Leerojanaprapa, Kanogkan

Preferred name

Alternative Name

Leerojanaprapa, K.

Main Affiliation

School of Science

kanogkan.le@kmitl.ac.th

Now showing 1 - 10 of 24

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Applying Bayesian network for noncommunicable diseases risk analysis: Implementing national health examination survey in Thailand
(2017-07-02)
Leerojanaprapa, K.
;
Atthirawong, W.
;
Aekplakorn, W.
;
Sirikasemsuk, K.
We propose using a Bayesian network to capture and understand the dependency risk factors affecting the prevalence of chronic diseases. By applying a Bayesian network model, we can visualize interdependencies between risks and their effects on the Noncommunicable disease (NCD) prevalence. By using a Bayesian network to model the prevalence of diabetes, we can define the top three risks as family history of diabetes, obesity, and age. Furthermore, the risk classification results can help to determine the managing strategy. For the Thai population, problems arising from family history of diabetes and obesity can be met by employing a transfer strategy. Age (especially ages of 35-59) and the risk incurred by low intake of fruits and vegetables should use a reduction or mitigation strategy. Finally, those at risk as a result of their area of residence (in urban areas) and socio-economic factors within the 4<sup>th</sup> quantile and low level of physical activity should apply a retain strategy.
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Using DEMATEL to explore the relationship of factors affecting consumers' behaviors in buying green products
(2018-01-01)
Atthirawong, Walailak
;
Panprung, Wariya
;
Leerojanaprapa, Kanogkan
The main purpose of this paper is to analyze factors influencing consumers' behaviors in buying green products by applying Decision-making Trial and Evaluation Laboratory (DEMATEL) method. Nine criteria i.e. perception on environmental concerns (A), safety and health concerns (B), green packaging (C), convenience to buy (D), environmental attitude (E), subjective norms (F), green product management (G), environmental laws (H) and perceived value (I) were employed from the previous study by Atthirawong and Panprung (2017). In this study, six experts were involved in order to determine the degree of direct influence between two factors through a pairwise comparison. The results revealed that the top three important criteria affecting consumers in buying green products are environmental attitude (E), safety and health concerns (B) and green product management (G), respectively. Furthermore, a cause and effect relation diagram was also constructed to gain a better understanding of the interactive relationship between those criteria. It was found that subjective norm (F) has the most influence on other factors, whereas perception on environmental concerns (A) gets the most impact from other factors. Finally, this paper provides some practical suggestions for relevant agencies and policy makers based on the analysis.
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Navigating online learning challenges and educational infrastructure in times of crisis: Insights and solutions among Thai engineering students utilizing a mixed-methods analysis
(2024-01-01)
Sirikasemsuk, Kittiwat
;
Leerojanaprapa, Kanogkan
;
Khwanpruk, Kankanit
The rapid shift to online learning during COVID-19 posed challenges for students. This investigation explored these hurdles and suggested effective solutions using mixed methods. By combining a literature review, interviews, surveys, and the analytic hierarchy process (AHP), the study identified five key challenges: lack of practical experience, disruptions in learning environments, condensed assessments, technology and financial constraints, and health and mental well-being concerns. Notably, it found differences in priorities among students across academic years. Freshmen struggled with the absence of hands-on courses, sophomores with workload demands, and upperclassmen with mental health challenges. The research also discussed preferred strategies for resolution, emphasizing independent learning methods, managing distractions, and adjusting assessments. By providing tailored insights, this study aimed to enhance online learning. Governments and universities should support practical work, prioritize student well-being, improve digital infrastructure, adapt assessments, foster innovation, and ensure resilience.
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Relationships between Labour Demand and Resource Factors for Textile and Garment Industry in Thailand
(2017-07-19)
Leerojanaprapa, Kanogkan
;
Bhundarak, Komn
This article aims to forecast and compare labor demand in textile industry represented by fiber manufacturing companies (ISIC CODE 13111) and in garment industry represented by the manufacturer of work wear (ISIC CODE 14111) in Thailand. Secondary data were acquired from the Department of Industrial Works where registered companies submitted their essential data and obtained the approval permit in doing business during 2015. Complete data from 494 textile companies and 656 garment companies are implemented in Multiple Regression Analysis. This research defined eight independent variables: Land capital (X1), Buildings capital (X2), Machinery capital (X3), Working capital (X4), Factory area (X5), Building area (X6), Horsepower (X7), and Type of manufacturer (X8). The results from the study revealed that 63.09% of labor demand variation for textile manufacturers can be explained by Y = 28.6246 + 0.0180X7 0.0004 X5 + 0.0081X6 + 0.0004X4 0.0002X3 while 51.50% of the labor demand variation for garment manufacturers can be explained by Y = 116.86 + 0.006X2+ 0.004X5 109.748X8 + 0.008X6 + 0.040X7 + 0.001X4.
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Optimal production volume of rubber gloves mold for rubber gloves production planning
(2016-01-01)
Somboonwiwat, Tuanjai
;
Jaturanonda, Chorkaew
;
Chotpan, Nattapong
;
Leerojanaprapa, Kanogkan
The production process of rubber glove is the continuous production line which the hand-shaped ceramic molds are installed and dipped into the concentrated latex to form the rubber gloves. Since, the rubber gloves are diverse in terms of size, surfaces and types of latex, the multiple molds and latex are changed and used in a production process in order to produce rubber gloves from customer requirement. Thus, the changing of mold is extremely complex for production ratio which the rubber glove production planning will be employed to meet anticipate customer orders. This research therefore develops the mathematical model to find the optimal quantity of molds and rubber gloves production planning. Finally, the developed model is applied to an example data set to find the minimum total volume of rubber gloves in every mold for keeping the minimal volume of inventory.
