Pub Date : 2022-12-07DOI: 10.1109/ICETECC56662.2022.10068932
Julie Ann B. Susa, Jo Ann D. Doculan, Jovencio V. Merin, Jeddie M. Zarate, Meriam L. Tria, R. S. Evangelista, Michelle C. Reyes
Everyone is generally aware that there is sex separation in restrooms. This emphasizes the significance of sex-based toilet restrictions. Student’s behavior and ability to learn decency will be impacted by a system that identifies a person’s sex. This study offers a detecting mechanism that distinguishes between males and females. To categorize both sexes in schools, sex identification utilizing image processing was developed. The implementation of the sex identification system used the YOLOv3 technology. The study’s conclusions state that the detection model used has an mAP value of 95.28 %. The implementation of the Sex Identification for Restroom Restrictions is successful since the chosen model is advised in sex identification for both males and females.
{"title":"Deep Neural Network-Based Gender Identification for Surveillance Restroom Restriction System","authors":"Julie Ann B. Susa, Jo Ann D. Doculan, Jovencio V. Merin, Jeddie M. Zarate, Meriam L. Tria, R. S. Evangelista, Michelle C. Reyes","doi":"10.1109/ICETECC56662.2022.10068932","DOIUrl":"https://doi.org/10.1109/ICETECC56662.2022.10068932","url":null,"abstract":"Everyone is generally aware that there is sex separation in restrooms. This emphasizes the significance of sex-based toilet restrictions. Student’s behavior and ability to learn decency will be impacted by a system that identifies a person’s sex. This study offers a detecting mechanism that distinguishes between males and females. To categorize both sexes in schools, sex identification utilizing image processing was developed. The implementation of the sex identification system used the YOLOv3 technology. The study’s conclusions state that the detection model used has an mAP value of 95.28 %. The implementation of the Sex Identification for Restroom Restrictions is successful since the chosen model is advised in sex identification for both males and females.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116847606","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}
Robotic technologies have opened up hundreds of new limitless perspectives for educational reform. We have conducted research to study the impact and outcomes of Robotic teaching in systematic studies, experimental studies, and surveys. The conclusions of this study reveal that educational robots have an impact on children, teachers, and students. We looked into how robots affect children’s behavior, learning outcomes, perceptions, and human interactions. The learning efficacy of educational Robot teachers is determined by a variety of factors, including learning outcome, student behavior and mood during class sessions, student reaction, and student involvement during workshops/class participation/quizzes/Q&A sessions. The majority of the research articles we chose were experimental studies, and they all met their objectives, which included teaching mathematical problems, unit conversion problems, teaching English/secondary language, developing analytical, and computational skills, behavior, and attitude development, critical thinking, and improving communication skills.
{"title":"Impact of Adopting Robots as Teachers: A Review Study","authors":"Muhammad Ali, Sehrish Munawar Cheema, Nasir Ayub, Ammerha Naz, Zaheer Aslam","doi":"10.1109/ICETECC56662.2022.10069714","DOIUrl":"https://doi.org/10.1109/ICETECC56662.2022.10069714","url":null,"abstract":"Robotic technologies have opened up hundreds of new limitless perspectives for educational reform. We have conducted research to study the impact and outcomes of Robotic teaching in systematic studies, experimental studies, and surveys. The conclusions of this study reveal that educational robots have an impact on children, teachers, and students. We looked into how robots affect children’s behavior, learning outcomes, perceptions, and human interactions. The learning efficacy of educational Robot teachers is determined by a variety of factors, including learning outcome, student behavior and mood during class sessions, student reaction, and student involvement during workshops/class participation/quizzes/Q&A sessions. The majority of the research articles we chose were experimental studies, and they all met their objectives, which included teaching mathematical problems, unit conversion problems, teaching English/secondary language, developing analytical, and computational skills, behavior, and attitude development, critical thinking, and improving communication skills.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116968446","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 : 2022-12-07DOI: 10.1109/ICETECC56662.2022.10069314
Umar Alvi, Ijaz Ahmed, Alveena Alvi, Babar Ashfaq, S. Mukhtar, Paghunda Roheela Ali
Green energy projects can benefit greatly from using RETScreen as a preliminary estimate for financial analysis and technology assessment. Energy shortages and climate change are wreaking havoc in Pakistan at the present time. In this study, we examine green energy sources to meet the country’s energy needs while keeping environmental concerns in mind. The NASA climate information is used to conduct a comprehensive technical, economical, and environmental analysis of the intended green plant. In addition, the statistical indications demonstrate that the project is feasible in terms of cost-emission-savings. It is anticipated that this strategy will make it easier to start new renewable energy projects in developing countries that are having difficulty developing renewable energy projects. The study will also encourage the investor and corporate sector to join national grid from a business perspective. Furthermore, the scheme will also assist government institutions in reducing their reliance on fuel based plants, so bolstering the state economy and provide clean and cost effective energy.
