• Journal of Multimedia Information System
• /
• v.3 no.3
• /
• pp.97-102
• /
• 2016

Deep learning enables machines to have perception and can potentially outperform humans in the medical field. It can save a lot of time and reduce human error by detecting certain patterns from medical images without being trained. The main goal of this paper is to build the optimal model for breast mass classification by applying various methods that influence the performance of Convolutional Neural Network (CNN). Google's newly developed software library Tensorflow was used to build CNN and the mammogram dataset used in this study was obtained from 340 breast cancer cases. The best classification performance we achieved was an accuracy of 0.887, sensitivity of 0.903, and specificity of 0.869 for normal tissue versus malignant mass classification with augmented data, more convolutional filters, and ADAM optimizer. A limitation of this method, however, was that it only considered malignant masses which are relatively easier to classify than benign masses. Therefore, further studies are required in order to properly classify any given data for medical uses.

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.3
• /
• pp.619-628
• /
• 2021

Enterprise system (ES) reflects a significant IT commitment to achieve corporate goals and satisfy its thrust toward a sustainable competitive advantage. This research investigates the required ES architecture, the value of a well-planned ES, and the human factor capabilities that drive the effective implementation of ES from a management perception. This paper examined the critical factors shaping the business systems' performance, architecture readiness, experts' readiness, and enterprise systems planning. Based on an extensive literature review, the attributes of factors mentioned earlier were identified, classified and then statistically examined using the author's' proposed conceptual structural model. This study employs a quantitative research methodology, with a random sampling technique. This paper has used the data collected from 510 respondents working in service, engineering and health sectors in OMAN. The study model analysis utilized both exploratory and confirmatory factor analysis, followed by a structural equation modeling using SPSS 25 and EQS6.3 statistical tools. The results unveil a piece of remarkable and robust evidence suggesting that ES planning is the most significant aspect of influencing performance, followed by IT personnel, staff and consumers expertise, and architecture readiness.

• The Journal of the Korea Contents Association
• /
• v.21 no.2
• /
• pp.301-314
• /
• 2021

Youth unemployment is a global social issue which leads to a waste of human resources and undermines the national economy. Job search self-efficacy (JSSE) can predict active job search and job search outcomes. The present study identified the factors affecting the JSSE of unemployed youth based on the Neuman Systems Model (NSM). The results indicated that job search period, job search stress, and problem-centred coping ability influenced young job seekers' JSSE, which increased especially with the perception of physical health. Therefore, to promote JSSE, it is necessary to not only establish social systems for the youth but also develop an intervention plan based on the NSM that optimises problem-centred coping ability, a normal line of defence in the individual's system, and maintains a healthy physical state, a line of resistance.

• Journal of KIISE
• /
• v.45 no.3
• /
• pp.251-279
• /
• 2018

Users can experience cybersickness when interacting with virtual reality (VR). The symptoms of cybersickness are similar to those of motion sickness which include eye fatigue, disorientation, and nausea. Despite the longstanding interest of user's discomfort, inconsistent results have been drawn on the underlying mechanisms and solutions of cybersickness. In this study, we propose an integrated view of cybersickness connecting causes of the symptoms, human perception model, and measurements of cybersickness. Cybersickness-related factors of previous research are reorganized into content, hardware, and human factors as well as analyzed in terms of VR fidelity. Also, pros and cons that measure the degree of cybersickness are discussed.

• Journal of Digital Convergence
• /
• v.17 no.3
• /
• pp.221-226
• /
• 2019

The characteristic of the beta wave among the EEG waves corresponds to the stress area of human perception. The over-bandwidth of the stress is extracted by analyzing the beta-wave correlation between the low-bandwidth and high-bandwidth. We present a KMeans clustering analysis model for unsupervised machine learning to construct an analytical model for analyzing and extracting the beta-wave correlation. The proposed model classifies the beta wave region into clusters of similar regions and identifies anomalous waveforms in the corresponding clustering category. The abnormal group of waveform clusters and the normal category leaving region are discriminated from the stress risk group. Using this model, it is possible to discriminate the degree of stress of the cognitive state through the EEG waveform, and it is possible to manage and apply the cognitive state of the individual.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.4
• /
• pp.43-48
• /
• 2018

This study was conducted to reproduce digital colour based on the lightness of the background and size of the colour stimulus so that colour can be similarly perceived under different conditions. With the evolution of display technologies, display devices of various sizes can now reproduce more accurate colour and enhanced images, thus affecting the overall quality of display images. This study reproduced digital colour by considering the visual characteristics of the digital media environment. To accomplish this, we developed a colour appearance model which distinguishes the properties of foveal and peripheral vision. The proposed model is based on existing research on the lightness of the background and size of the colour stimulus. Based on experimental results, an analysis of variance was performed in order to develop the colour appearance model. The algorithm and modelling were verified based on the proposed model. In addition, to apply this model to display technologies, a practical colour control system and a method for handling complex input images were developed. Through this research, colour conversion errors which might occur when the input image is converted to fit a specific display size are resolved from the perspective of the human visual system. As a result, more accurate colour can be displayed and enhanced images can be reproduced.

