2021 8th International Conference on Computer and Communication Engineering (ICCCE)最新文献

Advanced Adaptive PID Controller for BLDC Motor 先进的无刷直流电机自适应PID控制器

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/ICCCE50029.2021.9467185

Md Mahmud, S. Motakabber, A. H. M. Zahirul Islam, A. Nordin, S. A. Fawwaz Wafa

{"title":"Advanced Adaptive PID Controller for BLDC Motor","authors":"Md Mahmud, S. Motakabber, A. H. M. Zahirul Islam, A. Nordin, S. A. Fawwaz Wafa","doi":"10.1109/ICCCE50029.2021.9467185","DOIUrl":"https://doi.org/10.1109/ICCCE50029.2021.9467185","url":null,"abstract":"Brushless DC (BLDC) motors are very popular for applications in automation and electric vehicle systems due to their unique features. Although these motors have many advantages over conventional DC motors, they also suffer some limitations in their functionality due to their direct dependability on the controller driver circuit. The proportional integral derivative (PID) controller is a common and widely used control system in the BLDC motors and various applications. However, this simple system is insufficient to manage the BLDC motors’ precise control in variable load, speed, and driving voltage. An auto-tuner can be used with a PID controller to increase the system adaptation. The proposed adaptive PID controller would quickly control the BLDC motors with minimal adjustment time and oscillation. The proposed controller system has been designed using mathematical transfer function modelling and verified by simulation using MATLAB software. Preliminary results showed that the overall ripple is less than 1% and has a faster stabilization time, which is better than other controllers.","PeriodicalId":122857,"journal":{"name":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121367886","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

Sungai Pusu River Emergency Vital Signs Monitoring Using LoRaWAN 基于LoRaWAN的双溪浦浦河紧急生命体征监测

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/iccce50029.2021.9467252

Nur Sakinah Kosnin, Shihabeldin Fadli Yousif Hasan, M. H. Habaebi, Mod Rafiqul Islam

{"title":"Sungai Pusu River Emergency Vital Signs Monitoring Using LoRaWAN","authors":"Nur Sakinah Kosnin, Shihabeldin Fadli Yousif Hasan, M. H. Habaebi, Mod Rafiqul Islam","doi":"10.1109/iccce50029.2021.9467252","DOIUrl":"https://doi.org/10.1109/iccce50029.2021.9467252","url":null,"abstract":"Sungai Pusu is the river that passes through the IIUM Gombak campus. The river has been having a cloudy appearance for years hence it is needed to quantify the vital signs such as pH, temperature, and turbidity because these are the vital signs indicating the health of a river. Currently, there a lot of monitoring systems however the available monitoring systems do not support long-range communication and consume a lot of power. The data need to be transmitted at a long-range as it is being monitored remotely at a long distance. Therefore, a river pollution monitoring system must be developed to track the emergency vital signs (EVSs) of the river water The EVs include pH, temperature as well as turbidity. This project capitalizes on the long-range communication and low power consumption LoRaWAN system. The prototype monitoring station design can read the important EVSs of the river such as temperature, pH level, and turbidity. The sensors are connected to a microcontroller board. The readings of the EVSs are transmitted by the LoRa gateway which is forwarding the data to The Things Network Server. A graphical representation of the data is displayed on Ubidots. The results attained quantify the contribution of the IIUM populace to Sungai Pusu Pollution and raise awareness. It is also important to discuss the possibilities to the pollution of the river to see how one’s action could contribute to it. A statistical data of the results is as important so that an overall result can be deduced. Based on the results, the pH is decreased 1.32 pH, the temperature is increased by 2.29°C, and turbidity is decreased by 0.44 NTU throughout the monitoring period. In the future, six more monitoring stations will be added to accommodate KL River of Life (RoL) EVSs too.","PeriodicalId":122857,"journal":{"name":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125063357","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

Message from the Chairman of ICCCE 2021 2021年国际会议主席致辞

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/iccce50029.2021.9467210

引用次数: 0

Securing Wireless Communication Using RF Fingerprinting 使用射频指纹保护无线通信

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/ICCCE50029.2021.9467254

Nur Sabryna Aminuddin, M. H. Habaebi, S. Yusoff, M. R. Islam

{"title":"Securing Wireless Communication Using RF Fingerprinting","authors":"Nur Sabryna Aminuddin, M. H. Habaebi, S. Yusoff, M. R. Islam","doi":"10.1109/ICCCE50029.2021.9467254","DOIUrl":"https://doi.org/10.1109/ICCCE50029.2021.9467254","url":null,"abstract":"Recently, RF fingerprinting has become an arousing and emerging technology in identifying multiple wireless devices. The method is also believed to have a strong impact on its applications in the wireless security system. Security has always been a critical issue for wireless devices including in the application of Wireless Local Area Network (WLAN). For instance, Media Access Control (MAC) spoofing which is a malicious technique of changing a factory-assigned MAC address of a Network Interface Card (NIC) installed in a device. Due to this issue, this study suggests on making use of a network device’s unique RF fingerprint obtained from its raw baseband IQ samples to identify the transmitting radio. For WLAN, as RF fingerprinting is a physical layer security implementation, WLAN physical layer protocol data unit (PPDU) which contains L-LTF in preamble is extracted. Particularly, the RF fingerprinting process includes deep learning of convolutional neural network (CNN) as a classifier. The neural network is used to train a model by tuning and test-validation test before finalizing it as a final model for classification method for a security system.","PeriodicalId":122857,"journal":{"name":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121318150","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

