2022 International Conference on Machine Learning and Cybernetics (ICMLC)最新文献

The MIP-Based Large Neighborhood Local Search Method for Large-Scale Optimization Problems with Many Constraints: Application to the Machining Scheduling 基于mip的多约束大规模优化问题大邻域局部搜索方法在加工调度中的应用

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/ICMLC56445.2022.9941310

Jin Matsuzaki, K. Sakakibara, Masaki Nakamura

引用次数: 0

Simulation Of Bone Fracture Healing Process Using Ultrasound And BMD Data 利用超声和骨密度数据模拟骨折愈合过程

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/ICMLC56445.2022.9941331

T. Ueyama, Yohei Kumabe, K. Oe, T. Fukui, T. Niikura, R. Kuroda, Masakazu Morimoto, N. Yagi, Y. Hata

{"title":"Simulation Of Bone Fracture Healing Process Using Ultrasound And BMD Data","authors":"T. Ueyama, Yohei Kumabe, K. Oe, T. Fukui, T. Niikura, R. Kuroda, Masakazu Morimoto, N. Yagi, Y. Hata","doi":"10.1109/ICMLC56445.2022.9941331","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941331","url":null,"abstract":"In this paper, we simulate the fracture healing process using ultrasound and Bone Mineral Density (BMD). The frequency component of the reflected wave from the rat's bone is used. A hole was drilled in the center of the rat's femur to simulate a fracture. Firstly, the frequency response is obtained by adapting a Fast Fourier Transform to the resulting reflected wave, which is then cross spectrum to highlight characteristic frequencies. Next, we use the frequency and BMD healthy bone data to construct a pseudo-individual without considering overlap. Finally, we determine the degree of healing process for each individual. In our previous studies, it has the lack of reliability since there was only one data set that was set to be a bone hole was a problem, so the objective was to increase the number of data and improve reliability. The reliability of bone hole selection is demonstrated by comparing data increased frequencies data for pseudo-individuals with increased data frequencies to the healing process of pseudo-individuals used BMD from previous studies.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130302481","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

Magical-Decomposition: Winning Both Adversarial Robustness and Efficiency on Hardware 神奇分解:在硬件上赢得对抗鲁棒性和效率

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/ICMLC56445.2022.9941335

Xin Cheng, Meiqi Wang, Yuanyuan Shi, Jun Lin, Zhongfeng Wang

{"title":"Magical-Decomposition: Winning Both Adversarial Robustness and Efficiency on Hardware","authors":"Xin Cheng, Meiqi Wang, Yuanyuan Shi, Jun Lin, Zhongfeng Wang","doi":"10.1109/ICMLC56445.2022.9941335","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941335","url":null,"abstract":"Model compression is one of the most preferred techniques for efficiently deploying deep neural networks (DNNs) on resource- constrained Internet of Things (IoT) platforms. However, the simply compressed model is often vulnerable to adversarial attacks, leading to a conflict between robustness and efficiency, especially for IoT devices exposed to complex real-world scenarios. We, for the first time, address this problem by developing a novel framework dubbed Magical-Decomposition to simultaneously enhance both robustness and efficiency for hardware. By leveraging a hardware-friendly model compression method called singular value decomposition, the defending algorithm can be supported by most of the existing DNN hardware accelerators. To step further, by using a recently developed DNN interpretation tool, the underlying scheme of how the adversarial accuracy can be increased in the compressed model is highlighted clearly. Ablation studies and extensive experiments under various attacks/models/datasets consistently validate the effectiveness and scalability of the proposed framework.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116176054","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

Stock Price Prediction Based On Lstm And Bert 基于Lstm和Bert的股票价格预测

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/ICMLC56445.2022.9941293

Xiaojian Weng, Xudong Lin, S. Zhao

{"title":"Stock Price Prediction Based On Lstm And Bert","authors":"Xiaojian Weng, Xudong Lin, S. Zhao","doi":"10.1109/ICMLC56445.2022.9941293","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941293","url":null,"abstract":"Price movements in the stock market affect all aspects of the social economy, and forecasting stock prices is of great importance. Traditional stock forecasting models are based on statistical regression models, which are difficult to characterize the influential relationships between multiple variables and predict stock price trends with large errors. In recent years, with the development of neural networks, neural networks have become a common method for stock forecasting, which include Back Propagation (BP) neural network, Convolutional Neural Networks (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) neural network. However, most of the previous stock price prediction models only use the basic stock market data, ignoring the influence of stock market investor sentiment on stock prices. A new stock price prediction model is proposed to address the above problems. First, the investor sentiment before the stock opening is calculated by fine-tuning the BERT model, then the calculated investor sentiment and the basic stock quotation data are aggregated, and finally the LSTM model is used to predict the closing price of the next stock trading day. We validate the effectiveness of the model on a real dataset of three Chinese listed companies.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126266430","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

Automated Traffic Management System Using Deep Learning Based Object Detection 基于深度学习的自动交通管理系统