• Korean Institute of Interior Design Journal
• /
• v.21 no.1
• /
• pp.40-50
• /
• 2012

This study aims at suggesting the applicability of color combination based upon the characteristics of environmental color perception and the nuance concept of Natural Color System(NCS). The results are summarized below: First, NCS is a scientific coloring system in consideration of the relevance between people, light and environment, to be based on a phenomenological point of view. NCS can be called a psychometric model reflecting our natural color sense. Second, the color triangle established by NCS is one of the methods of expression based on the human visual mechanism, which is classified by two attributes of hue and nuance, not by the three color attributes of hue, lightness and saturation. The nuance concept of NCS implies the impression, atmosphere and tone that are perceived in colors, which are related to lightness and saturation. Accordingly, this paper suggests that the coloring arrangement emphasizing nuance and tone is more useful than hue in color planning. Third, aesthetic impression in environmental color perception is inclusive of instantly perceptive nuance, which is connected with affordance. The affordance is revealed by the different relation of similarity. In this regard, a strong relationship is noticed between color combination and the sense of pleasantness. The hypothesis regarding the complementation and similarity of contrasting nature is judged to provide observers with aesthetic order. Finally, this paper also suggests four harmonizing methods in the NCS color triangle based upon equal blackness, equal whiteness, equal chromaticness and same nuance. At the same time, opposition and a different concept of hue, lightness and lightness are combined complementarily with the nuance value to suggest patterns of color combination.

• Journal of Information Technology Services
• /
• v.20 no.3
• /
• pp.41-56
• /
• 2021

New drug discovery and development research enable clinical treatment that saves human life and improves the quality of life, but the possibility of success with new drugs is significantly low despite a long time of 14 to 16 years and a large investment of 2 to 3 trillion won in traditional methods. As artificial intelligence is expected to radically change the new drug development paradigm, artificial intelligence new drug discovery and development projects are underway in various forms of collaboration, such as joint research between global pharmaceutical companies and IT companies, and government-private consortiums. This study uses the TOE framework and the Value-based Adoption Model, and the technical, organizational, and environmental factors that should be considered for the acceptance of AI technology at the level of the new drug research organization are the value of artificial intelligence technology. By analyzing the explanatory power of the relationship between perception and intention to use, it is intended to derive practical implications. Therefore, in this work, we present a research model in which technical, organizational, and environmental factors affecting the introduction of artificial intelligence technologies are mediated by strategic value recognition that takes into account all factors of benefit and sacrifice. Empirical analysis shows that usefulness, technicality, and innovativeness have significantly affected the perceived value of AI drug development systems, and that social influence and technology support infrastructure have significant impact on AI Drug Discovery and Development systems.

• Korean Journal of Community Nutrition
• /
• v.28 no.1
• /
• pp.24-37
• /
• 2023

Objectives: This study aimed to investigate the current status of nutrition education via a free learning semester program (NE). The understanding of the program, the potential difficulties, and future initiatives for NE improvement were also investigated. Methods: A total number of 161 nutrition teachers from Gwangju and Jeonnam filled in a questionnaire and participated in this survey, which was performed from July to August 2019. Results: Our results showed that 8.1% of the nutrition teachers had taught nutrition education in free learning semester programs. The most frequently implemented model was subject selection, followed by club activities. Most of the nutrition teachers comprehended the purpose of NE. The attitude of nutrition teachers to NE differed by the understanding of its purpose. Positive attitude was evident due to a better understanding of the purpose by nutrition teachers. Nutrition teachers reported the most common difficulties of NE were the lack of preparation due to the heavy workload and the lack of a standard running program. The most effective method of NE was the activity classes. The experience of practicing NE influenced the choice of contents for each operating model. Nutrition teachers that were experienced in NE conducted via free learning semester programs preferred the selected topics model, but those without experience chose the career search model. Conclusions: Although some obstacles exist, nutrition teachers had a positive attitude and perceived well the importance of NE. Therefore, the awareness for the significance of NE of nutrition teachers needs to be improved. For better NE practice, it is necessary to reduce/ manage the workload of general food service. Furthermore, the development of standard running and promotion programs, and teacher training programs should be ensured.

• Journal of Broadcast Engineering
• /
• v.20 no.6
• /
• pp.818-826
• /
• 2015

Recently, objective image quality assessment (IQA) methods that elaborately reflect the visual quality perception characteristics of human visual system (HVS) have actively been studied. Among those characteristics of HVS, luminance adaptation (LA) effect, indicating that HVS has different sensitivities depending on background luminance values to distortions, has widely been reflected into many existing IQA methods via Weber's law model. In this paper, we firstly reveal that the LA effect based on Weber's law model has inaccurately been reflected into the conventional IQA methods. To solve this problem, we firstly derive a new LA effect-based Local weight Function (LALF) that can elaborately reflect LA effect into IQA methods. We validate the effectiveness of our proposed LALF by applying LALF into SSIM (Structural SIMilarity) and PSNR methods. Experimental results show that the SSIM based on LALF yields remarkable performance improvement of 5% points compared to the original SSIM in terms of Spear rank order correlation coefficient between estimated visual quality values and measured subjective visual quality scores. Moreover, the PSNR (Peak to Signal Noise Ratio) based on LALF yields performance improvement of 2.5% points compared to the original PSNR.