Detecting Poultry Movement for Poultry Behavioral Analysis using The Multi-Object Tracking (MOT) Algorithm 基于多目标跟踪(MOT)算法的家禽运动检测及其行为分析

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/ICCCE50029.2021.9467144

Jasmine Khairunissa, S. Wahjuni, I. Soesanto, W. Wulandari

{"title":"Detecting Poultry Movement for Poultry Behavioral Analysis using The Multi-Object Tracking (MOT) Algorithm","authors":"Jasmine Khairunissa, S. Wahjuni, I. Soesanto, W. Wulandari","doi":"10.1109/ICCCE50029.2021.9467144","DOIUrl":"https://doi.org/10.1109/ICCCE50029.2021.9467144","url":null,"abstract":"Poultry meat is one of the most consumed livestock products in Indonesia. Several studies have concluded that understanding the behavior of poultry will increase production cost efficiency as well as facilitate the fulfillment of animal welfare. Assuring the poultry’s welfare in this increasing business is not an easy task. Using the Multi-Object Tracking algorithm and a pre-trained object detection model trained by the Single Shot Multibox Detector algorithm, we extracted the poultry movement data from a surveillance video with a frame rate of 15 frames per second for behavioral analysis purposes with a precision value of 60.4%. We also managed to gain the object movement plots and periods of the detected objects. This research does not pay attention to the direction of intersecting objects which allows identities to be exchanged between objects. Our near-future research is to add an object identity label in the data preparation step and using a different method of identity assignment which might improve the performance of the algorithm.","PeriodicalId":122857,"journal":{"name":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114856789","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: 4

Banana Ripeness Classification Using Computer Vision-based Mobile Application 基于计算机视觉的香蕉成熟度分类手机应用

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/ICCCE50029.2021.9467225

Muhammad Farhan Mohamedon, Faridah Abd. Rahman, S. Mohamad, Othman Omran Khalifa

{"title":"Banana Ripeness Classification Using Computer Vision-based Mobile Application","authors":"Muhammad Farhan Mohamedon, Faridah Abd. Rahman, S. Mohamad, Othman Omran Khalifa","doi":"10.1109/ICCCE50029.2021.9467225","DOIUrl":"https://doi.org/10.1109/ICCCE50029.2021.9467225","url":null,"abstract":"The integration of smartphone applications with the increasingly growing influence of artificial intelligence provides users with new ways to do about anything and allows users to be practical. In this paper, a mobile application to identify the ripeness of banana fruits is built by implementing a computer vision technique. Image classification is performed by adopting transfer learning to extract edges from a pre-trained model. Convolutional neural network (CNN) model is used to train the classifier. Banana is chosen as an instance due to its short shelf life and widely consumed by Malaysian. For this project, Google Colab is utilized for the code execution as it is run on cloud and well-suited for machine learning. TensorFlow Lite with Model Maker library simplified the process of adapting and converting a TensorFlow neuralnetwork model to particular input data before deploying to an Android application. The result emerged with an accuracy of 98.25%. The app can instantly recognize banana live image, display the ripeness level on the screen based on highest percentage matched and display the ripeness, enabling the users to identify the banana ripeness quickly and easily.","PeriodicalId":122857,"journal":{"name":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126496322","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

Monitoring and Alarming Activity of Islamic Prayer (Salat) Posture Using Image Processing 基于图像处理的伊斯兰礼拜姿势监测与预警活动

