2018 International Conference on Machine Learning and Cybernetics (ICMLC)最新文献_第4页

Imbalanced High-Frequency Number Classification Based on DSUS 基于DSUS的不平衡高频号码分类

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8526943

Zhujie Lin, Jianjun Zhang, Wing W. Y. Ng

引用次数: 0

Lower Assignment Reduction Algorithm for Relation Decision Systems 关系决策系统的下赋值约简算法

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527041

Zheng Hua, Qianchen Li

引用次数: 1

Recognition Of Bolt Quality Base On Elman Neural Network By Ant Colony Optimization Algorithm 基于蚁群优化算法的Elman神经网络螺栓质量识别

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527051

Wei-Guo Di, Xiaoyun Sun, Mingming Wang, Hui Xing, Jingna Liu

引用次数: 0

A Novel Surveillance Video Processing Using Stochastic Low-Rank And Generalized Low-Rank Approximation Techniques 基于随机低秩和广义低秩逼近技术的监控视频处理

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527059

Liang Luo, Zhi-Qin Zhao, Xiao-Pin Li

引用次数: 5

Vision-Based Line-Following Control of a Two-Wheel Self-Balancing Robot 基于视觉的两轮自平衡机器人线路跟踪控制

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8526952

Chun-Fei Hsu, Chien-Ting Su, Wei-Fu Kao, Bore-Kuen Lee

引用次数: 9

An Improved Glowworm Swarm Optimization Algorithm 一种改进的萤火虫群优化算法

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8526982

Yazhen Hao, Guo-Li Zhang, Bo Xiong

引用次数: 3

A System To Detect Mental Stress Using Machine Learning And Mobile Development 一个使用机器学习和移动开发来检测精神压力的系统

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527004

Chandrasekar Vuppalapati, Mohamad S. Khan, N. Raghu, P. Veluru, Suma Khursheed

{"title":"A System To Detect Mental Stress Using Machine Learning And Mobile Development","authors":"Chandrasekar Vuppalapati, Mohamad S. Khan, N. Raghu, P. Veluru, Suma Khursheed","doi":"10.1109/ICMLC.2018.8527004","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8527004","url":null,"abstract":"Hans Selye1 coined, in 1936, the term “Stress” and definedit as “the non-specific response of the body to any demand for change.” Stress was generallyconsidered as being synonymous with distress. English language dictionaries (Oxford & Merriam-Webster) defined it as “physical, mental, or emotional strain or tension when a person perceives that demands exceed the personal and social resources the individual is able to mobilize.” Stress affects over 100 million Americans and is a driver of many chronic diseases. According to American Psychological Association (APA) 2012 study, “Stress is costing organizations a Fortune” and some cases as much as $300 billion a year. The challenges, importantly, for the individuals and the organizations are lack of proactive detection of the stress and inept preventive actions to manage mental health to circumvent adverse effects of the stress. This research paper addresses the challenge by developing and deploying machine learning enabled data driven & Electroencephalogram biosensor integrated mobile application that proactively gleans User’s stressful episodes, infuses collaborative intelligence derived from de-identified yet User relevant demographical, physiological, lifestyle and behavioral datasets and preventive healthcare insights to counter otherwise the long term negative effects of the stresson Users health. The paper presents prototyping solution as well as its application and certain experimental results.1Hans Selye was a pioneering Hungarian-Canadian endocrinologist. He conducted much important scientific work on the hypothetical nonspecific response of an organism to stressors - https://www.stress.org/what-is-stress/","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125890968","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: 21

ICMLC 2018 Program Committee ICMLC 2018项目委员会

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/icmlc.2018.8526919

引用次数: 0

Resource Allocation For D2D Communications With A Novel Distributed Q-Learning Algorithm In Heterogeneous Networks 基于分布式q -学习算法的异构网络D2D通信资源分配

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8526955

Yung-Fa Huang, Tan-Hsu Tan, Neng-Chung Wang, Young-Long Chen, Yu-Ling Li

引用次数: 12

A Wearable Device Of Gait Tracking For Parkinson’S Disease Patients 一种用于帕金森病患者步态跟踪的可穿戴设备

2018 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2018-07-01 DOI: 10.1109/ICMLC.2018.8527011

Chien-Nan Lee, V. Fong, Yiu-Tong Chu, Ling Cheng, Han-Wei Chuang, Chun-Yi Lo

{"title":"A Wearable Device Of Gait Tracking For Parkinson’S Disease Patients","authors":"Chien-Nan Lee, V. Fong, Yiu-Tong Chu, Ling Cheng, Han-Wei Chuang, Chun-Yi Lo","doi":"10.1109/ICMLC.2018.8527011","DOIUrl":"https://doi.org/10.1109/ICMLC.2018.8527011","url":null,"abstract":"Parkinson’s disease (PD) is characterized by gait disorders such as walking with a stoop, muscle rigidity, bradykinesia, and poor sense of balance. Patients with mild gait disorders tend to shuffle and have difficulties in lifting their feet when walking. Moreover, PD patients walk with nearly absence of arm swinging; hence, their gait lacks coordination between the legs and arms. By contrast, severe gait disorders are characterized by scurrying forward, often falls, unable to walk and stand, as well as difficulties in turning or crossing a threshold [1] [2]. Furthermore, overdose of the PD drugs can cause mental impairment, movement fluctuation, and orthostatic hypotension, whereas inadequate dose has limited effectiveness [2] [3]. This study proposed a wearable device evaluating Parkinsonian gait and the wearers’ gait over an extended period is analyzed. By using the device, the examiner can convert plantar pressure and postural sway data into statistical charts for the physician to determine whether the wearers’ gait is in a normal orParkinsonian gait. Subsequently, the results can provide information for the physician about medication modification to improve the functional status of the patient.","PeriodicalId":309312,"journal":{"name":"2018 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130057294","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: 7