Papers by nipat jongsawat
There are many e-learning web sites and e-learning systems that are available with excellent cont... more There are many e-learning web sites and e-learning systems that are available with excellent content and design but they generally lack interactive response and face-to-face communication. Students cannot ask questions and get responses immediately. It is similar to one way communication for learning. However, learning is most effective when it actively constructs knowledge during group social interaction and collaboration. Therefore,
A Study of Two Different Experimental Settings for Group Awareness Information in a Web-Based Group Decision Support System
International Journal of Information Technology and Decision Making, 2011
Group awareness information represents things such as group members' roles and responsibilit... more Group awareness information represents things such as group members' roles and responsibilities, their positions on an issue, their status, and the state of various group processes that group members know about when they work together. The group awareness information presented in this paper is designed to capture group member activities and their behaviors in web-based collaborative work. It consists of
Intelligent Systems (IS) …, 2010
In this paper, we consider a methodology that utilizes qualitative expert knowledge for inference... more In this paper, we consider a methodology that utilizes qualitative expert knowledge for inference in a Bayesian network. The decision-making assumptions and the mathematical equation for Bayesian inference are derived based on data and knowledge obtained from experts. A detailed method to transform knowledge into a set of qualitative statements and an "a priori" distribution for Bayesian probabilistic models are proposed. We also propose a simplified method for constructing the "a prior" model distribution. Each statement obtained from the experts is used to constrain the model space to the subspace which is consistent with the statement provided. Finally, we present qualitative knowledge models and then show a full formalism of how to translate a set of qualitative statements into probability inequality constraints.
Logistics service supply chains (LSSCs) are generally composed of logistic service integrators an... more Logistics service supply chains (LSSCs) are generally composed of logistic service integrators and providers that ensure reliable transport of a product or service from a producer to consumer. Given the usage of LSSC in many safety-critical applications, such as hospitals, it is very important to ensure their reliable operation. For this purpose, many LSSC structures are modeled using Reliability Block Diagrams (RBDs) and their reliability is assessed using paper-and-pencil proofs or computer simulations. Due to their inherent incompleteness, these analysis techniques cannot ensure accurate reliability analysis results. In order to overcome this limitation, we propose to use higher-order-logic (HOL) theorem proving to conduct the RBD-based reliability analysis of LSSCs in this paper. In particular, we present higher-order-logic formalizations of LSSC scenarios depicting logistic service providers offering various types of capacities to the logistic service integrators. As an illustrative example, we also present the formal reliability analysis of a simple three-node corporation.
A Fast Multi-Object Tracking Method using DDR Descriptor
2021 19th International Conference on ICT and Knowledge Engineering (ICT&KE), 2021
The Use of The Internet of Things for a More Effective and Efficient way of Growing Rice
2020 18th International Conference on ICT and Knowledge Engineering (ICT&KE), 2020
This research aimed to develop a smart farm system using a microcontroller and sensors in growing... more This research aimed to develop a smart farm system using a microcontroller and sensors in growing rice in the central region of Thailand. The system monitored the level of water in the planting area, the soil moisture and nutrition on the field in order to manage resources and other factors such as days of planting and pest control. There was a notification system for the user which used the Line Application and Google Firebase to store data. The system allowed the farmer to adapt from traditional way of growing rice to a better approach due to the information they received from the system and the notification system. This gave them a more effective and more efficient way to make profits and reduce costs of the procedures. ESP8266 was used as a controller with water level sensor and soil moisture sensor along with the Line application for notifying the user. Pathum- Thani 1 Rice was grown in this research by using System of Rice Intensification with wet and dry technique. The system...
