• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.436-450
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• 2005

Existing B2B, B2C computer systems and applications that executed business trans-actions were the client- server based architecture which consists of heterogeneous hardware and software including personal computers and mainframes. Due to the active boom of electronic business, integration and compatibility of exchanged data, applications and hardwares have emerged as hot issue. This paper designs and implements a message transport system and a document transformation system in order to solve the interoperability problem of integrated logistics system in e-Business when doing electronic business. Message transport system integrated ebMS 2.0 which is standard business message exchange format of ebXML, the international standard electronic commerce framework, and JMS of J2EE enable to ensure reliable messaging. The document transformation system could convert non-standard XML documents into standard XML documents and provide the web services after integrating message system. Using suggested business scenario and various test data, our message oriented system preyed to be interoperable and stable. We participated ebXML messaging interoperability test organized by ebXML Asia Committee ITG in oder to evaluate and certify the suitability for message system.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.79-85
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• 2022

Anomaly detection is a method to detect and block abnormal data flows in general users' data sets. The previously known method is a method of detecting and defending an attack based on a signature using the signature of an already known attack. This has the advantage of a low false positive rate, but the problem is that it is very vulnerable to a zero-day vulnerability attack or a modified attack. However, in the case of anomaly detection, there is a disadvantage that the false positive rate is high, but it has the advantage of being able to identify, detect, and block zero-day vulnerability attacks or modified attacks, so related studies are being actively conducted. In this study, we want to deal with these anomaly detection mechanisms, and we propose a new mechanism that performs both anomaly detection and classification while supplementing the high false positive rate mentioned above. In this study, the experiment was conducted with five configurations considering the characteristics of various algorithms. As a result, the model showing the best accuracy was proposed as the result of this study. After detecting an attack by applying the Extra Tree and Three-layer ANN at the same time, the attack type is classified using the Extra Tree for the classified attack data. In this study, verification was performed on the NSL-KDD data set, and the accuracy was 99.8%, 99.1%, 98.9%, 98.7%, and 97.9% for Normal, Dos, Probe, U2R, and R2L, respectively. This configuration showed superior performance compared to other models.

• Therapeutic Science for Rehabilitation
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• v.12 no.2
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• pp.85-98
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• 2023

Objective : We investigated the efficacy of an artificial intelligence computerized cognitive training program using motion capture to identify changes in cognition, depression, and quality of life in older adults with mild cognitive impairment. Methods : A total of seven older adults (experimental group = 4, control group = 3) participated in this study. During the COVID-19 period from October to December 2021, we used a program, "MOOVE Brain", that we had developed. The experimental group performed the program 30 minutes 3×/week for 1 month. We analyzed patients scores from the Korean version of the Mini-Mental State Examination-2, the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet for Daily Life Evaluation, the short form Geriatric Depression Scale, and Geriatric Quality of Life Scale. Results : We observed positive changes in the mean scores of the Stroop Color Test (attention), Stroop Color/Word Test (executive function), SGDS-K (depression), and GQOL (QoL). However, these changes did not reach statistical significance for each variable. Conclusion : The study results from "MOOVE Brain" can help address cognitive and psychosocial issues in isolated patients with MCI during the COVID-19 pandemic or those unable to access in-person medical services.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.3
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• pp.383-391
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• 2016

Ballast water provides stability and manoeuvrability to a ship. Foreign harmful aquatic organisms, which were transferred by ballast water, cause disturbing ecosystem. In order to minimize transference of foreign harmful aquatic organisms, IMO(International Maritime Organization) adopted the International Convention for the Control and Management of Ship's Ballast Water and Sediments in 2004. If the convention take effect, a port authority might need to check that ballast water is properly disposed of. In this paper, we propose a method of counting harmful aquatic organisms in ballast water thorough image processing. We extracted three samples from the ballast water that had been collected at Busan port in Korea. Then we made three grey-scale images from each sample as experimental data. We made a comparison between the proposed method and CellProfiler which is a well known cell-counting program based on image processing. Setting of CellProfiler is empirically chosen from the result of cell count by an expert. After finding a proper threshold for each image at which the result is similar to that of CellProfiler, we used the average value as the final threshold. Our experimental results showed that the proposed method is simple but about ten times faster than CellProfiler without loss of the output quality.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.967-971
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• 2023