{"title":"Technological, Financial and Ecological Analysis of Photovoltaic Power System using RETScreen® : A Case in Khuzdar, Pakistan","authors":"Umar Alvi, Ijaz Ahmed, Alveena Alvi, Babar Ashfaq, S. Mukhtar, Paghunda Roheela Ali","doi":"10.1109/ICETECC56662.2022.10069314","DOIUrl":"https://doi.org/10.1109/ICETECC56662.2022.10069314","url":null,"abstract":"Green energy projects can benefit greatly from using RETScreen as a preliminary estimate for financial analysis and technology assessment. Energy shortages and climate change are wreaking havoc in Pakistan at the present time. In this study, we examine green energy sources to meet the country’s energy needs while keeping environmental concerns in mind. The NASA climate information is used to conduct a comprehensive technical, economical, and environmental analysis of the intended green plant. In addition, the statistical indications demonstrate that the project is feasible in terms of cost-emission-savings. It is anticipated that this strategy will make it easier to start new renewable energy projects in developing countries that are having difficulty developing renewable energy projects. The study will also encourage the investor and corporate sector to join national grid from a business perspective. Furthermore, the scheme will also assist government institutions in reducing their reliance on fuel based plants, so bolstering the state economy and provide clean and cost effective energy.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116277011","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 : 2022-12-07DOI: 10.1109/ICETECC56662.2022.10069777
Rhowel M. Dellosa, Dennis C. Malunao, Jo Ann D. Doculan, R. R. Maaliw, Jeddie M. Zarate, R. S. Evangelista, Ma. Cecilia G. Adefuin
The most recent epidemic of coronavirus disease (COVID-19) was brought on by a coronavirus subsequently found. The general population was still required to wear surgical face masks, sometimes known as medical masks, to safeguard against the coronavirus disease and monkeypox disease as well brought on by COVID-19 and monkeypox virus. In the majority of regulated conditions, it might be challenging to see if someone is wearing their mask properly. The researchers imply a COVID-19 detection of correct and improper wearing of surgical face masks in regulated areas as a way to help with the ongoing development of identification of facemask wearing to limit the spread of the virus. Models generated using deep learning to identify persons’ proper wearing of masks were used. The model with the lowest performance in this study’s model evaluation, Model 3, has an mAP of 0.0777. With an mAP of 0.9668 (96.68%) and 3.31 training loss, the model produced the best results in model 42. The said model obtained the highest mAP, which was used for testing and inferencing as a result. This study showed promising results and might be used to reliably identify appropriate mask wear in public by using proper detection of facemask technology.
