Kimpan, Warangkhana

Preferred name

Kimpan, Warangkhana

Alternative Name

Kimpan, W.

Main Affiliation

School of Science

warangkhana.ki@kmitl.ac.th

Now showing 1 - 10 of 10

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Heuristic Task Scheduling with Artificial Bee Colony Algorithm for Virtual Machines
(2016-12-28)
Kimpan, Warangkhana
;
Kruekaew, Boonhatai
Cloud computing is one of the Information Technology services which are provided from IT infrastructures to application services. It is the combination of Distributed computing and virtualization technology using virtual machines, an essential component in Cloud computing. Therefore, task scheduling is an important matter to consider for virtual machines to balance load of each machine and to efficiently use the resources in Cloud computing. This paper proposes the use of Heuristic task scheduling with Artificial Bee Colony algorithm for virtual machines in heterogeneous Cloud computing, called HABC. The research aim is to introduce HABC, which is a new task scheduling and load balancing algorithm, for virtual machines in heterogeneous environments to reduce the makespan in the system. In the experiments, CloudSim was simulated to compare various types of the optimization task scheduling in using the virtual machines. The experimental results indicated that using the proposed Artificial Bee Colony algorithm when large job was considered first (HABC-LJF) in virtual machine scheduling, improved the efficiency in task scheduling and load balancing of virtual machines in Cloud computing. In addition, the proposed algorithm can minimize the makespan even if the tasks are increased and the different types of data are distributed.
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Simulation model of space optimization in containers arranging and sequencing for logistics
(2013-10-25)
Kimpan, Warangkhana
;
Tantawarak, Nake
This paper proposes the application using 3D Bin Packing to optimize the container space for logistics system. The aim is to reduce logistics costs, arrangement time and delivery time. The application can arrange different sizes of cubical boxes into the container bin of trucks, vans, or wagons considering their distributing sequence by using Best-Fit Decreasing algorithm to optimize the space. It also can be used to reduce the cost of product delivering because the container will be divided into many partitions and arranged by using delivery sequence. The different types of boxes and vehicles can be freely adjusted and arranged. The arranged boxes can be viewed in order to check their position. The experimental results of the application are shown in 3D with freely movement view.
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Using mobile application as an instrument for ptosis diagnosis
(2017-07-02)
Kimpan, Warangkhana
;
Sirivimonsattaya, Pongpicha
This article proposes a novel of mobile application to help ophthalmologists diagnose the Ptosis disease. This application applied digital image processing techniques to identify eye parameters: Marginal Reflex Distance-1, Marginal Reflex Distance-2, and L/M Ratio which doctors can use to diagnose patients besides using naked eyes. The application was built for iOS platform in the first version. The inputs of the application are the images of patient's eyes from a mobile device camera or from a mobile device memory. After using digital image processing techniques, at the end of the process, the eye parameters will be displayed on the mobile device screen for the doctors to be used. The experimental results indicated that the proposed mobile application can perform with 86.36% of accuracy in measuring Marginal Reflex Distance-1 value while it can measure Marginal Reflex Distance-2 value with 63.64% of accuracy.
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Virtual machine scheduling management on Cloud computing using Artificial Bee Colony
(2014-01-01)
Kruekaew, B.
;
Kimpan, W.
Resource scheduling management design on Cloud computing is an important problem. Scheduling model, cost, quality of service, time, and conditions of the request for access to services are factors to be focused. A good task scheduler should adapt its scheduling strategy to the changing environment and load balancing Cloud task scheduling policy. Therefore, in this paper, Artificial Bee Colony (ABC) is applied to optimize the scheduling of Virtual Machine (VM) on Cloud computing. The main contribution of work is to analyze the difference of VM load balancing algorithm and to reduce the makespan of data processing time. The scheduling strategy was simulated using CloudSim tools. Experimental results indicated that the combination of the proposed ABC algorithm, scheduling based on the size of tasks, and the Longest Job First (LJF) scheduling algorithm performed a good performance scheduling strategy in changing environment and balancing work load which can reduce the makespan of data processing time.
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NexusPSO: A novel algorithm to detect transcription factor binding sites
(2018-08-28)
Som, Sarawoot
;
Kimpan, Warangkhana
The detection of transcription factor binding sites is a major problem in research in Biology. Methods and computer algorithms can be applied to reduce time complexity and cost of detecting transcription factor binding sites in laboratory experiments. One of the well-known methods commonly used is swarm intelligence. However, errors in detection of transcription factor binding sites can be caused by different binding sites in the same genome sequence. The purpose of this research is to improve the effectiveness and accuracy in the detection of transcription factor binding sites by applying the newly developed pre-processing procedure, Nexus, to Particle Swarm Optimization algorithm (NexusPSO). The accuracy of the NexusPSO algorithm was measured in comparison with other algorithms, using information content (IC) as an indicator, with Escherichia coli data. This study found that NexusPSO is the most accurate method being tested. NexusPSO was then tested using consensus sequences on Saccharomyces cerevisiae and Homo sapiens. NexusPSO showed nearly identical results when compared to DNA footprinting methods.
