Papers by Sageemas Na Wichian
This purpose of this research were 1) to find achievement of new researcher and 2) to find satisf... more This purpose of this research were 1) to find achievement of new researcher and 2) to find satisfaction of new researcher who trained by the Blending Training Program Integration with Knowledge Management System for New Researcher in Research Proposal Performing. The simple random sampling samples were 30 new researchers who interested to write research proposal and had not experience for research proposal performing. The Blending Training Program Integration with Knowledge Management System efficiency equal to 82.03/80.67 which was divide to two parts that the first part was used in e-Learning were coaching, collaboration learning, and knowledge management system and that the second part was used The techniques used in Face-to-Face Learning. The after process of training , the new researchers were evaluated by posttest and trainee’s satisfaction questionnaire. The statistics implemented were mean and standard deviation. The finding of research : 1) the achievement of new researcher...
บทคัดย่อในอดีต อันตรกิริยาระหว่างอาหารกับบรรจุภัณฑ์นั้นไม่ได้รับการยอมรับเนื่องจากมีความเชื่อว่าท... more บทคัดย่อในอดีต อันตรกิริยาระหว่างอาหารกับบรรจุภัณฑ์นั้นไม่ได้รับการยอมรับเนื่องจากมีความเชื่อว่าทำให้เกิดการเปลี่ยนแปลงคุณภาพของอาหาร แต่ในปัจจุบัน หลายงานวิจัยได้พิสูจน์แล้วว่าการเกิดอันตรกิริยาบางอย่างระหว่างอาหารและบรรจุภัณฑ์นั้นไม่ส่งผลเสียต่อคุณภาพของอาหาร อีกทั้งยังสามารถชะลอการเสื่อมเสียของอาหารได้ ดังนั้นเทคโนโลยีบรรจุภัณฑ์ต้านจุลินทรีย์จึงเป็นหนึ่งในแนวคิดที่เหนี่ยวนำให้เกิดอันตรกิริยาระหว่างอาหารและบรรจุภัณฑ์ในขณะที่รักษาคุณภาพทางโภชนาการ คุณสมบัติรวมทั้งความปลอดภัยของอาหารไว้ไม่เปลี่ยนไป โดยสารเติมแต่งที่นิยมใช้เพื่อเป็นสารต้านจุลินทรีย์เป็นสารกลุ่มน้ำมันหอมระเหยซึ่งได้จากการสกัดสารสำคัญทางธรรมชาติจากพืช โดยสารเหล่านี้สามารถออกฤทธิ์ในการยับยั้งการเจริญเติบโตของจุลินทรีย์ทั้งในกลุ่ม เชื้อรา ยีสต์และแบคทีเรีย ซึ่งทำให้อาหารเสื่อมเสียและสามารถก่อโรคได้ ส่วนพลาสติกชีวภาพนั้นเป็นวัสดุที่มีแนวโน้มจะนำมาใช้เพื่อทดแทนพลาสติกจากปิโตรเลียมในอนาคต ในเชิงพาณิชย์นั้นได้มีการนำเอาพลาสติกชีวภาพมาใช้เป็นบรรจุภัณฑ์อาหารเนื่องจากมีสมบัติทางกลที่ดีพร้อมทั้งยังสามารถย่อยสลายได้ทางชีวภาพอีกด้...
The purpose of this study was to analyze the concept of empowerment in teachers’ work according t... more The purpose of this study was to analyze the concept of empowerment in teachers’ work according to the perception of teachers, by using Q-methodology. Twenty-six participants were teachers under jurisdiction the office of vocational education commission, who sorted 46 selected Q-statements on a nine-point scale. The results identified eight types of perspectives of empowerment in teachers’ work which consisted of empowering oneself and other people, understanding of the work environment, careful work, determination to work, working alone and working with other people, work empowering according to each person’s difference, direct and indirect effects on work and working under the management. Also, the findings may provide the basis for the development to empower in working of teachers in order to enhance the educational quality in the future.
This Gene expression data illustrates levels of genes that DNA encodes into the protein such as m... more This Gene expression data illustrates levels of genes that DNA encodes into the protein such as mus-cle or brain cells. However, some abnormal cells may evolve from unnatural expression levels. Therefore, finding a subset of informative gene would be ben-eficial to biologists because it can identify discrimi-native genes. Unfortunately, genes grow up rapidly into the tens of thousands gene which make it diffi-cult for classifying processes such as curse of dimen-sionality and misclassification problems. This paper proposed classification model based-on incremental learning algorithm and feature selection on gene ex-pression data. Three feature selection methods: Cor-relation based Feature Selection (Cfs), Gain Ratio (GR), and Information Gain (Info) combined with In-cremental Learning Algorithm based-on Mahalanobis Distance (ILM). Result of the experiment represented proposed models CfsILM, GRILM and InfoILM not only to reduce many dimensions from 2001, 7130 and 4026 into 26, 135, a...