Streamlining genetic testing for women with ovarian cancer in a large California health care system
Gynecologic Oncology, 2020
OBJECTIVE Referral to Genetics for pre-testing counseling may be inefficient for women with ovari... more OBJECTIVE Referral to Genetics for pre-testing counseling may be inefficient for women with ovarian cancer. This study assesses feasibility of gynecologic oncologists directly offering genetic testing. METHODS A prospective pilot study was conducted at two gynecologic oncology hubs in an integrated healthcare system from May 1 to November 6, 2019. Gynecologic oncologists offered multigene panel testing to women with newly diagnosed ovarian cancer, followed by selective genetic counseling. Outcomes were compared between study participants and women from other hubs in the health system. RESULTS Of ovarian cancer patients at study sites, 40 participated and all underwent genetic testing. Of 101 patients diagnosed at other sites, 85% were referred to genetics (p = .0061 compared to pilot participants) and 67% completed testing (p < .0001). The time from diagnosis to blood draw and notification of result was 18.5 and 34 days for the pilot group compared to 25.5 and 53 days at other sites. Panel testing detected 9 (22.5%) and 7 (10.3%, p = .08) pathogenic mutations in each group, respectively. Patients and providers were highly satisfied with the streamlined process. CONCLUSION Genetic testing performed at the gynecologic oncology point of care for patients with ovarian cancer is feasible, increases uptake of testing, and improves time to results.
Learners' acceptance toward blended learning
2016 SAI Computing Conference (SAI), 2016
A world of technology-driven innovation is continuously and rapidly growing. People can learn fro... more A world of technology-driven innovation is continuously and rapidly growing. People can learn from anywhere and at anytime. However, many people face obstacles when they first use online tools for collaborative learning or social media to support collaborative work. The aims of this survey research are 1) to finding a level of learners' acceptance toward the blended learning courses 2) investigating significant levels of learner satisfaction and acceptance among different groups of learners, computer-related and irrelevant fields of study. The research instrument was the questionnaire, which was divided into two parts, Part 1: Learners' background and Part 2: Learners' acceptance toward the blended learning environment. The questionnaire consists of both open-ended and Likert 5 scale closed-ended questions. Participants in this study were undergraduate students who studied at RMUTSB in the academic year 2014. With stratified sampling, the population is divided into groups that are assigned by the faculties. A simple random sampling is obtained based on students' field of study, computer-related and irrelevant. The data were collected from 300 correspondents and then analysed using statistical software. The statistical techniques include arithmetic means, standard deviation, and t-test. The learners' acceptance toward the blended learning courses in overall is at a very good level, including the perceived ease of use; the perceived usefulness; and behavior intention. There is no significant difference among different groups of learners, computer-related and irrelevant fields of study. For further study, the factors that influence teachers' acceptance with blended learning will be explored. The proportion between online and in-person learning will be included. Other approaches such as a flipped classroom and smart classroom will also be taken into consideration.
Creating behavior-based rules for snort based on Bayesian network learning algorithms
2015 International Conference on Science and Technology (TICST), 2015
Anomaly detection itself may not be considered as the perfect solution to detect any new threat. ... more Anomaly detection itself may not be considered as the perfect solution to detect any new threat. In this paper, we propose to use Bayesian approach to detect relationship among variables in a network traffic dataset of the University's computer network. We apply two algorithms for learning Bayesian networks in order to form a Bayesian model. Next, p Bayesian Inference is performed in order to examine relationships among variables. The strong relationship among variables and unusually strong influences on other variables in the BN model will be used to define the rules according to our environment and needs for building an intrusion detection system. Finally, we create Snort rules based upon the relationships in the model.
In the St Cassian fauna of Late Triassic (Early Carnian) age gastropods with protoconch coiled in... more In the St Cassian fauna of Late Triassic (Early Carnian) age gastropods with protoconch coiled in opposite direction to the teleoconch are common and belong to a number of quite different taxa. Twenty nine of these are here described, 11 of them for the first time: Promathilda misurinensis sp. nov., Turrithilda cassiana sp. nov., T. dockeryi sp. nov., Tirolthilda seelandica gen. et sp. nov., T. nuetzeli sp. nov., Tofanella cancellata sp. nov., Cristalloella cassiana gen. et sp. nov., C. sinuata sp. nov., C. delicata sp. nov., Stuorilda cassiana gen. et sp. nov., and S. tichyi sp. nov. All are newly defined and placed in the Mathildoidea. This connects the Triassic species of that superfamily with the modern Heterostropha (= Heterobranchia). In the family Mathildidae the genera Mathilda and Promathilda are differentiated, two species of Turrithilda described, and Tirolthilda and Schroederilda are included as new genera, with the type species T. seelandica gen. et sp. nov. and Pseudot...
