evaluate the prognosis of Diabetic Retinopathy. The performance of the trained models is visualised with a Grad-CAM and the results are analysed.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121217871","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: 6