• Journal of Information Processing Systems
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• 제18권2호
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• pp.268-281
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• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권10호
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• pp.1259-1265
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• 2004

분류학습에서 높은 정확도를 유지하기 위해서는 충분한 분류 데이타가 필요하게 되는데 분류 데이타는 미 분류 데이타보다 생성하기가 어려운 경우가 많다. 따라서 미 분류 데이타를 활용하여 분류의 정확도를 향상시키는 것은 큰 효용성을 가지며 이러한 미 분류 데이타를 활용하는 대표적인 학습방법 중의 하나는 협력학습(co-training) 알고리즘이다. 이는 데이타를 두 개의 독립적인 속성그룹으로 나누어 두개의 분류자로 학습한 후 미 분류 데이타를 분류하고 그중 가장 신뢰성이 높은 데이타를 분류 데이터에 포함하고 이를 반복하는 학습모델이다. 하지만 이 방법은 전체 데이타의 속성을 독립적인 두개의 집합으로 분할하여야하는 제약이 있다. 따라서 본 연구에서는 이와 같은 문제점을 개선하여 보통의 데이터베이스에 적용시킬 수 있는 새로운 협력학습방법을 제시 하고자한다. 즉. 두 개의 독립적인 속성 그룹으로 나누는 가정을 따르지 않고 전체 속성을 사용할 수 있으며 두 개 이상의 분류자를 사용하는 새로운 협력학습방법을 제안하였다.

• The Journal of Asian Finance, Economics and Business
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• 제8권10호
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• pp.37-45
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• 2021

The purpose of this study was to explore and investigate: the direct impact of training on entrepreneurial performance and self-efficacy, the direct impact of leadership attitudes on entrepreneurial performance, and self-efficacy, the direct impact of self-efficacy on entrepreneurial performance, self-efficacy as a mediator of the effect of training on entrepreneurial performance, and self-efficacy as a mediator of the effect of leadership attitudes on entrepreneurial performance. This study purposively involved 131 entrepreneurs in Village-Owned Enterprises, Kuningan, Indonesia. The data was collected using a questionnaire. The data obtained was analyzed using Path Analysis with SPSS statistical software. This study has several findings. First, training has a significant effect on entrepreneurial performance and self-efficacy. Second, leadership attitudes have a significant effect on entrepreneurial performance and self-efficacy. Third, self-efficacy has a significant effect on entrepreneurial performance. Fourth, self-efficacy mediates the effect of training on entrepreneurial performance. Fifth, self-efficacy mediates the effect of leadership attitudes on entrepreneurial performance. The findings demonstrated that using self-efficacy-based training and leadership attitudes can enhance entrepreneurial self-confidence and assist them to improve their performance.

• Safety and Health at Work
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• 제13권2호
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• pp.235-239
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• 2022

Background: The purpose of present study was to determine the effectiveness of training program based on job stress management in NEDSA and line staff. Methods: The study method of this study was quantitative and quasi-experimental research Methods: From the statistical population (all employees of the NEDSA and line staff in 2020-2021), 30 of these people were selected by judgmental sampling method and considering the inclusion and exclusion criteria. The participants were first matched based on age and education and were randomly divided into experimental and control groups. First, pre-test was taken from both groups (Job Stress Questionnaire). The experimental group was presented with a job stress management training package and no protocol was presented in the control group. After the sessions, post-test was received from both groups (experimental and control). After two months, a follow-up test was performed. Results: The results were entered into SPSS-24 software and analyzed. The results of repeated measure showed high effectiveness of the job stress management package (researcher-made). The results showed that the job stress management training package showed 67.5% effectiveness and also the training effect of job stress management training was stable for two months (follow-up). Conclusion: Based on these results, Training program based on stress management can be effective in military staff.

• The Journal of Asian Finance, Economics and Business
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• 제10권1호
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• pp.169-179
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• 2023

This study aims to determine the factors that influence training programs in increasing entrepreneurial success as a new model for developing entrepreneurship training in a new era. It intended to provide a suggestion for building an entrepreneurship training model for Beginner Young Entrepreneurs (BYE) organized by the Ministry of Youth and Sports of Indonesia. The study used a quantitative method by collecting data through a Google form questionnaire distributed via the WhatsApp group. This study employs samples from 358 BYE training participants for 2017-2020, and data was processed using Amos SEM software to analyze factors that influence the success of entrepreneurship. The results showed that entrepreneurial motivation is a partial mediator in increasing the effect of training on its success by BYE participants. Furthermore, the key factor for increasing entrepreneurial motivation is challenging young people to start businesses. This study recommends that BYE program policymakers build a training model by considering many practical case studies to increase motivation as an important mediator in influencing entrepreneurial success. Meanwhile, to boost the morale of training participants, it is necessary to add significant real challenges for participants to start entrepreneurship. Moreover, future studies should add other independent variables, such as personality.

