Pub Date : 2022-03-23DOI: 10.1109/DASA54658.2022.9765119
Seda Nur Yaşar, Ebru Karaköse
An unmanned aerial vehicle (UAV) is an autonomous aircraft without a pilot and passenger. UAVs are also called "drone". However, while drone is used to refer to any type of UAV in the common language, it mainly refers to UAV mostly used in military context. UAVs and today's competent usage areas are mentioned in this study. A detailed examination of quadcopters, which is a four-engine unmanned aerial vehicle, is given and it is emphasized why simulation is necessary for UAVs. The implementation of the study is carried out in Matlab-Simulink and the quadcopter is simulated in the Matlab environment. Two different simulation processes are considered in the study and with the Simulink model used for the first simulation, the trajectory tracking problem is tried to be overcome by adding a direct Eulerrate script instead of the PD controller output. A second simulation is needed to fly the UAV in a circular trajectory. When the results obtained for both simulations are examined, it has been determined that the second simulation provides a more periodic trajectory tracking than the first simulation.
{"title":"Trajectory Control of Quadcopter in Matlab Simulation Environment","authors":"Seda Nur Yaşar, Ebru Karaköse","doi":"10.1109/DASA54658.2022.9765119","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765119","url":null,"abstract":"An unmanned aerial vehicle (UAV) is an autonomous aircraft without a pilot and passenger. UAVs are also called \"drone\". However, while drone is used to refer to any type of UAV in the common language, it mainly refers to UAV mostly used in military context. UAVs and today's competent usage areas are mentioned in this study. A detailed examination of quadcopters, which is a four-engine unmanned aerial vehicle, is given and it is emphasized why simulation is necessary for UAVs. The implementation of the study is carried out in Matlab-Simulink and the quadcopter is simulated in the Matlab environment. Two different simulation processes are considered in the study and with the Simulink model used for the first simulation, the trajectory tracking problem is tried to be overcome by adding a direct Eulerrate script instead of the PD controller output. A second simulation is needed to fly the UAV in a circular trajectory. When the results obtained for both simulations are examined, it has been determined that the second simulation provides a more periodic trajectory tracking than the first simulation.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116930082","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 : 2022-03-23DOI: 10.1109/DASA54658.2022.9765008
Ankit Tomar, Santosh Kumar, Bhasker Pant
Crowd behavior investigation in images/videos is an important task applied in areas such as people counting, density estimation, emotion recognition, motion detection, and flow analysis, etc. The researchers devoted an excellent quality of work to deal with public issues such as crowd control, traffic monitoring, urban planning, vehicle counting in real-time; however, humanity did not get much success in handling these issues due to the limited cost of energy and time. For evaluation metrics, we need a year-wise analysis of used datasets, publications methodologies, and their performance, which is expected to yield good predictions and conclusions. Therefore, in this work, we have systematically and comprehensively revisited five year studies that conducted crowd analysis in video using deep learning techniques to make more effective research development and progress. We have got some new future directions from some of the prestigious survey works, which is a novel aspect of this study, that would provide potential and reliable solutions for investigating crowd behaviour in videos.
{"title":"Crowd Analysis in Video Surveillance: A Review","authors":"Ankit Tomar, Santosh Kumar, Bhasker Pant","doi":"10.1109/DASA54658.2022.9765008","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765008","url":null,"abstract":"Crowd behavior investigation in images/videos is an important task applied in areas such as people counting, density estimation, emotion recognition, motion detection, and flow analysis, etc. The researchers devoted an excellent quality of work to deal with public issues such as crowd control, traffic monitoring, urban planning, vehicle counting in real-time; however, humanity did not get much success in handling these issues due to the limited cost of energy and time. For evaluation metrics, we need a year-wise analysis of used datasets, publications methodologies, and their performance, which is expected to yield good predictions and conclusions. Therefore, in this work, we have systematically and comprehensively revisited five year studies that conducted crowd analysis in video using deep learning techniques to make more effective research development and progress. We have got some new future directions from some of the prestigious survey works, which is a novel aspect of this study, that would provide potential and reliable solutions for investigating crowd behaviour in videos.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116057532","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 : 2022-03-23DOI: 10.1109/DASA54658.2022.9765025
A. Ishraq, Aklima Akter Lima, Md. Mohsin Kabir, Md. Saifur Rahman, M. F. Mridha
Damage assessment is one reasonable method for adopting good procedures for obtaining speedy and dependable attention during natural calamities such as a hurricane. Lately, calamity researchers have often used satellite imagery to predict the number of damaged properties. It can detect the damaged structures in time by integrating satellite imagery and Convolutional Neural Network (CNN) transfer learning. Consequently, choosing the variables of transfer learning success in this scenario is demanded. To identify damaged structures post-hurricane, we introduce a technique based on VGG16 that utilizes satellite imagery features of the hurricane-affected region. The global average pooling, which is a layer substitutes the fully connected layer to minimize parameters and enhance convergence speed. The experimental outcome indicates which proposed model's overall accuracy for post-hurricane image classification can reach 0.98 per cent. Our proposed method approximates the classical CNN, VGG16, VGG19, AlexNet and surpasses their performance.