The principles of decision-analytic decision support, implemented in GeNIe (Graphical Network Int... more The principles of decision-analytic decision support, implemented in GeNIe (Graphical Network Interface) and SMILE (Structural Modeling, Inference, and Learning Engine) can be applied in practical decision support systems (DSSs). GeNIe plays the role of a developer's environment and SMILE plays the role of the reasoning engine. A decision support system based on SMILE can be equipped with a dedicated user interface. GeNIe's name and its uncommon capitalization originate from the name Graphical Network Interface, given to the original simple interface to SMILE, the library of functions for graphical probabilistic and decision-theoretic models. GeNIe is an outer shell to SMILE. GeNIe is implemented in Visual C++ and draws heavily on the MFC (Microsoft Foundation Classes). GeNIe runs under one of the most popular computing platforms: Windows operating systems so that this makes it not easily portable. GeNIe is platform dependent and runs only on Windows computers. This is one d...
Rendering of an animated scene is considered to be one of the most important steps in 3D animatio... more Rendering of an animated scene is considered to be one of the most important steps in 3D animation construction. Rendering basically converts 3D geometric models into graphic images. In 3D animation training courses, rendering complex 3D models is a very time consuming task since thousands of frames are needed to create an animation. It is considered one of the major limitations for creating professional 3D animation. This paper presents the use of grid computing for 3D rendering. It can reduce the rendering time and still maintain the quality of the final animation. Software and system architecture solutions are proposed and developed. A graphical user interface (GUI) plug-in and web portal were developed in order to access grid computing facilities. Animators are able to render highly complex 3D models in order to create their animation sequences by using high performance grid computer technologies, monitor rendered scenes, and download the finished images from the server to their...
Developing a Bayesian Network Model Based on a State and Transition Model for Software Defect Detection
2012 13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, 2012
ABSTRACT This paper describes a Bayesian Network model-to diagnose the causes-effect of software ... more ABSTRACT This paper describes a Bayesian Network model-to diagnose the causes-effect of software defect detection in the process of software testing. The aim is to use the BN model to identify defective software modules for efficient software test in order to improve the quality of a software system. It can also be used as a decision tool to assist software developers to determine defect priority levels for each phase of a software development project. The BN tool can provide a cause-effect relationship between the software defects found in each phase and other factors affecting software defect detection in software testing. First, we build a State and Transition Model that is used to provide a simple framework for integrating knowledge about software defect detection and various factors. Second, we convert the State and Transition Model into a Bayesian Network model. Third, the probabilities for the BN model are determined through the knowledge of software experts and previous software development projects or phases. Last, we observe the interactions among the variables and allow for prediction of effects of external manipulation. We believe that both STM and BN models can be used as very practical tools for predicting software defects and reliability in varying software development lifecycles.
Identifying the degree of influential effects for the causal relationships in a Bayesian network model using group decision making technique
2010 Eighth International Conference on ICT and Knowledge Engineering, 2010
In this paper, we propose a methodology based on group decision making for weighting expert opini... more In this paper, we propose a methodology based on group decision making for weighting expert opinions or the degree of an expert's belief in identifying influential effects from parent variables to child variables in a BN model. The methodology consists of three sequential steps. The first step is a pre-processing process where the experts need to identify and select every pair of variables that have a causal relationship between them for the BN model. All the experts in the group must agree with each other for the selections. Second, we map every pair of causal variables into alternatives. Next, experts sort the alternatives by means of a fixed set of linguistic categories; each one has associated a numerical score. We apply a method of weighting individual expert opinions in order to arrange the sequence of alternatives in each step of the decision making procedure. The sequential decision procedure is repeated until it determines a final subset of experts where all of them positively contribute to the agreement for group decision making. Lastly, we transform the alternatives and the collective scores that we obtain from previous step into the BN models. We select a simple diagnostic model of a vehicle fuel system as a case study.
