2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE)最新文献_第3页

Event Detection and Analysis in Thai News Using Bi-LSTM 基于Bi-LSTM的泰语新闻事件检测与分析

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836294

Kallaya Songklang, Wilaiporn Lee, A. Prayote

引用次数: 0

A new Hybrid PSO-SCA using Horse Optimization Algorithm's group behavior update 基于马优化算法群体行为更新的新型混合PSO-SCA

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836292

Wichaya Somgiat, Sukanya Chansamorn

引用次数: 0

Semantic-based Thai Recipe Recommendation 基于语义的泰式食谱推荐

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836293

Supannada Chotipant

{"title":"Semantic-based Thai Recipe Recommendation","authors":"Supannada Chotipant","doi":"10.1109/jcsse54890.2022.9836293","DOIUrl":"https://doi.org/10.1109/jcsse54890.2022.9836293","url":null,"abstract":"Nowadays, people are constantly affected by epidemics such as COVID-19. To reduce the risk of acquiring germs in the community, people's lifestyles have been changed, and they are more inclined to cook for themselves. Typically, people can usually quickly and easily find recipe information via websites and applications. The resulting recipes consist of ingredients as specified by the user. Unfortunately, users often have ingredients that disappear in available cooking recipes. This makes the system is unable to recommend all relevant recipes to users, although the users can use the existing ingredients instead of the ingredients specified in the recipes. Based on this limitation, this research proposes a semantic-based Thai cooking recipe recommendation system which can recommend recipes based on the ingredient substitutes. This research uses existing Thai food ontology to retrieve substitute ingredients based on three different ingredient properties, such as smell, taste, and texture. To recommend cooking recipes, the system expands the given user queries with substitute ingredients and then calculates similarities between all queries and each cooking recipe. Recipes with high similarities are presented and ranked to users. To evaluate the performances, precision, recall and f-measure are applied. The experiments demonstrate that the proposed method performs well with 0.96, 0.72, and 0.82 in precision, recall, and f-measure respectively.","PeriodicalId":284735,"journal":{"name":"2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"213 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133880973","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

Multi-directional Texture Feature Extraction for Glaucoma Classification from Color Retinal Images 彩色视网膜图像青光眼分类的多向纹理特征提取

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836277

Ungsumalee Suttapakti, Supawadee Srikamdee, Janya Onpans

{"title":"Multi-directional Texture Feature Extraction for Glaucoma Classification from Color Retinal Images","authors":"Ungsumalee Suttapakti, Supawadee Srikamdee, Janya Onpans","doi":"10.1109/jcsse54890.2022.9836277","DOIUrl":"https://doi.org/10.1109/jcsse54890.2022.9836277","url":null,"abstract":"Glaucoma is a type of eye disease in which there are no symptoms. As the disease progresses for a long time, the patients lose their visions permanently. An automatic glaucoma classification is essential for identifying early glaucoma diagnosis from retinal images to reduce the vision loss risk. Image analysis and machine learning techniques are applied to create an automatic method for glaucoma classification from retinal images. To increase the effectiveness of glaucoma classification, a multi-directional texture feature extraction (MTFE) is proposed. This method extracts texture features on segmented red, green, and blue images without background. Its extraction is based on 2D Gabor filters with SURE entropy to efficiently provide appropriate texture features with low dimensions for classifying glaucoma. For 455 images of the RIM-ONE R2 database, the MTFE method yields 90.44%, which is higher than other methods. The MTFE proposed method can extract proper texture features, thus improving the accuracy of glaucoma classification from retinal images.","PeriodicalId":284735,"journal":{"name":"2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131343408","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 Computational Workflow for Estimation of Short RNA Polyadenylation using Direct RNA Nanopore Sequencing with Polyuridylation 使用直接RNA纳米孔测序与多尿苷化估算短RNA聚腺苷化的计算工作流程

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836262

Jirachote Karunyakorn, Naruemon Pratanwanich, M. Pongpanich, Pornchai Kaewsapsak

{"title":"A Computational Workflow for Estimation of Short RNA Polyadenylation using Direct RNA Nanopore Sequencing with Polyuridylation","authors":"Jirachote Karunyakorn, Naruemon Pratanwanich, M. Pongpanich, Pornchai Kaewsapsak","doi":"10.1109/jcsse54890.2022.9836262","DOIUrl":"https://doi.org/10.1109/jcsse54890.2022.9836262","url":null,"abstract":"Polyadenylation or poly(A) tail at the 3’-end of RNA is a type of post-transcriptional modification that regulates RNA biological functions and stability. While poly(A) tails in eukaryotes are 80–200 nucleotides long and generally stabilize the RNAs, the poly(A) tails in prokaryotes are significantly shorter and usually destabilize the RNAs. Although Oxford Nanopore Technologies (ONT) direct RNA sequencing provides long-read sequencing that allows poly(A) tail length estimation in recent years, the standard nanopore RNA library preparation, which requires sequencing oligo(dT) adapter ligation, could not capture short poly(A) tail RNAs, especially RNAs in prokaryotes. Hence, we introduced in vitro uridylation and developed a computational processing workflow to dissect poly(A) tails and estimate their length. Using synthetic RNAs as standard, this study provides the workflow for short poly(A) tail length estimation by reassigning underestimated poly(A) tail length using base-called sequencing data and re-segmenting misassigned poly(A) tail. This workflow could be beneficial to obtain poly(A) tail length in different organisms and potentially provide insights into their gene expression, regulation, and modification.","PeriodicalId":284735,"journal":{"name":"2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134012390","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