• 정보처리학회논문지D
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• 제10D권4호
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• pp.689-696
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• 2003

설계 개체의 결함경향성을 판별하는 위험도 예측 모델은 분석이나 설계 같은 소프트웨어 개발 초기 단계에서 시스템의 문제 부분들을 찾아 내는데 사용된다. 복잡도 메트릭에 기반한 많은 위험도 예측 모델들이 제안되었지만 그들 대부분은 모델 훈련을 위한 훈련데이터 집합을 필요로 하는 모델들이었다. 하지만 대부분의 개발집단은 훈련데이터 집합을 보유하고 있지 않기 때문에 이들 모델들은 대부분의 개발집단에서 사용될 수 없다는 커다란 문제점이 있었다. 이러한 문제점을 해결하기 위해 본 논문에서는 Kohonen SOM 신경망을 이용하여 훈련데이터 집합을 사용하지 않는 새로운 예측 모델 KSM을 제안한다. 여러 내부 특성들과 모델 사용의 용이성 그리고 모의실험을 통한 예측 정확도 비교를 통해 KSM을 잘 알려진 예측 모델인 역전파 신경망 모델(BPM)과 비교하였으며 그 결과 KSM의 성능이 BPM에 근접하다는 것을 보였다.

• ETRI Journal
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• 제39권5호
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• pp.643-651
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• 2017

Human age estimation is one of the key factors in the field of Human-Robot Interaction/Human-Computer Interaction (HRI/HCI). Owing to the development of deep-learning technologies, age recognition has recently been attempted. In general, however, deep learning techniques require a large-scale database, and for age learning with variations, a conventional database is insufficient. For this reason, we propose an age estimation method using artificially generated data. Image data are artificially generated through 3D information, thus solving the problem of shortage of training data, and helping with the training of the deep-learning technique. Augmentation using 3D has advantages over 2D because it creates new images with more information. We use a deep architecture as a pre-trained model, and improve the estimation capacity using artificially augmented training images. The deep architecture can outperform traditional estimation methods, and the improved method showed increased reliability. We have achieved state-of-the-art performance using the proposed method in the Morph-II dataset and have proven that the proposed method can be used effectively using the Adience dataset.

• 전기학회논문지
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• 제56권8호
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• pp.1373-1381
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• 2007

This paper presents a graphical windows-based software for the education and training of transmission network charge. The motivation for the development of the simulator is to provide students with a simple and useable tool for gaining an intuitive feel for transmission network charge. The developed simulator consists of the main module (MMI, GUI), the power flow module (PF), the power flow tracing module (PFT), and usage cost DB module (UCD). Each module has a separate graphical and interactive interfacing window. The developed simulator provides with two power system analysis methods (i.e., DC-PF and Modified DC-PF) and supports the PSS/E input data format to load input data of power system. Also, power flow tracing can be calculate using four methods such as "Felix Wu", "Modified Felix Wu", "DCLF ICRP", and "Reverse MW mile". Results of calculation for transmission usage cost are displayed and compared on the window through the table and/or chart. Therefore, the developed simulator can be utilize as a useful tool for effective education and training of transmission network charge.

• Structural Engineering and Mechanics
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• 제72권1호
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• pp.83-97
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• 2019

In this research, the vulnerability of some reinforced concrete frames with different stories are studied based on the Park-Ang Damage Index. The damages of the frames are investigated under various earthquakes with nonlinear dynamic analysis in IDARC software. By examining the most important characteristics of earthquake parameters, the damage index and vulnerability of these frames are investigated in this software. The intensity of Erias, velocity spectral intensity (VSI) and peak ground velocity (PGV) had the highest correlation, and root mean square of displacement ($D_{rms}$) had the lowest correlation coefficient among the parameters. Then, the particle swarm optimization (PSO) algorithm was used, and the sinusoidal waves were equivalent to the used earthquakes according to the most influential parameters above. The damage index equivalent to these waves is estimated using nonlinear dynamics analysis. The comparison between the damages caused by earthquakes and equivalent sinusoidal waves is done too. The generations of sinusoidal waves equivalent to different earthquakes are generalized in some reinforced concrete frames. The equivalent sinusoidal wave method was exact enough because the greatest difference between the results of the main and artificial accelerator damage index was about 5 percent. Also sinusoidal waves were more consistent with the damage indices of the structures compared to the earthquake parameters.

• 한국컴퓨터그래픽스학회논문지
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• 제30권4호
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• pp.19-29
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• 2024

본 논문에서는 의료 영상 분류를 위한 심층 신경망 훈련에서 StyleGAN 합성 영상의 데이터 증강 효과를 분석한다. 이를 위해 흉부 X선 영상에서의 폐렴 진단과 복부 CT 영상에서의 간전이암 분류 문제에서 StyleGAN 합성 영상을 이용하여 VGG-16 심층 합성곱 신경망 훈련을 수행한다. 실험에서 분류 결과에 대한 정량적, 정성적 분석을 통해 StyleGAN 데이터 증강이 특징 공간에서 클래스 외곽을 확장하는 특성을 보이며, 이와 같은 특성으로 인해 실제 영상과의 적절한 비율을 통해 혼합했을 때 분류 성능이 개선될 수 있음을 확인하였다.