2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)最新文献_第3页

Dimensions of Agile Enterprise Architecture 敏捷企业架构的维度

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910275

Sirinuch Sararuch, P. Wannapiroon, P. Nilsook

{"title":"Dimensions of Agile Enterprise Architecture","authors":"Sirinuch Sararuch, P. Wannapiroon, P. Nilsook","doi":"10.1109/RI2C56397.2022.9910275","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910275","url":null,"abstract":"The Impact of Industry Revolution has been accelerated by global pandemic crisis recently. Disruptive technology is one of the key driving forces of transformation on the rapid change in business model and market demand. Traditional industries, including education, experience the challenge of maintaining business at lower cost while generating high performance (more revenue) and staying relevant in the market. Digital Transformation helps improve collaboration within and between organizations by creating immersive customer experience for better engagement. Enterprise organization wants to grow and give it a better chance of thriving post-pandemic by becoming more innovative and generating higher productivity and making better decisions with insights from data-driven platform. To achieve all the business requirements for transformation is not straightforward. By understanding the alignment of Business and Information Technology Architecture, Higher Education institutions can manage the challenges of the future trends. The success of Digital Transformation in enterprise organizations is determined by an agile implementation framework of Enterprise Architecture (EA). Enterprise Architecture is the critical intermediary between business and IT corporate wide strategy. Through understanding the current situation and performance of an enterprise, EA can help foresight future business challenges and deliver the information needed while simultaneously ensuring opportunities for business growth.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125417805","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

Analysis of Wood Collection Site in the Biofuel Supply Chain using Integrated K-means and Rectilinear Minisum Location Model 基于综合k -均值和线性最小区位模型的生物燃料供应链木材收集点分析

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910280

K. Ransikarbum, Sreenath Chalil Madathil

引用次数: 3

Generating and Evaluating Text Summarisations using Text-representing Centroids(TRC) 使用文本表示质心(TRC)生成和评估文本摘要

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910272

Yanakorn Ruamsuk, A. Mingkhwan, H. Unger

引用次数: 1

Antipodal Vivaldi Antenna with Dielectric Lens for Biomedical Imaging Applications 介质透镜对映维瓦尔第天线在生物医学成像中的应用

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910304

W. Thaiwirot, Dechawat Kamoldej, Phongsapuk Detchporn, P. Thongdit, Shalermchon Tangwachirapan

引用次数: 1

The Effect of Sensor Placement for Accurate Fall Detection based on Deep Learning Model 基于深度学习模型的传感器放置对准确跌倒检测的影响

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910267

S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul

{"title":"The Effect of Sensor Placement for Accurate Fall Detection based on Deep Learning Model","authors":"S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul","doi":"10.1109/RI2C56397.2022.9910267","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910267","url":null,"abstract":"The development of inertial sensor technology and the growing utilization of wearable electronics (such as smartwatches, smart bands, and other intelligent gadgets) have facilitated the advancement of studies into automated Fall Detection Systems (FDSs). In the last decade, there has been significant scientific interest in maintaining FDSs. Focused on assessing the data acquired by wearable inertial sensors, machine learning (ML) techniques have demonstrated high efficacy in distinguishing falls from typical motions or activities of daily living (ADLs). In most research, unfortunately, the effectiveness of machine learning classifiers was constrained by feature extraction and selection processes that relied on human-made decisions. Recently, deep learning (DL) model findings s how their effectiveness for FDS. One of these effective DL models is the ResNeXt model, a deep neural network that operates based on convolutional layers with aggregated residual transformation. This study investigates the influence of sensor placement on various body locations for the fall detection issue. The ResNeXt model was assessed and compared to other baseline deep learning algorithms using the public UMAFall dataset for fall detection. Employing sensor data on waist location, the suggested model attained the most significant classification ac curacy of 97.275% when classifying falls.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128620449","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

Microcontroller and Internet of Things Application for Smart Restroom 智能卫生间的单片机及物联网应用

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910335

Jirawat Thaenthong, Varinthon Kwanjun, Phimsai Charoensuk

引用次数: 0

Deep Learning Networks for Eating and Drinking Recognition based on Smartwatch Sensors 基于智能手表传感器的饮食识别深度学习网络