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/ICMLC56445.2022.9941332

Sumindar Kaur Saini, Mankaran Singh Ghumman

{"title":"Automated Traffic Management System Using Deep Learning Based Object Detection","authors":"Sumindar Kaur Saini, Mankaran Singh Ghumman","doi":"10.1109/ICMLC56445.2022.9941332","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941332","url":null,"abstract":"The traffic menace in India’s metropolitan cities causes many travelers to suffer daily. In traffic control, simple and old forms of signal controllers, known as electro-mechanical signal controllers, are used till-date which use dial timers that have fixed, signalized intersection time plans. As the time is fixed, the people in the lane with the greatest number of vehicles must wait the most, leading to wastage of time, money, and natural resources such as petrol and diesel. The proposed system is a traffic light system with feedback in real-time. The vehicles present in a specific lane are detected using a camera and then the deep learning algorithm, YOLO (You Only Look Once) detects the total number of vehicles in a lane which is used for feedback control of the lights. The traffic lights controller changes its parameters in response to traffic length in a lane, optimizing the road use and the signal timing of an intersection will benefit from being adapted to the dominant flows changing over the time of the day. The experiment analysis reveals that response time for green light in real-time increases in the lane with a greater number of vehicles and is decreased for the lane with lesser number of vehicles keeping the total time the same, so effective in managing traffic.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130723504","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

Estimation of Stimulus Time and Average Attention State Based on Collective Addition of Event-Related Electroencephalography 基于事件相关脑电图集体相加的刺激时间和平均注意状态估计

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/ICMLC56445.2022.9941311

Taichi Haba, Gaochao Cui, Hideaki Touyama

{"title":"Estimation of Stimulus Time and Average Attention State Based on Collective Addition of Event-Related Electroencephalography","authors":"Taichi Haba, Gaochao Cui, Hideaki Touyama","doi":"10.1109/ICMLC56445.2022.9941311","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941311","url":null,"abstract":"Brain-computer interface is mainly developed for clinical rehabilitation. Numerous studies have shown that it can also be applied to neuromarketing to assist customers in making decisions. By identifying the P300 component of the event-related potentials (ERPs), it can be known whether the target commodity or target stimuli is interesting to the consumer. However, when the target stimuli appear more frequently and people’s responses to stimuli vary, it is challenging to locate the target stimuli based on the P300 in practical applications. Moreover, a significant P300 component can only be obtained by stacking and averaging multiple ERPs in normal conditions. In this study, we propose a group electroencephalogram processing method to estimate the timing of evoked stimulus appearance without compromising real-time performance using convolutional neural networks. In addition, this method can be used to estimate the group’s attention to the target and standard stimulus. The results show that the effectiveness of the proposed processing method for stimuli presentation time estimation and group attention state estimation are 87.10 % and 96.55 %, respectively.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128027777","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

ICMLC 2022 Cover Page ICMLC 2022封面

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/icmlc56445.2022.9941305

引用次数: 0

Time Series Knee Joint Angle Analysis During Gait for Patients with Down Syndrome by 3d Pose Estimation 基于三维姿态估计的唐氏综合征患者步态时间序列膝关节角度分析

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/ICMLC56445.2022.9941317

Kohei Hayashi, N. Yagi, Yutaka Hata, Yoshiaki Saji, Y. Sakai

{"title":"Time Series Knee Joint Angle Analysis During Gait for Patients with Down Syndrome by 3d Pose Estimation","authors":"Kohei Hayashi, N. Yagi, Yutaka Hata, Yoshiaki Saji, Y. Sakai","doi":"10.1109/ICMLC56445.2022.9941317","DOIUrl":"https://doi.org/10.1109/ICMLC56445.2022.9941317","url":null,"abstract":"Down syndrome is the most common chromosomal abnormality. In recent years, the frequency of births with Down syndrome has been increasing in Japan. One of the reasons for this is the trend toward late childbearing. Many children with Down syndrome often have gait problems such as Genu valgum and Genu varum. In order to solve such gait problems, custom- made insoles need to be created. This is because the shape of the feet and the way of walking vary from patient to patient. In addition, it is necessary to investigate whether these custom-made insoles are suitable for the patients with Down syndrome or not. Currently, the evaluation is done visually by doctors and physical therapists, however the criteria for judgment are unclear. Therefore, we worked to develop a system to determine whether custom-made insoles would improve Genu valgum and Genu varum. Since the children with Down syndrome rarely walk straight when taking gait videos, we focused on performing gait analysis in 3D instead of 2D, which has been performed previously. In this study, we estimated the joint position coordinates of a person from a walking video using 3D pose estimation in order to quantitatively evaluate the gait condition of children with Down syndrome. Additionally, by detecting the time of knee joint loading and measuring the knee joint angle, we were able to propose a system that can confirm symptoms such as genu valgum and genu varum. This system is expected to be easier than the existing 3D analyzers for gait analysis of patients with Down syndrome. As a future work, the accuracy of the system itself needs to be evaluated using an existing 3D motion analyzer that measures with markers.","PeriodicalId":117829,"journal":{"name":"2022 International Conference on Machine Learning and Cybernetics (ICMLC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129619372","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

Examination of Analysis Methods for E-Learning System Grade Data Using Formal Concept Analysis 使用形式概念分析的电子学习系统成绩数据分析方法检验

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/ICMLC56445.2022.9941338

Yoshiki Asami, T. Motoyoshi, K. Sawai, H. Masuta, Noboru Takagi

引用次数: 0

Tooth Recognition in X-Ray Dental Panoramic Images with Prosthetic Detection 基于假体检测的x射线牙齿全景图像中的牙齿识别

2022 International Conference on Machine Learning and Cybernetics (ICMLC) Pub Date : 2022-09-09 DOI: 10.1109/ICMLC56445.2022.9941333

Kazunori Oka, Anas M. Ali, Daisuke Fujita, Syoji Kobashi

引用次数: 1