Pub Date : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465860
Nutnaree Apinantanapong, P. Nivesrangsan
Bearing is typical rotation parts in the machine. The failure of bearing under the machine operation can cause machine breakdown and also loss income. It is important for the industry to regularly check the condition of the machines for any malfunction because it can plan using efficient preventive maintenance. Nowadays, many factories use measuring devices to monitor and predict the machine’s conditions. When machine operates, vibration occurs and vibration pattern may be changed after machine operates for a while. In this study, the non-destructive testing by using vibration signal technique for bearing health monitoring was proposed in order to compare predicted results with various classification methods. In this experiment, bearings 6006z were simulated with six different conditions such as the normal condition of the bearing, the outer race fault, the inner race fault and the bearing fault with polishing grease of grit sizes of 100, 280 and 400, respectively. Vibration signals in time domain of each bearing type were detected by using accelerometer. Vibration signals were recorded into files. The vibration signals were interpreted using time domain and frequency domain techniques and compared precision of predicting bearing defect types using Vector Machine (SVM), K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN). It is found that Artificial Neural Networks gave the best result of predicting bearing defect types with accuracy of 98%
{"title":"Application of Artificial Neural Networks to Fault Detection of Rolling Ball Bearing","authors":"Nutnaree Apinantanapong, P. Nivesrangsan","doi":"10.1109/ICBIR52339.2021.9465860","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465860","url":null,"abstract":"Bearing is typical rotation parts in the machine. The failure of bearing under the machine operation can cause machine breakdown and also loss income. It is important for the industry to regularly check the condition of the machines for any malfunction because it can plan using efficient preventive maintenance. Nowadays, many factories use measuring devices to monitor and predict the machine’s conditions. When machine operates, vibration occurs and vibration pattern may be changed after machine operates for a while. In this study, the non-destructive testing by using vibration signal technique for bearing health monitoring was proposed in order to compare predicted results with various classification methods. In this experiment, bearings 6006z were simulated with six different conditions such as the normal condition of the bearing, the outer race fault, the inner race fault and the bearing fault with polishing grease of grit sizes of 100, 280 and 400, respectively. Vibration signals in time domain of each bearing type were detected by using accelerometer. Vibration signals were recorded into files. The vibration signals were interpreted using time domain and frequency domain techniques and compared precision of predicting bearing defect types using Vector Machine (SVM), K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN). It is found that Artificial Neural Networks gave the best result of predicting bearing defect types with accuracy of 98%","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134027859","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 : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465847
Phatcharika Naunthong
On-demand delivery is a transportation service that delivers goods based on customers’ requests of places and time. The literatures have reviewed and focused on different factors that affected the adoption of on-demand delivery; however, the gap was to identify the common characteristics of suitable organizations. The purposes of this research were to study the common factors for on-demand delivery adoption and to address the suitability of factors in different models of on-demand delivery. This paper collected 300 questionnaires from different firms in the central of Thailand. Data was analyzed based on descriptive analysis and significant tests. The important results showed that on-demand delivery was widely used among small organizations in food industry where sold finished products through online distribution channel and had semi-automation level in their operation. In addition, the significant factors for the adoption of on-demand delivery were automation level, type of industry and distribution channel while size of organizations and type of product showed no influence on the selection of on-demand delivery models including business-to-business, business-to-customer and customer-to-customer.