{"title":"Detecting Appropriate and Inappropriate COVID-19 Face Mask Wear in Controlled Environments Using Transfer Learning-Based Convolutional Neural Network","authors":"Rhowel M. Dellosa, Dennis C. Malunao, Jo Ann D. Doculan, R. R. Maaliw, Jeddie M. Zarate, R. S. Evangelista, Ma. Cecilia G. Adefuin","doi":"10.1109/ICETECC56662.2022.10069777","DOIUrl":"https://doi.org/10.1109/ICETECC56662.2022.10069777","url":null,"abstract":"The most recent epidemic of coronavirus disease (COVID-19) was brought on by a coronavirus subsequently found. The general population was still required to wear surgical face masks, sometimes known as medical masks, to safeguard against the coronavirus disease and monkeypox disease as well brought on by COVID-19 and monkeypox virus. In the majority of regulated conditions, it might be challenging to see if someone is wearing their mask properly. The researchers imply a COVID-19 detection of correct and improper wearing of surgical face masks in regulated areas as a way to help with the ongoing development of identification of facemask wearing to limit the spread of the virus. Models generated using deep learning to identify persons’ proper wearing of masks were used. The model with the lowest performance in this study’s model evaluation, Model 3, has an mAP of 0.0777. With an mAP of 0.9668 (96.68%) and 3.31 training loss, the model produced the best results in model 42. The said model obtained the highest mAP, which was used for testing and inferencing as a result. This study showed promising results and might be used to reliably identify appropriate mask wear in public by using proper detection of facemask technology.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120823453","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 : 2022-12-07DOI: 10.1109/ICETECC56662.2022.10068880
Julie Ann B. Susa, Rhowel M. Dellosa, Jo Ann D. Doculan, Roldan D. Jallorina, R. S. Evangelista, Godofredo S. Zapanta, Jennalyn N. Mindoro
Despite the advancements in many chemical medications used to treat diseases, medicinal plants have also been very effective in doing so. The global use of herbal products is increasing due to the growing contribution of science and technology to its ethical and scientific growth. In the Philippines, medicinal plants or herbs are popular in treating illness. Although the traditional identification method is effective and requires the expertise of skilled practitioners, it is time-consuming and prone to mistakes. Studies identifying the therapeutic use of naturally occurring plant chemicals have now been publicly disclosed that automatically detect the species of medicinal plants and leaves using machine vision and deep learning. This led to the first phase of this work, which used the readily available Philippine medicinal plants to identify the leaves automatically. With transfer learning using YOLOv3, this study seeks to identify Philippine medicinal plants in real-time. Only segmented leaves of Basella alba (alugbati), Mentha (mint), Moringa oleifera (malungay), Nerium oleander (adelfa), and Psidium guajava (bayabas) are used in the identification of medicinal leaves. The identification of the images utilized an inference approach in the real-time application based on the extracted features using YOLOv3. The result of the test performed illustrates an optimal outcome in the detection of different medicinal leaves. The optimal model performance results to mAP 98.63%. The test summary demonstrates a high detection accuracy and produces results at a fast speed. Thus, various model inferences using input images, live feed, and video inputs exemplify the model’s effectiveness in detecting the inputs medical leaves classes.
