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2022 26th International Computer Science and Engineering Conference (ICSEC)最新文献

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The Analysis of Research Literature on the Role of AI in Industrial Sector 人工智能在工业部门中的作用研究文献分析
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049336
Wasin Jiropakarn, Primabhads Rueangrong, Anshisa Denvuttivorakarn, P. Chanvarasuth, Issariyaporn Pooarb-On, Kuea Wattanavijit, Surattiya Inpahol
{"title":"The Analysis of Research Literature on the Role of AI in Industrial Sector","authors":"Wasin Jiropakarn, Primabhads Rueangrong, Anshisa Denvuttivorakarn, P. Chanvarasuth, Issariyaporn Pooarb-On, Kuea Wattanavijit, Surattiya Inpahol","doi":"10.1109/ICSEC56337.2022.10049336","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049336","url":null,"abstract":"According to the advancement of technology, artificial intelligence (AI) allows the machine to perform some intelligent tasks in the business operation. With the emerging trend of AI in the business application, grouping the journal articles of artificial intelligence based on the industrial classification framework using clustering in K-Means algorithm and topic modeling with LDA technique are performed within this study. The finding shows the relationship between two methods together with the linkage of the business sectors including information sector management of companies and enterprise sector, manufacturing sector, finance and insurance sector, professional, scientific and technical services sector, transportation sector, healthcare and social assistance sector, and retail sector.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127916501","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
G-AUC: An improved metric for classification model selection G-AUC:分类模型选择的改进度量
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049319
Shashank Sadafule, Sobhan Sarkar, Shaomin Wu
{"title":"G-AUC: An improved metric for classification model selection","authors":"Shashank Sadafule, Sobhan Sarkar, Shaomin Wu","doi":"10.1109/ICSEC56337.2022.10049319","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049319","url":null,"abstract":"The performance of classification models is often measured using the metric, area under the curve (AUC). The non-parametric estimate of this metric only considers the ranks of the test instances and fails to consider the predicted scores of the model. Consequently, not all the valuable information about the model’s output is utilized. To address this issue, the present paper introduces a new metric, called Gamma AUC (G-AUC) that can take into account both ranks as well as scores. The parameter G tackles the problem of overfitting scores into the metric. To validate the proposed metric, we tested it on 20 UCI datasets with 10 state-of-the-art models. Out of all the values of the parameter G that we tested, four of them got p-value less than 0.05 for the alternative hypothesis that, on the training sets, G-AUC has a greater correlation than AUC itself, with AUC on test sets. Furthermore, for all values of G considered, G-AUC always won majority of the times than AUC for selecting better models.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"18 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124300057","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
Exploring the Use of Different Feature Levels of CNN for Anomaly Detection 探索使用CNN的不同特征级别进行异常检测
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049323
Isack Farady, Lakshay Bansal, S. Ruengittinun, Chia-Chen Kuo, Chih-Yang Lin
{"title":"Exploring the Use of Different Feature Levels of CNN for Anomaly Detection","authors":"Isack Farady, Lakshay Bansal, S. Ruengittinun, Chia-Chen Kuo, Chih-Yang Lin","doi":"10.1109/ICSEC56337.2022.10049323","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049323","url":null,"abstract":"Anomaly detection is the task of uncovering out-of-distribution samples from the majority of data. Typically, this is treated as a one-class classification problem where the only data available to analyze is the normal data. With regard to collecting features of normal data, the high-dimensional features from CNN can be used to learn the normality. The last layer of CNN with more semantic information is generally used to learn the normality. In contrast, this work proposes learning features from different levels of high-dimensional features instead of using only high-level features. With the assumption that the training data is normally distributed, we present an anomaly detection algorithm consisting of a deep feature extraction stage with ResNet18 followed by dimensionality reduction via PCA. The anomaly classification stage comprises two class-conditional transformation models implemented via Gaussian Mixture Model. Our proposal leverages feature-reconstruction error as anomaly scores between two high-dimensional feature vectors. In this study, we analyze and compare the effect of using different blocks of a pre-trained ResNet18 on a well-known industrial anomaly detection dataset. Results suggest that using the best output features of CNN can significantly improve the model’s ability to predict anomalous samples.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123313201","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
Generic Laboratory Authoring Tool for Virtual and Remote Controlled Laboratories 用于虚拟和远程控制实验室的通用实验室创作工具
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049312
H. A. H. Hassan Hosny, Noha A. Elmosilhy, M. M. Elmesalawy, Ahmed M. Abd El-Haleem
