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2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )最新文献

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Real-time Detection of Change of Human Motion by Analyzing Millimeter-wave Doppler Radar Signals Using Deep Learning Techniques 利用深度学习技术分析毫米波多普勒雷达信号实时检测人体运动变化
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983587
Chien-Hung Lai, Y-S Hwang, Sheng-Long Kao
{"title":"Real-time Detection of Change of Human Motion by Analyzing Millimeter-wave Doppler Radar Signals Using Deep Learning Techniques","authors":"Chien-Hung Lai, Y-S Hwang, Sheng-Long Kao","doi":"10.1109/ICKII55100.2022.9983587","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983587","url":null,"abstract":"A system based on a millimeter-wave radar module is presented in this paper. After detecting the change of human motion, the changes in the point cloud are observed by analyzing the Doppler signal. Then, the change of human motion is classified in real-time through deep learning (DL) techniques that include long short-term memory (LSTM) and 1D time distributed convolutional neural network (CNN) methods. Temporal continuity and scalability are considered for the techniques. Measuring 100 mm wide, 40.8 mm long, and 52.8 mm high, this millimeter-wave radar module features Frequency Modulated Continuous Wave (FMCW) in the 60 to 64 GHz frequency range with 3 transmit (15 dBm) and 4 receive antennas (14 dB) on a package (AOP), 120° azimuth field of view (FoV), and 40° elevation FoV. An additional 5V/2A DC power supply is required during operation, and 1843200bps communication is used through the USB serial port.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125484878","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
Music Emotion Analysis Based on Deep Learning Techniques for Streaming Platforms 基于深度学习技术的流媒体平台音乐情感分析
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983602
Pin-Hua Lee, Alicia Wen-Yu Wang, Chih-Hsien Hsia
{"title":"Music Emotion Analysis Based on Deep Learning Techniques for Streaming Platforms","authors":"Pin-Hua Lee, Alicia Wen-Yu Wang, Chih-Hsien Hsia","doi":"10.1109/ICKII55100.2022.9983602","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983602","url":null,"abstract":"The purpose of music therapy is to help listeners explore self-emotions and experiences, reduce pain, soothe mood, and increase motor coordination through their responses to music. Many arguments deriving from the perspectives of thalamic function, endocrine volume, β-endorphin, and psychology strengthen the scientific status of music therapy. Using the Chinese music library from 1922 to 2021 provided by Spotify and the different music audio characteristics, we analyzed the melody style of songs in the library to train an artificial intelligence model and features of music emotion. In addition, we also analyzed and compared the effectiveness and results between machine learning and deep neural network after applying them to music emotion classification. According to the experimental results, the tagging of Chinese music assists the listener to understand the song. The feeling and memory triggered by the patient’s connection to the songs or the selection of music in appropriate occasions steer patient’s physical, mental, and emotional states toward the desired direction for therapeutic purposes.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116449667","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
Large Pose Detection and Facial Landmark Description for Pose-invariant Face Recognition 面向姿态不变人脸识别的大姿态检测与人脸地标描述
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983525
Shinfeng D. Lin, P. L. Otoya
{"title":"Large Pose Detection and Facial Landmark Description for Pose-invariant Face Recognition","authors":"Shinfeng D. Lin, P. L. Otoya","doi":"10.1109/ICKII55100.2022.9983525","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983525","url":null,"abstract":"Face recognition is an important computer vision task affected by several factors. These factors include the face pose of the input image, features used to describe the image, illumination conditions, and facial expression. In this study, a pose-invariant face recognition framework based on large pose detection and facial landmark description is proposed. During the training phase, a large pose detector model is proposed to process the 2D spatial distributions of the detected facial landmarks on a set of face images. This model can detect whether the yaw angle of the face is large or small (semi-frontal face image). This results in two face pose scenarios. Then, a feature descriptor is applied to a set of predefined facial landmarks on a face image for obtaining the feature vectors. These feature vectors are used to train two face recognition models for each person in the database. One for the large pose scenario and the other for the semi-frontal pose scenario. During the testing phase, the large pose detector is used to select a type of face recognition model (large pose or semi-frontal one). The selected model is utilized to determine the identity of the person. In this study, the CMU-PIE database is employed. Three feature descriptors, SIFT, HOG, and LBP, are adopted for comparison. The models used for face recognition are SVM, GMM, and Naive Bayes. The novelty of the proposed method is using a large pose detector to improve the face recognition rate. After performing experimental trials on face images with pose angles ±90°, a performance comparable with state-of-the-art methods is obtained.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114840391","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: 2