{"title":"Assessment of Building Damage on Post-Hurricane Satellite Imagery using improved CNN","authors":"A. Ishraq, Aklima Akter Lima, Md. Mohsin Kabir, Md. Saifur Rahman, M. F. Mridha","doi":"10.1109/DASA54658.2022.9765025","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765025","url":null,"abstract":"Damage assessment is one reasonable method for adopting good procedures for obtaining speedy and dependable attention during natural calamities such as a hurricane. Lately, calamity researchers have often used satellite imagery to predict the number of damaged properties. It can detect the damaged structures in time by integrating satellite imagery and Convolutional Neural Network (CNN) transfer learning. Consequently, choosing the variables of transfer learning success in this scenario is demanded. To identify damaged structures post-hurricane, we introduce a technique based on VGG16 that utilizes satellite imagery features of the hurricane-affected region. The global average pooling, which is a layer substitutes the fully connected layer to minimize parameters and enhance convergence speed. The experimental outcome indicates which proposed model's overall accuracy for post-hurricane image classification can reach 0.98 per cent. Our proposed method approximates the classical CNN, VGG16, VGG19, AlexNet and surpasses their performance.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115656988","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 : 2022-03-23DOI: 10.1109/DASA54658.2022.9765061
K. Gurrala, Maram Helmy, M. Ndiaye
Nations are under constant pressure to reduce the increasing amounts of food packaging waste generated across the world, as the demand and supply patterns for food across the world are expected to tremendously rise with the increasing population levels across the globe. However, the research focus in the domain of food packaging mainly concentrates on the usage of advanced technologies or implementation of atmospheric controls within the packaging, to protect food and prolong the shelf life of the foods to facilitate environmental impact reductions through food waste reductions, with little focus on the development of alternatives such as edible films, that can further facilitate significant reductions within the environmental pollution levels generated from food packaging wastes. Additionally, research concentrating on edible films resulted in the formulation of several biocomposites developed from alternative biopolymers i.e., polysaccharides (glucose derivatives), proteins (animal or vegetable derivatives), etc., exhibiting significant differences corresponding to physical, mechanical, optical, thermal, chemical, and barrier properties, necessitating the application of Multi-Criteria Decision-Making Methods (MCDM) towards the selection of an optimal biocomposite for edible film preparation. Therefore, this study aims at employing a Hybrid MCDM method formulated from CRITIC (Criteria Importance through Inter- Criteria Correlation) and TOPSIS (Technique by Order Preference by Similarity to Ideal Solution) methods, to facilitate the selection of an optimal green biocomposite sample from a set of film samples exhibiting different properties.
{"title":"Edible Packaging Selection Employing Hybrid CRITIC and TOPSIS Method","authors":"K. Gurrala, Maram Helmy, M. Ndiaye","doi":"10.1109/DASA54658.2022.9765061","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765061","url":null,"abstract":"Nations are under constant pressure to reduce the increasing amounts of food packaging waste generated across the world, as the demand and supply patterns for food across the world are expected to tremendously rise with the increasing population levels across the globe. However, the research focus in the domain of food packaging mainly concentrates on the usage of advanced technologies or implementation of atmospheric controls within the packaging, to protect food and prolong the shelf life of the foods to facilitate environmental impact reductions through food waste reductions, with little focus on the development of alternatives such as edible films, that can further facilitate significant reductions within the environmental pollution levels generated from food packaging wastes. Additionally, research concentrating on edible films resulted in the formulation of several biocomposites developed from alternative biopolymers i.e., polysaccharides (glucose derivatives), proteins (animal or vegetable derivatives), etc., exhibiting significant differences corresponding to physical, mechanical, optical, thermal, chemical, and barrier properties, necessitating the application of Multi-Criteria Decision-Making Methods (MCDM) towards the selection of an optimal biocomposite for edible film preparation. Therefore, this study aims at employing a Hybrid MCDM method formulated from CRITIC (Criteria Importance through Inter- Criteria Correlation) and TOPSIS (Technique by Order Preference by Similarity to Ideal Solution) methods, to facilitate the selection of an optimal green biocomposite sample from a set of film samples exhibiting different properties.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123677147","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 : 2022-03-23DOI: 10.1109/DASA54658.2022.9765193
Orhan Nooruldeen, S. Alturki, M. R. Baker, Ahmed Ghareeb
Time series modeling and forecasting are critical in various practical applications, including the energy sector, and have been actively investigated in this field for several years. Many relevant methods for enhancing the accuracy and efficacy of time series modeling and forecasting have been proposed in the literature. This study aims to provide a comparative analysis of various common time series modeling and forecasting techniques for the daily electricity demand of the city of Kirkuk. The ability of the presented models to be extrapolated as well as increasing the confidence in models are also examined. Two years of out-of-sample data are used to validate the models. The Long Short-term Memory (LSTM) outperformed the other series types, demonstrating good agreement with the actual data. This study has implications for boosting renewable energy deployment, planning demand-side management, and measuring energy and cost-saving actions.
