Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293803
M. E. Mital, Rogelio Ruzcko Tobias, Herbert V. Villaruel, Jose Martin Z. Maningo, R. Billones, R. R. Vicerra, A. Bandala, E. Dadios
The Aspergillus genus is deemed relevant for distinction and classification in the field of food, agriculture and medicine. As there are harmful and useful ones, it adds to the necessity of correct classification. Categorization of this conidial fungi is usually done through manual microscopical procedures which apparently has a degree of subjectiveness. In order to classify Aspergillus samples faster and more accurately, technology, specifically image processing and machine learning are incorporated in this study. Pre-trained deep learning models are employed in classifying 9 kinds of Aspergillus. The methodology is generally comprised of preprocessing, deep-learning (training) and performance evaluation. Performance evaluation pertains to the validation accuracy and running times of the system after training through visual display of graphs and tabulation of acquired data. This study achieved a 93.3333% testing accuracy proving that the transferred knowledge is accurate, compatible and reliable.
{"title":"Transfer Learning Approach for the Classification of Conidial Fungi (Genus Aspergillus) Thru Pre-trained Deep Learning Models","authors":"M. E. Mital, Rogelio Ruzcko Tobias, Herbert V. Villaruel, Jose Martin Z. Maningo, R. Billones, R. R. Vicerra, A. Bandala, E. Dadios","doi":"10.1109/TENCON50793.2020.9293803","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293803","url":null,"abstract":"The Aspergillus genus is deemed relevant for distinction and classification in the field of food, agriculture and medicine. As there are harmful and useful ones, it adds to the necessity of correct classification. Categorization of this conidial fungi is usually done through manual microscopical procedures which apparently has a degree of subjectiveness. In order to classify Aspergillus samples faster and more accurately, technology, specifically image processing and machine learning are incorporated in this study. Pre-trained deep learning models are employed in classifying 9 kinds of Aspergillus. The methodology is generally comprised of preprocessing, deep-learning (training) and performance evaluation. Performance evaluation pertains to the validation accuracy and running times of the system after training through visual display of graphs and tabulation of acquired data. This study achieved a 93.3333% testing accuracy proving that the transferred knowledge is accurate, compatible and reliable.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132665581","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}
Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293793
Edgardo Manuel H. Mariveles, Jimwell G. Porcare, Jovelyn M. Regonay, Meryll R. Cruz, M. G. Beaño, Florante M. Andaya, Ericson A. Mandayo, Bernie B. Domingo
Wearing of improper uniform has been one of the problems being faced by Pamantasan ng Cabuyao due to a massive number of students entering the university. The security guards do not have the ability to monitor the student’s attire all the time. There are also some students who do not wear Identification Cards (ID) upon entering the school premise which is also important for the student’s or staff’s identification as well as the school’s security and integrity. This paper aims to plan and built a device whose main function is to monitor student’s attire for most of the time. Uniform recognition-activated gate for dress code implementation of Pamantasan ng Cabuyao focused on improving the security system upon entering the gate of the university. This device used biometrics, barcode scanner of the Identification (ID) card and image recognition for uniform to open the gate. The mechanism to open the gate uses a servo motor which is connected to the gate structure. Based on the evaluation done by the professionals and preferred users, the device has been considered very good for each criteria provided of its scores. The device will be available for further improvement to develop more functions necessary to the workplace of its application.
