Browsing by Type "เอกสารตีพิมพ์ในการประชุม (Conference Proceedings)"

Now showing 1 - 20 of 274
  • No Thumbnail Available
    Publication
    1st-degree Atrioventricular (AV-block) and Bundle Branch Block Prediction using Machine Learning
    Rasel, Risul Islam; Sultana, Nasrin; Meesad, Phayung; Chowdhury, Anupam; Hossain, Meherab (Association for Computing Machinery, 2020)
    Heart block occurs when the flow of electricity interrupted or partially delayed between the top and bottom chambers of the heart. People are now more often affected by this kind of disease. However; early prediction of heart block can reduce the diagnosis complexity and treatment cost. In this study; a data mining and machine learning model is proposed to predict three types of heart blocks; such as 1st-degree A-V block; Left Bundle Branch Block (LBBB); and Right Bundle Branch Block (RBBB). Experiment data samples are collected from the cardiology department of Chittagong Medical College Hospital (CMCH); Bangladesh. The dataset contains 32 types of numeric and categorical features about the patient's ECG report; daily activities; and food habits. The prediction model has been designed; trained; and tested with some empirical machine learning algorithms namely Decision Tree; Random Forest; K-Nearest Neighbor; and Support Vector Machine. Finally; the experimentation shows that Decision Tree and Random Forest models outperform the other algorithms in overall heart block prediction with an accuracy of more than 92%.
  • No Thumbnail Available
    Publication
  • No Thumbnail Available
    Publication
    A Conceptual Model of Requirement Engineering in Cloud Project Delivery for Thai Government Organizations
    Chaipunyathat, Ajchareeya; Porrawatpreyakorn, Nalinpat; Nuchitprasitchai, Siranee; Viriyapant, Kanchana (2019)
    The shift to cloud computing has affected the future of software engineering in several ways i.e.; multilateral software development; scalability; and new technology stack such as an open-source software; plus infrastructure as code such as container; serverless architecture and software defined network (SDN). In order to support the cloud project delivery for government organizations; requirements engineering (RE) is a crucial step in software engineering that determines whether a project will be successful or result in a failure. RE steps include requirement elicitation; requirement analysis; requirement specification and requirement validation. Data is collected by semi-structured interview from the providers and the users of cloud services in 11 Thai government organizations; and from cloud service provider for meeting enterprise requirements and user requirements. The results reveal nine key issues that affect cloud project delivery: (1) lack of trust with external cloud service provider by generation X and baby boomer (2) lack of transparency as regards the legal agreement about the cloud user's personal data protection responsibility by cloud service provider; (3) the issues of reliability; security and service level agreements (4) lack of knowledge and lack of understanding of cloud technology (5) required training and a learning by doing (6) the policy to use government cloud services instead of developing their own cloud; (7) older people at top-level tend to resist cloud technology; (8) people in general lack of knowledge and understanding of cloud technology (9) problems about pricing model; it's impact on 23 cloud requirements (functional and non-functional) as well as factors that involved in RE phases. Based on these results this paper presents a Conceptual Model of Requirement Engineering for Cloud Project Delivery in Thai Government Organizations.
  • No Thumbnail Available
    Publication
    A crowd simulation in large space urban
    Sudkhot, Panich; Sombattheera, Chattrakul (IEEE, 2018)
    We present a multiagent-based framework for crowd simulation in large space urban area on a standalone PC. We use Belief-Desire-Intention (BDI) for modeling individual agent behavior. We use RVO for handling a large number of agents. The simulation engine is Unity3d which also take care of the visualization. We experimented our framework with up to 20;000 agents; navigating them from origins to destinations. We found that we can navigate agents successfully. The execution time increases when the number of agent increase. The visualization becomes slow when the number of agent is higher than 1000 agents. We found that the the simulation steps also increases when the number of agent is not higher than 5005.