{"title":"Understanding Organizational Characteristics for the Adoption of On-Demand Delivery: A Case Study of Thai Industries","authors":"Phatcharika Naunthong","doi":"10.1109/ICBIR52339.2021.9465847","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465847","url":null,"abstract":"On-demand delivery is a transportation service that delivers goods based on customers’ requests of places and time. The literatures have reviewed and focused on different factors that affected the adoption of on-demand delivery; however, the gap was to identify the common characteristics of suitable organizations. The purposes of this research were to study the common factors for on-demand delivery adoption and to address the suitability of factors in different models of on-demand delivery. This paper collected 300 questionnaires from different firms in the central of Thailand. Data was analyzed based on descriptive analysis and significant tests. The important results showed that on-demand delivery was widely used among small organizations in food industry where sold finished products through online distribution channel and had semi-automation level in their operation. In addition, the significant factors for the adoption of on-demand delivery were automation level, type of industry and distribution channel while size of organizations and type of product showed no influence on the selection of on-demand delivery models including business-to-business, business-to-customer and customer-to-customer.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129146375","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 : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465851
Warangrat Nitiwanakul
Customer perceived value is crucial as a key factor to predict future consumption behavior, to understand consumer decision process and deeply insights, sustainable growth, enhance competitive advantage and fundamental tools for development of marketing strategies. The purpose of this study is to examine the relationship between customers' perceived value and its drivers which influence online delivery restaurant selection toward application during COVID 19 crisis. This study based on theoretical of Zeithaml's customer perceived value (1988) to develop research hypotheses and conceptual framework. The focus groups discussion results designated that food quality, product innovation and brand image were important as key drivers influence on overall customer perceived value toward online delivery restaurant selection. The perceptions of customer perceived value and online delivery restaurant selection for young adults and senior customers were different. For young adult customer, product innovation, brand image, social value, food quality, nonmonetary cost, hedonic value was found to be essential factors which influence on online delivery restaurant selection. For senior customers, in contrast, emphasized the food quality, brand image, service quality effected on customer perceived value. Additionally, monetary cost elements and utilitarian value and product innovation also important effect toward senior customers. There are difference among senior customers concern toward monetary cost but young adult customer concern nonmonetary cost in online restaurant selection.
{"title":"The Study of Factors Impact on Customer Perceived Value as A Driver for Online Delivery Restaurant Selection: A Case of Young Adults and Senior Consumers","authors":"Warangrat Nitiwanakul","doi":"10.1109/ICBIR52339.2021.9465851","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465851","url":null,"abstract":"Customer perceived value is crucial as a key factor to predict future consumption behavior, to understand consumer decision process and deeply insights, sustainable growth, enhance competitive advantage and fundamental tools for development of marketing strategies. The purpose of this study is to examine the relationship between customers' perceived value and its drivers which influence online delivery restaurant selection toward application during COVID 19 crisis. This study based on theoretical of Zeithaml's customer perceived value (1988) to develop research hypotheses and conceptual framework. The focus groups discussion results designated that food quality, product innovation and brand image were important as key drivers influence on overall customer perceived value toward online delivery restaurant selection. The perceptions of customer perceived value and online delivery restaurant selection for young adults and senior customers were different. For young adult customer, product innovation, brand image, social value, food quality, nonmonetary cost, hedonic value was found to be essential factors which influence on online delivery restaurant selection. For senior customers, in contrast, emphasized the food quality, brand image, service quality effected on customer perceived value. Additionally, monetary cost elements and utilitarian value and product innovation also important effect toward senior customers. There are difference among senior customers concern toward monetary cost but young adult customer concern nonmonetary cost in online restaurant selection.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133727810","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 : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465835
Mitsukuni Yasui, Hiroyuki Fujiki
JABEE is a certification standard that has substantial agreement with Washington Accord for engineering education. Engineer ethics is an important subject in order to achieve education such as recognition of the influences and effects of the technology on society and nature. Therefore, before and after the class of engineer ethics, the educational effect was measured by a self-inspection questionnaire to improve the class. Even if the lesson content was the same, there were differences in the questionnaire results, that was, the lesson effect, depending on the individuality of the teacher in charge and the curriculum background. In particular, the class start time was a major factor affected to the effect of the lesson. Furthermore, it was clarified that the higher the understanding of research ethics in the curriculum background, the higher the understanding of engineer ethics in general. Curriculum reforms and major efforts to change lesson content are required to improve lessons. However, a great lesson effect was obtained by incorporating a small virtual case study and asking a simple question with almost no change in the lesson content. In other words, it was clarified that the opportunity to think for a short time produced a great effect.