Recently, a variety of AI-based platform services are available, and one of them is ChatGPT that processes a large quantity of data in the natural language and generates an answer after self-learning. ChatGPT can perform various tasks including software programming in the IT sector. Particularly, it may help generate a simple program and correct errors using C Language, which is a major programming language. Accordingly, it is expected that ChatGPT is capable of effectively using Verilog HDL, which is a hardware language created in C Language. Verilog HDL synthesis, however, is to generate imperative sentences in a logical circuit form and thus it needs to be verified whether the products are executed properly. In this paper, we aim to select small-scale logical circuits for ease of experimentation and to verify the results of circuits generated by ChatGPT and human-designed circuits. As to experimental environments, Xilinx ISE 14.7 was used for module modeling, and the xc3s1000 FPGA chip was used for module embodiment. Comparative analysis was performed on the use area and processing time of FPGA to compare the performance of ChatGPT products and Verilog HDL products.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.2
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• pp.1-13
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• 2018

This study examines the relationship between the organizational general characteristics (industry, size, location, development stage, and company age) and success factors of Korean venture firms using secondary data. Among the industries with the highest sales figures in 2016 are food / fiber / (non) metals, and the smallest category was software development. The sectors with the highest net profit were computer / semiconductor / electronic components, and the smallest category was telecommunication equipment / broadcasting equipment. The industries with the largest sales growth rate are IT / broadcasting services and software development. The industries with the highest net profit margin of sales are energy / medical / precision, and the smallest is telecommunication equipment / broadcasting equipment. In terms of the number of employees, venture firms with more than 100 employees have the largest sales and net profit, with employees between 1 and 9 have the smallest. However, these results are predictable. In general, the number of employees is highly correlated with sales and net profit. Rather, the sales growth rate and the net profit margin of sales may be meaningful. In particular, with employees between 50 ~ 99, the growth rate of sales and the net profit margin of sales were high. In terms of location, Seoul / Incheon / Gyeonggi were the regions with the highest sales and Daejeon / Sejong / Chungcheong / Gangwon were the least regions. Gwangju / Jeolla / Jeju and Seoul / Incheon / Gyeonggi were almost similar in the areas with the largest net profit. However, Daejeon / Sejong / Chungcheong / Gangwon had the lowest net profit. Unusually, the areas with the highest sales growth rate and the highest net profit margin of sales were Gwangju / Jeolla / Jeju, and the smallest areas were Busan / Jeonnam / Ulsan In the relationship between the stage of development and the performance of the company, the sales of maturity and decline stages were the highest and establishing stage was the lowest. Net profit was also the highest in mature stage and the smallest in establishing stage. The sales growth rate shows a typical pattern in the order of establishing stage, early growth stage, high growth stage, maturity stage, and decline stage. In terms of business performance, sales and net profit are the highest with 21 years or more of company age, and the smallest is less than 3 years. In addition, the sales growth rate was the highest in three years or less, and the net profit margin of sales was the highest in 4 to 10 years. This study can present lots of useful implications by suggesting integrated research model and examining the success factors of Korean venture firms and presenting the application methods of secondary data in analyzing the current status of venture industry in Korea.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.77-86
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• 2018