The Application Research on Self-Health Management of People based on Mobile Internet Use 基于移动互联网的人群自我健康管理应用研究
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983521
S. Weng, Qinyin Chen, Meng Liu
{"title":"The Application Research on Self-Health Management of People based on Mobile Internet Use","authors":"S. Weng, Qinyin Chen, Meng Liu","doi":"10.1109/ICKII55100.2022.9983521","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983521","url":null,"abstract":"Studies have shown that people desire to do many things for themselves, including self-health management. Often, they look to the internet for solutions. Information should be accessible on computer or mobile devices with easy to understand instructions and the assurance that their personal information is protected. In order to develop an application to research this information, which is called EHR (Electronic Health Records), the use of at least 2000 completed questionnaires collected in community will be used to create a database. Questions will be asked that investigate the interest people might have to self-manage their health. Then that data will be tested and analyzed using various statistical methods of transferring personal information safely. People using this application will be able to safely get useful effective health instructions to meet their self-health management needs.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132533135","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
Comparison of Carbon Emission Forecasting in Guangdong Province Based on Multiple Machine Learning Models 基于多机器学习模型的广东省碳排放预测比较
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983576
Ziteng Huang, Chengxi Huang, Zhanjie Wen
{"title":"Comparison of Carbon Emission Forecasting in Guangdong Province Based on Multiple Machine Learning Models","authors":"Ziteng Huang, Chengxi Huang, Zhanjie Wen","doi":"10.1109/ICKII55100.2022.9983576","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983576","url":null,"abstract":"Guangdong province was selected as the experimental region to construct and compare the prediction ability of carbon emissions with six machine learning models: K-Nearest Neighbor, Back Propagation neural network, Random Forest, multiple linear regression model, XGBoost, and LightGBM. mRMR algorithm was used to select the optimal features as the input for each model to conduct carbon emission prediction experiments. The prediction ability of each model was investigated by calculating and analyzing the prediction accuracy, model running time, and model memory consumption. The results show that Random Forest, XGBoost, and LightGBM models have higher prediction accuracy than other models, and the features of population size and GDP per capita have the highest importance. LightGBM has the advantages of the short model running time and small memory consumption with the best overall performance while having higher model accuracy.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133955980","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: 2
Fabrication and Electrical Properties of Novel ZnTiO3/Si Capacitors with Various Zn(NO3)2 Concentrations 不同Zn(NO3)2浓度的新型ZnTiO3/Si电容器的制备及其电性能
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983549
Chih-Feng Yen, Shen-Hao Tsao, Yu-Ya Huang, H. Hsu, Youxin Zhong, Po-Chih Chen, Zhong-Wei Pan
{"title":"Fabrication and Electrical Properties of Novel ZnTiO3/Si Capacitors with Various Zn(NO3)2 Concentrations","authors":"Chih-Feng Yen, Shen-Hao Tsao, Yu-Ya Huang, H. Hsu, Youxin Zhong, Po-Chih Chen, Zhong-Wei Pan","doi":"10.1109/ICKII55100.2022.9983549","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983549","url":null,"abstract":"LPD method has many advantages such as low-temperature deposition, large deposition area, good film uniformity, and good step coverage. Therefore, we choose the LPD method to deposit zinc titanate (ZnTiO<inf>3</inf>) thin films, using hexafluorotitanium ammonia ((NH<inf>4</inf>)<inf>2</inf>TiF<inf>6</inf>) powder and zinc nitrate (Zn(NO<inf>3</inf>)<inf>2</inf>•6H<inf>2</inf>O) powder to synthesize zinc titanate film. By changing the molar concentration of zinc nitrate and post-deposition annealing, we obtain the best thin film data. When zinc nitrate was 1.3 M molar volume concentration and annealed for one hour using nitrogen as the post-deposition annealing gas, measured electrical properties including oxide capacitance (C<inf>ox</inf>), leakage current Density, k value, equivalent oxide thickness (EOT) effective oxide charge density (Q<inf>EFF</inf>) and interface state density (D<inf>it</inf>) are 50.1 pF, 1.94 × 10<sup>-5</sup> A/cm<sup>2</sup> at +5 V, 16.95, 48.8 nm, 1.76 × 10<sup>11</sup> cm<sup>-2</sup>, and 6.2 × 10<sup>11</sup> cm<sup>-2</sup>eV<sup>-1</sup>, respectively. The data reveal that the zinc titanate (ZnTiO<inf>3</inf>) film is successfully deposited on Si and has good electrical properties.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131601850","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
Zirconium Oxide Dielectric Layer: Preparation and Characterization with Various Volumes of Acetylacetone 氧化锆介电层的制备及不同体积乙酰丙酮的表征
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983560
Chih-Feng Yen, Shen-Hao Tsao, Yu-Ya Huang
