2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)最新文献

Covid-19 Detection Based-On CT-Scan Images Using Inception Deep Learning 基于Inception深度学习的ct扫描图像Covid-19检测

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935633

S. Riyadi, Tety Dwi Septiari, Cahya Damarjati, S. Ramli

{"title":"Covid-19 Detection Based-On CT-Scan Images Using Inception Deep Learning","authors":"S. Riyadi, Tety Dwi Septiari, Cahya Damarjati, S. Ramli","doi":"10.1109/ICCSCE54767.2022.9935633","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935633","url":null,"abstract":"The SARS-Cov-2 strain caused COVID-19, inflicting mild to moderate respiratory problems. The spread of COVID-19 is extremely fast which has resulted in the number of victims who have been declared dead to date, up to 2,587,225. There are several ways to reduce the spread of COVID-19, one of which is early detection. Currently, there are alternative methods used for early detection, one of which is the neural network method. Deep learning is one type of artificial neural network that is often used for the detection of several kinds of diseases. In this study, we classify CT-Scan images of the lungs based on two classes, namely CT_COVID and CT-NonCOVID, using two models, Inception-v3 and Inception-v4. The total CT-Scan image data used is 2038 and comes from the Kaggle.com website. Results obtained were then compared with standard performance metrics and then analyzed between the best models among the models used in the COVID-19 classification. From the results of the study, the Inception-v3 model obtained an average accuracy value of 93.96%, a precision value of 90.57%, a recall value of 95.65%, a specificity value of 92.81% and an f-score value of 92.51% and The Inception-v4 model obtained an average accuracy value of 86.41%, a precision value of 77.01%, a recall value of 91.18%, a specificity value of 83.77% and an f-score value of 83.38%. Based on the research results, the method with the best performance in COVID-19 classification is the Inception-v3 model because the Inception-v3 model has more layers, with a total of 48 layers and utilizes the idea of factorization that is more suitable for CT-Scan image classification which has low contrast visualization.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117170688","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

Cardiac Abnormality Prediction using Logsig-Based MLP Network 基于loglog的MLP网络心脏异常预测

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935583

Syahrull Hi-Fi Syam Ahmad Jamil, Abdul Rashid Alias, Mohamad Taufik A. Rahman, F.R. Hashim, S. Shaharuddin, Mohd. Sabri

引用次数: 2

Smart Health Monitoring using ECG, 3D-Accelerometer, GPS and IoT 使用ECG, 3d加速度计，GPS和物联网的智能健康监测

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935648

Roslan Seman, Asyraf Bin Dzulkipli, Zuraidi Saad

{"title":"Smart Health Monitoring using ECG, 3D-Accelerometer, GPS and IoT","authors":"Roslan Seman, Asyraf Bin Dzulkipli, Zuraidi Saad","doi":"10.1109/ICCSCE54767.2022.9935648","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935648","url":null,"abstract":"Due to the majority population of the earth is now connected online, our healthcare technology needs to keep on track with it. But the things that keep blocking our way to achieving better healthcare technology are connectivity, speed, and continuous monitoring from the doctors. The objective of this study is to develop a system for continuously recording and monitoring patient health parameters. The concerned doctor and the medical assistant can receive the information via the Internet. The patient's heart rate and movement are measured in this paper. ECG, 3D-Accelerometer, and GPS sensors are employed. The information can be uploaded to the cloud for additional review and recording. Another option is to implement a system that notifies the physician or medical assistant. To facilitate remote health monitoring via the Internet, remote health monitoring systems could be developed to gather data that can be analyzed by doctors who are in charge of monitoring the patient in case of a fall/collapse incident. It was suggested to use an IoT system to develop a Smart Wearable System (SWS) for tracking health. To provide a connection for the monitoring process, a WIFI shield is fixed to it. The outcome of this study can have a significant impact on the healthcare sector because it demonstrates the ability to prevent a critical incident in real time.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130773420","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

MRI Thigh Sequences in Determining the Tumor Size Using Fuzzy C-Means for Patients with Osteosarcoma MRI大腿序列在确定骨肉瘤患者肿瘤大小中的应用模糊c均值

