• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.15-21
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• 2020

Although IoT systems are used in a variety of heterogeneous environments as cloud environments develop, all IoT devices are not provided with reliable protocols and services. This paper proposes an IoT data management technique that can extend the IoT cloud environment to an n-layer multi-level structure so that information collected from different heterogeneous IoT devices can be efficiently sorted and processed. The proposed technique aims to classify and process IoT information by transmitting routing information and weight information through wireless data link data collected from heterogeneous IoT devices. The proposed technique not only delivers information classified from IoT devices to the corresponding routing path but also improves the efficiency of IoT data processing by assigning priority according to weight information. The IoT devices used in the proposed technique use each other's reliable protocols, and queries for other IoT devices locally through a local cloud composed of hierarchical structures have features that ensure scalability because they maintain a certain cost.y channels of IoT information in order to make the most of the multiple antenna technology.

• Journal of the Korean Applied Science and Technology
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• v.38 no.1
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• pp.241-262
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• 2021

This paper reviewed the necessity of a information and communication technology (ICT)-based smart livestock system as a development strategy for the animal life industry in the future. It also predicted the trends of livestock and animal food until 2050, 30 years later. Worldwide, livestock raising and consumption of animal food are rapidly changing in response to population growth, aging, reduction of agriculture population, urbanization, and income growth. Climate change can change the environment and livestock's productivity and reproductive efficiencies. Livestock production can lead to increased greenhouse gas emissions, land degradation, water pollution, animal welfare, and human health problems. To solve these issues, there is a need for a preemptive future response strategy to respond to climate change, improve productivity, animal welfare, and nutritional quality of animal foods, and prevent animal diseases using ICT-based smart livestock system fused with the 4th industrial revolution in various aspects of the animal life industry. The animal life industry of the future needs to integrate automation to improve sustainability and production efficiency. In the digital age, intelligent precision animal feeding with IoT (internet of things) and big data, ICT-based smart livestock system can collect, process, and analyze data from various sources in the animal life industry. It is composed of a digital system that can precisely remote control environmental parameters inside and outside the animal husbandry. The ICT-based smart livestock system can also be used for monitoring animal behavior and welfare, and feeding management of livestock using sensing technology for remote control through the Internet and mobile phones. It can be helpful in the collection, storage, retrieval, and dissemination of a wide range of information that farmers need. It can provide new information services to farmers.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.81-93
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• 2021

Through processors, wholesale markets, intermediate sellers, and retailers, agricultural products have been distributed in a multi-level customary manner for a long time as they are easy to deteriorate and no not have a standardized system of size and quality. However, with the advancement of Internet networks and logistic services during the 2000s that facilitated the development of offline markets, and the rise of the non-contact purchase preference in direct response to COVID-19, previous offline consumers flowed into the online market to purchase agricultural goods. In other words, the volume of online agricultural transactions exploded since the pandemic. Against this social backdrop, this study focused on the difference in distribution costs as a result of converting from conventional offline distribution channels to online channels, and analyzed the reduced distribution costs through a case study of garlic sales on the online platform "H" shopping mall. The analysis found that considerable economic effects occurred, some of the effects being an approximate 39% decrease in distribution cost when comparing direct online transactions of the online shopping mall with other more traditional means, a reduced distribution cost rate of approximately 28%p, and increased profit for farmers.

• Informatization Policy
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• v.29 no.1
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• pp.38-59
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• 2022

The development of IT technology and the spread of smartphones are having a great impact on businesses and consumers. Consumers have been able to acquire more diverse and larger amounts of information than in the past due to information provided through smartphones and information search on the internet, which has a significant influence on decision-making. Companies have also become sensitive to such changes in consumer behavior patterns, reflected in their marketing. In addition, among the various characteristics of smartphones, location-based technology has become an important factor in providing targeted marketing from a company's point of view. Such technological development and social change have led to the expansion of the mobile advertising market, which promotes products or services based on the location of consumers and provides benefits such as discount coupons. In this study, we have analyzed the influence of consumer characteristics on intention to use in mobile location-based advertising, which has become an important marketing method in the mobile advertising market. The effects of variables of personalization, engagement, coupon proneness, economic efficiency, and irritation on attitude and information privacy concerns were analyzed, and the effects of attitude and information privacy concerns on intention to use were analyzed. The results of this study are deemed to be able to suggest factors to consider when providing mobile location-based advertising to consumers in the future.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.583-590
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• 2021

This study was attempted to identify the current status of education of gerontological nursing at nursing colleges across the country and to check whether 19 senior nursing competencies suggested by the American Association of Nursing Colleges are reflected in the courses. The subjects of this study were 198 nursing education institutions accredited by KABONE, and each university's website, department homepage, university handbook, admission-related information, curriculum table, and syllabus were collected and analyzed through an internet search engine. The collected syllabus and the most recent curriculum table of the elderly nursing course were checked and analyzed using SPSS 23.0. The current status of gerontological nursing management was presented by calculating the frequency and percentage, and the educational contents presented in the syllabus were analyzed based on 19 geriatric nursing competencies presented by AACN. 185 institutions (93.43%) operated the geriatric nursing subjects, 98 institutions (49.49%) offered theory subject, and 84 institutions (42.42%) offered both theory and practice. In the case of compulsory majors, 52.92% had the most, 27.84% for the first semester of the 4th year, and 53.54% for 2 credits. As a result of analyzing the lesson plan, communication-related educational competency was included in 40% of cases. As AACN gerontological nursing competency 'effective information provision ability for the elderly', 'ethical and non-coercive decision-making', 'care without restraint', 'safe and effective transition across levels of care' was not included in the education content. In conclusion, gerontological nursing education has been focused on disease, and effective information provision capabilities including communication with the elderly need to be reflected.