  • No Thumbnail Available
    Publication
  • No Thumbnail Available
    Publication
    A development of interactive media to enhance comprehension of primary GMP certification for entrepreneur
    Maneeruang, Nattida; Thienmongkol, Ratanachote; Singhkhum, Itdhipol (2019)
    การวิจัยครั้งนี้มีวัตถุประสงค์ดังนี้ 1) เพื่อศึกษาปัญหาและวิเคราะห์ข้อมูลการรับรองมาตรฐาน Primary GMP สำหรับผู้ประกอบการ 2) เพื่อพัฒนาสื่อปฏิสัมพันธ์ส่งเสริมความเข้าใจเรื่อง Primary GMP บนพื้นฐานของการประยุกต์ใช้ UCD และ 3) เพื่อประเมินคุณภาพในการใช้งานของสื่อต้นแบบที่ผลิตขึ้น และประเมินการรับรู้กับกลุ่มเป้าหมายหลังการเรียนรู้ โดยกลุ่มตัวอย่างที่ใช้ในงานวิจัย ประกอบไปด้วย 1) กลุ่มผู้ให้ข้อมูลสำคัญ ได้แก่ กลุ่มผู้เชี่ยวชาญ 4 คน และกลุ่มผู้ให้ข้อมูลสำคัญ 6 คน 2) กลุ่มเป้าหมายที่เป็นผู้ประกอบการที่ยังไม่ได้รับรองมาตรฐาน Primary GMP ในจังหวัดร้อยเอ็ด 50 คน เครื่องมือที่ใช้ในการวิจัย ประกอบไปด้วย 1) แบบสัมภาษณ์เชิงลึก 2) แบบสำรวจความต้องการและสำรวจความเข้าใจ 3) สื่อต้นแบบ 4) แบบประเมินคุณภาพสื่อ 5) แบบประเมินความพึงพอใจ และ 6) แบบทดสอบการรับรู้สำหรับกลุ่มเป้าหมายหลังจากการใช้งาน ผลการวิจัยสำคัญพบว่า 1) จังหวัดร้อยเอ็ดมีสถานประกอบการที่ยังไม่ได้รับรองถึงร้อยละ 60 เนื่องจากผู้ประกอบการส่วนมากขาดความเข้าใจในเรื่องของอาคารและสถานที่ผลิต และสื่อความรู้สำหรับผู้ประกอบการสามารถให้ได้เฉพาะคนที่เข้ารับการอบรมเท่านั้น 2) ได้สื่อส่งเสริมความเข้าใจ ประกอบไปด้วย สื่อปฏิสัมพันธ์รูปแบบแผ่นพับ สื่อปฏิสัมพันธ์รูปแบบเว็บไซน์ และสื่ออินโฟกราฟิก และ 3) ผลการประเมินเพื่อทดสอบคุณภาพสื่อโดยผู้เชี่ยวชาญ 5 คน โดยรวมอยู่ในระดับคุณภาพดีมาก (x̄ = 4.66; S.D. = 0.06) ผลการประเมินความพึงพอใจโดยกลุ่มเป้าหมาย 50 คน โดยรวมอยู่ในระดับคุณภาพดีมาก (x̄ = 4.74; S.D. = 0.12) และผลการทดสอบการรับรู้ของกลุ่มเป้าหมายโดยรวมทั้งหมดที่กลุ่มเป้าหมายทั้ง 50 คน ทำได้ คิดเป็นร้อยละ 90 ต่อ 100
  • No Thumbnail Available
    Publication
  • No Thumbnail Available
    Publication
    A form and API data management platform for progressive web application and serverless application architecture
    Namee, Khanista; Phoarun, Rittiphon; Albadrani, Ghadeer Mohsen; Polpinij, Jantima; Tanessakulwattana, Sarayoot; Sphanphong, Pongpol (Association for Computing Machinery, 2019)
    In the new global economy; web application has become a central issue for an enterprise organization with branches covering many countries around the world. One major issue in early business services research concerned in those organizations is that developing a web application that can support both global and local services at the same time is very difficult. Since at the local level; each country will have different languages; currencies; regulations. Therefore; to develop a system or web application to support business services around the world will have to be repeated the same; but with some details that are different; such as the same invoice form. However; to support services around the world that has repeated the same process but there is detailed information in each country or each language that is different. The objectives of this research are to determine whether to develop a platform that makes Form design to be shared in many countries more easily by automatically linking to the database via API. APIs can be embedded seamlessly into both the front-end and server side. The user interface can be designed smoothly. Export code can be used with HTML. In additional; it can work with serverless applications. Files can be managed in the form of JSON; csv and txt files. The results indicate that the designed platform can support the work that is intended to meet the objectives. Makes Form development in a web application very convenient and reduces many repetitive steps. In addition; data management is also effective. When creating this Form; it helps developers reduce the time it takes to create multiple Forms and reduces the form creation errors in the settings. Custom will help to keep the original Form.