The 8th Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology (ECTI) Association of Thailand - Conference 2011, 2011
This Gene expression data illustrates levels of genes that DNA encodes into the protein such as m... more This Gene expression data illustrates levels of genes that DNA encodes into the protein such as muscle or brain cells. However, some abnormal cells may evolve from unnatural expression levels. Therefore, finding a subset of informative gene would be beneficial to biologists because it can identify discriminative genes. Unfortunately, genes grow up rapidly into the tens of thousands gene which make it difficult for classifying processes such as curse of dimensionality and misclassification problems. This paper proposed classification model based-on incremental learning algorithm and feature selection on gene expression data. Three feature selection methods: Correlation based Feature Selection (Cfs), Gain Ratio (GR), and Information Gain (Info) combined with Incremental Learning Algorithm based-on Mahalanobis Distance (ILM). Result of the experiment represented proposed models CfsILM, GRILM and InfoILM not only to reduce many dimensions from 2001, 7130 and 4026 into 26, 135, and 135 that save time-resource but also to improve accuracy rate 64.52%, 34.29%, and 8.33% into 90%, 97.14%, and 83.33% respectively. Particularly, CfsILM is more outstanding than other models on three public gene expression datasets.
2010 Eighth International Conference on ICT and Knowledge Engineering, 2010
ABSTRACT Microarray data contains thousands of genes which are used to evaluate expression level.... more ABSTRACT Microarray data contains thousands of genes which are used to evaluate expression level. However, most of them are not associated with cancer diseases and leads to the curse of dimensionality. The challenge based on microarray data is feature selection which searches for subsets of informative genes. At the moment, these techniques focus on filter and wrapper approaches to discover subsets of genes. Filter approach is better than wrapper approach in terms of time consuming. On the contrary, the accuracy of wrapper approach is higher than that of filter approach. However, it is more beneficial to reduce the time process and increase accuracy simultaneously when searching for subsets of genes. Thus, this paper proposes comparison of hybrid feature selection models on gene expression datasets, this consists of four steps 1) filter subgroup of gene using Correlation based Feature Selection (CFS), Gain Ratio (GR), and Information Gain (INFO) 2) transfers output of each filter method into a wrapper approach that's based on the Support Vector Machine (SVM) classifier and two heuristic searches which are Greedy Search (GS) and Genetic Algorithm (GA) 3) generate hybrid feature selection model CFSSVMGA, CSFSVMGS, GRSVMGA, GRSVMGS, INFOSVMGA, and INFOSVMGS 4) performance comparison using precision, recall, F-measure, and accuracy rate. Results from the experiment concluded the CFSSVMGA model outperformed other models on three public gene expression datasets.
Applied Mechanics and Materials, 2011
Finding subset of informative gene is very crucial for biology process because several genes incr... more Finding subset of informative gene is very crucial for biology process because several genes increase sharply and most of them are not related with others. In general, feature selection technique consists of two steps 1) all genes is ranked by a filter approach 2) rank list is sent to a wrapper approach. Nevertheless, the accuracy rate for recognition gene is not enough. Therefore, this paper proposes efficient feature selection model for gene expression data. First, two filter approaches are used to define many subset of attribute such as Correlation based Feature Selection (Cfs) and Gain Ratio (GR). Second, wrapper approach is used to evaluate each length of attribute that based on Support Vector Machine (SVM) and Random Forest (RF). The result of experiment depicts CfsSVM, CfsRF, GRSVM, and GRRF based on proposed model produce higher accuracy rate such as 87.10%, 90.32%, 87.10, and 88.71%, respectively.
The purposes of this research were 1) to study researcherûs characteristics, researchership, rese... more The purposes of this research were 1) to study researcherûs characteristics, researchership, research competence and institutional support for research work as factors affecting research productivity, 2) to test for invariance of research productivity models across groups with size difference in Pedagogy Department, and 3) to compare the results of factors affecting research productivity using LISREL and Neural Network analyses. The sample consisted of 300 faculty members from 16 government universities. The research instruments were rating scales measuring research productivity, researchership, research competence and institutional supports for research work. The reliabilities of the instrument ranged from .76-.96. Data were analyzed through descriptive statistics, LISREL, and Neural Network Analyses. The major findings were: 1) The average of each faculty memberûs research productivity was 0.40 research pieces per year; 2) Researchership and research competence were high in average, and institutional support for research work was moderate; 3) Research productivity model fitted well to empirical data (Chi-square=80.007, p=0.132 df=67, GFI=0.963, AGFI=0.942, RMR=0.161). The test of model invariance across 2 groups of departments with different size indicated that the two models were invariant in form, but varied in loading and other parameters. The causal relationship using LISREL and Neural Network analyses suggested consistently that researcher characteristic, research competence, institutional support for research work and researchership had direct effects on research productivity; 4) The comparison of analyses with LISREL and Neural Network indicated similar results.