{"title":"Time Series Forecasting for Decision Making on City-Wide Energy Demand: A Comparative Study","authors":"Orhan Nooruldeen, S. Alturki, M. R. Baker, Ahmed Ghareeb","doi":"10.1109/DASA54658.2022.9765193","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765193","url":null,"abstract":"Time series modeling and forecasting are critical in various practical applications, including the energy sector, and have been actively investigated in this field for several years. Many relevant methods for enhancing the accuracy and efficacy of time series modeling and forecasting have been proposed in the literature. This study aims to provide a comparative analysis of various common time series modeling and forecasting techniques for the daily electricity demand of the city of Kirkuk. The ability of the presented models to be extrapolated as well as increasing the confidence in models are also examined. Two years of out-of-sample data are used to validate the models. The Long Short-term Memory (LSTM) outperformed the other series types, demonstrating good agreement with the actual data. This study has implications for boosting renewable energy deployment, planning demand-side management, and measuring energy and cost-saving actions.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124331764","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 : 2022-03-23DOI: 10.1109/DASA54658.2022.9765309
Indah Wigati, Mia Fithriyah
For the world of education, including students, instructors, and policymakers for adoption of digital literacy has now become a key concern. Teachers must be aware of the importance of mastering digital literacy in the learning experience. After the Covid-19 epidemic, this research intends to examine educator knowledge of the application of digital literacy in the learning process. The study employs a quantitative descriptive technique to carefully review the types of teacher digital literacy awareness, supportive factors in the usage of digital literacy, and the consequences of tutor computer literacy recognition following the Covid 19 epidemic. The research process was conducted in the Islamic Public Senior High School (MAN) in Palembang, Sumatra. The consistent findings indicated that positive' competence of digital literacy was significant in terms of their capacity to use technology about 100%. The most influential supporting factor correctly is the motivation of friends (97.90%). The implication of using digital literacy for teachers is the execution of virtual meeting learning (94%). The logical conclusion of this study is that teachers develop awareness in utilizing technology, and it is more effortless to convey material after the Covid-19 pandemic. Mastery of digital literacy for teachers needs to be carefully reviewed to the stage of performance and application to students.
{"title":"Post Covid-19 Strategy Through Supporting Teacher Digital Literacy as the Sustainable Decision to Enhance Education System: Indonesia Case Study","authors":"Indah Wigati, Mia Fithriyah","doi":"10.1109/DASA54658.2022.9765309","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765309","url":null,"abstract":"For the world of education, including students, instructors, and policymakers for adoption of digital literacy has now become a key concern. Teachers must be aware of the importance of mastering digital literacy in the learning experience. After the Covid-19 epidemic, this research intends to examine educator knowledge of the application of digital literacy in the learning process. The study employs a quantitative descriptive technique to carefully review the types of teacher digital literacy awareness, supportive factors in the usage of digital literacy, and the consequences of tutor computer literacy recognition following the Covid 19 epidemic. The research process was conducted in the Islamic Public Senior High School (MAN) in Palembang, Sumatra. The consistent findings indicated that positive' competence of digital literacy was significant in terms of their capacity to use technology about 100%. The most influential supporting factor correctly is the motivation of friends (97.90%). The implication of using digital literacy for teachers is the execution of virtual meeting learning (94%). The logical conclusion of this study is that teachers develop awareness in utilizing technology, and it is more effortless to convey material after the Covid-19 pandemic. Mastery of digital literacy for teachers needs to be carefully reviewed to the stage of performance and application to students.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123913989","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 : 2022-03-23DOI: 10.1109/DASA54658.2022.9765078
Sarutanan Sopanik
This research is considered to be a case - study research which explores the competence levels of three selected community-based tourism (CBT) communities in Chiang Rai, Thailand, for high value meetings incentives conferences (or conventions) and exhibitions (MICE) travelers who are considered to be a potentially untapped tourism segment for local CBT residents in Thailand. The framework of this research is adapted from governmental tourism organizations in Thailand and international organizations with the intention to promote CBT communities. The evaluation criteria focus on CBT community management, cultural presentation skills and natural resources. The unique ability to use local creativities to impress MICE travelers beyond their expectations is the key success which will indicate higher level of competence.