{"title":"Measuring and Using the Educational Effect of Engineer Ethics, and the Effect of Virtual Cases","authors":"Mitsukuni Yasui, Hiroyuki Fujiki","doi":"10.1109/ICBIR52339.2021.9465835","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465835","url":null,"abstract":"JABEE is a certification standard that has substantial agreement with Washington Accord for engineering education. Engineer ethics is an important subject in order to achieve education such as recognition of the influences and effects of the technology on society and nature. Therefore, before and after the class of engineer ethics, the educational effect was measured by a self-inspection questionnaire to improve the class. Even if the lesson content was the same, there were differences in the questionnaire results, that was, the lesson effect, depending on the individuality of the teacher in charge and the curriculum background. In particular, the class start time was a major factor affected to the effect of the lesson. Furthermore, it was clarified that the higher the understanding of research ethics in the curriculum background, the higher the understanding of engineer ethics in general. Curriculum reforms and major efforts to change lesson content are required to improve lessons. However, a great lesson effect was obtained by incorporating a small virtual case study and asking a simple question with almost no change in the lesson content. In other words, it was clarified that the opportunity to think for a short time produced a great effect.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121353868","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 : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465838
Supaporn Hongpisuttikul, Wut Sookcharoen
This research aimed to study the purchasing decision of clean food and to establish a marketing strategy for clean food products. Data were collected by random sampling method which presented a sample group of 400 people. This can be divided into 300 working-age people in the Central Business District of Bangkok and 100 social media users. The statistical tools used for data analysis were mean, percentage, frequency, T-Test, One-Way ANOVA Analysis and Pearson Correlation. The results revealed that the target group who decided to purchase clean food were 31 years old or older who have income more than 20,000 baht per month, regardless of gender. The design of clean food products should focus on ready-to-eat production processes. The quantities should be available in small (S), medium (M), and large (L) sizes. The results implied that the package should be designed to be easily opened and eaten. Consumers decided to purchase clean foods from well-known brands. Price should be set to suit the food quality. In addition, the products should be available at the storefront which consumers can easily grab and purchase. The results also pointed out that sales promotions should provide a discount when purchasing a specified quantity of products. Food delivery service to consumers’ home or office was a must. Moreover, the price level at which consumers were more likely to purchase was 40 baht. But the price level that will generate income was 70 baht.
{"title":"Marketing Strategy Framework for Clean Food Business","authors":"Supaporn Hongpisuttikul, Wut Sookcharoen","doi":"10.1109/ICBIR52339.2021.9465838","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465838","url":null,"abstract":"This research aimed to study the purchasing decision of clean food and to establish a marketing strategy for clean food products. Data were collected by random sampling method which presented a sample group of 400 people. This can be divided into 300 working-age people in the Central Business District of Bangkok and 100 social media users. The statistical tools used for data analysis were mean, percentage, frequency, T-Test, One-Way ANOVA Analysis and Pearson Correlation. The results revealed that the target group who decided to purchase clean food were 31 years old or older who have income more than 20,000 baht per month, regardless of gender. The design of clean food products should focus on ready-to-eat production processes. The quantities should be available in small (S), medium (M), and large (L) sizes. The results implied that the package should be designed to be easily opened and eaten. Consumers decided to purchase clean foods from well-known brands. Price should be set to suit the food quality. In addition, the products should be available at the storefront which consumers can easily grab and purchase. The results also pointed out that sales promotions should provide a discount when purchasing a specified quantity of products. Food delivery service to consumers’ home or office was a must. Moreover, the price level at which consumers were more likely to purchase was 40 baht. But the price level that will generate income was 70 baht.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130565187","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 : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465832
Vivat Thongchotchat, Kazuhiko Sato, H. Suto
Learning style is the preference way of learning which can be applied with recommender system to develop the computer-support learning system which can make the tailored learning path for each particular learner. This study did the systematic literature review to gain insight of gathered recently published articles involving recommender system utilizing recommender system from trustable sources; IEEE Xplore and ScienceDirect; using designed search keywords and criteria then extracted information for answering what is the most used learning style theory and recommender algorithm in recently developed recommender systems utilizing learning style. The review study found that Felder & Silverman’s theory has been the most used theory with 72.5% of all reviewed articles and suitable application is the most used recommender algorithm with 42.5% of all.