{"title":"Generic Laboratory Authoring Tool for Virtual and Remote Controlled Laboratories","authors":"H. A. H. Hassan Hosny, Noha A. Elmosilhy, M. M. Elmesalawy, Ahmed M. Abd El-Haleem","doi":"10.1109/ICSEC56337.2022.10049312","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049312","url":null,"abstract":"Due to the impact of Covid-19, many students all over the world have faced some educational issues. Therefore, many educational institutes focused on shifting their learning process to E-learning system. To provide a complete E-learning system, the performing of virtual and remote Laboratory experiments is needed. In this paper, a generic and flexible online authoring tool for the Laboratory Learning System (LLS) is presented. The LLS system is a platform that provides teachers and students with a flexible environment for virtual and remote controlled labs using the proposed authoring tool. The heart of the LLS system is the authoring tool which facilities the ease and flexibility of designing various laboratory experiments which includes a number of pages, and each page has a number of steps with many draggable components. Furthermore, the proposed authoring tool is the first authoring tool that provides general and reusable virtual laboratory resource (VLR) for automatically managing laboratory software and hardware resources. To support the new VRL feature of the authoring tool, the LLS supports the ability to remotely control the laboratory equipment while performing laboratory experiments and also has the capability to run any type of simulation tool for virtually simulated labs. The proposed authoring tool is designed considering all the needed components with well-defined interfaces to achieve an effective and flexible Laboratory learning system.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128643806","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
Blood Vessels Detection by Regional-based CNN for CT Scan of Lower Extremities 基于区域CNN的下肢CT血管检测
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049364
Littikrai Sakunpaisanwari, Nutcha Yodrabum, Tanongchai Sirirapisit, Taravichet Titijaroonroj
{"title":"Blood Vessels Detection by Regional-based CNN for CT Scan of Lower Extremities","authors":"Littikrai Sakunpaisanwari, Nutcha Yodrabum, Tanongchai Sirirapisit, Taravichet Titijaroonroj","doi":"10.1109/ICSEC56337.2022.10049364","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049364","url":null,"abstract":"Blood vessels on computed tomography (CT) scan images are difficult to identify and discriminate between vessels and noise because blood vessels are not only small and shapeless, but its location can also be inconsistent. This is a challenge of object detection. We proposed an automatic blood vessel detection method based on YOLOv3 for object detection from CT scan of lower extremities. This work focused on detecting four main arteries: popliteal, anterior tibial, posterior tibial, and peroneal arteries. To obtain the best architecture for blood vessel detection, we evaluated and compared the performances of seven region-based CNN architectures: Faster R-CNN, Cascade R-CNN, Mask R-CNN, RetinaNet, YOLOv3, CornerNet, and Centernet. Experimental results show that the best architecture was YOLOv3 with precision, recall, and f1-score of 0.982, 0.954, and 0.968, respectively. Good accomplishment of YOLOv3 came from skip connections, multi-scale feature map, and anchor generated by k-means clustering.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121068110","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
Emotion Detection of Thai Elderly Facial Expressions using Hybrid Object Detection 基于混合目标检测的泰国老年人面部表情情感检测
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049334
Thanapong Khajontantichaikun, S. Jaiyen, S. Yamsaengsung, P. Mongkolnam, Unhawa Ninrutsirikun
{"title":"Emotion Detection of Thai Elderly Facial Expressions using Hybrid Object Detection","authors":"Thanapong Khajontantichaikun, S. Jaiyen, S. Yamsaengsung, P. Mongkolnam, Unhawa Ninrutsirikun","doi":"10.1109/ICSEC56337.2022.10049334","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049334","url":null,"abstract":"An elderly population is a special group that needs to be taken care of closely. A key area of concern for the elderly is that of mental health and many technologies can be applied in this area. One possible tool is facial expression recognition (FER) that can be used to detect emotions of the elderly for the purpose of mental health care. In this research, we propose a hybrid of Faster R-CNN, SSD, and YOLOv5 object detection models for elderly facial expression detection. In our experiments, the proposed hybrid model was trained on a Thai elderly facial emotion dataset, and its performance was compared to a single-model of Faster R-CNN, SSD, and YOLOv5. The experimental results indicated that the proposed hybrid object detection model had achieved the best performance with an accuracy of 94.07%. This was comparatively better than YOLOv5, which gave the accuracy of 93.33%.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122486970","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
Securing Networks of IoT Devices With Digital Twins and Automated Adversary Emulation 利用数字孪生和自动对手仿真保护物联网设备的网络
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049355
Ewout Willem van der Wal, Mohammed El-hajj
{"title":"Securing Networks of IoT Devices With Digital Twins and Automated Adversary Emulation","authors":"Ewout Willem van der Wal, Mohammed El-hajj","doi":"10.1109/ICSEC56337.2022.10049355","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049355","url":null,"abstract":"With the number of Internet-connected devices (things), expected to be almost 30 billion by 2030, the Internet of Things (IoT) technologies already became a part of everyday life, various areas like public health, smart cars, smart grids, smart cities, smart manufacturing and smart homes. On the other hand there is also the necessity of securing all these devices from possible cyber-attacks. In this paper, We investigate the current state of the art of IoT security and Digital Twins, digital representations of physical objects. We then use this knowledge to propose a novel methodology to use Cyber Digital Twins and Autonomous Adversary Emulation to improve the security of IoT devices. Consequently, we show that this methodology has the potential to improve the security of IoT applications. This work contributes a review of the state of the art in IoT security research and a novel method for improving IoT device security.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133996267","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
