{"title":"A design of a home-based human health monitoring device with OneNET cloud platform","authors":"Xiaobo Liu, Mingyu Gao, Huipin Lin, Yi Chen","doi":"10.1109/IHMSC55436.2022.00040","DOIUrl":"https://doi.org/10.1109/IHMSC55436.2022.00040","url":null,"abstract":"As the pace of life continues to accelerate, the issue of subhealth becomes an important topic and the study of human health monitoring receives more attention. Compared with traditional health monitoring devices, a portable and low-cost monitoring system is urgently needed to help people obtain their human health status. In this paper, we design a home-based human health monitoring system. The system uses an STM32 microcontroller as the main controller of the embedded system and four human signal acquisition circuits to collect human heart rate signal, ECG signal, blood pressure signal, and body temperature signal. After processing the data, the system applies a wireless module and uploads the health data to the OneNET cloud platform. The experimental results show that the system can accurately collect human physiological signals, and the error of heart rate signal is within 10 Bmp, blood pressure is within 10 mmHg, and body temperature is within 1.5°C compared with professional medical equipment. Finally, the health data is stored and displayed in real-time on the OneNET cloud platform.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125629807","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}
{"title":"Application of support vector machines in photovoltaic power prediction","authors":"J. Xue, Dianlun Cai, Zhou Gang","doi":"10.1109/ihmsc55436.2022.00022","DOIUrl":"https://doi.org/10.1109/ihmsc55436.2022.00022","url":null,"abstract":"PV power generation is affected by environmental factors such as solar radiation intensity, temperature and humidity, and PV power generation is characterized by volatility and instability, and the prediction accuracy of traditional prediction algorithms is low. In this paper, support vector machine is used as the PV power generation prediction algorithm, and the training and testing samples for the experiment are selected from the historical data in the laboratory. The support vector machine model trained in MATLAB simulation environment is used to predict and analyze the laboratory PV power generation. The simulation experiment results show that the stability of PV prediction based on support vector machine is high and the prediction error is small, which overcomes the error brought by the traditional prediction algorithm pursuing empirical risk minimization and improves the accuracy of the prediction system.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130812076","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}
{"title":"The Jessen inequality of semi-E-preinvex functions and its applications","authors":"Zufeng Fu, Haiying Wang, Xiao Jia","doi":"10.1109/IHMSC55436.2022.00036","DOIUrl":"https://doi.org/10.1109/IHMSC55436.2022.00036","url":null,"abstract":"The Jensen inequality for the semi-E-preinvex functions is obtained by introducing the η-E-convex linear combination suitable for E-invex sets and semi-E-preinvex functions, and an upper bound of the error of the semi-E-preinvex functions’ Jensen inequality generated by two points is obtained.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"20 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130959397","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}
{"title":"Research on resonant power supply for plasma cleaning based on adaptive genetic optimization PID","authors":"Xue Jiaxiang, Wang Yitong, Ding Duhan, Zhou Gang","doi":"10.1109/IHMSC55436.2022.00015","DOIUrl":"https://doi.org/10.1109/IHMSC55436.2022.00015","url":null,"abstract":"In view of the large disturbance and non-linearity of the existing plasma discharge power supply system, an adaptive genetic optimization PID control algorithm is proposed to replace the original PID control algorithm. According to the three indexes of overshoot, regulation time and steady-state accuracy, the evaluation function is formulated. Considering the convergence performance and operation speed of the system, the dynamic crossover and mutation probabilities are formulated. Finally, the simulation program is built and the step response curves of the closed-loop transfer function before and after optimization are compared. The results show that the overshoot of the system decreases from 7.14% to 1.55%, and the regulation time decreases from 337.7μs to 5.17μs.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"56 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131858944","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}
{"title":"Customer Segmentation in the Retail Sector: A Data Analytics Approach","authors":"Kevser Sahinbas, Ferhat Ozgur Catak","doi":"10.1109/IHMSC55436.2022.00048","DOIUrl":"https://doi.org/10.1109/IHMSC55436.2022.00048","url":null,"abstract":"Data analytics techniques are widely used in customer segmentation, which groups objects according to the similarity difference on each object and provides a high level of homogeneity in the same cluster or a high level of heterogeneity between each group. In this study, the behavior of customers in the retail sector was analyzed using customer segmentation data mining methods such as OPTICS, BIRCH, Agglomerative Clustuering, K-Means and DBSCAN algithms. The aim of the study is to investigate different data analytics algorithms using a private textile and retail company that has an agreement with e-commerce sites and marketplaces. OPTICS, BIRCH, Agglomerative Clustuering, K-Means have shown almost same clustering results, DBSCAN has outperformed with 0.206086 Silhouette value. The purpose of this paper is to provide a proof of concept of how e-commerce data analytics can be used in customer segmentation.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132948281","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}