由于大量学生进入这所大学，穿着不合适的制服已经成为Pamantasan ng Cabuyao面临的问题之一。保安人员没有能力随时监控学生的着装。还有一些学生在进入校园时没有佩戴身份证(ID)，这对学生或员工的身份识别以及学校的安全和诚信也很重要。本文旨在设计并构建一个以监控学生着装为主要功能的设备。Pamantasan ng Cabuyao着装规范实施统一识别激活门，重点是完善进入大学大门的安全系统。该设备采用生物识别技术、条形码扫描器的身份识别(ID)卡和制服图像识别来打开大门。打开闸门的机构采用伺服电机，该伺服电机连接到闸门结构上。根据专业人士和首选用户的评估，该设备已被认为是非常好的每个标准提供它的分数。该设备可用于进一步改进，以开发其应用的工作场所所需的更多功能。
{"title":"Uniform Recognition Activated Gate for Dress Code Implementation of Pamantasan ng Cabuyao","authors":"Edgardo Manuel H. Mariveles, Jimwell G. Porcare, Jovelyn M. Regonay, Meryll R. Cruz, M. G. Beaño, Florante M. Andaya, Ericson A. Mandayo, Bernie B. Domingo","doi":"10.1109/TENCON50793.2020.9293793","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293793","url":null,"abstract":"Wearing of improper uniform has been one of the problems being faced by Pamantasan ng Cabuyao due to a massive number of students entering the university. The security guards do not have the ability to monitor the student’s attire all the time. There are also some students who do not wear Identification Cards (ID) upon entering the school premise which is also important for the student’s or staff’s identification as well as the school’s security and integrity. This paper aims to plan and built a device whose main function is to monitor student’s attire for most of the time. Uniform recognition-activated gate for dress code implementation of Pamantasan ng Cabuyao focused on improving the security system upon entering the gate of the university. This device used biometrics, barcode scanner of the Identification (ID) card and image recognition for uniform to open the gate. The mechanism to open the gate uses a servo motor which is connected to the gate structure. Based on the evaluation done by the professionals and preferred users, the device has been considered very good for each criteria provided of its scores. The device will be available for further improvement to develop more functions necessary to the workplace of its application.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131033707","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}
Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293808
Pimmy Gandotra, V. Bhatia, Brejesh Lall
With the recent outbreak of COVID-19 and other pandemics, improving the public safety communication is essential for efficient communication in the 5G and beyond wireless communication networks. The key requirements shall be lower delays, improved coordination and efficient resource utilization, to achieve higher efficiency in the network performance in an emergency/pandemic situation. Since deployment costs and scarce resource availability are major constraints in the network functioning, looking forward to a new network solution, a heterogenous network (HetNet) architecture has been proposed in this paper, for an efficient broadcast network set up during emergency situations. This paper proposes a two-tier heterogenous network (HetNet) architecture, with the macro base station (MBS) tier being Tier 1 and the small cell tier (SCT) being Tier 2. Here the SCT is mostly involved in setting up of a public warning communication system. The HetNets also intend to promote device-to-device (D2D) communication links, in case of absence of connectivity to the user via the MBT or the SCT. Use of small cells and D2D links shall improve the overall system performance. Certain research challenges however persist, and are stated in the paper.
{"title":"Paradigm Shift in Public Warning Systems: A Two-tier Approach towards Broadcasting","authors":"Pimmy Gandotra, V. Bhatia, Brejesh Lall","doi":"10.1109/TENCON50793.2020.9293808","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293808","url":null,"abstract":"With the recent outbreak of COVID-19 and other pandemics, improving the public safety communication is essential for efficient communication in the 5G and beyond wireless communication networks. The key requirements shall be lower delays, improved coordination and efficient resource utilization, to achieve higher efficiency in the network performance in an emergency/pandemic situation. Since deployment costs and scarce resource availability are major constraints in the network functioning, looking forward to a new network solution, a heterogenous network (HetNet) architecture has been proposed in this paper, for an efficient broadcast network set up during emergency situations. This paper proposes a two-tier heterogenous network (HetNet) architecture, with the macro base station (MBS) tier being Tier 1 and the small cell tier (SCT) being Tier 2. Here the SCT is mostly involved in setting up of a public warning communication system. The HetNets also intend to promote device-to-device (D2D) communication links, in case of absence of connectivity to the user via the MBT or the SCT. Use of small cells and D2D links shall improve the overall system performance. Certain research challenges however persist, and are stated in the paper.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133343545","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}
Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293719
Justin D. de Guia, Ronnie S. Concepcion, Hilario A. Calinao, Jonnel D. Alejandrino, E. Dadios, E. Sybingco
Energy production of photovoltaic (PV) system is heavily influenced by solar irradiance. Accurate prediction of solar irradiance leads to optimal dispatching of available energy resources and anticipating end-user demand. However, it is difficult to do due to fluctuating nature of weather patterns. In the study, neural network models were defined to predict solar irradiance values based on weather patterns. Models included in the study are artificial neural network, convolutional neural network, bidirectional long-short term memory (LSTM) and stacked LSTM. Preprocessing methods such as data normalization and principal component analysis were applied before model training. Regression metrics such as mean squared error (MSE), maximum residual error (max error), mean absolute error (MAE), explained variance score (EVS), and regression score function (R2 score), were used to evaluate the performance of model prediction. Plots such as prediction curves, learning curves, and histogram of error distribution were also considered as well for further analysis of model performance. All models showed that it is capable of learning unforeseen values, however, stacked LSTM has the best results with the max error, R2, MAE, MSE, and EVS values of 651.536, 0.953, 41.738, 5124.686, and 0.946, respectively.
