The objective of this research is to examine the factors affecting successful accounting information of Thai-listed companies. The factors affecting successful accounting information are two variables including accoun...The objective of this research is to examine the factors affecting successful accounting information of Thai-listed companies. The factors affecting successful accounting information are two variables including accounting professional and accounting information system （AIS） competency. Population and sample of this research is the companies listed in the Stock Exchange of Thailand （SET）. A questionnaire mail was used for collecting the data from chief accountant officer of the companies listed in the SET. The results indicate that accounting professional has a positive significant effect on successful accounting information in all dimensions including effective planning, efficient controlling, and promoting decision and communication. Moreover, AIS competency has a positive significant effect on successful accounting information only in dimension of promoting decision and communication. Overall, the results indicate that internal resource and capabilities including accounting professional and AIS competency are the primary factors that influence successful accounting information of Thai-listed companies. Theoretical and managerial contributions are explicitly provided. Conclusions, suggestions and directions for future research are also presented.展开更多
Maritime radar and automatic identification systems (AIS), which are essential auxiliary equipment for navigation safety in the shipping industry, have played significant roles in maritime safety supervision. However,...Maritime radar and automatic identification systems (AIS), which are essential auxiliary equipment for navigation safety in the shipping industry, have played significant roles in maritime safety supervision. However, in practical applications, the information obtained by a single device is limited, and it is necessary to integrate the information of maritime radar and AIS messages to achieve better recognition effects. In this study, the D-S evidence theory is used to fusion the two kinds of heterogeneous information: maritime radar images and AIS messages. Firstly, the radar image and AIS message are processed to get the targets of interest in the same coordinate system. Then, the coordinate position and heading of targets are chosen as the indicators for judging target similarity. Finally, a piece of D-S evidence theory based on the information fusion method is proposed to match the radar target and the AIS target of the same ship. Particularly, the effectiveness of the proposed method has been validated and evaluated through several experiments, which proves that such a method is practical in maritime safety supervision.展开更多
This study aims at investigating the AIS （Agricultural Information System） in Hamedan province, Iran, benefiting from the list of criteria for well functioning AISs that were identified in earlier researches. For th...This study aims at investigating the AIS （Agricultural Information System） in Hamedan province, Iran, benefiting from the list of criteria for well functioning AISs that were identified in earlier researches. For this purpose, a survey method with multi-stage stratified random sampling technique was used to select 31 agricultural researchers, and 62 extension workers in the province. The data were acquired by questionnaire and structured interviews. The instrument for data collection was subjected to pre-testing, validation and reliability tests. The results of the factor analysis revealed that the criteria could be categorized into four overarching groups based on their inter-correlation. The analysis of mentioned criteria in Hamedan province AIS showed less efficiency and effectiveness than studies conducted in other areas. But among these, two desirable criteria existed. It is recommended that the ecological knowledge system （EKS） should be integrated with AIS, and some ecological and sustainable development criteria should be added to the existing ones.展开更多
In this study, we conduct research to estimate the elements of fun in card games. Previously, we tried to estimate the elements of fun by conducting a questionnaire to players, but the results were not good. Therefore...In this study, we conduct research to estimate the elements of fun in card games. Previously, we tried to estimate the elements of fun by conducting a questionnaire to players, but the results were not good. Therefore, we propose an analysis using the player’s biological information to make a more accurate estimation. Specifically, we try to elucidate the elements of fun by having a player who is playing a game wear a smart watch, and measuring and analyzing the heart rate of that player. This paper conducts an experiment to determine whether our intended data can be collected. As a result, it was found that there is a response to the heart rate in a specific scene, and there is a possibility that the intended data can be collected. We plan to conduct larger experiments in the future.展开更多
The issue of opacity within data-driven artificial intelligence(AI)algorithms has become an impediment to these algorithms’extensive utilization,especially within sensitive domains concerning health,safety,and high p...The issue of opacity within data-driven artificial intelligence(AI)algorithms has become an impediment to these algorithms’extensive utilization,especially within sensitive domains concerning health,safety,and high profitability,such as chemical engineering(CE).In order to promote reliable AI utilization in CE,this review discusses the concept of transparency within AI utilizations,which is defined based on both explainable AI(XAI)concepts and key features from within the CE field.This review also highlights the requirements of reliable AI from the aspects of causality(i.e.,the correlations between the predictions and inputs of an AI),explainability(i.e.,the operational rationales of the workflows),and informativeness(i.e.,the mechanistic insights of the investigating systems).Related techniques are evaluated together with state-of-the-art applications to highlight the significance of establishing reliable AI applications in CE.Furthermore,a comprehensive transparency analysis case study is provided as an example to enhance understanding.Overall,this work provides a thorough discussion of this subject matter in a way that—for the first time—is particularly geared toward chemical engineers in order to raise awareness of responsible AI utilization.With this vital missing link,AI is anticipated to serve as a novel and powerful tool that can tremendously aid chemical engineers in solving bottleneck challenges in CE.展开更多
In the realm of Artificial Intelligence (AI), there exists a complex landscape where promises of efficiency and innovation clash with unforeseen disruptions across Information Technology (IT) and broader societal real...In the realm of Artificial Intelligence (AI), there exists a complex landscape where promises of efficiency and innovation clash with unforeseen disruptions across Information Technology (IT) and broader societal realms. This paper sets out on a journey to explore the intricate paradoxes inherent in AI, focusing on the unintended consequences that ripple through IT and beyond. Through a thorough examination of literature and analysis of related works, this study aims to shed light on the complexities surrounding the AI paradox. It delves into how this paradox appears in various domains, such as algorithmic biases, job displacement, ethical dilemmas, and privacy concerns. By mapping out these unintended disruptions, this research seeks to offer a nuanced understanding of the challenges brought forth by AI-driven transformations. Ultimately, its goal is to pave the way for the responsible development and deployment of AI, fostering a harmonious integration of technological progress with societal values and priorities.展开更多
文摘The objective of this research is to examine the factors affecting successful accounting information of Thai-listed companies. The factors affecting successful accounting information are two variables including accounting professional and accounting information system （AIS） competency. Population and sample of this research is the companies listed in the Stock Exchange of Thailand （SET）. A questionnaire mail was used for collecting the data from chief accountant officer of the companies listed in the SET. The results indicate that accounting professional has a positive significant effect on successful accounting information in all dimensions including effective planning, efficient controlling, and promoting decision and communication. Moreover, AIS competency has a positive significant effect on successful accounting information only in dimension of promoting decision and communication. Overall, the results indicate that internal resource and capabilities including accounting professional and AIS competency are the primary factors that influence successful accounting information of Thai-listed companies. Theoretical and managerial contributions are explicitly provided. Conclusions, suggestions and directions for future research are also presented.
