2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)最新文献

Data Mining for Analyzing GEM's Entrepreneurial Growth Indicators 基于数据挖掘的创业板企业成长指标分析

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00059

Bernadus Lukas, C. Nugraheni, Vania Natali

引用次数: 0

To Study the Effect of Changing Load Pattern on Voltage Profile in RDS 研究负载模式变化对RDS电压分布的影响

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00063

Meena Kumri, Surender Singh, Pinkey, Manisha, S. Tiwari, R. Sahdev

引用次数: 0

A thorough analysis of Microsoft HoloLens applications in the medical and healthcare fields 全面分析微软HoloLens在医疗保健领域的应用

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00067

Sanchit Vashisht, Neha Tuli, Avinash Sharma, A. Mantri, Shivam Sharma

引用次数: 0

Analyzing Textual Documents Indexes by Applying Key-Phrases Extraction in Fuzzy Logic Domain Based on A Graphical Indexing Methodology 基于图形索引方法的模糊逻辑域关键短语提取分析文本文档索引

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00035

Latifa Rassam, Mohamed Raoui, A. Zellou, Moulay Hafid El Yazidi

引用次数: 0

Deep Network-based Slow Feature Analysis for Human Fall Detection 基于深度网络的人体跌倒检测慢特征分析

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00024

Anima Pramanik, Kavya Venkatagiri, Sobhan Sarkar, S. Pal

{"title":"Deep Network-based Slow Feature Analysis for Human Fall Detection","authors":"Anima Pramanik, Kavya Venkatagiri, Sobhan Sarkar, S. Pal","doi":"10.1109/ICCMSO58359.2022.00024","DOIUrl":"https://doi.org/10.1109/ICCMSO58359.2022.00024","url":null,"abstract":"One of the most concerning safety hazards for elderly people is abnormal falls in public places. Vision-based fall detection using ambient cameras is a popular non-intrusive solution. Recent research uses Slow Feature Analysis (SFA), which can learn the slow invariant varying shape features obtained from input signals and is efficient. Another recent famous approach in motion detection is deep learning. However, the fall event in actual cases is diverse, resulting in complications in the detection task. Additionally, it is difficult to acquire fall-related data; hence, simulation is done on fall events to generate a training dataset, resulting in smaller data. Considering these complications, we have presented a novel method by combining SFA, deep learning models, namely Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM), and rule-base. CNN is used to extract the object region, thereby reducing the region of interest (RoI). Two shape features, such as aspect ratio and area of RoI are considered as input to the LSTM for retrieving the temporal information which is further used for rule generation, thereby increasing the detection accuracy. The efficacy of the proposed method for various features, such as aspect ratio, area, and aspect r$a$ tio+area is demonstrated over the UR Fall data with an accuracy of 95.2%, 93.8%, and 96.36%, respectively.","PeriodicalId":209727,"journal":{"name":"2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131744637","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

Improvement in Dents at Gear Manufacturer Company Through Lean Six Sigma 通过精益六西格玛改进齿轮制造公司的凹痕

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00085

S. Dhingra, Prateek Guleria, Rohit Khargotra, R. K. Shukla

{"title":"Improvement in Dents at Gear Manufacturer Company Through Lean Six Sigma","authors":"S. Dhingra, Prateek Guleria, Rohit Khargotra, R. K. Shukla","doi":"10.1109/ICCMSO58359.2022.00085","DOIUrl":"https://doi.org/10.1109/ICCMSO58359.2022.00085","url":null,"abstract":"Performance measurement of small and medium-sized businesses is the primary need for all companies to survive and thrive in a dynamic global company. A structured and systematic, the integrated organization increases employee reliability, sustainability, and loyalty. This paper is a case study of a gear manufacturing industry that was facing the problem of rejection due to dents and damages in gear. The DMAIC cycle along with different tools used in the research work includes SIPOC (Supply, Input, Process, Output, Control) Pareto analysis, Root & Cause analysis, and FMEA (Failure Mode and Effect Analysis). The six- sigma level was improved from 4.06 to 3.46 and the rejection rate reduced from 7.44% to 1.56%. These findings highlighted the influence of a Lean Six Sigma module in the gear manufacturing unit, which has already increased operational quality and continuity to increase market success and meet customer expectations. According to the findings, applying lean six sigma tools will result in increased productivity. The results could assist businesses to decide the quality tools that were likely to improve efficiency, competitiveness, and expense.","PeriodicalId":209727,"journal":{"name":"2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122164503","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

Response Surface Methodology in Valorization Process Modelling of Different wastes 响应面法在不同废物增值过程建模中的应用

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00036

R. Kaushal, Sonam Sandhu

引用次数: 0

Underwater Image Dehazing using Dark Channel Prior and Filtering Techniques 使用暗通道先验和滤波技术的水下图像去雾

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00016

Renjith V. Ravi, S. Goyal, Sardar M N Islam

引用次数: 0

Analysis of DenseNet201 with SGD optimizer for diagnosis of multiple rice leaf diseases 利用 SGD 优化器分析 DenseNet201，诊断多种水稻叶部病害

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00046

Shikha Prasher, Leema Nelson, Avinash Sharma

引用次数: 2

Performance Study and Development of a 5-Axis C.N. C. Machine 五轴数控机床的性能研究与开发

2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO) Pub Date : 2022-12-01 DOI: 10.1109/ICCMSO58359.2022.00080

Mukesh Kumar, Rajesh Baitha, Santosh Kumar, R. Kaushal

{"title":"Performance Study and Development of a 5-Axis C.N. C. Machine","authors":"Mukesh Kumar, Rajesh Baitha, Santosh Kumar, R. Kaushal","doi":"10.1109/ICCMSO58359.2022.00080","DOIUrl":"https://doi.org/10.1109/ICCMSO58359.2022.00080","url":null,"abstract":"Using the conceptual design method, a Five-axis C.N.C. machine has been developed using the already available C.N.C. setup (R.P. setup). The C.N.C. machine setup has got mechatronic controls and a computer interface through CAMSOFT for various C.N.C. operations. The present work highlights the importance of conceptual design and innovation's role in developing C.N.C. machines. The work initially begins with studying an existing partially developed 3-axis C.N.C. setup with certain significant flaws. Conceptual design is applied to correct the existing problems and fabricate new components for the Five-axis C.N.C. milling machine. After getting feasible designs, the work moves into the fabrication stage, where all the corrective measures are taken, and specific new components are developed/ fabricated and added to the C.N.C. setup accordingly. The New milling attachments is developed successfully and installed on the C.N.C. machine setup. The working of the developed five-axis C.N.C. milling is tested by making 2D & 3D contoured products (three cases). It is found to be satisfactory based on various experiments (visual and dimensional inspection).","PeriodicalId":209727,"journal":{"name":"2022 International Conference on Computational Modelling, Simulation and Optimization (ICCMSO)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133022067","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