For the past few years, KISTI has been servicing an online simulation execution platform, called EDISON, allowing users to conduct simulations on various scientific applications supplied by diverse computational science and engineering disciplines. Typically, these simulations accompany large-scale computation and accordingly produce a huge volume of output data. One critical issue arising when conducting those simulations on an online platform stems from the fact that a number of users simultaneously submit to the platform their simulation requests (or jobs) with the same (or almost unchanging) input parameters or files, resulting in charging a significant burden on the platform. In other words, the same computing jobs lead to duplicate consumption computing and storage resources at an undesirably fast pace. To overcome excessive resource usage by such identical simulation requests, in this paper we introduce a novel framework, called IceSheet, to efficiently manage simulation data based on execution metadata, that is, provenance. The IceSheet framework captures and stores each provenance associated with a conducted simulation. The collected provenance records are utilized for not only inspecting duplicate simulation requests but also performing search on existing simulation results via an open-source search engine, ElasticSearch. In particular, this paper elaborates on the core components in the IceSheet framework to support the search and reuse on the stored simulation results. We implemented as prototype the proposed framework using the engine in conjunction with the online simulation execution platform. Our evaluation of the framework was performed on the real simulation execution-provenance records collected on the platform. Once the prototyped IceSheet framework fully functions with the platform, users can quickly search for past parameter values entered into desired simulation software and receive existing results on the same input parameter values on the software if any. Therefore, we expect that the proposed framework contributes to eliminating duplicate resource consumption and significantly reducing execution time on the same requests as previously-executed simulations.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.25-34
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• 2020

In the current medical information system, a system environment is constructed in which Biometric data generated by using IoT or medical equipment connected to a patient can be stored in a medical information server and monitored at the same time. Also, the patient's biometric data, medical information, and personal information after simple authentication using only the ID / PW via the mobile terminal of the medical staff are easily accessible. However, the method of accessing these medical information needs to be improved in the dimension of protecting patient's personal information, and provides a quick authentication system for first aid. In this paper, we implemented an automatic authentication system based on the patient's situation and evaluated its performance. Patient's situation was graded into normal and emergency situation, and the situation of the patient was determined in real time using incoming patient biometric data from the ward. If the patient's situation is an emergency, an emergency message including an emergency code is send to the mobile terminal of the medical staff, and they attempted automatic authentication to access the upper medical information of the patient. Automatic authentication is a combination of user authentication(ID/PW, emergency code) and mobile terminal authentication(medical staff's role, working hours, work location). After user authentication, mobile terminal authentication is proceeded automatically without additional intervention by medical staff. After completing all authentications, medical staffs get authorization according to the role of medical staffs and patient's situations, and can access to the patient's graded medical information and personal information through the mobile terminal. We protected the patient's medical information through limited medical information access by the medical staff according to the patient's situation, and provided an automatic authentication without additional intervention in an emergency situation. We performed performance evaluation to verify the performance of the implemented automatic authentication system.

• Korean Journal of Social Welfare
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• v.57 no.2
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• pp.5-40
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• 2005

Social welfare centers and residential care facilities where provide the socially disadvantaged with proper social services, face financial difficulties. This is because not only of the lack of governmental support, but also of social welfare centers and residential care facilities' lack of skills in developing abundant resources from the private sector. In this context, this study tried to find factors affecting resource mobilization of the social welfare facilities to devise policies in resource development. Mail survey was conducted with the structured questionnaire. Employees in charge of community resource development were asked to answer the questionnaire. The study population were welfare centers and residential care facilities. A total of 293 community welfare centers and 632 residential care facilities responded to the survey. The response rate was about 62%. The dependent variables of the study were the amount of resource mobilization in the year 2001 which was measured as the number of donors, the total amount of donation, and estimated amount of gift-in-kind. Three types models were constructed per each welfare institution. Independent variables were selected based on the previous research findings: community environment factor, structural factor, and resource development factor. Multiple regression was utilized to analyze the data. The resource development factor turned out to be significant variable in various models. In the models of donors, the amount of donation, and the amount of gift-in-kind (except for the welfare center model), at least one out of six variables of the resource development factors was significant welfare center. Welfare centers which establish the resource development department or hire employees to take care of resource development, utilize computer softwares to file donors, and utilize donor management programs, have more donors and/or donations than their counterparts. In addition, residential care facilities located in urban area have more donors and donations, and among residential facilities those for the disables, those with longer history and more employees, receive more donations than their counterparts. As for the gift-in-kind model, the welfare centers located in high income area and residential care facilities for the elderly, children and mentally retarded receive less gift-in-kind than their counterparts Based on the above findings, this study suggested that to mobilize resources the welfare centers as well residential care facilities need to have community resource development department or resource development staffs, adopt computer software to systematically organize donors, and utilize donor mobilizing and maintaining programs.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.