2022 IEEE 10th Conference on Systems, Process & Control (ICSPC)最新文献_第6页

Data Mining Analysis of Online Drug Reviews 在线药品评论的数据挖掘分析

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001810

S. Ajibade, A. Zaidi, Catherine P. Tapales, Dai-Long Ngo-Hoang, Muhammad Ayaz, Johnry Dayupay, Yakubu Aminu Dodo, Sushovan Chaudhury, Anthonia O. Adediran

{"title":"Data Mining Analysis of Online Drug Reviews","authors":"S. Ajibade, A. Zaidi, Catherine P. Tapales, Dai-Long Ngo-Hoang, Muhammad Ayaz, Johnry Dayupay, Yakubu Aminu Dodo, Sushovan Chaudhury, Anthonia O. Adediran","doi":"10.1109/ICSPC55597.2022.10001810","DOIUrl":"https://doi.org/10.1109/ICSPC55597.2022.10001810","url":null,"abstract":"Data mining methods like sentiment analysis provide useful information. This paper examines drug online user reviews. This research predicts user satisfaction with sentiments and applied drugs on effectiveness and side effects using sentiment analysis based on classification and analyzes model transfer across data sources like Emzor and May & Baker data. Online medication review data. Web crawlers was used to collect the ratings and comments of forum members. Emzor Pharmaceutical Company had 463 reviews and May & Baker Pharmaceutical Company had 421 reviews. Data was split 70% for training and 30% for testing. We used sentiment analysis to predict user ratings on overall satisfaction, side effects, and drug efficacy. Emzor data performs better 89.1% in-domain sentiment analysis, while May & Baker data accuracy is 86.90% overall. In cross-data sentiment analysis, the Emzor and May & Baker data performed well when the trained model was applied to side effects. This study acquired data by trawling an internet drug review forum. This study shows that transfer learning can leverage cross-domain similarities to analyze cross-domain sentiment.","PeriodicalId":334831,"journal":{"name":"2022 IEEE 10th Conference on Systems, Process & Control (ICSPC)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115593952","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

Development of an Autonomous Mobile Manipulator for Pick and Place Operation Using 3D Point Cloud 基于三维点云的自主移动搬运机械手的研制

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001817

Sheng-Wei Sim, Ban-Hoe Kwan, W. Yap, D. Ng

引用次数: 0

Detecting Abnormality on Coronary Artery Image by Extracted Edges to Deep Learning 基于深度学习提取边缘的冠状动脉图像异常检测

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001819

Le Nhi Lam Thuy, Quang Ngoc Trieu, P. Bao, Truong Dat Nhan

引用次数: 1

Chronic Kidney Disease Prediction based on Data Mining Method and Support Vector Machine 基于数据挖掘方法和支持向量机的慢性肾脏病预测

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001806

Muhamad Huzaimi Bin Abdul Ghafar, Nurul Aleena Binti Abdullah, Abdul Hadi Abdul Razak, Megat Syahirul Amin Bin Megat Ali, Syed Abdul Mutalib Al-Junid

{"title":"Chronic Kidney Disease Prediction based on Data Mining Method and Support Vector Machine","authors":"Muhamad Huzaimi Bin Abdul Ghafar, Nurul Aleena Binti Abdullah, Abdul Hadi Abdul Razak, Megat Syahirul Amin Bin Megat Ali, Syed Abdul Mutalib Al-Junid","doi":"10.1109/ICSPC55597.2022.10001806","DOIUrl":"https://doi.org/10.1109/ICSPC55597.2022.10001806","url":null,"abstract":"Chronic Kidney Disease (CKD) is when the kidneys are no longer working normally as they used to be, and filtering the blood was one of their obligations. The condition is classified as \"chronic\" since the kidney damage occurs gradually over time. This will cause waste to build up in the body. This study is aimed to predict the stages suffered by Chronic Kidney Disease patients, which might help in early detection and prevention. A Support Vector Machine (SVM) serves as the foundation for the prediction system developed by MathWorks and the missing data analysis will be done by using IBM SPSS Statistic 21. The work will show the feature selection and classification-based methods to enhance the performance accuracy of the algorithm in giving effective analysis and prediction of Chronic Kidney Disease. In conclusion, the accuracy achieved by using SVM with 50% holdout validation had the highest accuracy percentage of 93.5% out of other types of validation involved for the analysis of the datasets.","PeriodicalId":334831,"journal":{"name":"2022 IEEE 10th Conference on Systems, Process & Control (ICSPC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129998767","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

Raspberry PI Based: Design an Android-Thermal Surveillance Robot 基于树莓派的android -热监控机器人设计

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001772

Safaa N. Saud Al-Humairi, Ummar Idraqi Bin Mohamad Noh, Wee Ying Ci

引用次数: 0

DC Motor System Identification Simulator App for Online Learning of Automatic Control System Subject 直流电机系统辨识模拟器应用程序，用于自动控制系统学科在线学习

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001790

Riady Siswoyo Jo, Hudyjaya Siswoyo Jo

引用次数: 0

Indoor Safety Monitoring and Auto Temperature Detector for COVID-19 新型冠状病毒肺炎室内安全监测与自动温度探测器

