Kreesuradej, Worapoj

Preferred name

Alternative Name

Kreesuradej, W.

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School of Information Technology

worapoj.kr@kmitl.ac.th

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A Technique for Estimating Updated Frequent Itemsets in ESC-Growth Algorithm
(2019-07-01)
Kreesuradej, Worapoj
;
Thurachon, Wannasiri
In discovering association rules from a dynamic database, iteration through the frequent itemsets requires significant resources and computational time for construction of sub-trees, sub-tree traversal and generation of conditional pattern bases, and it is quite possible that no updated frequent itemsets may have been found at all, resulting in a waste of resources and computational time. We describe a technique for estimating the support count for the itemsets for the next iteration of discovery of the frequent itemsets by our ESC-Growth Algorithm. This technique reduces the need to construct a new sub-tree and next discovery step. If no frequent itemsets in the updated database have been found in the next iteration, ESC-Growth will not construct a new sub-tree and will stop discovering new frequent itemsets in that iteration, reducing the waste of resources and computational time. We measured execution time and sub-tree counts for FP-Growth, FUFP-tree, FPISC-Growth and ESCGrowth on the same synthetic dataset; we found that, at 5% minimum support threshold, ESC-Growth used only 40.3, 96.5, and 99.6% of the execution time required by FP-Growth, FUFPtree and FPISC-Growth, respectively.
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Fast adaptive fuzzy autoregressive model
(1999-12-01)
Kreesuradej, Worapoj
;
Bunyarodol, Decha
In this paper, a fuzzy autoregressive model with a multiple criteria adaptive algorithm is proposed. The proposed algorithm consists of two independent criteria for adjusting the fuzzy rules and some related parameters. First, the proposed algorithm adapts the existent fuzzy rules by gradient descent method based on predicting error criteria. In addition to rule adaptation, the learning rate of each rule adaptation can also be adjusted based on matching of rule confidence of each fuzzy rule. With the combination of the two independent criteria for adaptation, the proposed algorithm can increase the speed of learning.
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Input selection using binary particle swarm optimization
(2006-01-01)
Amonchanchaigul, Thavit
;
Kreesuradej, Worapoj
Nowadays, multi-layer feed forward networks are often used for modeling complex relationships between the data sets. And if we can choose only the important data from the training sets, it will make the networks less size and can save more time. Because we realize in this point, this paper provides procedure of feature selection to train the neural networks using binary particle swarm optimization. It also introduces the suitable function for the binary particle swarm optimization technique by changing concept in part of member value adjustment function for each particle. © 2006 IEEE.
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Webcam based eye gaze prediction system with automatic calibration for web browser
(2019-07-01)
Karngumpol, Niphat
;
Kreesuradej, Worapoj
Now a day, researches about Eye Gaze Prediction Systems with General Webcam was interested by many researchers and has been continuously developed because it is cheap and can be applied in many ways. Currently, a Browser based open source library for eye gaze prediction has been developed, which is easy to use and can be developed in a variety fields. However, this method is still limited because of low precision and inconveniences because users must perform calibration every time before use it. Therefore, we propose ways to develop and solve the above problems. This research has two objectives. The first is to improve the accuracy of an existing Eye Gaze Prediction System. The solution is using the Simple Moving Average to reduce the volatile of results and increase accuracy. From a results, this method gives a test scores higher than the existing method with statistically significant at 0.01, calculated as 14.96 percent increase from average score of the old method. The second objective is to propose a solution for making the system can recalibrate itself to improve accuracy in a long time without having to perform calibration by the users. We record the gaze data from system in the first 1 minute and then take the recorded data to calculate the boundary of the screen. And then, compare the calculated boundary with the real screen boundary to find error factors. This calculated error factor has been applied back to the next result to increase accuracy. From the test results, we found that over time the average test scores gradually increase. And at the last minute, the average score from this method is higher than the average score from traditional method up to 13.66 percent.
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Prosody analysis of Thai emotion utterances
(2011-07-01)
Yimngam, Sukanya
;
Premchaisawadi, Wichian
;
Kreesuradej, Worapoj