  • No Thumbnail Available
    Publication
    A foundry of human activities and infrastructures
    Allen, R. B; Yang, Eunsang; Timakum, Tatsawan (Springer, Cham, 2017)
    Direct representation knowledgebases can enhance and even provide an alternative to document-centered digital libraries. Here we consider realist semantic modeling of everyday activities and infrastructures in such knowledgebases. Because we want to integrate a wide variety of topics, a collection of ontologies (a foundry) and a range of other knowledge resources are needed. We first consider modeling the routine procedures that support human activities and technologies. Next, we examine the interactions of technologies with aspects of social organization. Then, we consider approaches and issues for developing and validating explanations of the relationships among various entities.
  • No Thumbnail Available
    Publication
    A hybrid forecasting model of cassava price based on artificial neural network with support vector machine technique
    Polyiam, Korawat; Boonrawd, Pudsadee (2017)
    Thailand is the world's largest exporter of cassava. The cassava prices fluctuate because of many factors such as the production cost; economic condition; and price intervention. Therefore; this research aims to propose a forecasting model of cassava price based on the 11-year data (from 2005 to 2015) obtained from the Thai Tapioca Starch Association and Office of Agricultural Economics. Various techniques were applied for the forecast such as Artificial Neural Network; Support Vector Machine; k-Nearest Neighbor and Hybrid Technique. The statistics used to determine the effectiveness of this model were Mean Absolute Percentage Error (MAPE); Root Mean Squared Error (RMSE) and Mean Squared Error (MSE). The results of this research showed that Hybrid Technique demonstrated the lowest value of error followed by Artificial Neural Network; k-Nearest Neighbor and Support Vector Machine; respectively. Therefore; it could be concluded that using the Hybrid Technique to forecast the price of cassava was better than other techniques and generated the predicted price closest to the actual price.
  • No Thumbnail Available
    Publication
    A leveling control media prototype in automatic control
    Joochim, Chanin; Kaewkorn, Supod; Keeratiwintakorn, Phongsak (IEEE, 2019)
    In order to study the control theory; students need to learn about basic theories that are sometimes difficult to understand. Only in-class lecturing is not enough; and hand-on practices are very important; in which theory and practice can be integrated to create knowledge and skills simultaneously. Although there are many learning tools available for practicing with sample exercises; they are not enough for students to understand properly especially in the subject that are abstraction and requires imagination. This paper presents a didactic tool for a study of leveling control system which maintains the surface level using multiple sensors including IMUs and ultrasonic sensors; and multiple models including digital filters; coordination; digital automatic control; and kinematic model. The data obtained from the IMU are used to calculate the tilt angle using the complementary filter method; and from the ultrasonic sensors are used to find the distance between the platform and ground using low-pass filter. The difference tilt from both roll and pitch angles and the distance are used to control the tilt angle and the correct distance using the PID controller. This system can be used to study IMU sensor functions; digital signal processing and digital controller as well; and will enable students to understand and use the sensor system to easily create automatic control systems in the future.
  • No Thumbnail Available
    Publication
    A method for handling text classification with imbalanced data
    Polpinij, Jantima; Sibunruang, Chumsak (2019)
  • No Thumbnail Available
    Publication
    A methodology of personalized recommendation system on mobile device for digital television viewers
    Sibunruang, Chumsak; Polpinij, Jantima (2017)
    With the increasing of the number of digital television (TV) channels in Thailand; this becomes a problem of information overload for TV viewers. There are mass numbers of TV programs to watch but the information about these programs is poor. Therefore; this work presents a personalized recommendation system on mobile device to recommend a TV program that matches viewer’s interests and/or needs.The main mechanism of the system is content-based similarity analysis (CBSA).Initially; the viewer defines favorite programs; and then the system utilize this list as query to find their annotations on the WWW.These annotations will be used to find other programs that are similar by using CBSA.Finally; all similar programs are grouped to the same class and stored as a dataset in a personal mobile device. For the usage; if a TV program matches the interest and specified time of viewer; the system on mobile device will notify the viewer individually.