{"title":"A Vehicle Detection Method Based on Improved YOLOV5s","authors":"Mingyue Hu, Songlin Gao, Xinbiao Lu","doi":"10.1109/ihmsc55436.2022.00035","DOIUrl":"https://doi.org/10.1109/ihmsc55436.2022.00035","url":null,"abstract":"Along with the advancement of artificial intelligence technology, the development of autonomous driving has been expanding. Vehicle detection is an indispensable part of autonomous driving technology. To achieve high accuracy and high speed, this paper proposes a vehicle detection method based on improved YOLOV5s. Firstly, the Convolutional Block Attention Module (CBAM) is introduced, which enhances the ability of the network to extract vehicle features and improves the detection accuracy significantly. Secondly, some ordinary convolutions are replaced by the Ghost Module, which is a lightweight convolutional module in Backbone in order to reduce the computational cost and the number of parameters significantly. Finally, experimental results show that the proposed method improves the accuracy by 2 % over the original YOLOV5s, reduces the parameter quantity to 82.97% of the original model, and achieves the target detection of vehicles effectively.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"718 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123863153","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}
{"title":"Super-Large Building Oriented BIM Lightweight Method","authors":"Hua Tian, Daping Li, Zimu Xiao, Qingxiang Zhao, Hongjie Shen","doi":"10.1109/ihmsc55436.2022.00045","DOIUrl":"https://doi.org/10.1109/ihmsc55436.2022.00045","url":null,"abstract":"With the development of building information technology, building information modeling (BIM) plays an increasingly important role in the construction industry. Aiming at the handling of large amount of original data, data exchange difficulty, and low efficient rendering for super-large buildings, the data conversion method, geometric data compression algorithm and high-performance transmission and rendering engine for heterogeneous models are studied, and an integrated transmission and rendering engine is designed.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125016419","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}
Shaohui Chang, Xiaohui Wang, Tingzhang Fang, Lin Qian
{"title":"Design and Implementation of Wake-on-Voice and Command Recognition Algorithm","authors":"Shaohui Chang, Xiaohui Wang, Tingzhang Fang, Lin Qian","doi":"10.1109/ihmsc55436.2022.00009","DOIUrl":"https://doi.org/10.1109/ihmsc55436.2022.00009","url":null,"abstract":"This paper analyzes methods of speech recognition and lays an emphasize on acoustic model, language model and decoding algorithm based on the output of these two models. Hidden Markov Model is applied to acoustic model to build a state graph of acoustic features of input speech sample. After testing, the arousing rate is above 95%, the mis-arousing-rate is below 5% and response time of the wake-on-voice model is about 0.2s.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130847657","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}
{"title":"Research on improved A-star algorithm for global path planning of unmanned logistics vehicles","authors":"Liu Jianqin, Guo Xiao","doi":"10.1109/ihmsc55436.2022.00019","DOIUrl":"https://doi.org/10.1109/ihmsc55436.2022.00019","url":null,"abstract":"Global path planning process of unmanned logistics vehicles, such as difficulty in improving accuracy, long operation time, and poor driving stability, this paper improves map construction, acquisition node mode, and expansion node mode. Firstly, road nodes instead of obstacle nodes are used in map construction so that the search times and search time are reduced. Secondly, UTM nodes are collected in the field to construct scatter maps instead of grid maps, which solves the problem of long searching time under high precision caused by the positive correlation between grid accuracy and path accuracy in the traditional A-star algorithm. Finally, the k- nearest neighbor is used to expand the sub-nodes instead of the nine-grid method to improve the path accuracy of the Astar algorithm, reduce the search time, and improve the driving stability of unmanned logistics vehicles. Based on the unmanned logistics vehicle experimental platform of an intelligent vehicle research and development company in Tianjin, this paper uses the proposed algorithm to carry out global path planning in a specified area of 27,800 square meters. The experimental results show that the centimeter- level (10 significant digits of the path node) searches were reduced to 765. Compared with the A-Star algorithm under the grid map, it is reduced by 99.88% and the search time was reduced from 41884s to less than 2s. At the same time, by changing the value of k, several controlled experiments were conducted to compare the number and distance of nodes in each group. Finally, when k is 5, the number of nodes is 117, and the distance between nodes is 0.5 to 2m, the unmanned logistics vehicle can run continuously and stably.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128576901","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}
{"title":"GlueGAN: Gluing Two Images as a Panorama with Adversarial Learning","authors":"Yongxing He, Wei Li, Z. Li, Yongchuan Tang","doi":"10.1109/IHMSC55436.2022.00053","DOIUrl":"https://doi.org/10.1109/IHMSC55436.2022.00053","url":null,"abstract":"Inspired by panorama photos and Chinese handscroll paintings, we propose an unsupervised algorithm to glue two similar independent images with a generated image as a panorama. Different from existing inpainting methods which can only be used to complete limited missing area with supervised training, the advantage of our GlueGAN lies in generating an image with almost the same size as the input image to form an overall image. To overcome mode collapse which is common in GANs, we propose a two-stage framework. In the first generation stage of HED edge, the model generates simple HED edge images. The second image generation stage aims to generate color image with the aid of HED edge image generated in the first stage. Moreover, we additionally train a doodle-to-edge generator to help users participate in the generation process. To verify our proposed method, a dataset, including 90000 Chinese landscape painting auctions dataset, is created. Experiment results on the dataset show our proposed method can solve this problem well and has greater performance than existing algorithms.","PeriodicalId":447862,"journal":{"name":"2022 14th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133091504","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}