{"title":"Recommender System Utilizing Learning Style: Systematic Literature Review","authors":"Vivat Thongchotchat, Kazuhiko Sato, H. Suto","doi":"10.1109/ICBIR52339.2021.9465832","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465832","url":null,"abstract":"Learning style is the preference way of learning which can be applied with recommender system to develop the computer-support learning system which can make the tailored learning path for each particular learner. This study did the systematic literature review to gain insight of gathered recently published articles involving recommender system utilizing recommender system from trustable sources; IEEE Xplore and ScienceDirect; using designed search keywords and criteria then extracted information for answering what is the most used learning style theory and recommender algorithm in recently developed recommender systems utilizing learning style. The review study found that Felder & Silverman’s theory has been the most used theory with 72.5% of all reviewed articles and suitable application is the most used recommender algorithm with 42.5% of all.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116439885","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 : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465875
Benjamas Chimmalee, Anuchit Anupan
Computer-based simulation of disease distribution is an important tool used to investigate the spread of infectious diseases. One of the most important theoretical developments has been the integration of mathematical modeling and the implementation of cloud-based technology. We propose the use of cloud technology to simulate a network model. The data generated as output from C++ software, based on the assumption of a mathematical framework of a SEIQR network model, are used as datasets for simulation. The simulation results of the mathematical model were studied in this paper. By applying mathematical software to cloud technology, this study investigates using available cloud services as a SaaS model. The data were analyzed using content analysis. The approach for simulation using mathematical software and cloud-based mathematical software were analyzed as follows: 1. the display of the graph; 2. the runtime performance. The results of the simulation are also discussed.
{"title":"Simulation of Network Model on Cloud Technology based on Mathematical Framework","authors":"Benjamas Chimmalee, Anuchit Anupan","doi":"10.1109/ICBIR52339.2021.9465875","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465875","url":null,"abstract":"Computer-based simulation of disease distribution is an important tool used to investigate the spread of infectious diseases. One of the most important theoretical developments has been the integration of mathematical modeling and the implementation of cloud-based technology. We propose the use of cloud technology to simulate a network model. The data generated as output from C++ software, based on the assumption of a mathematical framework of a SEIQR network model, are used as datasets for simulation. The simulation results of the mathematical model were studied in this paper. By applying mathematical software to cloud technology, this study investigates using available cloud services as a SaaS model. The data were analyzed using content analysis. The approach for simulation using mathematical software and cloud-based mathematical software were analyzed as follows: 1. the display of the graph; 2. the runtime performance. The results of the simulation are also discussed.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130669979","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 : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465865
Palida Sapsiriroht, K. Kittipeerachon
Mooney viscosity is an important parameter in rubber compound industry because it is one of the processing windows and key properties of a rubber compound. As dynamic behaviors of rubber compounds are nonlinear and rubber product manufacturing process affects dynamic behaviors, an exact model for predicting Mooney viscosity has not been found. This paper presents the prediction models based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for rubber compounds with different architectures and the effects of changes of certain parameters in each model on prediction performance. The database is collected from the historical data of manufacturing and then cleansed by removing errors in process and out-of-spec values. Both premise and consequent parameters of rules are created using the parameter initialization algorithm. The effects of different numbers of inputs and epochs, different input variables, and different interpretation methods are investigated. The simulation results show that the minimum value of RMSE for data testing is obtained by using the parameters initialization algorithm with 100 epochs, 3 inputs and OR interpretation method. Moreover, the lower number of epochs indicates the faster processing of the model. It is expected that the Mooney viscosity can be predicted and shown immediately at the end of mixing process.