{"title":"The Competence Development of Community Based Tourism Communities in Chiang Rai for MICE Travelers","authors":"Sarutanan Sopanik","doi":"10.1109/DASA54658.2022.9765078","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765078","url":null,"abstract":"This research is considered to be a case - study research which explores the competence levels of three selected community-based tourism (CBT) communities in Chiang Rai, Thailand, for high value meetings incentives conferences (or conventions) and exhibitions (MICE) travelers who are considered to be a potentially untapped tourism segment for local CBT residents in Thailand. The framework of this research is adapted from governmental tourism organizations in Thailand and international organizations with the intention to promote CBT communities. The evaluation criteria focus on CBT community management, cultural presentation skills and natural resources. The unique ability to use local creativities to impress MICE travelers beyond their expectations is the key success which will indicate higher level of competence.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124080744","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 : 2022-03-23DOI: 10.1109/DASA54658.2022.9765114
S. Rani, Sandeep Kumar, D. Ghai, K. Prasad
Automatic detection of brain tumors from CT and MRI images is always an effortful task because of the complexity and heterogeneous images. Many neural networks architecture (NN) have recently been developed for segmentation and classification tasks and have proved quite successful. Studies that have taken into account the sizes of items have been rare; as a result, the majority of them show poor detection performance for tiny objects. This has the potential to have a significant influence on illness identification. Recently, the 3D neural network became popular because it can work with a large labeled dataset. We proposed a 3D Alex-Net-based architecture that can classify the different types of a brain tumors at an early stage. First, the image contour is identified and given to the classifier for class-wise identification. We tested our proposed approach on RSNA- MICCAI brain tumors and found that the proposed method delivers the highest accuracy, and the results provide a clear advantage for the classification of a brain tumor in medical images.
由于图像的复杂性和异质性，从CT和MRI图像中自动检测脑肿瘤一直是一项艰巨的任务。近年来，许多神经网络架构(NN)被开发用于分割和分类任务，并被证明是相当成功的。考虑到物品大小的研究很少;因此，它们中的大多数对微小物体的检测性能较差。这有可能对疾病鉴定产生重大影响。最近，3D神经网络因其可以处理大型标记数据集而受到欢迎。我们提出了一个基于3D alex - net的架构，可以在早期阶段对不同类型的脑肿瘤进行分类。首先，识别图像轮廓并将其交给分类器进行分类识别。我们在RSNA- MICCAI脑肿瘤上测试了我们提出的方法，发现我们提出的方法提供了最高的准确性，结果为医学图像中脑肿瘤的分类提供了明显的优势。
{"title":"Automatic Detection of Brain Tumor from CT and MRI Images using Wireframe model and 3D Alex-Net","authors":"S. Rani, Sandeep Kumar, D. Ghai, K. Prasad","doi":"10.1109/DASA54658.2022.9765114","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765114","url":null,"abstract":"Automatic detection of brain tumors from CT and MRI images is always an effortful task because of the complexity and heterogeneous images. Many neural networks architecture (NN) have recently been developed for segmentation and classification tasks and have proved quite successful. Studies that have taken into account the sizes of items have been rare; as a result, the majority of them show poor detection performance for tiny objects. This has the potential to have a significant influence on illness identification. Recently, the 3D neural network became popular because it can work with a large labeled dataset. We proposed a 3D Alex-Net-based architecture that can classify the different types of a brain tumors at an early stage. First, the image contour is identified and given to the classifier for class-wise identification. We tested our proposed approach on RSNA- MICCAI brain tumors and found that the proposed method delivers the highest accuracy, and the results provide a clear advantage for the classification of a brain tumor in medical images.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128499451","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}
The objective research was to study the transformation of the coffee consumption behavior of coffee drinkers and factors affecting the coffee consumption behavior before and during the COVID-19 pandemic. Because coffee is a famous beverage among university student groups. Therefore, we want to know the coffee consumption behavior and aspects of coffee drinkers such as the time most people need to consume coffee, the price, and the amount of coffee consumed each day. Both before and during the pandemic. To benefit those who are interested in studying coffee and as a guide for decision making in the business development of coffee shop operators. The sample used in this study is 407 students at the University of Thailand who consume coffee. The questionnaire was used to collect data for surveys of coffee consumption behavior. The study results revealed that consumer behavior has changed in coffee drinking patterns, health effects, and budgets for coffee purchases have decreased. Including the amount of coffee consumed on average per day by consumers, slightly increased from before the pandemic.