{"title":"Using Stacked Long Short Term Memory with Principal Component Analysis for Short Term Prediction of Solar Irradiance based on Weather Patterns","authors":"Justin D. de Guia, Ronnie S. Concepcion, Hilario A. Calinao, Jonnel D. Alejandrino, E. Dadios, E. Sybingco","doi":"10.1109/TENCON50793.2020.9293719","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293719","url":null,"abstract":"Energy production of photovoltaic (PV) system is heavily influenced by solar irradiance. Accurate prediction of solar irradiance leads to optimal dispatching of available energy resources and anticipating end-user demand. However, it is difficult to do due to fluctuating nature of weather patterns. In the study, neural network models were defined to predict solar irradiance values based on weather patterns. Models included in the study are artificial neural network, convolutional neural network, bidirectional long-short term memory (LSTM) and stacked LSTM. Preprocessing methods such as data normalization and principal component analysis were applied before model training. Regression metrics such as mean squared error (MSE), maximum residual error (max error), mean absolute error (MAE), explained variance score (EVS), and regression score function (R2 score), were used to evaluate the performance of model prediction. Plots such as prediction curves, learning curves, and histogram of error distribution were also considered as well for further analysis of model performance. All models showed that it is capable of learning unforeseen values, however, stacked LSTM has the best results with the max error, R2, MAE, MSE, and EVS values of 651.536, 0.953, 41.738, 5124.686, and 0.946, respectively.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129443278","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}
Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293709
Masayuki Odagawa, Takumi Okamoto, T. Koide, S. Yoshida, H. Mieno, Toru Tamaki, B. Raytchev, K. Kaneda, Shinji Tanaka
This paper presents a classification method for a Computer-Aided Diagnosis (CAD) system in a colorectal magnified Narrow Band Imaging (NBI) endoscopy. For the classification of a histologic findings, we consider an output result of a lesion endoscopic image from a pre-learned Convolutional Neural Network (CNN) as a feature vector and construct a set of Support Vector Machines (SVMs) by learning a set of the CNN feature vectors. In the video images, each frame has appearance changes such as blur, color shift, reflection of light and so on and it affects classification results. To improve the robustness of CAD system, we construct the SVM learned by multiple image sizes data sets so as to adapt to the noise peculiar to the video image. We confirmed that the proposed method achieves higher robustness, stable, and high classification accuracy in the endoscopic video image. The proposed method also can cope with differences in resolution by old and new endoscopes and perform stably with respect to the input endoscopic video image. We evaluated the proposed method on a customizable embedded DSP core implemented into a FPGA based prototyping system.
