Proceedings of the 2023 9th International Conference on Computing and Data Engineering最新文献

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New Fitness Evaluation for a Single Machine Scheduling Problem with an Overtime Option 带超时选项的单机调度问题的新适应度评价
Watcharapan Sukkerd, Jakkrit Latthawanichphan, W. Songserm, T. Wuttipornpun
{"title":"New Fitness Evaluation for a Single Machine Scheduling Problem with an Overtime Option","authors":"Watcharapan Sukkerd, Jakkrit Latthawanichphan, W. Songserm, T. Wuttipornpun","doi":"10.1145/3589845.3589859","DOIUrl":"https://doi.org/10.1145/3589845.3589859","url":null,"abstract":"This research studies a single machine scheduling problem with overtime option. The objective is to minimise the total penalty cost (TPC), which is the sum of tardiness, earliness, and overtime costs. A new fitness evaluation heuristic (FEH) capable of minimising TPC is developed. Since FEH works well only when the sequence of jobs is known, it is then integrated into the fitness evaluation step of a variable neighbourhood search (VNS-FEH) to determine the optimal sequence of jobs that obtains the minimum TPC. Effectiveness of the proposed VNS-FEH is evaluated by using real data from three industrial case studies consisting of five job sizes (5, 10, 20, 50, 100) for each, resulting in 270 experiments. The best common parameter setting (BCS) of VNS-FEH applicable for all of the case studies is determined. The results show that TPC obtained from VNS-FEH with its BCS is deviated on average from the best TPC of 0.02%. Moreover, it is better than the bound obtained from the mathematical model with the relative percentage improvement (RPI) of 37.22%.","PeriodicalId":302027,"journal":{"name":"Proceedings of the 2023 9th International Conference on Computing and Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116199888","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-view Subspace Clustering with Complex Noise Modeling 基于复杂噪声建模的多视图子空间聚类
Xiangyu Lu, Lingzhi Zhu, Yuyang Sun
{"title":"Multi-view Subspace Clustering with Complex Noise Modeling","authors":"Xiangyu Lu, Lingzhi Zhu, Yuyang Sun","doi":"10.1145/3589845.3589854","DOIUrl":"https://doi.org/10.1145/3589845.3589854","url":null,"abstract":"Multi-view data clustering often aims to utilize various representations or views of original data to improve the clustering performance compared to the single-view clustering approach. Most multi-view subspace clustering methods are proposed to construct the affinity matrix of each view individually and then implement with spectral clustering for multi-view data clustering. The multi-view low-rank sparse subspace clustering (MLRSSC) is an effective and popular clustering algorithm among multi-view subspace clustering. This method can explore the joint subspace representation through creating an affinity matrix integrated of all views of input data. In addition, the low-rank and sparsity constraints are introduced into this method to enhance the clustering results. However, the original MLRSSC uses the mean square error as the fidelity term while not consider the complex noise pollution in real situations. Therefore, we introduce a complex noise modeling approach, i.e., independent and piecewise identically distributed (IPID) noise model, for MLRSSC to improve its performance. The related experimental results confirm that this proposed algorithm surpasses many state-of-the-art subspace clustering methods on several real-world datasets.","PeriodicalId":302027,"journal":{"name":"Proceedings of the 2023 9th International Conference on Computing and Data Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131089302","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
Computer-aided Design System for Anti-Corrosion of Coal Preparation Equipment Based on Improved Technology of High-salt Coal Washing Wastewater 基于高盐洗煤废水改进工艺的选煤设备防腐计算机辅助设计系统
Wenjuan Sun, Guozhi Liang
{"title":"Computer-aided Design System for Anti-Corrosion of Coal Preparation Equipment Based on Improved Technology of High-salt Coal Washing Wastewater","authors":"Wenjuan Sun, Guozhi Liang","doi":"10.1145/3589845.3589858","DOIUrl":"https://doi.org/10.1145/3589845.3589858","url":null,"abstract":"Coal preparation plant production mainly depends on equipment. Through on-site investigation, coal preparation equipment will inevitably come into contact with various materials during use, wear and tear, which is very easy to cause corrosion, and the longer the time, the more serious the corrosion situation and degree, which will lead to the gradual loss rate of equipment. As a result, corrosion protection technology needs to be taken into account when designing large industrial installations or equipment. Aiming at the characteristics of high-salt coal washing wastewater, a computer-aided design system for corrosion protection of coal preparation equipment is established in this paper, which is suitable for the actual situation of coal preparation plants. This system uses computer-aided technology to collect all corrosion data into the overall anti-rust computer for unified management and maintenance. In order to achieve effective data support for the anti-corrosion information system, it is necessary to establish a scientific data query system to meet the needs of information technology. The research results show that the computer-aided design system for corrosion protection of coal preparation equipment can design anti-corrosion schemes based on different types of corrosion data, and users can analyze the anti-corrosion schemes through the evaluation system, thereby determining the practicability of the system and scheme. The advantage of this system application is that it can prevent all kinds of complex corrosive factors, prolong the service life of coal preparation equipment, provide great convenience for staff to deal with corrosion data and information, and improve work efficiency and economic benefits.","PeriodicalId":302027,"journal":{"name":"Proceedings of the 2023 9th International Conference on Computing and Data Engineering","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121728467","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
Classification and Prediction on Cardiovascular disease datasets 心血管疾病数据集的分类与预测
Chu-An Tsai, Haiqi Zhu, Haochen Su, Yuni Xia, S. Fang
{"title":"Classification and Prediction on Cardiovascular disease datasets","authors":"Chu-An Tsai, Haiqi Zhu, Haochen Su, Yuni Xia, S. Fang","doi":"10.1145/3589845.3589852","DOIUrl":"https://doi.org/10.1145/3589845.3589852","url":null,"abstract":"Cardiovascular disease is the leading cause of death worldwide and in the U.S. Almost half of adults in the U.S. have some form of cardiovascular disease. It affects people of all ages, sexes, ethnicities and socioeconomic levels. However, people who have Cardiovascular diseases might be asymptomatic, which means the patient does not feeling anything at all. Asymptomatic patients would not get diagnosed until they reach a more serious stage and may miss the best time for treatment. The aim of this project is to collect data on cardiovascular disease, analyze the data and use them to build a predictive machine learning model for early-stage heart disease detection. Multiple different data pre-processing and classification methods have been applied and compared for the best prediction accuracy.","PeriodicalId":302027,"journal":{"name":"Proceedings of the 2023 9th International Conference on Computing and Data Engineering","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129981953","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
Proceedings of the 2023 9th International Conference on Computing and Data Engineering 2023第9届计算与数据工程国际会议论文集
{"title":"Proceedings of the 2023 9th International Conference on Computing and Data Engineering","authors":"","doi":"10.1145/3589845","DOIUrl":"https://doi.org/10.1145/3589845","url":null,"abstract":"","PeriodicalId":302027,"journal":{"name":"Proceedings of the 2023 9th International Conference on Computing and Data Engineering","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115737173","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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