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/ICCCE50029.2021.9467155

M. M. Rahman, R. A. A. Alharazi, Muhammad Khairul Imran B Zainal Badri

{"title":"Monitoring and Alarming Activity of Islamic Prayer (Salat) Posture Using Image Processing","authors":"M. M. Rahman, R. A. A. Alharazi, Muhammad Khairul Imran B Zainal Badri","doi":"10.1109/ICCCE50029.2021.9467155","DOIUrl":"https://doi.org/10.1109/ICCCE50029.2021.9467155","url":null,"abstract":"This paper introduced a Salat Inspection and Training System based on Machine Vision and Image Processing Subject. In Islam, prayer (i.e., Salat) is the second pillar of Islam. It is the most important and fundamental worshipping activity that believers have to perform five times a day. From gestures’ perspective, there are predefined human postures that must be performed in a precise manner. There are lots of materials on the Internet and social media for training and correction purposes. However, some people do not perform these postures correctly due to being new to salat or even having learned prayers incorrectly. Furthermore, the time spent in each posture has to be balanced. To address these issues, we propose to develop an assistive intelligence framework that guides worshippers to evaluate the correctness of their prayer’s postures. Many features of images are being extracted and analyzed. Methods for image comparison and pattern matching are used to study the system’s effectiveness by using several combining algorithms, such as Euclidean Distance, Template Matching and Grey-Level Correlation, to compare the images of the user and the database. The experiments’ results, both correct and incorrect salat performances, are shown via pictures and graph for each of the postures of salat. Limitations of the system, such as lighting, is discussed regarding how it affects the system’s performance.","PeriodicalId":122857,"journal":{"name":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","volume":"50 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130177157","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

Sentiment Analysis from Depression-Related User-Generated Contents from Social Media 社交媒体中与抑郁症相关的用户生成内容的情绪分析

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/ICCCE50029.2021.9467214

Ananna Saha, A. Marouf, Rafayet Hossain

{"title":"Sentiment Analysis from Depression-Related User-Generated Contents from Social Media","authors":"Ananna Saha, A. Marouf, Rafayet Hossain","doi":"10.1109/ICCCE50029.2021.9467214","DOIUrl":"https://doi.org/10.1109/ICCCE50029.2021.9467214","url":null,"abstract":"In this paper, we try to detect the sentiment levels such as positive, negative and neutral sentiments from depression related posts and comments generated in social media platforms. Social media platforms such as Facebook, Twitter are not only used for communication or building networks among connections, but also are getting useful for supporting needy peoples who are on special need or care in terms of mental support. In Facebook, there are several depression support groups, which are very much effective to provide mental support to the victims. In this paper, we try to formalize the depression-related posts and comments into a concise lexicon database and detect the sentiment levels form each instance. We have segmented the total work into two parts: sentiment detection and applying machine learning algorithms to analyze the ability to detect sentiment from such special category of texts. We have utilized python textblob package to detect the sentiment levels and applied traditional machine learning algorithms such as Naïve Bayes (NB), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), Sequential Minimal Optimization (SMO), Logistic Regression (LR), Adaboost (AB), Bagging (Bg), Stacking (St) and Multilayer Perceptron (MP) on the linguistic features. We have determined the precision, recall, F-measure, accuracy, ROC values for each of the classifiers. Among the classifiers Random Forest has outperformed others showing 60.54% correctly classified instance. We believe such sentiment analysis on special category of texts may lead to further investigation in natural language understandings.","PeriodicalId":122857,"journal":{"name":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","volume":"283 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116039335","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

Component Spread Minimization for Integrated Active-RC Filter Using Genetic Algorithm Optimization Technique 基于遗传算法优化技术的集成有源rc滤波器的分量扩展最小化

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/ICCCE50029.2021.9467140

E. Abdo, A. Younis

{"title":"Component Spread Minimization for Integrated Active-RC Filter Using Genetic Algorithm Optimization Technique","authors":"E. Abdo, A. Younis","doi":"10.1109/ICCCE50029.2021.9467140","DOIUrl":"https://doi.org/10.1109/ICCCE50029.2021.9467140","url":null,"abstract":"The most important challenge in the analog integrated fitter design is the selecting the proper values of the filter components, and particularly the realization of the big value of the inductor in the applications that required low frequencies such as biomedical (medical) applications. This paper analyze and design integrated active low pass filter of Chebyshev third and fifth order based on the concept of Frequency Dependent Negative Resistance (FDNR) as substitutional to inductors. The design parameters of this filter has been optimized using genetic algorithm by selecting the optimum component speared of the filter. The genetic algorithm (GA) technique using MATLAB is applied to obtain the optimum component spreads and a significant reduction in component spreads are obtained, RSpread ≈ 86, and CSpread ≈ 2. Advance Design system simulator program (ADS) is used to verify that the obtained optimum parameters satisfy the specified filter performance. It is also shown that this technique is useful as the required filter order increased that leads to increase the component spread.","PeriodicalId":122857,"journal":{"name":"2021 8th International Conference on Computer and Communication Engineering (ICCCE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117177844","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

Extended Dijkstra Algorithm in Path Planning for Vision Based Patrol Robot 基于视觉的巡逻机器人路径规划中的扩展Dijkstra算法

2021 8th International Conference on Computer and Communication Engineering (ICCCE) Pub Date : 2021-06-22 DOI: 10.1109/ICCCE50029.2021.9467157

Choon Kiat Teh, Wai Kit Wong, Thu Soe Min

引用次数: 1