Clustering of Human Gene Expression Stimulated by Bacterial Infection from Microarray Analysis 细菌感染刺激人类基因表达的微阵列分析
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049353
Panthong Kulsantiwong, Phanarut Srichetta, Wannasiri Thurachon
{"title":"Clustering of Human Gene Expression Stimulated by Bacterial Infection from Microarray Analysis","authors":"Panthong Kulsantiwong, Phanarut Srichetta, Wannasiri Thurachon","doi":"10.1109/ICSEC56337.2022.10049353","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049353","url":null,"abstract":"Gene expression profiling of human cells against bacterial infection has become a major tool that allows explaining genome-wide expression changes in health and disease, which is important for the diagnosis and prognosis of diseases. A good way to identify human genes with similar biological activities or functions when stimulated by bacteria injection is by clustering. The objective of this research is to cluster human gene expression stimulated by wide-type (WS) and mutant strain (MS) of Burkholderia pseudomallei compared to controls via microarray transcriptional profile. K-means clustering algorithm was used to cluster human gene expression based on the fold change (FC) values of primary human monocytes (PHM) stimulated by both strains. In the phase of determining k-cluster experimented on PHM genes stimulated with WS, with MS and without strains stimulation (control), it results were 7, 7 and 7 clusters, respectively. According to three clustering patterns based on bacterial strain of stimulation, genes in cluster in the same ranked level reveals the similar molecular functions whereas different levels have different functions. Moreover, the clusters with highest FC values are also crucial. In the first top cluster, gene expression in PHM stimulated with WS and MS compared to the control, the cytokine genes especially csf2, csf3, il23A, il6 and stat4 were found in all bacterial stimulation. These gene clusters showed the molecular functions in PHM including cytokine activity, growth receptor binding, growth factor activity and cytokine receptor binding. These results indicated that the cluster of human genes infected by B. pseudomallei revealed the association between immune response genes and their molecular functions. These clusters of PHM genes might be the important biomarker genes which related for understanding the human immune response against B. pseudomallei infection and prognosis the melioidosis patients.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"352 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134453534","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
Thai Paraphrasing Tool for Chatbot Intent Recognition Training 用于聊天机器人意图识别训练的泰语释义工具
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049337
Darlyn Sirikasem, Siripen Pongpaichet
{"title":"Thai Paraphrasing Tool for Chatbot Intent Recognition Training","authors":"Darlyn Sirikasem, Siripen Pongpaichet","doi":"10.1109/ICSEC56337.2022.10049337","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049337","url":null,"abstract":"This paper introduced a novel tool to automatically generate Thai paraphrased sentences specialized for intent recognition training. This technique is devised to improve intent recognition accuracy and reduce the training time, especially during the creation of applications like Thai natural language-based games and chatbots. The switching if-conjunction clauses in question sentences and the thesaurus-based paraphrasing methods have been explored. For the evaluation, a group of participants used the prototype tool to develop Thai chatbots. Which were tested to recognize question-type messages in the Thai national identification card domain provided by another group. The results demonstrated that the proposed techniques increase the accuracy F1 score compared to the state-ofthe-art pattern-aided chatbot by approximately 39%. On average, expert chatbot developers scored 8.25 out of 10 points on the prototype tool satisfaction.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133857520","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
Analysis of Thai Fake News Using Naïve Bayes Models 利用Naïve贝叶斯模型分析泰国假新闻
2022 26th International Computer Science and Engineering Conference (ICSEC) Pub Date : 2022-12-21 DOI: 10.1109/ICSEC56337.2022.10049359
Peemapat Podsoonthorn, Thapana Boonchoo, Wanida Putthividhya
{"title":"Analysis of Thai Fake News Using Naïve Bayes Models","authors":"Peemapat Podsoonthorn, Thapana Boonchoo, Wanida Putthividhya","doi":"10.1109/ICSEC56337.2022.10049359","DOIUrl":"https://doi.org/10.1109/ICSEC56337.2022.10049359","url":null,"abstract":"Detecting fake news in an early stage, even though it is challenging, is thus adventurous to protect harms to people. In this paper, we present a framework for revealing the evidences of fake news in Thai news titles using the Naïve Bayes model. The framework enables us to discover footprints for fact news and fake news through the four back-to-back steps: data acquisition, data pre-processing, data exploration, and data modeling. We also intensely examine the Naïve Bayes model discrimination of fact and fake news when employing different text normalization methods. The experiments show that the Naïve Bayes model can achieve the accuracy performance up to 89%. Moreover, we provide the extensive discussions about our data exploration. We also discuss our application of posterior probabilities to reveal evidences of fake news.","PeriodicalId":430850,"journal":{"name":"2022 26th International Computer Science and Engineering Conference (ICSEC)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116710760","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
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