Abstract: In fact, cancer is produced for genetic reasons. So, gene feature selection techniques ... more Abstract: In fact, cancer is produced for genetic reasons. So, gene feature selection techniques are very important for biological processes which help to find subsets of informative genes. However, the quality of recognition is still not sufficient and leads to low accuracy rates. Hence, this research proposes integrating a feature selection method (IFS). There two phases of IFS: 1) determining feature length by Gain Ratio (GR) and 2) estimating each rank list using a wrapper approach based on K-nearest neighbor classification (KNN), Support Vector Machine (SVM), and Random Forest (RF). Experimental results based on two gene expression datasets, it is found that the proposed method not only has higher accuracy rate than tradition methods, but also reduce many irrelevant features. In addition, most models based on IFS method are more beneficial when working with two or multi-classes. 1
The purposes of this research are to develop and validate the causal model of factors influencing... more The purposes of this research are to develop and validate the causal model of factors influencing the responses to sexual harassment in the workplace of female universities personnel. The sample of this research was a proportional stratified random sampling of 587 female universities personnel members from all regions of Thailand. The data was วารสารศรีนครินทรวิโรฒวิจัยและพัฒนา (สาขามนุษยศาสตร์และสังคมศาสตร์) ปีท่ี 7 ฉบับท่ี 13 มกราคม มิถุนายน 2558 142 collected by questionnaires with the reliability ranging from 0.92 to 0.96. Hypothesis testing regarding the causal model of factors influencing the responses to sexual harassment in the workplace, were analyzed by computer programs. The research findings revealed that the casual model of factors influencing the response to sexual harassment in the workplace of the female university personnel fitted the empirical data. The Model indicated that the chi-square/df = 1.26, P-Value = 0.12, RMSEA = 0.020, GFI = 0.99, AGFI = 0.96 and CN = 73...
This study aims to: 1) study employment data, capacity, problems and obstacles to work of elderly... more This study aims to: 1) study employment data, capacity, problems and obstacles to work of elderly workers; and 2) analyze roles of elderly workers when they were out of the employment system. This qualitative research studied employees workingin furniture manufacturing in the following groups : 1) wood manufacturing; 2) plywoodmanufacturing; 3) plywood and veneer board manufacturing; 4) plywood piece manufacturing; 5) wood base fiber; and 6) furniture and household furnishings. The research was divided into four steps: 1) primary data survey; 2) study on employment from executives; 3) study on employment status from elderly workers; and 4) analysis to provide recommendations.Interview sessions were conducted with 29 people (23 workers and six executives). It was found that employment status was in accordance with agreements between employees and companies that did not have retirement policies. Work skills and physical fitness of employees were emphasized. Most executives stated that...
ECTI Transactions on Computer and Information Technology (ECTI-CIT), 1970
This Gene expression data illustrates levels of genes that DNA encodes into the protein such as m... more This Gene expression data illustrates levels of genes that DNA encodes into the protein such as muscle or brain cells. However, some abnormal cells may evolve from unnatural expression levels. Therefore, finding a subset of informative gene would be beneficial to biologists because it can identify discriminative genes. Unfortunately, genes grow up rapidly into the tens of thousands gene which make it difficult for classifying processes such as curse of dimensionality and misclassification problems. This paper proposed classification model based-on incremental learning algorithm and feature selection on gene expression data. Three feature selection methods: Correlation based Feature Selection (Cfs), Gain Ratio (GR), and Information Gain (Info) combined with Incremental Learning Algorithm based-on Mahalanobis Distance (ILM). Result of the experiment represented proposed models CfsILM, GRILM and InfoILM not only to reduce many dimensions from 2001, 7130 and 4026 into 26, 135, and 135 that save time-resource but also to improve accuracy rate 64.52%, 34.29%, and 8.33% into 90%, 97.14%, and 83.33% respectively. Particularly, CfsILM is more outstanding than other models on three public gene expression datasets.
The International Journal of Learning: Annual Review, 2010
International Journal of Economic Policy in Emerging Economies, 2017
Polish Journal of Management Studies, 2016
Advanced Materials Research, Feb 9, 2012
ABSTRACT Education Surveillance System is designed for predicting the state of education based on... more ABSTRACT Education Surveillance System is designed for predicting the state of education based on form of alarm signal using Incremental Leaning based on Mahalanobis Distance (ILM). However, ILM need to define two crucial parameters (co-variance matrix and distance threshold) it is not only very difficult for determining by general user but also depend on dataset property. This research proposed GAILM algorithm based on Ordinary National Education Test (Bangkok) dataset for finding approximate parameter and predicting. The result of experiment is represent GAILM technique discovering proximate co-variance matrix (0.91) and distance threshold parameter (0.44) and also high accuracy rate as 90.91% and 92.07%, in the year 2007 to 2008 respectively. This result was higher than the accuracy rate of traditional technique by K-Means algorithm and Cobweb.
Asian Journal of Education and E Learning, Apr 11, 2013
International Journal of Information and Education Technology, 2016
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Papers by Sageemas Na Wichian