• Journal of Korea Entertainment Industry Association
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• v.14 no.6
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• pp.13-27
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• 2020

This study aims to analyze the effect on the adherence intention of enterprise image, trust, and relationship maintenance by the relation marketing in companies, especially in design companies, to examine the relationship establishment in the operation and communication between customers (users) on using the company's service and the member working for the company, and to suggest its substantiation of the mutual satisfaction effect. The research method was, first, analyzed based on the data collected after examining the published domestic and foreign papers, academic journals, publications, books, and internet in order to conduct the theoretic consideration. Also, for objective validity and empirical proof, the empirical analysis was conducted on the survey conducted and collected over two months for the employees of design companies living in Seoul and Gyeonggi-do, and the results are as follows. First, the result of verifying the relationship between relationship marketing and trust showed that the company's expertise does not significantly affect its trust while the company's communication and reputation affect significantly on trust. Second, the relationship between relationship marketing and sustainability has been verified that all variables, such as expertise, communication and reputation does not significantly effect the relationship maintenance. Third, the company's trust has significant effect on relationship maintenance. In addition, the implication and limitation of the study related to this were suggested in the conclusion.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.185-200
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• 2022

The innovative development of museum cultural products is an important way for museums to play the function of cultural communication with their collections. In the context of consumer upgrading, traditional cultural product design and sales methods gradually fail to meet the diverse needs of consumers. This study aims to propose the construction of a customized interactive experience platform for museum cultural products, promote the development of museum cultural products, and facilitate the inheritance and preservation of museum culture. The research methodology analyzes the model and characteristics of existing cultural product customization platforms by collating existing literature studies, and distributes 159 questionnaires to investigate the needs of cultural product consumers, and finally combines the customization experience with existing e-tailing platform systems according to user needs, proposes a theoretical framework and conducts design practice and usability testing using the Shenyang Palace Museum as an example. The findings show that users have a high acceptance of the customized platform for cultural products and that the design of the customized platform can be used to promote the dissemination of the cultural connotations of museums, optimize the personalized user experience of cultural products, and provide new ideas for the development, design, and retailing of museum cultural products. Based on the above findings, this paper suggests that museums' cultural product development can utilize the design model of customized platforms to further enhance consumers' personalized service experience.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.95-117
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• 2022

With the emergence of various media types due to the development of Internet technology, advertisers have difficulty choosing media suitable for corporate advertising strategies. There are challenging to effectively reflect consumer contextual information when advertising media is selected based on traditional marketing strategies. Thus, a recommender system is needed to analyze consumers' past data and provide advertisers with personalized media based on the information consumers needs. Since the traditional recommender system provides recommendation services based on quantitative preference information, there is difficult to reflect various contextual information. This study proposes a methodology that uses deep learning to recommend personalized media to advertisers using consumer contextual information such as consumers' media viewing time, residence area, age, and gender. This study builds a recommender system using media & consumer research data provided by the Korea Broadcasting Advertising Promotion Corporation. Additionally, we evaluate the recommendation performance compared with several benchmark models. As a result of the experiment, we confirmed that the recommendation model reflecting the consumer's contextual information showed higher accuracy than the benchmark model. We expect to contribute to helping advertisers make effective decisions when selecting customized media based on various contextual information of consumers.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.175-185
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• 2023

Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.139-149
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• 2010

Internet was designed for network scalability and best-effort service which makes all hosts connected to Internet to be vulnerable against attack. Many papers have been proposed about attack detection algorithms against the attack using IP spoofing and DoS/DDoS attack. Purpose of DoS/DDoS attack is achieved in short period after the attack begins. Therefore, DoS/DDoS attack should be detected as soon as possible. Attack detection algorithms using false alarm rates consist of the false negative rate and the false positive rate. Moreover, they are important metrics to evaluate the attack detections. In this paper, we analyze the performance of the attack detection algorithms using the impact of false negative rate and false positive rate variation to the normal traffic and the attack traffic by simulations. As the result of this, we find that the number of passed attack packets is in the proportion to the false negative rate and the number of passed normal packets is in the inverse proportion to the false positive rate. We also analyze the limits of attack detection due to the relation between the false negative rate and the false positive rate. Finally, we propose a solution to minimize the limits of attack detection algorithms by defining the network state using the ratio between the number of packets classified as attack packets and the number of packets classified as normal packets. We find the performance of attack detection algorithm is improved by passing the packets classified as attacks.