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Regression sum of squares of randomized complete block design with one unrecorded observation
(2018-09-26)
Sirikasemsuk, Kittiwat
;
Leerojanaprapa, Kanogkan
;
Sirikasemsuk, Sirisak
In the classical design of experiment, a randomized complete block design (RCBD) is a helpful experimental design because this design uses a small number of experimental units. The randomized complete block design is comprised of two factors, i.e., one nuisance factor and one potential factor. In many real experiments, some data may be missing or unrecorded. The instant formulae were not provided for an analysis of variance in this case. This paper took into account the RCBD with a treatments and b blocks. In this contribution, the RCBD with an unrecorded value was analyzed by means of the exact scheme with the general linear model. Due to no ready-made formula in the past, this research paper provided the mathematical formulae for the fitted parameters and the overall regression sum of squares (ORSS) for the full model of experimental data.
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Inventory Management for Consumer Products: A Distribution Center in Thailand
(2022-01-01)
Leerojanaprapa, Kanogkan
;
Bhundarak, Komn
;
Atthirawong, Walailak
;
Sirikasemsuk, Kittiwat
The objective of the study is to formulate an appropriate order quantity policy. A best-selling product, a cleaner fresher mouth, was selected to be a representative of this study. Monthly Sales data of the cleaner fresher product was collected from January 2013 to December 2021, for 9 years, to forecast the sales of each product. Two forecasting techniques i.e. Exponential Smoothing and Box-Jenkins methods were compared to select the appropriate forecasting method by using MSE criterion. It was found that the Triple Exponential Method was the suitable forecasting model to forecast demand for the cleaner fresher products. These forecast values were then applied in inventory planning to determine the order policy by using Economic Order Quantity (EOQ) method of inventory management. The results found that EOQ technique resulted in a reduction in total cost rather than the company's current technique by 27.80%•
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Work posture risk comparison of RULA and REBA based on measures of assessment-score variability: A case study of the metal coating industry in Thailand
(2024-01-01)
Sirikasemsuk, Kittiwat
;
Kittipanya-Ngam, Pichawadee
;
Luanwiset, Darin
;
Leerojanaprapa, Kanogkan
This study examines the work posture risk comparison of RULA and REBA based on measures of assessment-score variability. During the metal coating process, chemicals were frequently employed, necessitating a heightened level of caution among the employees. The Cornell Musculoskeletal Discomfort Questionnaires (CMDQ) revealed the manifestation of physical discomfort among employees. In this study, the rapid upper limb assessment (RULA) and the rapid entire body assessment (REBA) were used to identify ergonomic concerns related to the work of employees in the black oxide coating department of a metal coating firm. The sensitivity of risk assessment between the two methods was investigated, considering the mean and variability of the assessment scores. Consideration was given to the diverse and crucial work positions of employees at each station, focusing exclusively on the standing working posture. In the black oxide coating section, there were 12 steps that 20 workers had to complete. Under the same wo rking postures, the overall average RULA score was determined to be at a high-risk level, whereas the overall average REBA score was at a moderate-risk level. As a result, the RULA method had a greater capacity for risk warning than the REBA method. Levene's test was also applied to determine whether the variances of the risk scores computed using the two techniques were equal. The results of the analysis showed that the variances in the scores using the two methods were not significantly different.
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Modeling supply risk using belief networks: A process with application to the distribution of medicine
(2014-11-18)
Leerojanaprapa, K.
;
Van Der Meer, R.
;
Walls, L.
We propose a modeling approach based on belief networks to capture and understand the systemic nature of risks affecting supply networks. By aligning the purpose of a model with the nature of supply management decisions, we provide a mechanism for identifying relevant supply risks so that we can visualize inter-dependencies between risks and predict their effects on supply performance. By using a belief network modeling formalism we can use diagnostics to understand the key drivers of unwanted risk scenarios and to explore the efficacy of possible risk mitigating actions. We illustrate how belief network modeling can be used to manage the risk/reward position and provide new insights into supply risks through an example for the medicine supply chain of a regional health service provider.
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Regression sum of squares of symmetric balanced incomplete block design consisting of another one missing observation by accident
(2017-07-02)
Sirikasemsuk, Kittiwat
;
Leerojanaprapa, Kanogkan
A balanced incomplete block design (BIBD) is the effective way to help analyze a treatment variable and one block variable under the condition where experimental units are limited. This paper considered the symmetric balanced incomplete block design (SBIBD) with t treatments and t blocks of size t-1. The trouble of analysis is caused if another one missing value unintentionally occurs in the experiments. The SBIBD with another one missing value was analyzed by means of the exact approach, i.e., the general regression significance testing procedure. There was no ready-made formula in the past. Hence, the paper provided the mathematical formulae for the fitted parameters and the regression sum of squares for the full effect model of experimental data.
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Leerojanaprapa, Kanogkan

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