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935630

Mohamad Haizan Othman, Belinda Chong Chiew Meng, N. S. Damanhuri, M. Aziz, N. A. Othman

{"title":"MRI Thigh Sequences in Determining the Tumor Size Using Fuzzy C-Means for Patients with Osteosarcoma","authors":"Mohamad Haizan Othman, Belinda Chong Chiew Meng, N. S. Damanhuri, M. Aziz, N. A. Othman","doi":"10.1109/ICCSCE54767.2022.9935630","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935630","url":null,"abstract":"Osteosarcoma is the common type of bone cancer in children and adolescents. A magnetic resonance imaging (MRI) is one of the medical imaging techniques used by specialist to diagnose the medical conditions of Osteosarcoma patient. A radiofrequency pulse and gradient sequence known as MRI sequence produces a set of pictures with a specific appearance. In clinical, radiologists need to interpret MRI images and correlating them from various sequences for medical image findings. The process requires a lot of human input and therefore it is subjective, time-consuming, and non-reproducible. Image segmentation can be used to automate MR images into different segments. In image processing, various algorithms used to segment the medical images into region. However, due to the overlap of grayscale pixel values make the segmentation process becomes very difficult and challenging. The purpose of this study is to extract tumor on MRI Osteosarcoma based on three MRI thigh sequences namely T1, T2 and T1_FSE+GADO. The area and perimeter of the extracted tumor are then compared with the ground truth. In this study, two algorithms namely OTSU Thresholding (OT) and Fuzzy C-Means (FCM) were used to perform the segmentation on the MRI Osteosarcoma images. The performance of these two algorithms on segmenting the MRI Osteosarcoma from three MRI sequences are compared and discuss. The result shows that FCM could discriminate the abnormal region better in T1_FSE+GADO sequence. The average percentage error for area in T1_FSE+GADO sequence is 6.20% and average percentage error for perimeter is 6.74% compared to T2 sequence which is 7.18% and 7.71%.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116337687","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

Output Feedback Stabilization of Nonholonomic Wheeled Mobile Robot Using Backstepping Control 基于反步控制的非完整轮式移动机器人输出反馈镇定

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935650

Muhammad Junaid Rabbani, A. Memon

引用次数: 0

Characterization of Flexible Piezoelectric Cantilever in Vibration Energy Harvesting 柔性压电悬臂梁在振动能量收集中的特性研究

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935665

Edgar Irwin Michael Pawing, K. A. Ahmad, S. Setumin, A. I. C. Ani, M. A. Idin, A. Ahmad, M. K. Osman, R. Boudville

{"title":"Characterization of Flexible Piezoelectric Cantilever in Vibration Energy Harvesting","authors":"Edgar Irwin Michael Pawing, K. A. Ahmad, S. Setumin, A. I. C. Ani, M. A. Idin, A. Ahmad, M. K. Osman, R. Boudville","doi":"10.1109/ICCSCE54767.2022.9935665","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935665","url":null,"abstract":"Nowadays, the increasing intention in the research community on small sized electrical energy generators due to the wide use of wireless sensor networks and the drawbacks of conventional chemical batteries, such as their limited lifespan and large physical dimensions. Therefore, the principle of harvesting energy from solar power, electromagnetic fields, wind and the human body have been introduced as alternatives. Among these energy resources, wind energy is clean, renewable and can be easily turned into mechanical vibrations that can be used to generate electrical energy via vibration-to-electrical energy conversion mechanisms using electromagnetic, electrostatic and piezoelectric transducers. From these transducers, piezoelectric materials have received the most attention because of their higher conversion efficiency. Therefore, flexible piezoelectric cantilever was tested for characterized cantilever in vibration energy harvesting. The parameters of the cantilever such as length, width and thickness were varied and investigated for energy conversion and performance. The piezoelectric cantilever was designed and simulated using COMSOL Multiphysics 5.5 tool. The simulation result and performance of each design was compared. Performances were plot based on generated voltage vs applied vibration frequency. Result shows that generated voltage of 4.3V at applied vibration frequency of 155Hz was the most optimal result compared to the rest of the design for a piezoelectric cantilever with the width, length and height of 30mm, 20mm and 0.2mm respectively. This was ideal as most of the devices nowadays uses 5V supply and the small design allows the piezoelectric cantilever to be portable or even easily installed in projects that utilizes it.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124095562","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