{"title":"Identification of Philippine Therapeutic Leave using Deep Learning","authors":"Julie Ann B. Susa, Rhowel M. Dellosa, Jo Ann D. Doculan, Roldan D. Jallorina, R. S. Evangelista, Godofredo S. Zapanta, Jennalyn N. Mindoro","doi":"10.1109/ICETECC56662.2022.10068880","DOIUrl":"https://doi.org/10.1109/ICETECC56662.2022.10068880","url":null,"abstract":"Despite the advancements in many chemical medications used to treat diseases, medicinal plants have also been very effective in doing so. The global use of herbal products is increasing due to the growing contribution of science and technology to its ethical and scientific growth. In the Philippines, medicinal plants or herbs are popular in treating illness. Although the traditional identification method is effective and requires the expertise of skilled practitioners, it is time-consuming and prone to mistakes. Studies identifying the therapeutic use of naturally occurring plant chemicals have now been publicly disclosed that automatically detect the species of medicinal plants and leaves using machine vision and deep learning. This led to the first phase of this work, which used the readily available Philippine medicinal plants to identify the leaves automatically. With transfer learning using YOLOv3, this study seeks to identify Philippine medicinal plants in real-time. Only segmented leaves of Basella alba (alugbati), Mentha (mint), Moringa oleifera (malungay), Nerium oleander (adelfa), and Psidium guajava (bayabas) are used in the identification of medicinal leaves. The identification of the images utilized an inference approach in the real-time application based on the extracted features using YOLOv3. The result of the test performed illustrates an optimal outcome in the detection of different medicinal leaves. The optimal model performance results to mAP 98.63%. The test summary demonstrates a high detection accuracy and produces results at a fast speed. Thus, various model inferences using input images, live feed, and video inputs exemplify the model’s effectiveness in detecting the inputs medical leaves classes.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122741759","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 : 2022-12-07DOI: 10.1109/ICETECC56662.2022.10069682
Umar Alvi, Ijaz Ahmed, Syed Rizwan Hasan, Babar Ashfaq, Muhammad Raza, Sana Mukhtar
Approximately 70–90 percent of today’s energy usage is derived from fossil fuels. Due to global warming and countless air pollutants, the atmosphere is polluted, compelling us to use new computer paradigms for efficient dispatching of smart energy grids. In order to solve the difficult nonlinear, non-convex, and constrained confined EEDs, a new whale optimization algorithm (WOA) is devised for the minimization of total cost and emission. The proposed method takes into account the social behaviour of humpback whales, with an emphasis on the nature of suggested meta-heuristic optimization algorithms. The proposed optimization paradigm generated data demonstrating AWSOA superiority to other advanced approaches. To ensure the efficacy of the proposed method, we compare it to other approaches and consider a number of technological constraints; the findings demonstrate that our approach is both cost-effective and accurate. In addition, the research assists electric energy firms in controlling emissions as required by emission regulatory agencies and saving the annual operational cost of thermal plants.
{"title":"Adaptive Swarm Intelligence-Based Optimization Approach for Smart Grids Power Dispatch","authors":"Umar Alvi, Ijaz Ahmed, Syed Rizwan Hasan, Babar Ashfaq, Muhammad Raza, Sana Mukhtar","doi":"10.1109/ICETECC56662.2022.10069682","DOIUrl":"https://doi.org/10.1109/ICETECC56662.2022.10069682","url":null,"abstract":"Approximately 70–90 percent of today’s energy usage is derived from fossil fuels. Due to global warming and countless air pollutants, the atmosphere is polluted, compelling us to use new computer paradigms for efficient dispatching of smart energy grids. In order to solve the difficult nonlinear, non-convex, and constrained confined EEDs, a new whale optimization algorithm (WOA) is devised for the minimization of total cost and emission. The proposed method takes into account the social behaviour of humpback whales, with an emphasis on the nature of suggested meta-heuristic optimization algorithms. The proposed optimization paradigm generated data demonstrating AWSOA superiority to other advanced approaches. To ensure the efficacy of the proposed method, we compare it to other approaches and consider a number of technological constraints; the findings demonstrate that our approach is both cost-effective and accurate. In addition, the research assists electric energy firms in controlling emissions as required by emission regulatory agencies and saving the annual operational cost of thermal plants.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130211010","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 : 2022-12-07DOI: 10.1109/ICETECC56662.2022.10068922
M. Azlan, B. Muneer, B. S. Chowdhry
The accumulation of fluid in the lungs is known as pulmonary oedema. The excess fluid that is trapped in the organs of body tissues cause swelling and this is known as Oedema. A model is designed in this research that detects the existence of fluid in the lungs. A wideband antenna beam is used for transmission and reception of the signals, which are then further processed using signal processing techniques to detect the fluid accumulation in the lungs. Detection of fluid can be achieved by detecting the change in the amplitude of transmitted and received signals, detecting phase change of the signals, or using a digital processing technique on the received spectrum or else. But these are either sensitive to the environment and positioning of the setup, or very sensitive to phase change. In this research, scattering profile is processed to detect fluid accumulation in the lungs.
