Boongasame, Laor

Preferred name

Boongasame, Laor

Alternative Name

Boongasame, Labor

Main Affiliation

School of Science

laor.bo@kmitl.ac.th

Now showing 1 - 10 of 10

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Fake News Detection on Social Media: Case Study of 2019 Novel Coronavirus
(2021-12-17)
Kowirat, Rutchaneewan
;
Boongasame, Laor
Fake news is news that is created with the intent to deceive and mislead readers. It is a problem that occurs in every era because it creates misunderstandings for people through a variety of media channels such as newspapers, radio, or television. Nowadays, fake news has become a big problem. When social media has become another channel to increase the spread of fake news and came to play a big role during the epidemic like COVID-19. Fake news creates panic and creates false knowledge of how to protect yourself from COVID-19. Therefore, the objective of this research is to create a method that can detect fake news on social media. It focuses only on news related to COVID-19. In addition, the information was extracted directly from social media such as Twitter. Moreover, this research applying machine learning processes to classify real and fake news. From the experimental results, the accuracy was measured at 99.92% with the Decision Tree model.
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The theory of maximal social welfare feasible coalition
(2007-01-01)
Boongasame, Laor
;
Boonjing, Veera
;
Leung, Ho Fung
This paper proposes a new theory for forming a maximumvalue-cooperation coalition known as the Maximal Social Welfare Feasible Coalition. This theory can give such solution because it does not assume that each player requesting to join a coalition knows information of other players. However, all players' private information requesting to join the coalition is known by an honest coordinator. This allows the coordinator to select a coalition structure with maximal value of cooperation among successful players so as they get at least at their required minimum values. Not only this maximal value is shown to be equal to or larger than the value of a core coalition but also the value allocation is shown to be Pareto optimal. © Springer-Verlag Berlin Heidelberg 2007.
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Combinatorial portfolio selection with the ELECTRE III method: Case study of the stock exchange of Thailand
(2017-01-01)
Boonjing, Veera
;
Boongasame, Laor
Various techniques of portfolio selection are applied to interpret the status of the market and predict the market's future trend, but they are not beneficial to small investors because these techniques should be administered by an expert. In addition, these techniques cannot help investors compare business on ambiguity multi-criteria and desire accumulation of data about the market. Therefore, portfolio selection with two significant financial ratios using the ELECTRE III method is proposed for small investors to make trading decisions. In order to demonstrate the effectiveness of this research, it is compared to the situation where a fix-percentage allocation existed and data was collected from the stock exchange of Thailand (SET). Empirical results show that portfolio selection with the ELECTRE III method offer significantly better ranking performance than the fix-percentage allocation method.
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Combinatorial portfolio selection with the ELECTRE III method: Case study of the Stock Exchange of Thailand (SET)
(2016-11-03)
Boonjing, Veera
;
Boongasame, Laor
Various techniques of portfolio selection are applied to interpret the status of the market and predict the market's future trend, but they are not beneficial to small investors because these techniques should be administered by an expert. In addition, these techniques desire accumulation of data about the market and complicated calculations, which is too much effort for individual small investors. Therefore, portfolio selection with two significant financial ratios using the ELECTRE III method is proposed for these investors to make trading decisions. In order to demonstrate the effectiveness of this new method, it is compared to the situation where a fix percentage allocation existed and data was collected from the Stock Exchange of Thailand (SET).
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Clustering Mutual Funds by Net Asset Value Change Ratios
(2020-12-29)
Boongasame, Laor
;
Narabin, Akan
The traditional factors of the clustering mutual fund (such as Net Asset Value (NAV)) are not always an efficient measure in both maximizing returns and minimizing portfolio risk. This research presents a novel measure, Net Asset Value Change Ratios for some of time durations N (NAVCR-N), to assist the mutual fund clustering. We proved the usage of the NAVCR-N as mutual fund LTF similarity measures and LTF are then selected from differing clusters to create a diversified mutual fund portfolio. Approximately a hundred mutual fund data different times from the set for the fiscal year 2010-2018 are applied in the experiment to evaluate the effectiveness of the random approach and our diverse approaches.