Personalized Tourist Attraction Recommendation System Using Collaborative Filtering on Tourist Preferences 基于游客偏好协同过滤的个性化旅游景点推荐系统

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836255

Weeriya Supanich, Suwanee Kulkarineetham

引用次数: 0

A Microservices Quality Model Based on Microservices Anti-patterns 基于微服务反模式的微服务质量模型

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836297

Sermsook Pulnil, T. Senivongse

{"title":"A Microservices Quality Model Based on Microservices Anti-patterns","authors":"Sermsook Pulnil, T. Senivongse","doi":"10.1109/jcsse54890.2022.9836297","DOIUrl":"https://doi.org/10.1109/jcsse54890.2022.9836297","url":null,"abstract":"Microservices architecture is becoming popular as many software organizations have the need to transform large complex systems into small-sized software units whose functions are separated by business capabilities. Microservices architecture is preferable since it promotes independence of software modification, maintenance, and deployment. However, anti-patterns or poor development patterns of microservices can decrease the software quality. Nonetheless, quality measurement of microservices design based on anti-patterns has not been found in existing research. Using the QMOOD method for quality model design, this paper proposes a microservices quality model based on 11 microservices anti-patterns and ISO/IEe 25010 as a standard reference for quality attributes. Also, a microservices quality measurement tool called MSA Nose+ is developed to measure the quality of microservices applications. In an experiment to validate the proposed model, the result shows that the quality values obtained from the proposed model improve consistently with the refactorings that are applied to a microservice-based system. Thus, development teams can use the proposed model and quality measurements as part of the decision making on quality improvement and maintenance of microservices applications.","PeriodicalId":284735,"journal":{"name":"2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126894020","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

Matching Corporate Software Engineers and Data Offerings - from Discovery to Recommendations 匹配企业软件工程师和数据产品-从发现到推荐

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836285

B. Martens, Jörg Franke

{"title":"Matching Corporate Software Engineers and Data Offerings - from Discovery to Recommendations","authors":"B. Martens, Jörg Franke","doi":"10.1109/jcsse54890.2022.9836285","DOIUrl":"https://doi.org/10.1109/jcsse54890.2022.9836285","url":null,"abstract":"Data plays an essential role in developing software, especially in large and complex projects. Data can be collected from different stages of the software life cycle and can form the basis for decision-making and thereby the success of projects. With increasingly automated and tool-supported development landscapes, the amount of data that is generated and accessible rises as well. Large corporate software projects, in addition to generating data also give rise to a high volume of offerings based on the data. These aim to increase the value generated by stakeholders like developers, requirement engineers, and testers. The offering land-scape brings new complexities and difficulties with it and needs to be managed, systematized, and brought to the correct person at the right time in order to create value. In this publication, models for abstracting and generalizing data offerings and data consumers are presented and their applicability is verified in a global corporate software environment. In addition, approaches for matching data offerings and consumers are presented. Our results show that offerings and consumers can be abstracted and matched using a recommender system.","PeriodicalId":284735,"journal":{"name":"2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123587101","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

A Hybrid Recommender System for Improving Rating Prediction of Movie Recommendation 一种改进电影推荐评级预测的混合推荐系统

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836257

Nikorn Kannikaklang, S. Wongthanavasu, W. Thamviset

引用次数: 2

AiRadar: A Sensing Platform for Indoor Air Quality Monitoring 空气雷达:室内空气质量监测的传感平台

2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE) Pub Date : 2022-06-22 DOI: 10.1109/jcsse54890.2022.9836252

Dolvara Gunatilaka, Purinat Sanbundit, Supawit Puengchim, Chayarat Boontham

{"title":"AiRadar: A Sensing Platform for Indoor Air Quality Monitoring","authors":"Dolvara Gunatilaka, Purinat Sanbundit, Supawit Puengchim, Chayarat Boontham","doi":"10.1109/jcsse54890.2022.9836252","DOIUrl":"https://doi.org/10.1109/jcsse54890.2022.9836252","url":null,"abstract":"Rapid urbanization and the expansion of industrial societies have increased air pollution, which deteriorates the health of a population and impacts global warming and climate change. Indoor air quality (IAQ) has been a topic of growing concern since people spend most of their time indoors. This drives the need for a system that can continuously monitor indoor air pollutants and consequently control indoor air quality. Therefore, this paper aims to develop an IoT-enabled system capable of measuring, aggregating, and visualizing indoor air quality. Our IAQ sensing platform collects several common air quality factors consisting of particulate matter (PM2.5 and PM10), Carbon Monoxide (CO), Volatile Organic Compound (VOC), humidity, and temperature. We implement a web application to enable access to real-time air quality data, to promptly notify users of the unhealthy environment, and to provide recommendations for air quality improvement. Additionally, we calibrate the sensors to enhance their accuracy and conduct an indoor test for system performance assessment.","PeriodicalId":284735,"journal":{"name":"2022 19th International Joint Conference on Computer Science and Software Engineering (JCSSE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114748195","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