• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.556-561
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• 2015

The actual aircraft flight training can be done, throw this platform. this paper focuses on identifying the functions with respect to software components in the development of a aerodynamics system, which is based on the functions necessary to develop the real environment aircraft system. It also design activity diagram, concept as well as class diagram. This paper presents the main features and direction of aircraft to be equipped in the future gaming platforms. By designing a pilot platform updates that allow for new aircraft models students can understand exactly what they want and aircraft. this study presents a use case based on the aerodynamic simulation CSU concept to execution.

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.738-747
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• 2019

Both within the country and internationally, discussions about core technologies that will be prominent in future society have been initiated, and software education for the rapidly changing industrial framework has been essential and implemented in earnest. Also, there is an increasing interest in interactive technology and software education where people and people, people and computers, and computers and objects communicate with each other in today's day-to-day life, connected through the digital world. Therefore, it is necessary to investigate the user's field of interest and the best technical education method for teaching how to operate the production tool for implementing the interactive technology. In this study, we utilize the Processing program which is widely used as interactive technology software training and creativity tool to improve the understanding of the interactive technology related to the 4th industrial revolution. This study aims to determine and propose the best method of using a Processing library that can be applied to each major field.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.101-116
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• 2020

This study attempts to derive critical success factors and prioritize activities for implementing the automation of software test. Software testing proceeds in five steps of test plan, test case design, test scripting & test environment setup, test execution & evaluation, and test closure. From the literature, twenty influence factors in the five steps were identified. Focus Group Interviews with ten experts in software testing selected fourteen factors on the basis of importance and feasibility. Some factors were further divided to clarify their meanings and the number of influence factors finally became twenty one. A survey on the influence factors was conducted with 75 IT professionals. An importance-feasibility analysis was applied to the survey responses and classified the influence factors into four groups of essential factors, critical factors, low priority factors, and minimal factors. Essential factors include objectives for test automation, strategies for test automation, test automation training, test automation education, setting up test automation environment, setting up test environment, test automation tool selection. Critical factors include management's continued support, management's continued interest, role of automation engineers, and skills of automation engineers. This result suggests that a lot of efforts should be put into SW test plan for the successful SW test automation and SW automation should proceed in consideration with the priorities and resource consumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1275-1292
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• 2021

As a fine-grained classification problem, aspect-level sentiment classification predicts the sentiment polarity for different aspects in context. To address this issue, researchers have widely used attention mechanisms to abstract the relationship between context and aspects. Still, it is difficult to effectively obtain a more profound semantic representation, and the strong correlation between local context features and the aspect-based sentiment is rarely considered. In this paper, a hybrid attention capsule network for aspect-level sentiment classification (ABASCap) was proposed. In this model, the multi-head self-attention was improved, and a context mask mechanism based on adjustable context window was proposed, so as to effectively obtain the internal association between aspects and context. Moreover, the dynamic routing algorithm and activation function in capsule network were optimized to meet the task requirements. Finally, sufficient experiments were conducted on three benchmark datasets in different domains. Compared with other baseline models, ABASCap achieved better classification results, and outperformed the state-of-the-art methods in this task after incorporating pre-training BERT.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.66-74
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• 2014

Recently a variety of study of Korean parsing system is carried out by many software engineers and linguists. The parsing system mainly uses the method of machine learning or symbol processing paradigm. But the parsing system using machine learning has long training time because the data of Korean sentence is very big. And the system shows the limited recognition rate because the data has self error. In this thesis we design system using feature module which can reduce training time and analyze the recognized rate each the number of training sentences and repetition times. The designed system uses the separated modules and sorted table for binary search. We use the refined 36,090 sentences which is extracted by Sejong Corpus. The training time is decreased about three hours and the comparison of recognized rate is the highest as 84.54% when 10,000 sentences is trained 50 times. When all training sentence(32,481) is trained 10 times, the recognition rate is 82.99%. As a result it is more efficient that the system is used the refined data and is repeated the training until it became the steady state.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.5
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• pp.1851-1855
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• 2015

