2022 IEEE International Conference on Computing (ICOCO)最新文献_第2页

The Improvement of Stress Level Detection in Twitter: Imbalance Classification Using SMOTE Twitter中应力水平检测的改进:基于SMOTE的不平衡分类

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031684

Mohd Shahrul Nizam Mohd Danuri, Rohizah Abd Rahman, I. Mohamed, Azzan Amin

{"title":"The Improvement of Stress Level Detection in Twitter: Imbalance Classification Using SMOTE","authors":"Mohd Shahrul Nizam Mohd Danuri, Rohizah Abd Rahman, I. Mohamed, Azzan Amin","doi":"10.1109/ICOCO56118.2022.10031684","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031684","url":null,"abstract":"This study developed a model to improve stress level detection using Synthetic Minority Oversampling Technique (SMOTE) imbalanced data classification. SMOTE is a method to address imbalanced datasets to oversample the minority class. The data collected from Twitter may seem vague mainly due to the massive amount of data. This research used the framework model of Data, Experts Data Annotation, Text Pre-processing, and Text Representation and Classification. The Bag of Word (BoW), Term Frequency-Inverse Document Frequency (TFIDF), and Lemma were used for the text representation. The data were collected only from Twitter under certain circumstances. The Subject Matter Experts (SMEs) on mental health problems have annotated the text from the tweets based on four levels: Normal, Mild, Moderate, and Severe. The data group for the Normal stress level was relatively large compared to the other groups. Due to the imbalanced data group, the SMOTE technique was used for data argumentation. The result showed that the model classification using Support Vector Machine with SMOTE increased by improving the cardinality of the minority class label through the significant Macro Avg Recall and Macro Avg F1-Score analysis results compared to the baseline.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131669921","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

Preliminary Analysis on Nursing Students Intention to Use Virtual Reality Application as a Learning Tool for Basic Human Anatomy Course 护生利用虚拟现实应用作为人体解剖学基础课程学习工具意向的初步分析

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031994

H. Sulaiman, R. Ramli, Azmi Bin Mohd Yusof

{"title":"Preliminary Analysis on Nursing Students Intention to Use Virtual Reality Application as a Learning Tool for Basic Human Anatomy Course","authors":"H. Sulaiman, R. Ramli, Azmi Bin Mohd Yusof","doi":"10.1109/ICOCO56118.2022.10031994","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031994","url":null,"abstract":"Virtual Reality (VR) refers to the use of computer technology to create a simulated environment. The simulated environment can be of something that represents a real-world scenario. The rapidly changing learning landscapes also indicate that learning methods in higher education institutions must evolve to keep up with the trend of incorporating integrated technologies into the learning modules. The existence of new millennial classrooms, blended learning applications and advance learning labs have allowed lecturers to experiment with new teaching styles. Nevertheless, these facilities may not exist in all faculties due to restricted budgets and lack of resources. Healthcare related faculties have been reported to be slow in acceptance and use of technologies in teaching fundamental subjects. A common fundamental subject across all health-related studies is Basic Human Anatomy. This subject requires visualization and memorization of human body parts that would be more interesting to have the use of technology devices as the supporting learning tool. As the uptake of technology namely VR is relatively low in the health education field, it is imperative to explore the suitability of VR learning tools for the human anatomy subject. A survey was conducted to first- and second-year nursing students who have taken and currently taking the basic human anatomy course. Data was analyzed using basic descriptive statistics to gauge the intention to use virtual reality application for the course. A proposed virtual reality intention to use model is conceptualized from previous learning models and results of the survey depicting factors that would affect learning of human anatomy subject through virtual reality.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123046350","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

Residual Value Prediction 残值预测

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031995

Huayi Jing, Xinfeng Ye, S. Manoharan

引用次数: 0

A Framework for Supporting Deaf and Mute Learning Experience Through Extended Reality 通过扩展现实支持聋哑人学习体验的框架

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031865

S. A. Mubin, Jacob Sow Tian You, Edwin Pio Rufus Samiraj, Sharizal Pujahaas Jaafar

引用次数: 0

Age Differences Classification Associated with Corpus Callosum Measurement 胼胝体测量的年龄差异分类

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031802

Shafaf Ibrahim, Nur Aina Shahirah Mat Jelaini, Nor Azura Md. Ghani, R. Janor, Mohd Hanif Ali

{"title":"Age Differences Classification Associated with Corpus Callosum Measurement","authors":"Shafaf Ibrahim, Nur Aina Shahirah Mat Jelaini, Nor Azura Md. Ghani, R. Janor, Mohd Hanif Ali","doi":"10.1109/ICOCO56118.2022.10031802","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031802","url":null,"abstract":"A medical visualization is a tool used in medicine to detect aspects of the human body in terms of digital health. The corpus callosum is a large white matter structure that separates the two hemispheres of the brain. It is an extremely essential structural and functional component of the brain. Assessing the corpus callosum measurement could reveal the information on age differences category of each individual, as well as atypical growth such as multiple sclerosis (MS), Alzheimer’s, and autism spectrum disorder (ASD). Thus, this study proposed the use of Magnetic Resonance Imaging (MRI) sagittal brain images to classify age differences associated with corpus callosum measurement. Three age differences were studied; children (0-10 years), adolescent (10-18 years), and adult (18-25 years). The present results provided evidence that adult and children differ in terms of developmental trajectories for the brain structure, with significant age-related changes discernable from infancy to early adulthood. A few steps of MRI corpus callosum image collection, Median Filtering image enhancement, Otsu binarization, and K-Means clustering segmentation, corpus callosum measurement, and Support Vector Machine (SVM) classification were involved. The performance of the corpus callosum classification was evaluated using a confusion matrix. The overall mean percentage of accuracy reflected a very high accuracy which are 97.72%, 95.56%, and 97.72% for children, adolescent, and adult respectively. It can be deduced that the proposed techniques of corpus callosum classification are found to be successful.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116670573","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