{"title":"Lungs Fluid Accumulation Detection Using Microwave Imaging Technique","authors":"M. Azlan, B. Muneer, B. S. Chowdhry","doi":"10.1109/ICETECC56662.2022.10068922","DOIUrl":"https://doi.org/10.1109/ICETECC56662.2022.10068922","url":null,"abstract":"The accumulation of fluid in the lungs is known as pulmonary oedema. The excess fluid that is trapped in the organs of body tissues cause swelling and this is known as Oedema. A model is designed in this research that detects the existence of fluid in the lungs. A wideband antenna beam is used for transmission and reception of the signals, which are then further processed using signal processing techniques to detect the fluid accumulation in the lungs. Detection of fluid can be achieved by detecting the change in the amplitude of transmitted and received signals, detecting phase change of the signals, or using a digital processing technique on the received spectrum or else. But these are either sensitive to the environment and positioning of the setup, or very sensitive to phase change. In this research, scattering profile is processed to detect fluid accumulation in the lungs.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130590050","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 : 2022-12-07DOI: 10.1109/ICETECC56662.2022.10069200
Aaron Alcantara, G. Magwili
Philippines continues its plan for becoming industrialized country, despite that fact, it is still an agricultural country for most of its population lives in rural areas and rely on farming to support their needs and it still contributes to the gross domestic product of the country. Agricultural sector contributes 9.28% of the total GDP as of 2018. Though that sector contributes only close to 10%, its employment comprises to 24.3% of the total labor work force in the country. There are some pressing concerns in agricultural sector, obvious reduction of its essential elements -farmers and resources. There is a reduction of employment rate of farmers for the past years from 12, 030 in 2008 and dropped to 10,001 during 2018. Other concern are problems on resources-land, capital, machinery, seedlings, and the method used in farming. Farmlands degraded due to excessive use of inorganic compound for weeding and as fertilizer and other thing is the soil compaction due to use of heavy farm equipment. Significance of this study is it will offer land farming method more effective and provide a conservative approach to environment. The prototype will serve as an aid to farmers not to reduce them, in fact, with machine, some uncultivated land can be converted to plantation easier thus will result in an increase of farm land area. The prototype was fully custom built having its mechanical parts ease of replacements. Based on the results, the prototype can do the farming tasks even on the compacted soil that has not been used for years for planting though the researcher recommends some design enhancement and modification to attain more precision in farming.
{"title":"CROPBot: Customized Rigid Organic Plantation Robot","authors":"Aaron Alcantara, G. Magwili","doi":"10.1109/ICETECC56662.2022.10069200","DOIUrl":"https://doi.org/10.1109/ICETECC56662.2022.10069200","url":null,"abstract":"Philippines continues its plan for becoming industrialized country, despite that fact, it is still an agricultural country for most of its population lives in rural areas and rely on farming to support their needs and it still contributes to the gross domestic product of the country. Agricultural sector contributes 9.28% of the total GDP as of 2018. Though that sector contributes only close to 10%, its employment comprises to 24.3% of the total labor work force in the country. There are some pressing concerns in agricultural sector, obvious reduction of its essential elements -farmers and resources. There is a reduction of employment rate of farmers for the past years from 12, 030 in 2008 and dropped to 10,001 during 2018. Other concern are problems on resources-land, capital, machinery, seedlings, and the method used in farming. Farmlands degraded due to excessive use of inorganic compound for weeding and as fertilizer and other thing is the soil compaction due to use of heavy farm equipment. Significance of this study is it will offer land farming method more effective and provide a conservative approach to environment. The prototype will serve as an aid to farmers not to reduce them, in fact, with machine, some uncultivated land can be converted to plantation easier thus will result in an increase of farm land area. The prototype was fully custom built having its mechanical parts ease of replacements. Based on the results, the prototype can do the farming tasks even on the compacted soil that has not been used for years for planting though the researcher recommends some design enhancement and modification to attain more precision in farming.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114014515","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 : 2022-12-07DOI: 10.1109/ICETECC56662.2022.10069506
Zhengyi Yang, Leonard L. Alejandro, Charlene I. Vergara, R. R. Maaliw, A. Alon, R. S. Evangelista, Reden Paul Layug Rivera, Ronnel Cabral Delos Santos
Multi-Active Multi-Datacenter zookeeper is a very core basic component of Ele.me. It is equivalent to the database of basic components, including GZS (Global Zone Service, global state coordinator), DAL (Data Access Layer, database middleware software), Huskar (SOA framework that the online publishing system depends on), maxq (Ele.me message queue), Samaritan (load balancer with service discovery), abtest and other basic components. We are based on the apache official zookeeper for the secondary development to enable it to synchronize data in multiple IDCs. Such an important component must improve the stability and efficiency by the way of DevOps. For this reason, we have developed the EZK operation and maintenance management platform.
