Atchariyachanvanich, Kanokwan

Preferred name

Main Affiliation

School of Information Technology

kanokwan.at@kmitl.ac.th

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Bridge Sub Structure Defect Inspection Assistance by using Deep Learning
(2019-10-01)
Kruachottikul, Pravee
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Cooharojananone, Nagul
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Phanomchoeng, Gridsada
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Chavarnakul, Thira
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Kovitanggoon, Kittikul
Road transportation is the most popular transportation in Thailand, which the top two highest traffic are the region-to-region highways; and then inter-city highways. Therefore, the regular maintenance is required to maintain the good condition due to road safety. The most significant process of bridge inspection procedures is sub structure inspection, which requires visual inspection as an initial step. This process is used to quick determine the damage severity i.e. appearance and crack that may cause damage to the structure strength. The current process requires that the experienced maintenance engineer to be on the field in order to visual inspect and estimate whether the maintenance is required. Yet, due to the limitation of number of expert engineers to be on the field, the photo verification is introduced to assist them so that they are no need on every inspection site. However, using human to verify has no standard and uncontrollable. They need to have experience and good knowledge. As well as it is highly depended on individual decision-making skill. Thus, in this paper, the deep learning technique will be presented to assist the expert for quality inspection process of bridge sub structure images. That is using image enhancement and then image splitting and overlapping for image pre-processing. After that applying CNNs for object classification. As a result, the total accuracy is 89% based on 3926 dataset.
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A Data Visualization for Helping Students Decide Which General Education Courses to Enroll: Case of Chulalongkorn University
(2019-01-01)
Cooharojananone, Nagul
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Dilokpabhapbhat, Jidapa
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Rimnong-ang, Thanaporn
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Choosuwan, Manutsaya
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Bunram, Pattamon
Chulalongkorn University has been utilizing information systems for course administration system, named CU-CAS, to help manage the course syllabus, course contents and course satisfaction survey. While current students have been selecting courses based on information from seniors and friends, we recognize that the data from CU-CAS could be useful in selecting course, but have not been fully utilized. Therefore, this project aims to design a data dashboard to help students select courses to register, based on the data from course satisfaction survey by students from the past three years of course offerings. In this work, we developed CU-CAS data visualization using Google Data Studio. Data were analyzed and presented the overall of the evaluation result in term of dashboard. According to our pilot study, students make decisions for enrollment by comparing the evaluation result in the past three years, in the form of different indicators. We also collected and analyzed data from the student blogs that review courses that they took using word cloud and Markov chain. Both data from CU-CAS and blogs will be represented to students to help students make decision in registering courses. This project is one of the e orts to utilize data in a way that is easy to understand to students, allow Chulalongkorn University to understand students learning behavior, and bring back to plan and adjust teaching strategies.
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What Makes university students use cloud-based e-learning?: Case study of KMITL students
(2015-01-13)
Atchariyachanvanich, Kanokwan
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Siripujaka, Nutchanon
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Jaiwong, Nattapong
Cloud computing technology has been influential in overcoming problems in e-learning systems, such as the lack of scalability and storage limitation. Therefore, a framework for applying cloud computing on e-learning systems has been prepared. However, to develop a cloud-based e-learning system that matches well with the learners' needs and solves the current problems, it is important to know the learners' requirements. This research evaluated the key significant factors required for university students to use Cloud-based e-learning based on a research model, including the theory of motivation, and characteristics of cloud computing. In total, 250 students from King Mongkut's Institute of Technology Ladkrabang were surveyed by questionnaire. Data analysis was performed by factor and multiple regression analyses. Overall the factors that influence the intention to use cloud-based e-learning were identified as the availability, collaboration, cloud-based e-learning notifications, intrinsic motivation and extrinsic motivation. However, these account for only 62.9% of the usage intention, and so other factor(s) still remain to be determined.
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RSQLG: The Reverse SQL Question Generation Algorithm
(2019-05-14)
Julavanich, Thanakrit
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Nalintippayawong, Srinual
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Atchariyachanvanich, Kanokwan
Nowadays, the people who learn and teach SQL commands require to get a hand-on practice with real environment to make the learning effective. The creating SQL exercise is a time-consuming task for instructors. As a result, students might not get enough questions to meet their demands. The reverse SQL question generation algorithm (RSQLG) is developed to solve this problem. The RSQLG has ability to automatically generate SQL exercise for students. The RSQLG can reverse the manual question creation process which starts from creating question to start creating query answer first instead. The RSQLG considers the existing data and database structure by using various constraints. The instructors also can specify the language, format and explanation of the questions. The RSQLG supports DML commands-SELECT, INSERT, UPDATE and DELETE-and support data retrieval from multiple tables which perform by JOIN and subquery operations. The algorithm has ability to generate bulk questions with less effort. The instructor is not required to writing requirements and validating the queries. The RSQLG can be implemented in e-learning to enhance sustainable practices and improve learning outcome for students.
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Determinants of Personal Health Information Disclosure: A Case of Mobile Application
(2018-01-01)
Atchariyachanvanich, Kanokwan
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Mitinunwong, Nichaporn
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Tamthong, Butsaraporn
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Sonehara, Noboru
This study explored the factors that affect personal health information (PHI) disclosure via a mobile application (app) in Thailand. Since mobile apps are increasingly popular, as is the Thai people's concern on their health condition, many mobile app service providers want to know which factors would persuade customers to reveal their PHI via mobile apps. This research model was, therefore, developed and included the six factors of: personalized service, self-presentation, mobile app reputation, familiarity, perceived benefits and privacy concerns. The hypotheses were tested by structural equation modeling using the questionnaire responses from 294 valid subjects. Surprisingly, privacy concern was not significantly negatively related to the intention to disclose PHI. However, the significance effect of the perceived benefit, personalized service and self-presentation were consistent with previous studies. In addition, the respondents were willing to reveal different personal information in different situations. The implication of the result will shed light on the development of a healthcare mobile app service provider.