{"title":"Classification Method with CNN features and SVM for Computer-Aided Diagnosis System in Colorectal Magnified NBI Endoscopy","authors":"Masayuki Odagawa, Takumi Okamoto, T. Koide, S. Yoshida, H. Mieno, Toru Tamaki, B. Raytchev, K. Kaneda, Shinji Tanaka","doi":"10.1109/TENCON50793.2020.9293709","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293709","url":null,"abstract":"This paper presents a classification method for a Computer-Aided Diagnosis (CAD) system in a colorectal magnified Narrow Band Imaging (NBI) endoscopy. For the classification of a histologic findings, we consider an output result of a lesion endoscopic image from a pre-learned Convolutional Neural Network (CNN) as a feature vector and construct a set of Support Vector Machines (SVMs) by learning a set of the CNN feature vectors. In the video images, each frame has appearance changes such as blur, color shift, reflection of light and so on and it affects classification results. To improve the robustness of CAD system, we construct the SVM learned by multiple image sizes data sets so as to adapt to the noise peculiar to the video image. We confirmed that the proposed method achieves higher robustness, stable, and high classification accuracy in the endoscopic video image. The proposed method also can cope with differences in resolution by old and new endoscopes and perform stably with respect to the input endoscopic video image. We evaluated the proposed method on a customizable embedded DSP core implemented into a FPGA based prototyping system.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133454845","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}
Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293840
Tessya Rismonita, Devi T. Avalokita, A. Handayani, A. W. Setiawan
Fetal head circumference (HC) is one of the fetal biometrics that is often used to determine gestational age and monitor the fetal growth in the womb. Nowadays, head circumference measurement from ultrasound images is performed manually by a doctor or sonographer by drawing a line or forming an ellipse to surround the fetal head. However, manual annotations are prone to human error and intra-observer as well as inter-observer variabilities. In this research, an automatic fetal head candidate localization was implemented using Haar Cascade Classifier (HCC) and further optimized by Enhanced Localization Algorithm (ELA). The combination of HCC and ELA was evaluated on 703 ultrasound images of the second trimester and 141 ultrasound images of the third trimester using the Jaccard Index (JI), Dice Similarity Coefficient (DSC), and Overlapped Area Ratio (OAR). The localization results showed that the HCC + ELA produced an average JI of 90.5%, DSC of 94.58%, OAR of 97.77% for the second trimester and an average JI of 88.17%, DSC of 93.33%, OAR of 96.97% for the third trimester. Based on the three evaluation parameters, we analyzed the factors affecting the accuracy of the localization algorithm and the correspondence of the localization results with the ellipse fitting outcome as the final process to determine the fetal head circumference.
胎儿头围(HC)是胎儿生物特征之一，常用于确定胎龄和监测胎儿在子宫内的生长。现在，从超声图像中测量头围是由医生或超声医师通过在胎儿头部周围画一条线或形成一个椭圆来手工完成的。但是，手动注释容易出现人为错误，并且容易出现观察者内部和观察者之间的变量。本研究采用Haar级联分类器(HCC)实现胎儿头候选物的自动定位，并通过增强定位算法(ELA)进一步优化。采用Jaccard指数(JI)、Dice Similarity Coefficient (DSC)、Overlapped Area Ratio (OAR)对703张妊娠中期超声图像和141张妊娠晚期超声图像进行HCC合并ELA的评价。定位结果显示HCC + ELA在妊娠中期平均JI为90.5%，DSC为94.58%，OAR为97.77%，晚期平均JI为88.17%，DSC为93.33%，OAR为96.97%。基于这三个评价参数，我们分析了影响定位算法准确性的因素，以及定位结果与椭圆拟合结果的对应关系，作为确定胎儿头围的最终过程。
{"title":"Automatic Fetal Head Candidate Localization from 2D Ultrasound Images using Haar Cascade Classifier and Enhanced Localization Algorithm","authors":"Tessya Rismonita, Devi T. Avalokita, A. Handayani, A. W. Setiawan","doi":"10.1109/TENCON50793.2020.9293840","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293840","url":null,"abstract":"Fetal head circumference (HC) is one of the fetal biometrics that is often used to determine gestational age and monitor the fetal growth in the womb. Nowadays, head circumference measurement from ultrasound images is performed manually by a doctor or sonographer by drawing a line or forming an ellipse to surround the fetal head. However, manual annotations are prone to human error and intra-observer as well as inter-observer variabilities. In this research, an automatic fetal head candidate localization was implemented using Haar Cascade Classifier (HCC) and further optimized by Enhanced Localization Algorithm (ELA). The combination of HCC and ELA was evaluated on 703 ultrasound images of the second trimester and 141 ultrasound images of the third trimester using the Jaccard Index (JI), Dice Similarity Coefficient (DSC), and Overlapped Area Ratio (OAR). The localization results showed that the HCC + ELA produced an average JI of 90.5%, DSC of 94.58%, OAR of 97.77% for the second trimester and an average JI of 88.17%, DSC of 93.33%, OAR of 96.97% for the third trimester. Based on the three evaluation parameters, we analyzed the factors affecting the accuracy of the localization algorithm and the correspondence of the localization results with the ellipse fitting outcome as the final process to determine the fetal head circumference.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130252104","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}
Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293819
Shalitha Jayasekara, Y. Fernando
Cooking is an essential activity in the households in Sri Lanka. Sri Lankan households utilize several types of fuel to produce heat for their daily cooking needs. The most commonly used energy sources are Liquid Petroleum Gas (LPG) and Electricity. Therefore, it is essential to investigate the economic aspects of using each of these energy sources. This research aims to use existing data on several cooking appliances along with LPG and Electricity charges in Sri Lanka to calculate the costs of using each of the energy sources. With the total monthly cost of LPG at Rs.560/= and Electricity at Rs.1150/= as of March 2020, this study suggests that LPG is the most suitable energy source for cooking in Sri Lankan households.