多活动多数据中心zookeeper是饿了么非常核心的基本组件。它相当于数据库的基本组件，包括GZS (Global Zone Service，全局状态协调器)、DAL (Data Access Layer，数据库中间件软件)、Huskar(在线发布系统所依赖的SOA框架)、maxq (Ele。(消息队列)、Samaritan(带有服务发现的负载平衡器)、abtest和其他基本组件。我们基于apache官方的zookeeper进行二次开发，使其能够同步多个idc中的数据。这样一个重要的组件必须通过DevOps的方式来提高稳定性和效率。为此，我们开发了EZK运维管理平台。
{"title":"Multi-Active Multi-Datacenter Distributed Database Architecture Design based-on Secondary Development Zookeeper","authors":"Zhengyi Yang, Leonard L. Alejandro, Charlene I. Vergara, R. R. Maaliw, A. Alon, R. S. Evangelista, Reden Paul Layug Rivera, Ronnel Cabral Delos Santos","doi":"10.1109/ICETECC56662.2022.10069506","DOIUrl":"https://doi.org/10.1109/ICETECC56662.2022.10069506","url":null,"abstract":"Multi-Active Multi-Datacenter zookeeper is a very core basic component of Ele.me. It is equivalent to the database of basic components, including GZS (Global Zone Service, global state coordinator), DAL (Data Access Layer, database middleware software), Huskar (SOA framework that the online publishing system depends on), maxq (Ele.me message queue), Samaritan (load balancer with service discovery), abtest and other basic components. We are based on the apache official zookeeper for the secondary development to enable it to synchronize data in multiple IDCs. Such an important component must improve the stability and efficiency by the way of DevOps. For this reason, we have developed the EZK operation and maintenance management platform.","PeriodicalId":364463,"journal":{"name":"2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114703801","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 : 2022-12-07DOI: 10.1109/ICETECC56662.2022.10069109
I. Alam, Azhar R Uddin, Shah Khusro
YouTube is a popular social media networking site that contains billions of videos. Many YouTube videos target children of different ages with offensive, inappropriate, violent, etc. Numerous one-size-fits-all countermeasures and research work have been deployed and suggested. However, these solutions are ineffective in accurately detecting inappropriate content for a diverse audience of different needs and requirements. In this research work, instead of one-size-fits-all, we consider a mutable age-based context, where different Age-Groups (AG) have different choices and needs. A novel and real-time approach have been proposed to prevent and allow the audience of varying AG towards the diverse content of YouTube, specifically in a smart TV-watching scenario. The proposed system analyses the running video through its metadata for teenagers, children, and adults. In parallel with data, the proposed model captures the viewers in real-time, detects their age, and checks the displayed video against the detected AG for appropriateness. The same system responds to parental consent and overrides its stop/play policies according to the direct input provided by parents/guardians with a diverse psychological setup, developed by their beliefs, religion, and cultural sensitivities. The proposed solution leverages Random Forest Classifier–a supervised text classification approach with 80% accuracy and Convolutional Neural Network for age determination using the Caffe model.
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