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A new approach to Multi-criteria Decision Making (MCDM) using the fuzzy binary relation of the ELECTRE III method and the principles of the AHP method
(2010-03-31)
Boongasame, Laor
;
Boonjing, Veera
There are several methods for Multi Criteria Decision Making (MCDM) such as multiple attribute utility theory (MAUT), the analytical hierarchy process (AHP), and Fuzzy AHP. However, these methods are compensatory optimization approaches for which bad score on some criteria can be compensated by excellent scores on other criteria. So, the Elimination and Choice Translating Reality III (ELECTRE III) was proposed to solve such problem. Nevertheless, thresholds determined by identified experts and used in this method may be inconsistent. Therefore, this paper proposes an integrated approach which employs ELECTRE III and partial concepts of AHP together, called the Consistency ELECTRE III. In this method, ELECTRE III is used in ranks the alternatives and AHP is used in determining the consistency of the criteria thresholds within ELECTRE III. In the simulation, it is found that threshold values of criteria within ELECTRE III affect the ranking of the alternatives. Specially, the ranking of the Consistency ELECTRE III and that of the ELECTRE III are different. © 2010 Springer-Verlag Berlin Heidelberg.
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Classification of Thai Rice Varieties Using Image Processing and Deep Learning Techniques
(2025-01-01)
Kongmanee, Panpatsorn
;
Puengpradith, Sorapojana
;
Boongasame, Laor
The methods for identifying Thai rice varieties are complex, time-consuming, and require high expertise to achieve accurate results. This research explores different deep learning techniques to efficiently classify the strains of Thai rice that optimize accuracy and speed. The focus rice varieties are Khao Hom-Mali Thai and Thai Hom Pathum Thani 1 fragrant rice; both have similar shapes and characteristics but differ in price, market value, and recognition. The proposed model is based on an instance segmentation model of YOLOv8, which is compared against popular instance segmentation models such as YOLACT, SOLOv2, and Mask R-CNN. Additionally, hyperparameter tuning is performed to ascertain the most optimal values. The evaluation of the model performance reports in the form of mean average precision (mAP), inference time, and model stability. Experimental results indicate that YOLOv8n-seg, with the fewest parameters, achieves the highest accuracy comparable to other YOLOv8-based models with more parameters. The proposed model demonstrates superior accuracy and processing speed performance compared to other state-of-the-art models.
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Combining Group Compromised Price with bundle search strategies
(2005-12-01)
Boongasame, Labor
;
Boonjing, Veera
;
Thipakorn, Bundit
This paper proposes combining the buyer coalition strategy, called Group Compromised Price, with bundle search strategy to obtain the greater discounts from forming a coalition that gives the number of buyers as large as possible. Copyright 2005 ACM.
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Forming buyer coalitions with bundles of items
(2009-09-10)
Boongasame, Laor
;
Leung, Ho Fung
;
Boonjing, Veera
;
Chiu, Dickson K.W.
There are several existing buyer coalition schemes, but they do not consider bundles of items. This research presents an algorithm for forming a buyer coalition with bundles of items, called the GroupBuyPackage scheme, in order to maximize the total discount. Our simulation results show that the total discount of the coalitions in this scheme are close to that in the optimal scheme. © 2009 Springer Berlin Heidelberg.
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A Cluster Analysis of Mutual Funds Data
(2018-11-26)
Narabin, Santit
;
Boongasame, Laor
The factors of clustering mutual fund (such as Net Asset Value (NAV)) do not direct to both return and risk of mutual funds which they are important factors for investors. This research helps an investor can estimate profit and loss rate of the mutual fund in his/her portfolio by using the net asset value change ratios (NAVCR). Then, both the NAVCR and value of each mutual fund will be used for clustering. For building a portfolio, the mutual funds could be selected from the diversified groups in order to reduce risk. The mutual fund data at different times from the set for the fiscal year 2010 - 2017 are used. The results of our analysis show that our models offer significantly better performance than the portfolio management model derived from the random portfolio management.
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Boongasame, Laor

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