{"title":"Reviewing the Economics of Using LPG Vs. Electricity for Household Cooking in Sri Lanka","authors":"Shalitha Jayasekara, Y. Fernando","doi":"10.1109/TENCON50793.2020.9293819","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293819","url":null,"abstract":"Cooking is an essential activity in the households in Sri Lanka. Sri Lankan households utilize several types of fuel to produce heat for their daily cooking needs. The most commonly used energy sources are Liquid Petroleum Gas (LPG) and Electricity. Therefore, it is essential to investigate the economic aspects of using each of these energy sources. This research aims to use existing data on several cooking appliances along with LPG and Electricity charges in Sri Lanka to calculate the costs of using each of the energy sources. With the total monthly cost of LPG at Rs.560/= and Electricity at Rs.1150/= as of March 2020, this study suggests that LPG is the most suitable energy source for cooking in Sri Lankan households.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131330861","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}
Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293895
Masaaki Komatsu, Hideaki Aburatani, Sanit Teawhim
The KOSEN-KMITL, the first Japanese style KOSEN in Thailand, was established on May 2019 in King Mongkut’s Institute of Technology Ladkrabang (KMITL). KOSEN-KMITL is an Engineering, Technology and Innovation workforce development project, to support, raise the investment and increase the industrial capacity of the Thai industry region. The establishment of the KOSEN-KMITL, which adopts the high-quality teaching and learning program courses under the guidance of the Japan KOSEN system, will build and develop the skilled human resources in engineering who can apply knowledge and skill, not only to create and develop innovations that help solving problems, but also to make “value added” in the industrial and social sector in Thailand. The KOSEN-KMITL course is different from the typical Engineering program in the Universities, with its 5-year course focusing on the practical engineering along with the theory and building knowledge based in several areas such as social sciences and economics that will students to understand human, public mind, social responsibility and the ability to communicate in both English and Japanese. In the first year in KOSEN-KMITL, students will learn “Introduction to Engineering Approach”, “Introduction to Engineering Design”, and “Lab work” as an early Engineering introductory education stage. These are the main subjects to learn the concept and methodology of Engineering Approach, Engineering Design, and various measurement technique and theoretical concepts by practical lab work experience. When we define the “Reverse Engineering”, these basic courses are to be defines as the Forward Engineering, and the Reverse Engineering shall be placed as the collaborated subject with one another to enhance an early Engineering introductory education.