{"title":"Comparative Study of Mooney Viscosity Prediction Models for Rubber Compounds based on ANFIS with Different Architectures","authors":"Palida Sapsiriroht, K. Kittipeerachon","doi":"10.1109/ICBIR52339.2021.9465865","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465865","url":null,"abstract":"Mooney viscosity is an important parameter in rubber compound industry because it is one of the processing windows and key properties of a rubber compound. As dynamic behaviors of rubber compounds are nonlinear and rubber product manufacturing process affects dynamic behaviors, an exact model for predicting Mooney viscosity has not been found. This paper presents the prediction models based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for rubber compounds with different architectures and the effects of changes of certain parameters in each model on prediction performance. The database is collected from the historical data of manufacturing and then cleansed by removing errors in process and out-of-spec values. Both premise and consequent parameters of rules are created using the parameter initialization algorithm. The effects of different numbers of inputs and epochs, different input variables, and different interpretation methods are investigated. The simulation results show that the minimum value of RMSE for data testing is obtained by using the parameters initialization algorithm with 100 epochs, 3 inputs and OR interpretation method. Moreover, the lower number of epochs indicates the faster processing of the model. It is expected that the Mooney viscosity can be predicted and shown immediately at the end of mixing process.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114081631","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 : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465878
Kasidit Rengthian, Sakditat Kaewprajam, Pannathadh Chomchark, Araya Hongchindaket
This research aims to study the marketing mix factors affecting the decision to purchase Whey protein supplement products in Bangkok. This is the quantitative research employing questionnaire as a tool for data collection through content validity from experts and to examine the reliability of the instruments by using the experimental group, consisting of 30 samples, with validity values greater than 0.67 for all questions. The result of the Cronbach’s alpha (α) of each factor ranged from 0.70-0.98 in all components. Then the data was collected from 520 samples. After that it was analyzed and then summarized according to the research framework in order to understand the decision to purchase Whey protein supplement products in Bangkok by SPSS.The results of the study revealed that (1) Demographic factors affected the decision to purchase Whey protein supplements products in Bangkok (2) Marketing mix affects the decision to buy Whey protein supplements products in Bangkok.
{"title":"Marketing Mix Factors Affecting the Decision to Purchase Whey Protein Supplements Products in Bangkok","authors":"Kasidit Rengthian, Sakditat Kaewprajam, Pannathadh Chomchark, Araya Hongchindaket","doi":"10.1109/ICBIR52339.2021.9465878","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465878","url":null,"abstract":"This research aims to study the marketing mix factors affecting the decision to purchase Whey protein supplement products in Bangkok. This is the quantitative research employing questionnaire as a tool for data collection through content validity from experts and to examine the reliability of the instruments by using the experimental group, consisting of 30 samples, with validity values greater than 0.67 for all questions. The result of the Cronbach’s alpha (α) of each factor ranged from 0.70-0.98 in all components. Then the data was collected from 520 samples. After that it was analyzed and then summarized according to the research framework in order to understand the decision to purchase Whey protein supplement products in Bangkok by SPSS.The results of the study revealed that (1) Demographic factors affected the decision to purchase Whey protein supplements products in Bangkok (2) Marketing mix affects the decision to buy Whey protein supplements products in Bangkok.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116437639","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 : 2021-05-20DOI: 10.1109/ICBIR52339.2021.9465856
Shohei Chiba, Hisayuki Sasaoka
Reinforcement learning, deep learning, and deep reinforcement learning can effectively acquire action rules for the autonomous motion of objects. However, some researchers have reported that the machine learning process requires a large amount of learning time. Besides, the process needs to consider the similarity of the environment between the training target and the test target. There is no such thing as driving only on a course learned in advance in actual autonomous driving. In this study, we have used a transfer learning algorithm for autonomous drivings for model cars. The training target for acquiring the learning model and the actual driving courses are changed. In this study, we report on the effectiveness of transfer learning using a model car as the basis for a learning model acquired by reinforcement learning.
{"title":"Basic Study for Transfer Learning for Autonomous Driving in Car Race of Model Car","authors":"Shohei Chiba, Hisayuki Sasaoka","doi":"10.1109/ICBIR52339.2021.9465856","DOIUrl":"https://doi.org/10.1109/ICBIR52339.2021.9465856","url":null,"abstract":"Reinforcement learning, deep learning, and deep reinforcement learning can effectively acquire action rules for the autonomous motion of objects. However, some researchers have reported that the machine learning process requires a large amount of learning time. Besides, the process needs to consider the similarity of the environment between the training target and the test target. There is no such thing as driving only on a course learned in advance in actual autonomous driving. In this study, we have used a transfer learning algorithm for autonomous drivings for model cars. The training target for acquiring the learning model and the actual driving courses are changed. In this study, we report on the effectiveness of transfer learning using a model car as the basis for a learning model acquired by reinforcement learning.","PeriodicalId":447560,"journal":{"name":"2021 6th International Conference on Business and Industrial Research (ICBIR)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114606164","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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