Facial Expression Electric Wheelchair Control Instruction Using Image Processing 基于图像处理的面部表情电动轮椅控制指令

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935639

Muhammad Faiz Ahmad Sobri, Z. Hussain, S. Z. Yahaya, R. Boudville, Noraiza Aqilah Abdul Aziz

{"title":"Facial Expression Electric Wheelchair Control Instruction Using Image Processing","authors":"Muhammad Faiz Ahmad Sobri, Z. Hussain, S. Z. Yahaya, R. Boudville, Noraiza Aqilah Abdul Aziz","doi":"10.1109/ICCSCE54767.2022.9935639","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935639","url":null,"abstract":"Tetraplegia is a type of paralysis that affects upper and lower limbs due to damage of spinal cord or brain. This condition causes difficulty to move and most of the time caretaker is needed to help the patients. This project proposed the design and implementation of an image processing technique in capturing and categorizing different facial gesture and use it as control instructions for electric wheelchair. The aim was to reduce the dependency to caretaker especially for mobility oftetraplegia patient. The deep learning Haar Cascade Classifier identify the expression of a face through image processing in livevideo capture. The Open Computer Vision (OpenCV) in Python was used to detect, recognize, and analyze the facial expression. Convolution Neural Network (CNN), a deep learning operation will act as trainer that analyze an open-source data to create a model as reference for the facial expression recognition. In orderto make the system operated as a standalone system, the Raspberry Pi module that connects with Pi Camera was used as the platform to capture the live video, perform processing, and produce the output control that give instructions to move such as forward, right, left and stop. Based on the analysis of the system performance, the system was capable to produce high accuracyof detection and correctly produce the electric wheelchair controlinstruction according to the facial expressions.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126474862","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

Liver Tumour Segmentation based on ResNet Technique 基于ResNet技术的肝脏肿瘤分割

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935636

Adelisa Sirco, A. Almisreb, N. Tahir, Jamil Bakri

引用次数: 2

Improvement of Voltage Stability in Power System using SVC 用SVC提高电力系统电压稳定性

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935625

Amirul Hakim Ramli, N. A. M. Leh, Shabinar Abdul Hamid, Z. Muhammad

{"title":"Improvement of Voltage Stability in Power System using SVC","authors":"Amirul Hakim Ramli, N. A. M. Leh, Shabinar Abdul Hamid, Z. Muhammad","doi":"10.1109/ICCSCE54767.2022.9935625","DOIUrl":"https://doi.org/10.1109/ICCSCE54767.2022.9935625","url":null,"abstract":"The increased demand for electricity has pushed the electrical grid closer to its stability limit. Due to many methods used to enhance the power system, voltage instability and line overloading have become a difficulty. The creation, transmission, and consumption of reactive power can all be used to investigate the nature of voltage stability. Reactive power unbalancing, which happens when the power system is strained, is one of the key reasons of voltage instability. Flexible AC transmission system (FACTS) devices are vital for enhancing the performance of a power system, but they are also quite expensive, thus they must be placed optimally in the power system. Static var compensator (SVC), a FACTS device, can be used to minimise flows in densely laden lines, resulting in minimal system loss and enhanced voltage stability. A method is proposed based on the index of line stability and overall system of VAR power losses was used to select the best position for the SVC device. Using VSI calculation on the power flow system, the weakest bus will be determined and will be assign as the optimal location for SVC. Also, along with this paper an observation on a power flow system with and without SVC are compared. Therefore, the finding of this research paper will show that SVC can stabilize the voltage profile of a power flow system.","PeriodicalId":346014,"journal":{"name":"2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129340634","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

Design a Speed Control for DC Motor Using an Optimal PID Controller Implementation of ABC Algorithm 基于ABC算法的最优PID控制器设计直流电机转速控制

2022 IEEE 12th International Conference on Control System, Computing and Engineering (ICCSCE) Pub Date : 2022-10-21 DOI: 10.1109/ICCSCE54767.2022.9935644

A. I. Tajudin, Muhammad Affi Daneal Izani, A. Samat, S. Omar, M. A. Idin

引用次数: 0