• Journal of Korea Society of Industrial Information Systems
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• v.14 no.3
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• pp.15-21
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• 2009

In this paper, we proposed an iterative digital image watermarking technique using encrypted binary phase computer generated hologram in the discrete cosine transform(OCT) domain. For the embedding process of watermark, using simulated annealing algorithm, we would generate a binary phase computer generated hologram(BPCGH) which can reconstruct hidden image perfectly instead of hidden image and repeat the hologram and encrypt it through the XOR operation with key image that is ramdomly generated binary phase components. We multiply the encrypted watermark by the weight function and embed it into the DC coefficients in the DCT domain of host image and an inverse DCT is performed. For the extracting process of watermark, we compare the DC coefficients of watermarked image and original host image in the DCT domain and dividing it by the weight function and decrypt it using XOR operation with key image. And we recover the hidden image by inverse Fourier transforming the decrypted watermark. Finally, we compute the correlation between the original hidden image and recovered hidden image to determine if a watermark exits in the host image. The proposed watermarking technique use the hologram information of hidden image which consist of binary values and encryption technique so it is very secure and robust to the external attacks such as compression, noises and cropping. We confirmed the advantages of the proposed watermarking technique through the computer simulations.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.91-100
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• 2009

In this paper, we propose autonomous intelligent wheelchair system which recognize the commands using the gaze recognition and avoid the detected obstacles by sensing the distance through range sensors on the way to driving. The user's commands are recognized by the gaze recognizer which use a centroid of eye pupil and two reflection points extracted using a camera with infrared filter and two infrared LEDs. These are used to control the wheelchair through the user interface. Then wheelchair system detects the obstacles using 10 ultrasonic sensors and assists that it avoid collision with obstacles. The proposed intelligent wheelchair system consists of gaze recognizor, autonomous driving module, sensor control board and motor control board. The gaze recognizer cognize user's commands through user interface, then the wheelchair is controled by the motor control board using recognized commands. Thereafter obstacle information detected by ultrasonic sensors is transferred to the sensor control board, and this transferred to the autonomous driving module. In the autonomous driving module, the obstacles are detected. For generating commands to avoid these obstacles, there are transferred to the motor control board. The experimental results confirmed that the proposed system can improve the efficiency of obstacle avoidance and provide the convenient user interface to user.

• Journal of Digital Convergence
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• v.20 no.1
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• pp.129-139
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• 2022

This study aims to identify which factors affect successful big data system construction, identify the relationship between the factors, and identify the success model and success factors necessary for public institutions to build big data systems. Therefore, the preceding and related studies related to this study were reviewed, and success factors for the establishment of a big data system were derived based on this. As a research method, a survey was conducted on users of institutions that have established or planned to build a big data system, and a structural equation (AMOS) was conducted to verify the impact relationship between success factors. As a result of the analysis, organizational support factors, development support factors, user support factors, information quality, service quality, system quality, use, and net benefit were derived as success factors for building big data systems, and a success model was presented. This can be seen as significant and academic contributions in that it is the first study of the success model for building an information system reflecting big data characteristics, and it is expected that this study will be used as basic data for building a big data system in public institutions in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.240-257
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• 2022

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.

• Information Systems Review
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• v.23 no.3
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• pp.127-158
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• 2021

Many online travel agencies (OTAs) provide average ratings and time-relevant information or the most recently posted reviews regarding hotels to satisfy customers. To identify these two factors' relative influence on behavioral decision-making processes, we conducted two studies: (1) an experimental research design to explore the relative influence of the two on online review consumption and (2) an empirical approach to examine their relative impact on online review generation. The results show that when review posters observe an inconsistency between average ratings and recent reviews, they tend to deviate from the recent reviews regardless of the overall direction (reactance behavior). Meanwhile, review consumers tend to conform to the opinions presented in recent reviews (herding behavior). Additionally, in both cases, the effects are amplified in case of a negative aberration. Based on the findings, this study provides theoretical and practical implications regarding the relative influences of average rating and recently posted reviews and their different impacts on online review consumption and generation.

• Information Systems Review
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• v.24 no.1
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• pp.105-123
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• 2022

Thanks to the remarkable success of Artificial Intelligence (A.I.) techniques, a new possibility for its application on the real-world problem has begun. One of the prominent applications is the bankruptcy prediction model as it is often used as a basic knowledge base for credit scoring models in the financial industry. As a result, there has been extensive research on how to improve the prediction accuracy of the model. However, despite its impressive performance, it is difficult to implement machine learning (ML)-based models due to its intrinsic trait of obscurity, especially when the field requires or values an explanation about the result obtained by the model. The financial domain is one of the areas where explanation matters to stakeholders such as domain experts and customers. In this paper, we propose a novel approach to incorporate financial domain knowledge into local rule generation to provide explanations for the bankruptcy prediction model at instance level. The result shows the proposed method successfully selects and classifies the extracted rules based on the feasibility and information they convey to the users.