Emotion speech synthesis is the most important process to generate the naturalness of utterances in text-to-speech system. The interjection utterances in Thai language are employed in express a number of emotions. This paper presents a study of the prosody parameters of the interjection utterances clipped from Thai utterances in the movies. The Thai emotional utterances from various movies have been analyzed and classified into 8 emotional types consisting of neutral, anger, happiness, sadness, fear, pleasant, unpleasant and surprise. The classification of prosodic features is based on fundamental frequency (F0), intensity and duration. This paper compares the prosodic features in the Thai language and other languages including English, Italian, French, Spanish and Arabic. The comparison results show that there are significant differences of prosodic features for each emotion in each language. Therefore, the quality of a text-to-speech system is based on the prosodic analysis of each language. © 2011 Springer-Verlag.
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The acceptance model of M-payment using smartphone devices in Thailand: A conceptual framework
(2018-01-01)
Nakwari, Parisgawin
;
Kreesuradej, Worapoj
;
Chaveesuk, Singha
In this paper, we have proposed the M-payment method using the smartphone applications, from which all electronic transactions such as purchasing, sales and the provision of other financial services can be applied. This is the investigation of the UTAUT2 extended theory that can be more appropriate for the consumers. The UTAUT2 extended theory is integrated with the service quality, which can be used to examine the acceptance potential of the M-Payment user by smartphone devices. The outcomes of this study will benefit the financial industry in their effort to initiate an extensive online-payment process in all users, especially, in Thailand.
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State of the art review on thai text-to-speech system
(2008-12-26)
Yimngam, Sukanya
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Premchaisawadi, Wichian
;
Kreesuradej, Worapoj
Text-to-speech system is a system that converts the input text into speech sound. In Thai language, Thai text-to-speech system was developed in many years. There are many problems with Thai text to speech transformations such as Thai language is a Tonal language that differentiates from others languages. There are 4 main components in Thai text-to-speech synthesis system and several problems in each component. In text analysis, Thai is a language which has no punctuation marks to separate word boundaries and word ambiguity. In letter-to-sound, Thai has several sounds within one word called Homographs. In prosody generation, Thai has five tones which generate many different sounds. Finally, in speech synthesis, naturalness of speech has improved significantly. This paper presents the problems and development of recent researches in Thai text-to-speech system such as Characteristics of the Thai Tonal language, Corpus, Issues in Thai text-to-speech, Recent Thai text-tospeech applications, Future work and Conclusions. © 2008 IEEE.
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A new association rule-based text classifier algorithm
(2005-01-01)
Buddeewong, Supaporn
;
Kreesuradej, Worapoj
This paper proposes a new association rule-based text classifier algorithm to improve the prediction accuracy of Association Rule-based Classifier By Categories (ARC-BC) algorithm. Unlike the previous algorithms, the proposed association rule generation algorithm constructs two types of frequent itemsets. The first frequent itemsets, i.e. L<inf>k</inf>, contain all term that have no an overlap with other categories. The second frequent itemsets, i.e. OL <inf>k</inf>, contain all features that have an overlap with other categories. In addition, this paper also proposes a new join operation for the second frequent itemsets. The experimental results are shown a good performance of the proposed classifier © 2005 IEEE.
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Discovery of incremental association rules based on a new FP-growth algorithm
(2019-02-01)
Kreesuradej, Worapoj
;
Thurachon, Wannasiri
In this paper, we propose a new FP-Growth algorithm for incremental association rule discovery. We also design a new FPISC-tree based on the FUFP-tree structure. The new FPISC-tree is more suitable for the task of incremental association rule discovery than FUFP-tree structure. The basic ideas of the proposed algorithm are to retrieve the frequent itemsets from the original database and to use their support count in the update of the new support count of the incremental database so that the original paths do not need to be reprocessed as well as to strategically use them to discover frequent itemsets from the FPISC-tree. Experimental results show that the proposed algorithm was able to reduce the number of constructed subtrees and the execution time was significantly less than those of the FP-Growth and FUFP-tree.
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Text processing simplified ARTMAP neural network
(2005-02-01)
Kreesuradej, Worapoj
;
Kunasit, Puangpaka
This paper proposes text processing simplified ARTMAP neural network. The algorithm works directly on textual information without transforming to numerical value. The input layer of the neural network can directly receive a qualitative value without mapping the qualitative value into numerical value. Then, based on simplified fuzzy ARTMAP neural network and the concept of similarity measure for symbolic objects, the proposed neural network can assigns class labels to the objects correctly.

Kreesuradej, Worapoj

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