• Korean Journal of Social Welfare
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• v.62 no.1
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• pp.317-342
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• 2010

The purpose of this study is to investigate daily lives of the intellectually disabled living in residential facilities. The daily time use method that monitors and records 24 hours of the subject was used for the analysis of daily lives of the institutionalized disabled and verbal interaction patterns within each facility. In particular, the analysis focused on 'frequency of activities' and 'lives', with the method of time budget. Based on the activity category table of the 2004 nationwide Time Use Survey, the analysis aimed to identify differences and similarities between the non-disabled and the disabled in terms of daily time use. The interaction pattern analysis method on grounds of the Flanders Category system(1963) indicates the level, the type, and the full details of interaction between the institutionalized disabled and the living rehabilitation teachers. This study is all the more significant in that it monitored the daily lives of the institutionalized disabled for the first time to allow in-depth understanding about the daily lives of the disabled; analyzed interaction patterns between the institutionalized disabled and living rehabilitation teachers; applied time budget study method, a frequently used one in adjacent fields, and therefore should serve as a valuable source material for future studies.

• Journal of Korea Artificial Intelligence Association
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• v.2 no.1
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• pp.1-6
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• 2024

In this paper, we develop an AI-based recommendation system that matches the specifications of smartphones from company 'S'. The system aims to simplify the complex decision-making process of consumers and guide them to choose the smartphone that best suits their daily needs. The recommendation system analyzes five specifications of smartphones (price, battery capacity, weight, camera quality, capacity) to help users make informed decisions without searching for extensive information. This approach not only saves time but also improves user satisfaction by ensuring that the selected smartphone closely matches the user's lifestyle and needs. The system utilizes unsupervised learning, i.e. clustering (K-MEANS, DBSCAN, Hierarchical Clustering), and provides personalized recommendations by evaluating them with silhouette scores, ensuring accurate and reliable grouping of similar smartphone models. By leveraging advanced data analysis techniques, the system can identify subtle patterns and preferences that might not be immediately apparent to consumers, enhancing the overall user experience. The ultimate goal of this AI recommendation system is to simplify the smartphone selection process, making it more accessible and user-friendly for all consumers. This paper discusses the data collection, preprocessing, development, implementation, and potential impact of the system using Pandas, crawling, scikit-learn, etc., and highlights the benefits of helping consumers explore the various options available and confidently choose the smartphone that best suits their daily lives.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.95-103
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• 2019

According to the Statistics Korea in 2017, the 10 leading causes of death contain a cardiac disorder disease, self-injury. In terms of these diseases, urgent assistance is highly required when people do not move for certain period of time. We propose an unusual event detection algorithm to identify abnormal user behaviors using dust, vision and activity sensors in their houses. Vision sensors can detect personalized activity behaviors within the CCTV range in the house in their lives. The pattern algorithm using the dust sensors classifies user movements or dust-generated daily behaviors in indoor areas. The accelerometer sensor in the smartphone is suitable to identify activity behaviors of the mobile users. We evaluated the proposed pattern algorithms and the fusion method in the scenarios.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.59-66
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• 2019

According to the KT telecommunication statistics, people stayed inside their houses on an average of 11.9 hours a day. As well as, according to NSC statistics in the united states, people regardless of age are injured for a variety of reasons in their houses. For purposes of this research, we have investigated an abnormal event detection algorithm to classify infrequently occurring behaviors as accidents, health emergencies, etc. in their daily lives. We propose a fusion method that combines three classification algorithms with vision pattern, audio pattern, and activity pattern to detect unusual user events. The vision pattern algorithm identifies people and objects based on video data collected through home CCTV. The audio and activity pattern algorithms classify user audio and activity behaviors using the data collected from built-in sensors on their smartphones in their houses. We evaluated the proposed individual pattern algorithm and fusion method based on multiple scenarios.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.321-327
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• 2021

Mobile devices have recently developed to be an integral part of humans' daily lives because they meet business and personal needs. It is challenging to design a feasible and effective user authentication method for mobile devices because security issues and data privacy threats have significantly increased. Biometric approaches are more effective than traditional authentication methods. Therefore, this paper aims to analyze the existing biometric user authentication methods on mobile platforms, particularly those that use face recognition, to demonstrate the methods' feasibility and challenges. Next, this paper evaluates the methods according to seven characteristics: universality, uniqueness, permanence, collectability, performance, acceptability, and circumvention. Last, this paper suggests that solely using the method of biometric authentication is not enough to identify whether users are authentic based on biometric traits.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.233-239
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• 2020