{"title":"Application of the Reverse Engineering as an early Engineering Education","authors":"Masaaki Komatsu, Hideaki Aburatani, Sanit Teawhim","doi":"10.1109/TENCON50793.2020.9293895","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293895","url":null,"abstract":"The KOSEN-KMITL, the first Japanese style KOSEN in Thailand, was established on May 2019 in King Mongkut’s Institute of Technology Ladkrabang (KMITL). KOSEN-KMITL is an Engineering, Technology and Innovation workforce development project, to support, raise the investment and increase the industrial capacity of the Thai industry region. The establishment of the KOSEN-KMITL, which adopts the high-quality teaching and learning program courses under the guidance of the Japan KOSEN system, will build and develop the skilled human resources in engineering who can apply knowledge and skill, not only to create and develop innovations that help solving problems, but also to make “value added” in the industrial and social sector in Thailand. The KOSEN-KMITL course is different from the typical Engineering program in the Universities, with its 5-year course focusing on the practical engineering along with the theory and building knowledge based in several areas such as social sciences and economics that will students to understand human, public mind, social responsibility and the ability to communicate in both English and Japanese. In the first year in KOSEN-KMITL, students will learn “Introduction to Engineering Approach”, “Introduction to Engineering Design”, and “Lab work” as an early Engineering introductory education stage. These are the main subjects to learn the concept and methodology of Engineering Approach, Engineering Design, and various measurement technique and theoretical concepts by practical lab work experience. When we define the “Reverse Engineering”, these basic courses are to be defines as the Forward Engineering, and the Reverse Engineering shall be placed as the collaborated subject with one another to enhance an early Engineering introductory education.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132230558","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}
Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293759
Toshiro Nunome, Atsunori Ito
This paper proposes a control method for the transmission rate of haptic media to avoid network congestion in audiovisual and haptic interactive communications using TCP. The previous study has proposed a media-adaptive buffering control for QoE enhancement of audiovisual and haptic interactive communications over UDP. Most of the communications on the Internet use TCP. When we communicate audiovisual and haptic using TCP because of some restrictions, communication delay occurs by such as retransmission control, and media output quality degrades. Then, we control the media transmission rate according to network conditions and enhance QoE. We employ an application-level QoS parameter in the judgment of rate control of haptic media. We show that the interactive communication of audiovisual and haptic using TCP is feasible as using UDP through a subjective experiment.
{"title":"A Rate Control Method for QoE Enhancement of TCP-based Audiovisual and Haptic Interactive Communications","authors":"Toshiro Nunome, Atsunori Ito","doi":"10.1109/TENCON50793.2020.9293759","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293759","url":null,"abstract":"This paper proposes a control method for the transmission rate of haptic media to avoid network congestion in audiovisual and haptic interactive communications using TCP. The previous study has proposed a media-adaptive buffering control for QoE enhancement of audiovisual and haptic interactive communications over UDP. Most of the communications on the Internet use TCP. When we communicate audiovisual and haptic using TCP because of some restrictions, communication delay occurs by such as retransmission control, and media output quality degrades. Then, we control the media transmission rate according to network conditions and enhance QoE. We employ an application-level QoS parameter in the judgment of rate control of haptic media. We show that the interactive communication of audiovisual and haptic using TCP is feasible as using UDP through a subjective experiment.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132594173","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}
Pub Date : 2020-11-16DOI: 10.1109/TENCON50793.2020.9293907
Rayed Md. Muhaymin Hasan, Nahian Islam, Mehrab Azam Khan, Sams Shafiul Amin, A.K.M Abdul Malek Azad
Cooking system has been evolving for a long time. From the parabolic system to solar cooking. Every method had its unique concepts. Attempts towards solar cooking have always been proven beneficent and successful. Solar cooking is a system where energy comes from the photovoltaic solar panel which is powered by sunlight. We have designed a system where solar energy will be stored in a pack of battery which can be used in the absence of the sun. Combination of PV panels and batteries will provide the required power during sun time. A full-time main grid back- up is also present in the system.
{"title":"Improvement of Energy Efficiency and Effectiveness of Cooking in Solar Electric Slow Cooker for Tropical Countries","authors":"Rayed Md. Muhaymin Hasan, Nahian Islam, Mehrab Azam Khan, Sams Shafiul Amin, A.K.M Abdul Malek Azad","doi":"10.1109/TENCON50793.2020.9293907","DOIUrl":"https://doi.org/10.1109/TENCON50793.2020.9293907","url":null,"abstract":"Cooking system has been evolving for a long time. From the parabolic system to solar cooking. Every method had its unique concepts. Attempts towards solar cooking have always been proven beneficent and successful. Solar cooking is a system where energy comes from the photovoltaic solar panel which is powered by sunlight. We have designed a system where solar energy will be stored in a pack of battery which can be used in the absence of the sun. Combination of PV panels and batteries will provide the required power during sun time. A full-time main grid back- up is also present in the system.","PeriodicalId":283131,"journal":{"name":"2020 IEEE REGION 10 CONFERENCE (TENCON)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116794316","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}
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