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001792

Omar Ismael Al-Sanjary, Batrisyia Anati Binti Idzhar, M. Kashmola

引用次数: 0

CopyPoppy – A Source Code Plagiarism Detector copyoppy -一个源代码抄袭检测器

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001740

Nik Faris Aiman Nik Rahiman, M. Johar, Rabab Alayham Abbas Helmi

{"title":"CopyPoppy – A Source Code Plagiarism Detector","authors":"Nik Faris Aiman Nik Rahiman, M. Johar, Rabab Alayham Abbas Helmi","doi":"10.1109/ICSPC55597.2022.10001740","DOIUrl":"https://doi.org/10.1109/ICSPC55597.2022.10001740","url":null,"abstract":"As the technology advances over the years, students have flooded into courses that are related to computer science across the globe, recognizing them as an opportunity to work at known companies like Google and Facebook as one of their main interests. Though, the spike in interest for these courses coincided with an undesirable side effect: a rising number of source code plagiarism. This paper is about solving programming plagiarism problems by developing a source code plagiarism system in Java called CopyPoppy. It is important to note that there are students that understand code solutions and use them as a foundation to write their own code. These kinds of cases may not be necessarily considered as plagiarising as they are only using other’s source code as an inspiration for their finished code. Therefore, there are a lot of aspects that need to be taken into account when deciding whether a source code is plagiarised or not. Therefore, CopyPoppy is designed to be able to distinguish between what is considered plagiarism and what is not. The existence of CopyPoppy hopefully will encourage more and more students to learn and write their own source code with their highest level of ability and quality as a way to develop self-discipline and to grasp their level of understanding through concepts and skills that they have learnt.","PeriodicalId":334831,"journal":{"name":"2022 IEEE 10th Conference on Systems, Process & Control (ICSPC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125346658","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

Ego Lane Yaw Rate Extraction Using LaneNet Network 基于LaneNet网络的Ego Lane偏航速率提取

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001818

Wan Muhammad Hafeez Bin Wan Azree, M. Ariff, H. Zamzuri

{"title":"Ego Lane Yaw Rate Extraction Using LaneNet Network","authors":"Wan Muhammad Hafeez Bin Wan Azree, M. Ariff, H. Zamzuri","doi":"10.1109/ICSPC55597.2022.10001818","DOIUrl":"https://doi.org/10.1109/ICSPC55597.2022.10001818","url":null,"abstract":"Evolution of transportation has rapidly grown with the existence of autonomous navigation technology in the world. Good navigation comes with a high accuracy localization system. The current localization techniques are always prone to solidity and availability of extracted features. These occurrences might have limitations to places where it has limited features and wide area to be extracted such as on highways. This situation could bring error to the localization system and the autonomous vehicle (AV) may cause fatality to the people around it. Hence, an alternative localization method needs to be implemented which makes use of the non-changing features and available in all roads in the world which is the road lane marking information. To integrate the AV localization system with the road lane information, the vehicle first needs to extract the yaw orientation of the detected lane to predict the pose and orientation estimation based on the curvature of the road and slope of the road lane observed. Therefore, this paper proposed a yaw rate extraction method onto LaneNet network to extracts the road lane using a High Definition (HD) camera. This experiment is conduct in two different frames which are in the local frame (vehicle coordinate frame) and in the global frame (UTM coordinate frame) and the result are compared. The yaw rate extracted in local frame is the best solution if compared to yaw rate extraction in global frame due to the transformation coordinates into global coordinates are exposed to tolerance error which possibly cause by multi-path error or noise interruption at atmospheric layer.","PeriodicalId":334831,"journal":{"name":"2022 IEEE 10th Conference on Systems, Process & Control (ICSPC)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116999189","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

An Application of Principal Component Analysis in Aspergillus Species Identification 主成分分析在曲霉种类鉴定中的应用

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC) Pub Date : 2022-12-17 DOI: 10.1109/ICSPC55597.2022.10001780

Nur Rodiatul Raudah Mohamed Radzuan, H. Jaafar, Farah Nabilah Zabani

{"title":"An Application of Principal Component Analysis in Aspergillus Species Identification","authors":"Nur Rodiatul Raudah Mohamed Radzuan, H. Jaafar, Farah Nabilah Zabani","doi":"10.1109/ICSPC55597.2022.10001780","DOIUrl":"https://doi.org/10.1109/ICSPC55597.2022.10001780","url":null,"abstract":"Aspergillus sp. is one of the filamentous fungi that has a number of benefits in the food industry. Despite its important roles in industry level, they have several shortcomings especially to immunocompromised individuals that appear to be highly susceptible to disease or infection. Normally, the identification of species was manually screened by the trained microscopists but, the machine learning application becomes as an alternative to identify the species of Aspergillus. However, the development of machine learning is not straightforward and time consuming if the data is not well presented. In order to fasten the identification process of Aspergillus while retaining its characteristics, principal component analysis (PCA) and principal component analysis and Histogram of Oriented Gradient (PCAHOG) were employed to reduce the dimensionality of the dataset. Different values of eigen in PCA were executed and the classification by support vector machine (SVM) with two different kernels such as polynomial and radial basis function (RBF) was done afterwards. Based on the performance evaluation, PCAHOG-SVM (Polynomial) with eigenvalue of 48 outperformed the others with accuracy of 99.43% for training number of 18. Moreover, three Aspergillus sp. have been recorded 100% of accuracy with the same number of trainings.","PeriodicalId":334831,"journal":{"name":"2022 IEEE 10th Conference on Systems, Process & Control (ICSPC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125256562","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