{"title":"COVID-19 pandemic affected on coffee beverage decision and consumers’ behavior","authors":"Akedanai Thubsang, Chanu Thiwongwiang, Chuleeporn Wisetdee, Jutamanee Chompoonuch, Maesaya Anson, Sairin Phalamat, T. Arreeras","doi":"10.1109/DASA54658.2022.9765074","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765074","url":null,"abstract":"The objective research was to study the transformation of the coffee consumption behavior of coffee drinkers and factors affecting the coffee consumption behavior before and during the COVID-19 pandemic. Because coffee is a famous beverage among university student groups. Therefore, we want to know the coffee consumption behavior and aspects of coffee drinkers such as the time most people need to consume coffee, the price, and the amount of coffee consumed each day. Both before and during the pandemic. To benefit those who are interested in studying coffee and as a guide for decision making in the business development of coffee shop operators. The sample used in this study is 407 students at the University of Thailand who consume coffee. The questionnaire was used to collect data for surveys of coffee consumption behavior. The study results revealed that consumer behavior has changed in coffee drinking patterns, health effects, and budgets for coffee purchases have decreased. Including the amount of coffee consumed on average per day by consumers, slightly increased from before the pandemic.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130559465","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 : 2022-03-23DOI: 10.1109/DASA54658.2022.9765251
Ibna Suhail, Samaya Pillai
With the advent of digital transformation, technology has brought about a gigantic and momentous change in almost every industry. Internet of Things (IoT), being one of the most revolutionizing technology, has been impacting all fields of life immensely, but its impact on the healthcare industry has been particularly significant due to its cutting edge transition. The objective of this paper is to understand the role of IoT in this sector, its various use cases, and on how the devices assists medical professionals to function more efficiently and patients for an enhanced treatment. For instance, the Intelligent Asthma Monitoring wearable technology can forecast the oncoming asthma attack way before the person wearing it can comprehend. Apple watches, though not designed with this agenda in the first place, have now been a significant part in gathering information about people with the new blood oxygen measuring functionality, echocardiogram (ECG) tracking, and also detecting irregular heartbeat which is an indicator of Atrial Fibrillation (AFib). Furthermore, the paper will also address the probable challenges of the technology in the sector and understand the current and future adaptability of internet of medical thing devices.
{"title":"IoT enabled applications for Healthcare decisions","authors":"Ibna Suhail, Samaya Pillai","doi":"10.1109/DASA54658.2022.9765251","DOIUrl":"https://doi.org/10.1109/DASA54658.2022.9765251","url":null,"abstract":"With the advent of digital transformation, technology has brought about a gigantic and momentous change in almost every industry. Internet of Things (IoT), being one of the most revolutionizing technology, has been impacting all fields of life immensely, but its impact on the healthcare industry has been particularly significant due to its cutting edge transition. The objective of this paper is to understand the role of IoT in this sector, its various use cases, and on how the devices assists medical professionals to function more efficiently and patients for an enhanced treatment. For instance, the Intelligent Asthma Monitoring wearable technology can forecast the oncoming asthma attack way before the person wearing it can comprehend. Apple watches, though not designed with this agenda in the first place, have now been a significant part in gathering information about people with the new blood oxygen measuring functionality, echocardiogram (ECG) tracking, and also detecting irregular heartbeat which is an indicator of Atrial Fibrillation (AFib). Furthermore, the paper will also address the probable challenges of the technology in the sector and understand the current and future adaptability of internet of medical thing devices.","PeriodicalId":231066,"journal":{"name":"2022 International Conference on Decision Aid Sciences and Applications (DASA)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130714275","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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