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DBLearn: Adaptive e-learning for practical database course - An integrated architecture approach
(2017-08-29)
Nalintippayawong, Srinual
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Atchariyachanvanich, Kanokwan
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Julavanich, Thanakrit
In this paper, an integrated architecture approach in designing and developing a DBLearn web-based application is presented. The DBLearn system is a personalized and adaptive e-learning system designed especially for learning practices in database courses. This approach focused on topics that are important but difficult for new learners, such as database design and structured query language (SQL) command query. The concept of adaptive e-learning and autonomous agents were applied in this system to eliminate the traditional constraints of effective e-learning, such as the problem of different learning sensory and knowledge levels. Four approaches were used to solve this problem. First, learning style theory was used to classify the way of learning for each student. Second, the student activity (historical data) is kept in the system to analyze the next knowledge the student should learn or review. Next, the SQL query automated grader was used to judge the correctness of the student's query. This grader supports all the necessary commands in both DML and DDL. Finally, the SQL query question generator module that can generate SQL query questions automatically is presented. This will reduce the instructor's work load in creating enough questions and allow the students to practice at their own pace as much as they want. By using these four techniques, the students will have a better learning experience and becoming more successful in learning outcomes.
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ScrambleSQL: A Novel Drag-and-drop SQL Learning Tool
(2019-10-01)
Phewkum, Chanapat
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Kaewchaiya, Jittakan
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Kobayashi, Kazuki
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Atchariyachanvanich, Kanokwan
Structured Query Language (SQL) is a standard language for forming queries to access relational database systems, e.g. create table, as well as read, update, and delete data from the database. Thus, it is commonly taught in computer science classes. Technology growth helps developers to create many SQL tools which encourage students to learn effectively. Although many SQL learning tools have been developed, they are not suitable for some users who prefer to use a tablet for learning SQL, because the existing tools were not developed for a touchscreen device. Thus, we developed prototype ScrambleSQL, optimized for tablets. The purpose was to enhance learning, speed up SQL command writing and allow users to practice SQL commands anywhere and anytime, with the internet. We tested undergraduate students from an Information Technology program. They wrote SQL commands by ScrambleSQL and then completed a questionnaire. The participants were satisfied with its screen, learning and system capabilities. ScrambleSQL reduced typing errors and helped novice users to learn SQL commands with the provided keywords. In addition, the participants enjoyed learning with ScrambleSQL.
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Extracting brand names and product names from product review webpages: A case of mixed languages
(2016-11-18)
Atchariyachanvanich, Kanokwan
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Jantararoungtong, Sakda
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Jirabovolvanit, Vichayanan
Most of Thai product review websites display mixed contents by showing the product name and brand name in English language and reviewed contents in Thai language. However, the current product extraction application programming interfaces (API) could not extract product name written in English language from Thai product review websites. Therefore, this paper proposed the algorithm to extract brand names and product names from mixed Thai-English language product review websites. The experimental result revealed the proposed algorithm had a 97.48% of precision. The contribution of the proposed algorithm can be a part of location-based m-commerce. The algorithm extracts product name from the logs file of wireless access point in a shopping mall in order to recognize customers' interest. The sale promotion or advertising will be offered to the customers based on their interest via their mobile phone.
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Factors affecting disclosure of personal health information via mobile application
(2017-06-27)
Atchariyachanvanich, Kanokwan
;
Mitinunwong, Nichaporn
;
Tamthong, Butsaraporn
This study explored the factors that affect personal health information (PHI) disclosure via a mobile application (app) in Thailand. Since mobile apps are increasingly popular, as is the Thai people's concern on their health condition, many mobile app service providers want to know which factors would persuade customers to reveal their PHI via mobile apps. This research model was, therefore, developed and included the six factors of: personalized service, self-presentation, mobile app reputation, familiarity, perceived benefits and privacy concerns. The hypotheses were tested by structural equation modeling using the questionnaire responses from 252 valid subjects. Surprisingly, privacy concern was not significantly negatively related to the intention to disclose PHI. However, the significance effect of the perceived benefit, personalized service and self-presentation were consistent with previous studies. The implication of the result will shed light on the development of healthcare mobile apps.
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The study of the local community products (OTOP) website characteristics toward buyer decision using eye tracking
(2018-05-08)
Cooharojananone, Nagul
;
Akasarakul, Krittika
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Wongkhamdi, Thipsuda
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Pruetthiwongwanich, Phonkornkrit
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Atchariyachanvanich, Kanokwan
Thai government has launched a policy to encourage local community people to sell their products (OTOP) through e-commerce. One Tambon One Product or OTOP was derived from the concept of One Village One Product (OVOP) in Japan. Currently, people sell their products through the e-commerce web portal such as Facebook rather than having their own OTOP official websites. Therefore, this study aims to study and develop the prototype of the official website. The results show that social influence, perceived ease of use, reliability of website and reliability of product have a positive relationship to the intention to buy a product. Researchers further investigated using eye tracking device to analyze the participants' purchasing behavior. The results show that participants spent time looking at images on the center of the homepage, the product menu bar at the bottom of the center of the homepage, and the components from the product page, respectively. Moreover, participants did not spend time looking or even clicking the social network icon such as Facebook. The results of this study and implications are further discussed.

Atchariyachanvanich, Kanokwan

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