{"title":"Zirconium Oxide Dielectric Layer: Preparation and Characterization with Various Volumes of Acetylacetone","authors":"Chih-Feng Yen, Shen-Hao Tsao, Yu-Ya Huang","doi":"10.1109/ICKII55100.2022.9983560","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983560","url":null,"abstract":"The zirconium dioxide film was prepared by sol-gel method, and the electrical properties of the film were explored by adjusting the added amount of acetylacetone. When an appropriate amount of acetylacetone was added, the film became smooth and dense. However, when excess acetylacetone was added, the film started to become rough. Thus, as the amount of acetylacetone gradually increased, the curve of the accumulation area became steeper. It was found that the amount of acetylacetone affected shallow energy levels and induced capacitance. Adding 2.5 ml of acetylacetone allowed the best film quality and near-ideal capacitance curve of the zirconium dioxide film with good electrical characteristics. Oxide capacitance, k value, flat band voltage difference, trapped charge densities, effective oxide charge density, and interface state density were 152.6 pF, 27.5, 0.1 V, 1.35 × 1011 cm-2, 3.1 × 1011 cm-2, and 4.36 × 1011 eV-1 cm-2, respectively.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117246779","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
Mirroring Reality: Surreal Tourist Gaze of Chinese Landscape Painting by Artificial Neural Networks 镜像现实:人工神经网络对中国山水画的超现实游客凝视
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983554
Hung-Cheng Chen, Yi-Fang Kao
{"title":"Mirroring Reality: Surreal Tourist Gaze of Chinese Landscape Painting by Artificial Neural Networks","authors":"Hung-Cheng Chen, Yi-Fang Kao","doi":"10.1109/ICKII55100.2022.9983554","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983554","url":null,"abstract":"In 2015, Google released the \"Deep-dream\" algorithm based on deep learning of artificial neural networks. This method reverses the path of feature capture in artificial intelligence image recognition. Instead, the artificial neural network captures hidden image features in the reverse direction. The original image is transformed into a fantasy world with dream-like animals and strange geometric shapes by iterating, reinforcing, and deepening. This dreamlike visual encounter demonstrates more than mere filtering of contrived images. The deep-dream algorithm inspires a bionic view of how artificial neural networks view and interpret the world. With this view, the algorithm constructs a bionic vision that reassembles, collages, and even emerges with species features. We explore the world of the Deep-dream in Chinese landscape painting from the viewpoint of the tourist gaze. The possible connections between AI and creativity and imagination are explored by comparing the work with that of Midjourney, a powerful prompt-based AI-generated art platform.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123634912","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
Leaf Feature Extraction and Classification Based on Combination Algorithm and Probabilistic Neural Network 基于组合算法和概率神经网络的叶片特征提取与分类
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983589
Wenbo Chen
{"title":"Leaf Feature Extraction and Classification Based on Combination Algorithm and Probabilistic Neural Network","authors":"Wenbo Chen","doi":"10.1109/ICKII55100.2022.9983589","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983589","url":null,"abstract":"In order to solve the problem of low precision in plant leaf identification, a method of plant leaf recognition is proposed based on a combination algorithm and probabilistic neural network. Firstly, the features of the leaf shape are quantitatively extracted by the improved corner point detection algorithm SUSAN, Hough transform, and other methods. Then, the improved probabilistic neural network (PNN) model is established to judge the type of leaves, and the leaves are classified again by using the texture data of leaves in parallel series. The experimental results show that the average recognition accuracy is 92.3%. Compared with other recognition techniques, this method improves the accuracy of leaf recognition.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129701364","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
Exploring Educational Applicability of Virtual Touch System on Maker Space 探索虚拟触摸系统在创客空间的教育适用性
2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII ) Pub Date : 2022-07-22 DOI: 10.1109/ICKII55100.2022.9983524
Pao-Ta Yu, Hung-Ting Lo, Yu-Cheng Fang, An-Fang Li, Ying-Han Liao, Cheng-Yu Tsai
{"title":"Exploring Educational Applicability of Virtual Touch System on Maker Space","authors":"Pao-Ta Yu, Hung-Ting Lo, Yu-Cheng Fang, An-Fang Li, Ying-Han Liao, Cheng-Yu Tsai","doi":"10.1109/ICKII55100.2022.9983524","DOIUrl":"https://doi.org/10.1109/ICKII55100.2022.9983524","url":null,"abstract":"Interaction with gestures is more intuitive than traditional input with a keyboard and a mouse. It has gradually become the major technology for extended reality. However, for most users, gesture control is not familiar as other interactive devices, and most user interfaces of daily-use applications are currently not designed for gesture control. Thus, we propose a mid-air hand gesture control system, named vTouch to realize a touch device trained by deep learning with a convolutional neural network for image feature extraction, attention mechanisms for extracting time-series data features, and fully connected layer for classification. Besides, there is a customized driver in kernel mode which treats the vTouch system as a virtual multi-touch device. An experimental design is also proposed to evaluate the effectiveness of the training and the usability of the system.","PeriodicalId":352222,"journal":{"name":"2022 IEEE 5th International Conference on Knowledge Innovation and Invention (ICKII )","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128660463","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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