Development of Tuition Centre Management System 学费中心管理系统的开发

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031819

Nur 'Amirah Binti Hanafiah, R. A. Aziz

引用次数: 0

Mapping Study of Critical Success Factor for Agile Software Project 敏捷软件项目关键成功因素的映射研究

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031946

Nurul Annisa Azhar, N. Abdullah

引用次数: 0

The Evaluation of Cognitive Load Significance for Mobile Learning Application via User Interface Design Violations 基于用户界面设计违规的移动学习应用认知负荷意义评估

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031943

M. A. Faudzi, Masitah Ghazali, Z. C. Cob, Ridha Omar, Sharul Azim Sharudin

{"title":"The Evaluation of Cognitive Load Significance for Mobile Learning Application via User Interface Design Violations","authors":"M. A. Faudzi, Masitah Ghazali, Z. C. Cob, Ridha Omar, Sharul Azim Sharudin","doi":"10.1109/ICOCO56118.2022.10031943","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031943","url":null,"abstract":"COVID-19 has changed how the world operates, and education is one of the sectors that are highly affected by these changes. Previously, mobile learning is just an optional or a supplementary learning method. However, with the increased in the number of COVID-19 cases around the world, education system has switched from the traditional face-to-face mode in a classroom setting, to an online learning environment. Learning using a mobile device or mobile learning is a concept that is new to most learners, especially those who have never before experienced an online learning setting. One of the prevalent factors that leads to ineffective mobile learning process is badly designed user interfaces that will disengage learners from learning materials presented, and increase the cognitive load of the learners. Among the factors that results in bad user interface is the violation of a user interface guideline/framework. Therefore, the main objective of this research-work is to evaluate the learners’ cognitive load significance for mobile learning application by identifying Nielsen’s Heuristics’ violation. By implementing this study, important user interface design (UID) attributes that increase learner’s cognitive load can be identified. Understanding how UID can affect the learners’ cognitive load can assist designers in deciding which user interface designs that can improve or minimize learners’ cognitive load. The outcome of this research will enable mobile learning application designers, developers, educators, teachers and people who are interested in developing a mobile learning application to deliver an effective mobile learning experience to learners.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123883822","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

A Preliminary Lightweight Random Forest Approach-Based Image Classification for Plant Disease Detection 基于轻量级随机森林方法的植物病害图像分类初探

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031846

Mashitah Ibrahim, Muzaffar Hamzah, M. F. Asli

{"title":"A Preliminary Lightweight Random Forest Approach-Based Image Classification for Plant Disease Detection","authors":"Mashitah Ibrahim, Muzaffar Hamzah, M. F. Asli","doi":"10.1109/ICOCO56118.2022.10031846","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031846","url":null,"abstract":"In recent years, the rapid development of environmental sensors and artificial intelligence is changing the traditional mode of agricultural production and moving towards intelligent and efficient precision agriculture. According to the demand of developing precision agriculture, this study plans to carry out comprehensive improvise research on the intelligent unmanned plant disease detection technology for agricultural ecosystems. The production can be adversely affected if plant disease problems cannot be detected in the early stage. Therefore, the biggest challenge in disease detection is the accurate early diagnosis for loss prevention. However, achieving high accuracy requires a computationally intensive approach to the system, which can cause overhead and high technical costs. Random Forest is a special kind of ensemble learning technique and it turns out to perform very well compared to other classification algorithms such as Support Vector Machines (SVM) and Artificial Neural Networks (ANN). In this study, we modified the structure of, RF model to improve the overall accuracy and accessibility, to transform it into a lightweight detection system. This lightweight framework is for cost-effective distribution with high performance without requiring extensive computational resources or complex algorithms. With that, this system can be more practical and easier to use.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129708748","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

Green Software Process Based on Sustainability, Waste and Evaluation Theory Approach: The Conceptual Model 基于可持续性、浪费和评价理论的绿色软件过程:概念模型

2022 IEEE International Conference on Computing (ICOCO) Pub Date : 2022-11-14 DOI: 10.1109/ICOCO56118.2022.10031699

Siti Rohana Ahmad Ibrahim, J. Yahaya, H. Sallehudin

{"title":"Green Software Process Based on Sustainability, Waste and Evaluation Theory Approach: The Conceptual Model","authors":"Siti Rohana Ahmad Ibrahim, J. Yahaya, H. Sallehudin","doi":"10.1109/ICOCO56118.2022.10031699","DOIUrl":"https://doi.org/10.1109/ICOCO56118.2022.10031699","url":null,"abstract":"Green technology is the solution that responds to the environment and meets development needs. Climate change has led to an increasing global need to develop green and sustainable technology with economic development, employment opportunities, and long-term investment. Nowadays, people are increasingly responsive to the importance of green and sustainability. It has become progressively crucial to the government, business, products, and software industry. Green software engineering is proposed for software development to provide environmental awareness and also less waste generation throughout the development process. The current green software process model only concentrated on environmental and economic elements and was not integrated with waste elements in the development phase. Model development often consists of smaller component models, each representing a specific domain based on sustainability elements and waste elimination. Organisations and industries conducted assessments to determine the level of the greenness of a development process in their real environment. This paper presents the concept of the theory evaluation approach in the green software process, which focuses on the components and factors embedded in this model.","PeriodicalId":319652,"journal":{"name":"2022 IEEE International Conference on Computing (ICOCO)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126773444","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