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A Mobile Application for Electronic Parts Counting and Identification in Physics Laboratory
(2025-01-01)
Leelawattananon, Tanaporn
;
Chittayasothorn, Suphamit
Counting of small objects such as resistors, capacitors, and inductors in physics laboratories are tedious and challenging tasks because of their numbers and small size. In this paper we present the development of a mobile application for counting and identifying small electronics parts. The system employs object edges detection using the difference of gaussian operator and classify the objects using template matching. Pictures taken using mobile phone camera are used as the input to the mobile application which correctly classify and count the objects. Electronics objects used in the counting and classification include resistors, mylar capacitors, and ceramic capacitors. The mobile application helps reduce the work required by laboratory personnel for intermediate physics laboratory management and is now deployed in the physics laboratory of the School of Science, King Mongkut's Institute of Technology Ladkrabang.
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Some Practical Aspects of the Relational Database Normalization Process
(2025-01-01)
Pornphol, Putsadee
;
Chittayasothorn, Suphamit
Database normalization is a ubiquitous theoretical relational database analysis process. It comprises several levels of normal forms and encourage database designers not to split database tables into smaller ones unless it is necessary. Nevertheless, there are many aspects of relational database normalization which are not very well applied or well understood in practice. One of the biggest misconceptions is the misunderstanding that database normalization encourages splitting tables until they can be no longer spilt. Other popular practical misconceptions include over normalizations, performance issues, the complexity and rarity of multivalued and join dependencies, the projection/join normal form, and the unnecessity of carrying the normalization process beyond the third normal form or Boyce-Codd Normal Form (BCNF). This paper clarifies these practical misconceptions with positive examples and argues that relational database normalization process is a very practical analysis and quality control process of relational database table structures.
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Using DeepSeek LLM AI System on Database Concepts and Design
(2025-01-01)
Pornphol, Putsadee
;
Chittayasothorn, Suphamit
The use of Large Language Model (LLM) artificial intelligence (AI) systems in learning environments is ubiquitous. They are used by learners for self-studying, assignments, and exam preparation. Practitioners use them as junior assistants. Major concerns include the correctness and the completeness of the answers generated by the AI systems. In this paper, we explore how well an LLM AI system DeepSeek, answers database concepts and design questions. Selected questions on database design and frequently misunderstood topics are asked. Related knowledge is explained. The answers are reviewed and marked to provide an assessment on its use in the subject area.
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Using LLM Artificial Intelligence Systems as Complex SQL Programming Assistants
(2024-01-01)
Pornphol, Putsadee
;
Chittayasothorn, Suphamit
Learning database programming such as SQL programming is a challenging task when the queries become more complex. SQL is a declarative language based on relational calculus which describes the definition of the query results instead of describing the procedure or steps used to obtain the query result. Tutorial sessions using tutorial assistances are generally required to support the learning of advanced part of the language. Recently generative AI systems demonstrated question answering capabilities including programming codes generation. This paper verifies the SQL code generating capabilities of four generative AI systems: Bing, Bard, ChatGPT, and Copilot and their suitability as SQL programming assistants.
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Electronic Parts Counting in Physics Laboratory Using Difference of Gaussians Edge Extraction
(2024-01-01)
Leelawattananon, Tanaporn
;
Chittayasothorn, Suphamit
Small electronic parts counting in the physics laboratory is a challenging task. These small objects such as resistors, capacitors, and inductors are used in physics laboratories and because of their numbers and small size, are hard to count in a short period of time. The precise inventory of these small electronics parts is therefore compromised. In this paper we present the development of a small electronics parts counting system. The system employs object edges detection using the difference of gaussian operator. This technique is suitable for those small electronic objects which have clear boundaries. By adjusting relevant parameters sigma and threshold to suit the size of the objects, the edge images are clearly detected thus enable correct counting of the objects which leads to correct inventory of electronics parts. An alternative technique using the canny edge detector operator is also used as a comparison technique. The experimental results are precise.
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Identifier Handling in Information Systems: The Case of University Student Registration Systems in Thailand
(2024-01-01)
Boonam, Pattana
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Chittayasothorn, Suphamit
In modern information systems, identifiers play important roles in information systems and databases. An information system can be regarded as a simulated computerized system. Each object instance or entity instance represents a real-world object. There must be a unique identifier or a key value which uniquely identifies each such object instance. One of the earliest applications in a university is the student registration system or students' record management system. These systems originated some decades ago using the old-style record-at-a-time languages and file-based technology. Instead of using the identifier concept, these systems employ the classifier concept which affects the functionality of the systems. This paper addresses the issues related to using identifiers as classifiers and proposes a solution. Case studies from several universities in Thailand are also presented.
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Handling Null Values in SQL Queries on Relational Databases
(2024-01-01)
Méndez, Manuel
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Merayo, Mercedes G.
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Chittayasothorn, Suphamit
The lack of information within relational databases expressed as NULL values presents a problem in ensuring the quality of data and the information retrieved by SQL queries. This is so because there are different interpretations of NULL values. Actually, in many cases, queries either do not consider that NULL values can appear as a result of their evaluation or do not reflect in the code the correct interpretation of these values. NULL values have been present in databases since almost the earliest implementations of relational database management systems, but the implementation of the SQL standard raises multiple problems. When querying on a database that handles NULL values, the results may not be as expected, either by omission of results (false negatives) or by incorrect results (false positives). In this work we propose a methodology that analyses different SQL queries and allows the user to detect possible errors in those queries that have NULL values.
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Verification of Relational Database Languages Codes Generated by ChatGPT
(2023-10-27)
Pornphol, Putsadee
;
Chittayasothorn, Suphamit
The potential of using large language model artificial intelligence systems to generate program codes for application development is significant. Database codes in SQL (Structured Query Language), which is the standard relational database language, can be generated by such systems. Generative AI systems know database languages syntax through their training data and the text patterns from various sources that include SQL queries and related text. Thus, the generated codes may not be perfect and need verification before usage. This paper verifies the relational completeness of the SQL codes generated by ChatGPT, one of the most widely used large language model systems. Relational algebra operators are used for the relational complete verification. An equivalent relational calculus statement is generated for each SQL and relational algebra statement. The results confirmed that ChatGPT has the ability to generate relational complete SQL, relational algebra, and relational calculus codes.
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Relational Database Principles Consideration for SQL Programming
(2023-01-01)
Pornphol, Putsadee
;
Chittayasothorn, Suphamit
In practice, SQL programmers often encounter queries which are hard to formulate using SQL statements. Many of them do not know if the queries are too hard beyond their capabilities, or they are the limitations of the language. Many of these programmers only know that SQL statements work on database tables and are not aware of relational database and the relational complete language principle. This paper presents the common problems that SQL programmers encounter and refers to the relevant relational database principles as solutions.
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Message from the Chairs QRS 2023
(2023-01-01)
Eric Wong, W. E.
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Tse, T. H.
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Chittayasothorn, Suphamit
;
Jiang, He

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