Due to the development of digital technology, users can record their daily lives without being restricted by time and space. The trend is growing rapidly, but lifelogging cases are still insufficient. Google's Timeline and domestic application 'Daily' were analyzed through in-depth interviews. Based on the Creating Pleasurable Interface Model, the factors influencing user satisfaction were identified by the Reckard 7-point scale based on the Honeycomb model. The results of the in-depth interviews and the 7-point scale were similar, and we could see what and why users preferred the recording application. This study is meaningful to evaluate the user experience for recording application and analyzing the needs of users obtained through in-depth interviews to assess the usability that provide a service record and recall.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.5
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• pp.189-203
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• 2021

Environmental changes, which are strongly requiring technological cooperation, such as technological development and strategic alliances according to industrial ecosystem change, have a significant impact on not only product quality but also services. Thus, there is a need for 'servitization' that can satisfy the needs of customers and the ecosystem of businesses through the convergence of manufacturing companies and services. This study uses the Expectation-Confirmation Model to examine the impact on user satisfaction and Continuance Usage Intention. Research(Study) was conducted on users who are using high-tech-based cars. For this, we used Expectation Confirmation(match expections for the user's pre-and post-use relationships), Perceived Ease, Perceived Usefulness, User Satisfaction and Habitual Use and using Continuance Usage Intention as a dependent variable. Their causation was examined with the spss 26.0 and smartpls 2.0 statistical programs. As implications of this study, Expectation Confirmation has been shown to have significant positive effects on Perceived Ease, Perceived Usefulness, User Satisfaction and Habitual Use. For this results, the expectations before and after the use of high-tech cars lead to improved daily lives convenience and(or) work efficiency, leading to user satisfaction and further Continuance Usage Intention. Motors consider it important to pursue the work improvements that consumers want and use it useful in daily lives in the production and sale of high-tech cars. It is expected that it will create natural habits for services that users are satisfied with, and that these habits will affect the continuous growth and understanding of the trend of change.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.77-82
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• 2010

Residential network is the hybrid technology of wireless, Ethernet, Bluetooth and RF to the internet via broadband connection at home to facilitate the convenient, safe and pleasant daily lives of home user with various home network services regardless of device, time and place. For ubiquitous development more devices will be wireless and most of them will be roaming. Since these roaming devices carry private information of daily life of residential users, the interaction among the roaming devices of residential network must be secure. This paper presents to secure registration of roaming devices using IP Security (IPSec) Protocol Suite without the need to trust foreign agents.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1471-1481
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• 2016

As concern about IoT is increasing recently, various IoT services are being launched. Smart home is closely related to our daily life by combining IoT with user's residential space. Therefore, if an unauthorized user accesses a device inside a Smart home, it can cause more serious damage to user as it is related with daily lives. For instance executing the command allowing unauthenticated access for the internal locking device can be a real harm to user's property like a home invasion. To prevent this problem, this paper introduces 3PAKE Techniques, which provides authenticated Key exchange through Home gateway using Password-based Authenticated Key Exchange(PAKE).

• Journal of Families and Better Life
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• v.27 no.3
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• pp.201-212
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• 2009

The purpose of research is to investigate patterns and diffusion of consumer participation on Internet UCC based on digital contents services. A sample survey of internet users was conducted, responses were collected from 629 respondents and consumer streaming data were analyzed. Some of the practical implications of the results are follows. Research can find out that patterns of user participation in UCC. The major genres of UCC are like daily lives of individuals, humors, parodies of star entertainers and types of contents like still pictures or images, texts are relatively highly generated comparing with multimedia UCC. Although participants have been being increased in UCC recently, the consumers as prosumers who are classified in contents generating group are ten percents at the most. In generating community-based UCC such as posting answers of questions and activities in Blog, prosumers who are in contents making group(recreational group) show more positive attitudes than simple participants(consuming only). The results of multiple regression analysis indicated that fun & entertainment, arousal, self-expression, user friendly web interface variable commonly posited a significant effect in multimedia UCC Services between two groups. Information sharing and perceived usefulness posited a significant effect in recreational group.