Information Technology Journal KMUTNB

Applying Fuzzy Multi-Criteria Decision Making for the Selection of Competitive Factors in Robotics Based on System Development Life Cycle

2024-09-24T18:35:58+07:00

Robots are a technology that plays an important role in many industries today. Competition in the robot market is high, so choosing the right competitive factors for robots is important. This study uses a Fuzzy Analytic Hierarchy Process (F-AHP) method to select appropriate competitive factors for the robot. It considers competitive factors in robots and system development life cycles (SDLC). The research results found that important competitive factors for robots include: All 5 experts focus on (C1) interaction factors giving robots flexibility and adaptability to changing environmental conditions while (SC1–5) image processing gives robots the ability to sense and respond to the environment while competing effectively. Combining these two factors improves competitive performance and allows the robot to maximize its time in changing situations. Among the alternative scenarios compared with factors at levels 1 and 2, option A1 (Robotic 1) performed the best in terms of achieving optimal time, as indicated by its calculated weight (Ni) = 0.508 and All 5 students determined the weight values according to Table 1, focusing on factors (C2) Posture factors affect a robot's performance in competition. Maintaining the correct posture helps the robot be agile and efficient in carrying out its tasks and factors (SC2-6) in level 2 Climbing steep slopes gives robots the ability to burn off energy and maintain stability in difficult conditions. Efficient operation in steep conditions is an important competitive factor. Among the alternative scenarios compared with factors at level 1 and level 2, option A1 (Robotic 1) performed the best in terms of achieving optimal time, as indicated by its calculated weight (Ni) = 0.573. This study shows that the F-AHP is an effective tool for selecting appropriate competitive factors for robots.

Modern Marketing Platform for Surin Farmer Group

2024-09-24T18:58:11+07:00

The objective of this research was to create a modern marketing platform for the Surin Farmer Group and evaluate user satisfaction with the platform. The platform development process involved integrating the Line application (Line), which is highly popular among farmers, to provide convenience and user-friendly functionality. The Software Development Life Cycle (SDLC) process was employed to assist in system development, and the tools used for system development included Visual Studio Code, PHP as the programming language, JavaScript Library (jQuery), and MySQL database management system. Additionally, the LINE Frontend Framework or LIFF, a technology used for connecting Line applications, was incorporated. The principles of a LINE business account (Line OA) were applied to enhance the development into an online marketing platform. The study included a sample of individuals interested in buying and selling products online in Surin province. The sample groups consisted of 20 farmers from Surin province and 50 general users. The research findings indicated that the developed platform is effective and responsive to user needs. The satisfaction evaluation results revealed that the sellers (farmers) had a satisfaction rating of 4.32, S.D. = 0.45, indicating significantly high satisfaction levels. On the other hand, the buyers (general users) had a satisfaction rating of 4.40, S.D. = 0.39, also indicating significantly high satisfaction levels.

Thinking Skills Level Classification of Scientific Questions Using Bidirectional LSTM

2024-09-24T19:06:08+07:00

Science education with a suitable learning activity can help students enhance their thinking skills. Examination is one of the assessment tools to evaluate the student learning outcome in the domain of thinking skills. The Revised Bloom's Taxonomy, a well-known theory used to describe cognitive domains, divides thinking skills into two categories: basic and advanced thinking skills. Classifying questions according to their level of thinking abilities is an important task for teachers to design effective assessment tools. The objective of this study is to propose a model for classifying Thai language questions in science subjects. Initially, we used three algorithms: Bidirectional LSTM (BiLSTM), Naive Bayes (NB), and Support Vector Machine (SVM) for selecting Thai word tokenization algorithms. Then, we compare the model's performance using different feature sets. The combination of the question, training choice, and length of choice features with BiLSTM obtained an accuracy of 70%. Moreover, we employed part-of-speech (POS) tagging for feature selection. According to the findings, using nouns, verbs, adjectives, and adverbs enhances accuracy by 80.24%. This study shows the ability to use a model to categorize science questions to assist teachers in choosing questions that are appropriate to encourage higher-order thinking skills in students.

Green Space Network in Nakhonratchasima City Municipality, Thailand

2024-09-24T19:15:59+07:00

Urban green space still is one critical role for developing sustainability of cities that well-planed and well-designed green networks can create attractive settings for daily life, distinctive local identities for places and can help guide future settlement growth. Therefore, this study aims to plan green space network (GSN) or urban greenways’ network in Nakhonratchasima City Municipality (NCM), Thailand. This GSN in NCM used GIS techniques such as the least-cost path analysis in ArcGIS, it was analyzed by the selected output of road nodes' and green space nodes' location. As results, the obtained GSN in NCM was found that Mittraphap Road (Highway no.2), cuts through the middle of NCM area as main potential green space location to connect other minor potential green space locations. Consequently, this obtained GSN can help not only in local decision-making for planning and designing green city of NCM, but also in Thai city municipal areas to use its future approach or case study for their green areas.

Invention The Program of Hands Motion Detector for Translating Disabilities People's Sign Language

2024-09-24T19:28:31+07:00

The number of people with disabilities is currently increasing, and in Thai society, the proportion of individuals with disabilities is notably high, approximately 3% of the population (Krungthep Turakij, 2022). Providing support and facilitating accessibility for people with disabilities is of great importance. As part of these efforts, we developed a motion detection program aimed at translating sign language for individuals with disabilities. This program utilizes object detection techniques, such as MediaPipe, in combination with machine learning. It accesses the camera to capture sign language gestures and compares them with models trained on a sign language gesture dataset. The program then displays the corresponding meaning on the screen, with the goal of aiding communication for people with disabilities. The results indicate that the model performs well when tested with a benchmark dataset of 75,000 sign language gestures. However, challenges arise when gestures are unclear, incorrect, not included in the dataset, or closely resemble other gestures, which may lead to misclassification. Additionally, limitations due to insufficiently powerful training equipment have caused a delay in processing and displaying gesture meanings, with a lag time of approximately 5-10 seconds. Despite these challenges, the model achieves an accuracy of 76.40%, which is considered satisfactory. The program is also capable of translating the detected gestures into the Thai language.