文摘Maritime radar and automatic identification systems (AIS), which are essential auxiliary equipment for navigation safety in the shipping industry, have played significant roles in maritime safety supervision. However, in practical applications, the information obtained by a single device is limited, and it is necessary to integrate the information of maritime radar and AIS messages to achieve better recognition effects. In this study, the D-S evidence theory is used to fusion the two kinds of heterogeneous information: maritime radar images and AIS messages. Firstly, the radar image and AIS message are processed to get the targets of interest in the same coordinate system. Then, the coordinate position and heading of targets are chosen as the indicators for judging target similarity. Finally, a piece of D-S evidence theory based on the information fusion method is proposed to match the radar target and the AIS target of the same ship. Particularly, the effectiveness of the proposed method has been validated and evaluated through several experiments, which proves that such a method is practical in maritime safety supervision.
文摘This study aims at investigating the AIS （Agricultural Information System） in Hamedan province, Iran, benefiting from the list of criteria for well functioning AISs that were identified in earlier researches. For this purpose, a survey method with multi-stage stratified random sampling technique was used to select 31 agricultural researchers, and 62 extension workers in the province. The data were acquired by questionnaire and structured interviews. The instrument for data collection was subjected to pre-testing, validation and reliability tests. The results of the factor analysis revealed that the criteria could be categorized into four overarching groups based on their inter-correlation. The analysis of mentioned criteria in Hamedan province AIS showed less efficiency and effectiveness than studies conducted in other areas. But among these, two desirable criteria existed. It is recommended that the ecological knowledge system （EKS） should be integrated with AIS, and some ecological and sustainable development criteria should be added to the existing ones.
文摘In this study, we conduct research to estimate the elements of fun in card games. Previously, we tried to estimate the elements of fun by conducting a questionnaire to players, but the results were not good. Therefore, we propose an analysis using the player’s biological information to make a more accurate estimation. Specifically, we try to elucidate the elements of fun by having a player who is playing a game wear a smart watch, and measuring and analyzing the heart rate of that player. This paper conducts an experiment to determine whether our intended data can be collected. As a result, it was found that there is a response to the heart rate in a specific scene, and there is a possibility that the intended data can be collected. We plan to conduct larger experiments in the future.
文摘The issue of opacity within data-driven artificial intelligence(AI)algorithms has become an impediment to these algorithms’extensive utilization,especially within sensitive domains concerning health,safety,and high profitability,such as chemical engineering(CE).In order to promote reliable AI utilization in CE,this review discusses the concept of transparency within AI utilizations,which is defined based on both explainable AI(XAI)concepts and key features from within the CE field.This review also highlights the requirements of reliable AI from the aspects of causality(i.e.,the correlations between the predictions and inputs of an AI),explainability(i.e.,the operational rationales of the workflows),and informativeness(i.e.,the mechanistic insights of the investigating systems).Related techniques are evaluated together with state-of-the-art applications to highlight the significance of establishing reliable AI applications in CE.Furthermore,a comprehensive transparency analysis case study is provided as an example to enhance understanding.Overall,this work provides a thorough discussion of this subject matter in a way that—for the first time—is particularly geared toward chemical engineers in order to raise awareness of responsible AI utilization.With this vital missing link,AI is anticipated to serve as a novel and powerful tool that can tremendously aid chemical engineers in solving bottleneck challenges in CE.
文摘In the realm of Artificial Intelligence (AI), there exists a complex landscape where promises of efficiency and innovation clash with unforeseen disruptions across Information Technology (IT) and broader societal realms. This paper sets out on a journey to explore the intricate paradoxes inherent in AI, focusing on the unintended consequences that ripple through IT and beyond. Through a thorough examination of literature and analysis of related works, this study aims to shed light on the complexities surrounding the AI paradox. It delves into how this paradox appears in various domains, such as algorithmic biases, job displacement, ethical dilemmas, and privacy concerns. By mapping out these unintended disruptions, this research seeks to offer a nuanced understanding of the challenges brought forth by AI-driven transformations. Ultimately, its goal is to pave the way for the responsible development and deployment of AI, fostering a harmonious integration of technological progress with societal values and priorities.