• Information Systems Review
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• v.24 no.1
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• pp.125-155
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• 2022

Platform contrasts with traditional industry in terms of innovativeness as it is rapidly developing with information technology. To redeem preceding researches which have separately focused on either platform acceptance based on technology acceptance model or resistance factors against platform's innovation, this study applied dual factor theory to check the simultaneous influence of enablers and inhibitors on resistance. This study chose purchasers of online used trading platform as a subject of study since it contrasts with other platforms in many characteristics. Based on preceding studies, the moderating effects of their past purchase numbers on the relations between resistance and use intention were also checked. The findings reveal that economic benefit as an enabler had significant negative influence on the resistance, but social influence didn't have expected influence. In case of inhibitors, both perceived complexity and perceived risk had significant positive influence on the resistance. Though resistance had significant negative influence on the use intention, its influence was moderated into the positive direction as users' purchase number increased. Lastly, resistance had mediation effect between antecedent factors (economic benefit and perceived complexity) and use intention.

• Information Systems Review
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• v.22 no.2
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• pp.25-41
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• 2020

Along with the expectation about 5G network commercialization, interests in realistic and immersive media industries such as virtual reality (VR) are increasing. However, most of studies on VR still focus on video technologies instead of factors for popularity and consumption. Thus, the main objective of this research is to identify meaningful factors, which affect the view counts of VR videos and to provide business implications of the content strategies for VR video creators and service providers. Using a regression analysis with 700 VR videos, this study tries to find major factors that affect the view counts of VR videos. As a result, user assessment factors such as number of likes and sicknesses have a strong influence on the view counts. In addition, the result shows that both general information factors (video length and age) and content characteristic factors (series, one source multi use (OSMU), and category) are all influential factors. The findings suggest that it is necessary to support recommendation and curation based on user assessments for increasing popularity and diffusion of VR video streaming.

• Information Systems Review
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• v.18 no.4
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• pp.89-106
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• 2016

The latest movement in live video streaming service is mobile personal broadcasting (MPB), which refers to consumers accessing the service through social media with mobile devices, such as smartphones and tablet PCs. This service is possible through the advancements in mobile video technology and platforms. Features such as enhanced user interaction, personalization, and real-time broadcasting, combined with a greater variety of content, have led to the development of MPB. The increase in MPB users calls for research, including that on the hedonic motivational angle. This study aims to assess MPB users' intrinsic motives through the hedonic-motivation system adoption model (HMSAM) using seven factors: joy, temporal dissociation, escapism, focused immersion, perceived ease of use, perceived usefulness and intention to watch. Survey data collected from 154 samples were analyzed with statistical techniques, such as structural equation modeling. Results showed that time dissociation, escapism, and perceived ease of use have a positive relationship with heightened enjoyment. Joy significantly affects focused immersion and intention to watch. Escapism also had a statistically significant influence on focused immersion. This study contributes to the advancement of the MPB study under the HMSAM theoretical framework and offers practical suggestions to managers to enhance MPB content viewership.

• Information Systems Review
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• v.20 no.1
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• pp.41-59
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• 2018

This study analyzed the factors that affect acceptance of online direct marketing in agricultural companies. Empirical analysis was conducted using the research model based on the individual's technology acceptance model (TAM) and the information technology adoption models in organizations. These models have four dimensions: 1) technology characteristics, which include perceived usefulness and perceived ease of use of TAM 2) CEO characteristics, which including the innovativeness and IT capability of CEOs; 3) organizational readiness, which include financial, technological, and human resources capabilities and 4) environment and external pressure, which include government support and changes to the Internet environment. These concepts were empirically tested. A total of 209 valid data were collected through questionnaires and analyzed using confirmatory factor analysis and path analysis through the application of structural equation modeling. Results show that perceived usefulness, IT capability of CEOs, and changes to the Internet environment have significant effects on the adoption intention of online direct marketing. However, perceived ease of use, CEO innovativeness, government support, and the variables of organizational readiness dimension did not have significant effects on adoption intention. This study suggests practical implications for adoption of online direct marketing in agricultural companies.