Background: There are increasing data about microRNAs (miRNA) in the literature, providing abundant evidence that they play important roles in pathogenesis and development of colorectal cancer. In this study, we aimed to investigate the miRNA expression profiles in surgically resected specimens of patients with recurrent and non-recurrent colorectal cancer. Materials and Methods: The study population included 40 patients with stage II colorectal cancer (20 patients with recurrent tumors, and 20 sex and age matched patients without recurrence), who underwent curative colectomy between 2004 and 2011 without adjuvant therapy. Expression of 16 miRNAs (miRNA-9, 21, 30d, 31, 106a, 127, 133a, 133b, 135b, 143, 145, 155, 182, 200a, 200c, 362) was verified by quantitative real-time polymerase chain reaction (qRT-PCR) in all resected colon cancer tissue samples and in corresponding normal colonic tissues. Data analyses were carried out using SPSS 15 software. Values were statistically significantly changed in 40 cancer tissues when compared to the corresponding 40 normal colonic tissues (p<0.001). MiR-30d, miR-133a, miR-143, miR-145 and miR-362 expression was statistically significantly downregulated in 40 resected colorectal cancer tissue samples (p<0.001). When we compared subgroups, miRNA expression profiles of 20 recurrent cancer tissues were similar to all 40 cancer tissues. However in 20 non-recurrent cancer tissues, miR-133a expression was not significantly downregulated, moreover miR-133b expression was significantly upregulated (p<0.05). Conclusions: Our study revealed dysregulation of expression of ten miRNAs in Turkish colon cancer patients. These miRNAs may be used as potential biomarkers for early detection, screening and surveillance of colorectal cancer, with functional effects on tumor cell behavior.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.339-346
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• 2003

This paper proposes a multiple classifier system having massive micro classifiers. The micro classifiers are trained by using a local set of training patterns. The k nearest neighboring training patterns of one training pattern comprise the local region for training a micro classifier. Each training pattern is incorporated with one or more micro classifiers. Two types of micro classifiers are adapted in this paper. SVM with linear kernel and SVM with RBF kernel. Classification is done by selecting the best micro classifier among the micro classifiers in vicinity of incoming test pattern. To measure the goodness of each micro classifier, the weighted sum of correctly classified training patterns in vicinity of the test pattern is used. Experiments have been done on Elena database. Results show that the proposed method gives better classification accuracy than any conventional classifiers like SVM, k-NN and the conventional classifier combination/selection scheme.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.8 no.4
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• pp.275-281
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• 2014

The purpose of this study was development and evaluation of putting training system with specialized guides which were adjustable its width and changeable its distance from the ball. The system hardwares that used in this study were made by LEGO NXT and Tetrix set. The system software was made by LabVIEW ver. 2010. The subjects were organized in non-experts(10persons) and KPGA(5persons) players. The putting training schedule was composed of 10 sets and each sets were identically same, which were organized in 4 different width of its guide at 3 different distance from the ball hitting spot, 3 repetition each. The speed/acceleration in wrist area and movement in head area were both reduced by the putting training. Most of testees submitted positive comments in aspect of concentration and motivation. This training method which had changeable width and distance will be able to adapt easily to another sports for the handicapped and the elderly such as ParkGolf or Gateball.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.4
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• pp.450-458
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• 2013

The aim of this study was to develop and verify gait training system for post-stroke hemiplegia patients with step length asymmetry. Most post-stroke hemiplegic patients show gait asymmetry and weight shifting training has been suggested as a useful method for improving the walking ability. However, verbal cue by physical therapist may be not effective. Therefore, our weight shift training system was designed to give a feedback to patients through precise plantar pressure and center of pressure (COP) measurement. This weight shifting biofeedback training system is composed of F-Scan plantar pressure measurement system and software development kit (SDK) for Windows operating system. Two post-stroke patients with step length asymmetry were enrolled in this study. After training for six weeks, the weight shift score and step length ratio of two all patients were improved and approached to them of non-disabled. This system developed in this study may improve the step length asymmetry, and therefore this system is also expected to improve a walking ability in hemiplegic patients.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.34-41
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• 2020

There has not been any scientific analysis on appropriate size of workforce and salary for civilian workers in military so far. Thus, this paper conducted analysis on propriety in employment size of military doctrine researchers using system dynamic methodology based on annual military doctrine workload. Vensim software was mainly used to measure complement of the research group based on data from job analysis. Secondly, a multiple regression analysis was performed to study an appropriate wage for researchers based on their expertise and working condition. The data from twenty public research institutions and twenty eight job positions that are performing similar duty with military doctrine researchers was obtained and utilized to create a salary-estimation regression equation in the analysis. Finally, with cost-benefit analysis method this paper studied financial effectiveness of hiring military doctrine researchers. Contingent valuation method, which has been recognized as one of the most effective methodologies in cost-benefit analysis on intangible value, was utilized to measure benefit of hiring the researchers. The methodology presented in this paper can be applied to measure and improve the efficiency of military organization not only in military doctrine research area but also in several military functional area (military training, logistics, administration, combat development, and combat support).