  • No Thumbnail Available
    Publication
    A mobile recommender system for location-aware telemedical diagnostics
    Komkhao, Maytiyanin; Sodsee, Sunantha; Halang, Wolfgang A.; Rautaray, Siddharth Swarup, Eichler, Gerald, Erfurth, Christian, Fahrnberger, Günter (Springer International Publishing, 2020)
    As recommender systems have proven their effectiveness in providing personalised recommendations based on previous user preferences in e-commerce; this approach is to be transferred for use in medicine. In particular; the aim is to complement the diagnoses made by physicians in rural hospitals of developing countries; in remote areas or in situations of uncertainty by machine recommendations that draw on large bases of expert knowledge to reduce the risk to patients. To this end; a database of patients’ medical history and a cluster model is maintained centrally. The model is constructed incrementally by a combination of collaborative and knowledge-based filtering; employing a weighted similarity distance specifically derived for medical knowledge. In the course of this process; the model permanently widens its base of knowledge on a medical area given. To give a recommendation; the model’s cluster best matching the diagnostic pattern of a considered patient is sought. Fuzzy sets are employed to cope with possible confusion in decision making; which may occur when large data sets cause clusters to overlap. The degrees of membership to these fuzzy sets are expressed by the Mahalanobis distance; whose weights are derived from risk factors identified by experts. The therapy actually applied after the recommendation and its subsequently observed consequences are fed back for model updating. Readily available mobile digital accessories can be used for remote data entry and recommendation display as well as for communication with the central site. The approach is validated in the area of obstetrics and gynecology.
  • No Thumbnail Available
    Publication
    A multi agent-based video tracking algorithm
    Sombattheera, Chattrakul (IEEE, 2018)
    One well known and long-lasting problem in the video tracking is that one particular algorithm would perform well on a certain environmental characteristic. Whenever the characteristic in the scene changes; the performance of the algorithm affected. This research proposes a multiagent-based for video tracking system. The agents follow the odd-man out strategy; which odd agents will be credited less than the favorite ones. We tested our algorithm against two tough videos. The results show that our approach yield satisfactory outcomes. The final tracking results are always within the boundary of the groundtruth; given that there are two out of five correct results.
  • No Thumbnail Available
    Publication
    A Novel Solution for Virtual Server on the Data Consistency Maintenance in Cloud Storage Systems
    Doan, Van Thang; Khang, Vo Quang Hoang; Nguyen, Ha Huy Cuong; Huynh, Cong Phap; Meesad, Phayung; Boonyopakorn, Pongsarun; Meesad, Phayung; Sodsee, Sunantha; Unger, Herwig (Springer International Publishing, 2020)
    Currently; systems P2P cloud is built on the resources of computing; to implement features such as storage and communication; it is possible to find these cloud systems in smart homes. The systems P2P cloud must also ensure that the salient features of clouds—on-demand resource provisioning; elasticity and measured service—are maintained. In this era; several organizations are storing their data on P2P cloud storage in order to meet the requirements of efficient operation like stability; scalability; and availability of services. Data replication services in cloud storage systems are there to improve performance. In this context; the requirements for ensuring data consistency became increasingly important. In this paper; we propose a new technical solution the data consistency maintenance in Cloud Storage Systems. In this manuscript; we have shown that the proposed solution yields the results for the schema which ensures consistent data on costs and latency. In this paper; we use the Open Stack tool; which incorporates a proposed algorithm Balancing Consistency Availability On System Physical Machine for maintaining data consistency in Cloud Storage Systems.
  • No Thumbnail Available
    Publication
  • No Thumbnail Available
    Publication
    A Preliminary Study on Information Graphic for Information Dissemination in Thailand
    Yoowang, Anurak (Daegu: Korean Library and Information Science Society, 2017)
  • No Thumbnail Available
    Publication
    A study of feature affecting on Stroke prediction using machine learning, multi-disciplinary trends in artificial intelligence
    Songram, Panida; Jareanpon, Chatklaw (Springer International Publishing, 2019)
  • No Thumbnail Available
    Publication