• Informatization Policy
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• v.25 no.3
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• pp.75-94
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• 2018

Today, Software as a Service(SaaS) is being recognized as a key means to enable the innovation of software distribution. Despite the increase in the interest in SaaS, individuals as well as businesses are not yet making an extensive use of it. This research is aimed at identifying and analyzing the antecedents of intentions to use SaaS. We proposed a research model to predict an individual's intention to use SaaS based on the Technology Acceptance Model(TAM). To this end, we conducted a questionnaire survey in which actual software users participated. An empirical analysis has been performed to test the reliability and validity and the hypotheses using SPSS and AMOS software packages. The results of the analysis revealed that functionality, interoperability and economic benefits have positive effects on the intention to use SaaS, while system quality has no significant effect on the behavioral intention. We discussed practical as well as academic implications, and provided research directions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.6
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• pp.1-9
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• 2015

Recently, with smart device proliferation and providing the various services using this, they have interested in mobile and Smart TV security. Smartphone users are enjoying various service, such as cloud, game, banking. But today's mobile security solutions and Study of Smart TV Security simply stays at the level of malicious code detection, mobile device management, security system itself. Accordingly, there is a need for technology for preventing hacking and leakage of sensitive information, such as certificates, legal documents, individual credit card number. To solve this problem, a variety of security technologies(mobile virtualization, ARM TrustZone, GlobalPlatform, MDM) in mobile devices have been studied. In this paper, we propose an efficient method to implement security technology based on TYPE-I virtualization using ARM TrustZone technology.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1233-1242
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• 2017

Various attempts have been made to prevent crime risk. One of the cases where outdoor pedestrians are attacked by criminals is the abnormal health condition. When a mental or mental condition that can not sustain normal walking due to drunkenness is exposed, the case of being a crime is revealed through crime case analysis. In this study, we propose a method for estimating the state of an individual that can be detected in outdoor activities. In order to avoid the inconvenience of installing a separate terminal for event information transmission of sensors and sensors, it is possible to estimate an abnormal state by using a 3-axis acceleration sensor built in a smart phone. The state of the user can be estimated by analyzing the momentum of the user and analyzing it with the passage of time. It is possible to distinguish the flow of time at regular intervals, to recognize the activity patterns in each time band, and to distinguish between normal and abnormal. In this study, we have evaluated the total amount of kinetic energy and kinetic energy in each direction of the acceleration sensor and the Fourier transformed value of the total energy amount to distinguish the abnormal state.

• Journal of Convergence for Information Technology
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• v.10 no.1
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• pp.13-21
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• 2020

Due to the dramatic improvement of Internet technologies and digital content authoring, many independent media creators produce various digital items and share them with others. In this situation, the independent media platforms must support the well-defined usage rights(licenses) specification, usage monitoring, and license trading trace for enabling complex types for selling, buying, using and reproducing digital items created by independent media creators. In this paper, we design an extended policy model based on the ODRL policy class model and implement a user interface prototype to specify multi types of usage rights like use, own, share, and cede. Our proposed model can be referenced to create license management modules of the independent media platforms.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2632-2637
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• 2010

Information in UbiComp Environment are transformed to knowledge by relationship in a spatio-temporal location, and then became intelligent contents with task procedures or application models. The entities in U-City has lots of relationships. It is important in U-City contents to provide intelligent and personalized response to meet the intention of users. We extend the spatial ontology model of SPIRIT to other domain. Domain ontologies are consist of type, relation, and instance ontologies. When the relationship model by shared concepts are not defined, we used the spatio-temporal events to find relationships. So we proposed the methods to recommend semantically related terms, not syntactically.