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Neural network training model for weather forecasting using fireworks algorithm
(2017-02-21)
Suksri, Saktaya
;
Kimpan, Warangkhana
Weather forecasting is the application of science and technology in order to predict the weather conditions. It is important for agricultural and industrial sectors. Models of Artificial Neural Networks with supervised learning paradigm are suitable for weather forecasting in complexity atmosphere. Training algorithm is required for providing weight and bias values to the model. This research proposed a weather forecasting method using Artificial Neural Networks trained by Fireworks Algorithm. Fireworks Algorithm is a recently developed Swarm Intelligence Algorithm for optimization. The main objective of the method is to predict daily mean temperature based on various measured parameters gained from the Meteorological Station, located in Bangkok. The experimental results indicate that the proposed method is advantageous for weather forecasting.
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Thai Sign Language Translation Using Leap Motion Controller
(2017-01-01)
Tumsri, Jirawat
;
Kimpan, Warangkhana
In this article, algorithm for transforming sign language into Thai alphabets is presented to fill the gap in communication between the hearing impairment and normal people. Leap Motion Controller was applied to detect 5-finger-tip position and palm center in the form of X and Y axis. Then, decision tree was created by using the Quadtree technique and the research result on transforming Thai sign language into finite automata was applied to improve algorithm in creating finite automata of Thai alphabet sign language to increase efficiency and speed in processing sign language. The test result shows that it can discriminate 44-Thai alphabet sign language at 72.83% accuracy.
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Online code editor on Private cloud computing
(2013-12-01)
Kimpan, Warangkhana
;
Meebunrot, Theerasak
;
Sricharoen, Busaya
Programming tools are important for programmers to develop software. If the developers have a good tool, it can help them develop system faster and more accurate. This paper proposed the Online Code Editor that was created for programmers or developers who want to write programs without any platform requirements or without any specific physical computers. It bases on web application running on the Private cloud computing. The features of the editor are performed on web programming languages, e.g. HTML, PHP, CSS, and JavaScript. The editor is able to isolate programming languages by highlighting syntax of programs. Users can create new projects and files, import and export files that they want on a server. Moreover, Save, Auto save, Delete, and etc. are the additional functions of the editor. In this research of the text editor development, the open source software called, 'Ace' was used for some functions such as Undo, Redo, and Syntax highlight. The experimental results indicated that the proposed editor can be practically used on Private cloud computing. Moreover, the comparison of the features among the proposed editor running on Private cloud, Notepad++, and EditPlus which running on personal computers, was summarized. © 2013 IEEE.
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The design of golf swing pattern analysis from motion sensors
(2014-01-01)
Reintrakulchai, Natee
;
Kimpan, Warangkhana
This paper proposes a new idea of an analysis of golf swing patterns. The body movement data are collected from upper back and lower back muscles using Razor IMUs. The data are then classified in two steps according to the similarity of the changing ratio: the deviation reduction from sensors and the changing ratio at each period of time. The experimental results show the modified data in the form of Linear equation which consists of many straight lines. Each line represents each player's swing which can be compared to one another or defined the golf swing pattern among golf players and coaches and can also be adapted to the similar golf swing pattern data classification which can help golf trainers or doctors for physical therapy. This proposed method can be applied to use with other sports with certain patterns such as baseball, tennis, and ping pong.
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Applied Particle Swarm Optimization in Solving Container Loading Problem for Logistics
(2019-04-10)
Koonsintananan, Sasithom
;
Kimpan, Warangkhana
Container loading problem (CLP) is a major problem for logistics in distributing cargoes to customers. As cost and time savings are important in shipping management, the process of cargo handling is essential. Cargoes must be effectively packed into a container. This paper, therefore, proposes container loading problem solving using a strategy for positioning non placement heuristics to reduce space between different buildings. Particle Swarm Optimization (PSO) is used to select the orientation of boxes to be packed into a single container to minimize the space which simulated in 3D. The condition for this solution is packing must be placed within the container with no part of the box overhanging the container, and the boxes must be placed parallel to the container surface area or other boxes. Weight and orientation of the box condition are also considered. The experiments are 12 cases. Different sizes of boxes and different sizes of containers are used. The experimental results are satisfied and it can be concluded that varied sizes of boxes are applicable for the space utilization in the container.

Kimpan, Warangkhana

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