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910318

S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul

{"title":"Deep Learning Networks for Eating and Drinking Recognition based on Smartwatch Sensors","authors":"S. Mekruksavanich, Ponnipa Jantawong, Narit Hnoohom, A. Jitpattanakul","doi":"10.1109/RI2C56397.2022.9910318","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910318","url":null,"abstract":"Smartwatches are becoming more popular for recognizing and monitoring human actions in everyday life. These wearable devices are equipped with various IMU sensors for ubiquitous data processing and recording of human physical activity data. Sensor-based human activity recognition (HAR) has risen to the top of the list of the most active research topic due to its widely real-life applications in various practical domains, such as healthcare monitoring, sports and exercise tracking, and misbehavior prevention. Many machine learning and deep learning approaches have been recently proposed to solve the problem of human activity recognition, focusing on activities of daily living. However, an exciting and challenging HAR topic deals with more complex human activities such as eating-related activities. This paper proposes a sensor-based HAR framework using data from eating-related activities recorded by a smartwatch sensor. In this framework, five d eep learning networks (CNN, LSTM, BiLSTM, Stacked LSTM, CNN-LSTM, and LSTM-CNN) are evaluated for their recognition of eating-related activities. To ensure the model’s dependability, data from eating-related activities on the standard publicly available dataset WISDM-HARB are utilized to evaluate the proposed framework using state-of-the-art metrics: accuracy and confusion matrices. Experiment findings demonstrate that the S tacked LSTM model outperforms other deep learning models, achieving an accuracy of 97.37%.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127194222","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

Effect of Laser Pulse Overlap using Nanosecond Pulsed Lasers for Paint Removal on AA6061 激光脉冲重叠对纳秒脉冲激光去除AA6061涂层的影响

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910309

P. Kittiboonanan, Jack B. McWilliams, Polsin Taechamaneesatit, A. Ratanavis

引用次数: 0

An Incorporated 3D-Printed Lens with Square Microstrip Patch Antenna for NaCl Solution Discrimination 一种集成3d打印方形微带贴片天线透镜用于NaCl溶液判别

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910338

N. Chudpooti, Patchadaporn Sangpet, Sukanya Chudpooti, P. Akkaraekthalin, I. Robertson, N. Somjit

{"title":"An Incorporated 3D-Printed Lens with Square Microstrip Patch Antenna for NaCl Solution Discrimination","authors":"N. Chudpooti, Patchadaporn Sangpet, Sukanya Chudpooti, P. Akkaraekthalin, I. Robertson, N. Somjit","doi":"10.1109/RI2C56397.2022.9910338","DOIUrl":"https://doi.org/10.1109/RI2C56397.2022.9910338","url":null,"abstract":"This paper presents a 3D-printed hemispherical lens incorporated with a square patch microstrip antenna for liquid-mixture characterization. The proposed hemispherical lens antenna is designed, fabricated, and integrated with the microstrip patch planar antenna. An Acrylonitrile Butadiene Styrene (ABS) is selected to design the 3D-printed lens antenna by using the fused deposition modeling (FDM) method, due to available 3D-printed material in the laboratory. The optimum dimensions and shape of the hemispherical lens antenna are obtained by using the 3D EM Simulation CST Studio, which is used to investigate the characteristic of the antenna, e.g., gain, radiation pattern, and reflection coefficient. To characterize the liquid content in NaCl solution, the level of the transmission coefficient (S21) is detected. The proposed sensor system offers various preferable features, e.g., non-destructive method and non-contact measurement. Five liquid solutions under test (LUT), e.g., 5%, 10%, 15%, 20%, and 25% NaCl in the NaCl-aqueous solutions, are measured and performed to generate the extraction model. The proposed sensor also offers other advantages, e.g., real-time monitoring and no life-cycle limitation.","PeriodicalId":403083,"journal":{"name":"2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C)","volume":"229 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122661614","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

Metal Crack Detection with Chipless RFID Sensor using Shot-Time Matrix Pencil Method 基于短时矩阵铅笔法的无芯片RFID传感器金属裂纹检测

2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics (RI2C) Pub Date : 2022-08-04 DOI: 10.1109/RI2C56397.2022.9910285

Nattawat Chantasen, Nattakarn Shutimarrungson, A. Boonpoonga, Lakkhana Bannawat, P. Akkaraekthalin

引用次数: 0