2009 IEEE International Conference on Systems, Man and Cybernetics, 2009
Bayesian networks (BNs) are probabilistic graphical models that are widely used for building diag... more Bayesian networks (BNs) are probabilistic graphical models that are widely used for building diagnosis-and decision-support expert systems. The construction of BNs with the help of human experts is a difficult and time consuming task, which is prone to errors and omissions especially when the problems are very complicated. Learning the structure of a Bayesian network model and causal relations from a dataset or database is important for large BNs analysis. This paper focuses on using a SMILE web-based interface for building the structure of BN models from a dataset by using different structural learning algorithms. In addition to building the structure of BN models, a SMILE web-based interface also provides the feature set of Bayesian diagnosis for the user. The web application uses a novel user-friendly interface which intertwines the steps in the data analysis with brief support instructions to the Bayesian approach adopted. A SMILE web-based interface has been developed based on SMILE (Structural Modeling, Interface, and Learning Engine), SMILEarn, and SMILE.NET wrapper.
International Journal of Decision Support System Technology, 2010
Group awareness information is important information for group work. It represents group members’... more Group awareness information is important information for group work. It represents group members’ roles and responsibilities, their positions on an issue, their status, and the state of various group processes. The group awareness information presented in this article is designed to capture group member activities and their behaviors in web-based collaborative work. In this article, group awareness information is represented with a visual display and consists of activity and availability information. The application of this proposed scheme is designed and implemented in a web-based group decision support system. This article reports on the results of a study that examined group performance on a given task in a web-based group decision support system with and without group awareness information. The study examined how group awareness information impacts the quality of the work effort and a given task, group decision making by members in the same group and different groups, the commun...
Real options analysis for valuing strategic investments and decisions of the Mobile Virtual Network Operator's investment in E-UMTS
2011 Ninth International Conference on ICT and Knowledge Engineering, 2012
ABSTRACT In this paper we propose a pricing model for Mobile Virtual Network Operator&#39;s i... more ABSTRACT In this paper we propose a pricing model for Mobile Virtual Network Operator&#39;s investment in Enhanced-Universal Mobile Telecommunication System (E-UMTS) networks. We conceptualize the relationship among MNO, MVNO, and other related variables in the proposed pricing model. Next, we study financial options design for MVNO&#39;s investment in Enhanced-Universal Mobile Telecommunication System (E-UMTS) networks. We also present the relationship between MNO and MVNO and investigate the total costs, total revenues, and net profit. Finally, we propose a real options analysis as a tool for valuing strategic investments and decisions of the MVNO in enhanced UMTS network market. The aim is to investigate the weighted average cost of capital (WACC) of the MVNO and net present value (NPV). The cases are examined and analyzed both qualitatively and quantitatively, using realistic assumption and parameters. The analysis of the results obtained from the model focuses on of capital expenditure (CapEx) and operational expenditure (OpEx) to provide recommendations which may be utilized and made a greater contribution in the MVNO&#39;s investment decision making process.
2010 IEEE International Conference on Systems, Man and Cybernetics, 2010
In this paper, we propose a methodology based on group decision making for weighting expert opini... more In this paper, we propose a methodology based on group decision making for weighting expert opinions or the degree of an expert's belief in identifying influential effects from parent variables to child variables in a BN model. The methodology consists of three sequential steps. The first step is a pre-processing process where the experts need to identify and select every pair of variables that have a causal relationship between them for the BN model. All the experts in the group must agree with each other for the selections. Second, we map every pair of causal variables into alternatives. Next, experts sort the alternatives by means of a fixed set of linguistic categories; each one has associated a numerical score. We apply a method of weighting individual expert opinions in order to arrange the sequence of alternatives in each step of the decision making procedure. The sequential decision procedure is repeated until it determines a final subset of experts where all of them positively contribute to the agreement for group decision making. Lastly, we transform the alternatives and the collective scores that we obtain from previous step into the BN models.
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Papers by nipat jongsawat