• Journal of the Korea Convergence Society
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• v.12 no.3
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• pp.115-124
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• 2021

The outbreak of covid-19 has brought the characteristics and advantages of non-contact services to increased prominence, and the development of smart hotels"has accelerated. This study aims to identify, categorize and define the smart service experience at different touch points of the customer experience. The concept and characteristics of the smart hotel were examined based on existing research and literature. An analytical framework was designed using smart experience factors and customer touch points of smart hotels. Selected Chinese smart hotels were then examined under this framework. The case analysis results show that the customer experience design of smart hotels has developed to different degrees, in terms of interactivity, personalization, accessibility, information and privacy security. Based on the above findings, this article suggests that the design of smart hotels should use integrated data to further enhance personalized service experience.

• Smart Media Journal
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• v.12 no.4
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• pp.27-40
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• 2023

Many researchers have investigated ways to enhance recommender systems by integrating heterogeneous data to address the data sparsity problem. However, only a few studies have successfully integrated heterogeneous data using knowledge graph. Additionally, most of the knowledge graphs built in these studies only incorporate explicit relationships between entities and lack additional information. Therefore, we propose a method for expanding knowledge graphs by using deep learning to model latent relationships between heterogeneous data from multiple knowledge bases. Our extended knowledge graph enhances the quality of entity features and ultimately increases the accuracy of predicted user preferences. Experiments using real music data demonstrate that the expanded knowledge graph leads to an increase in recommendation accuracy when compared to the original knowledge graph.

• Journal of Platform Technology
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• v.11 no.5
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• pp.37-48
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• 2023

Since the announcement of the Financial Services Commission's 'Token Securities Issuance and Distribution System Improvement Plan' in February 2023, financial institutions, securities firms, and blockchain companies have been actively considering implementing IT platforms, but they are facing difficulties in selecting IT platforms for token securities because related legal regulations have not yet been clearly established. As a result, the need for rational and systematic criteria for the selection of blockchain-based token securities IT platforms has emerged, and this study explores and evaluates the key factors of token securities IT platform selection. Four factors were identified as the top-level factors, including 'maturity of the platform', 'operation and management of the platform', 'cost of introducing and maintaining the platform', and 'regulatory compliance for token securities', and 17 factors were identified as sub-level factors, including 'diversity', 'user authentication management', 'Adoption Costs', and 'financial regulations'. Among the 17 sub-factors, 'government financial regulation' and 'personal information protection' are selected as important factors, and the results of this study can help related organizations and financial companies make strategic decisions by providing systematic decision-making criteria for selecting token securities IT platforms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.4
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• pp.15-20
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• 2024

Local governments are conducting smartphone usage training for the elderly to bridge the information gap caused by a super-aged society. However, the one-to-many educational approach has limitations, and the elderly face difficulties due to insufficient learning effectiveness. This study proposes an educational service that can be used in offline training settings, considering an environment where the elderly can repeatedly learn to address these issues. This service utilizes generative AI to identify the parts that users find challenging and provides personalized problems for individualized practice. Integrating this app with existing local government training programs is expected to significantly enhance the efficiency of smartphone education in terms of personalized 1:1 training, time management, and the appropriateness of educational content.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.671-678
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• 2005

In this paper, we suggest an algorithm that allows us to extract the important obbject from motion pictures and then replace the background with arbitrary images. The suggested technique can be used not only for protecting privacy and reducing the size of data to be transferred by removing the background of each frame, but also for replacing the background with user-selected image in video communication systems including mobile phones. Because of the relatively large size of image data, digital image processing usually takes much of the resources like memory and CPU. This can cause trouble especially for mobile video phones which typically have restricted resources. In our experiments, we could reduce the requirements of time and memory for processing the images by restricting the search area to the vicinity of major object's contour found in the previous frame based on the fact that the movement of major object is not wide or rapid in general. Specifically, we detected edges and used the edge image of the initial frame to locate candidate-object areas. Then, on the located areas, we computed the difference image between adjacent frames and used it to determine and trace the major object that might be moving. And then we computed the contour of the major object and used it to separate major object from the background. We could successfully separate major object from the background and replate the background with arbitrary images.