• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4706-4724
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• 2020

With various structured data, such as the company size, loan balance, and savings accounts, the voice of customer (VOC), which is text data containing contact history and counseling details was analyzed in this study. To analyze unstructured data, the term frequency-inverse document frequency (TF-IDF) analysis, semantic network analysis, sentiment analysis, and a convolutional neural network (CNN) were implemented. A performance comparison of the models revealed that the predictive model using the CNN provided the best performance with regard to predictive power, followed by the model using the TF-IDF, and then the model using semantic network analysis. In particular, a character-level CNN and a word-level CNN were developed separately, and the character-level CNN exhibited better performance, according to an analysis for the Korean language. Moreover, a systematic selection model for optimal text mining techniques was proposed, suggesting which analytical technique is appropriate for analyzing text data depending on the context. This study also provides evidence that the results of previous studies, indicating that individual customers leave when their loyalty and switching cost are low, are also applicable to corporate customers and suggests that VOC data indicating customers' needs are very effective for predicting their behavior.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1246-1262
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• 2021

Recent studies have demonstrated the strong ability of deep convolutional neural networks (CNNs) to significantly boost the performance in single image super-resolution (SISR). The key concern is how to efficiently recover and utilize diverse information frequencies across multiple network layers, which is crucial to satisfying super-resolution image reconstructions. Hence, previous work made great efforts to potently incorporate hierarchical frequencies through various sophisticated architectures. Nevertheless, economical SISR also requires a capable structure design to balance between restoration accuracy and computational complexity, which is still a challenge for existing techniques. In this paper, we tackle this problem by proposing a competent architecture called Enhanced U-Net Network (EUN), which can yield ready-to-use features in miscellaneous frequencies and combine them comprehensively. In particular, the proposed building block for EUN is enhanced from U-Net, which can extract abundant information via multiple skip concatenations. The network configuration allows the pipeline to propagate information from lower layers to higher ones. Meanwhile, the block itself is committed to growing quite deep in layers, which empowers different types of information to spring from a single block. Furthermore, due to its strong advantage in distilling effective information, promising results are guaranteed with comparatively fewer filters. Comprehensive experiments manifest our model can achieve favorable performance over that of state-of-the-art methods, especially in terms of computational efficiency.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.295-303
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• 2022

Information and communication technology (ICT) is one of the primary zones that stimulates economic development in today's globalized world. It promotes technological developments in worldwide communication and manufacturing systems, as well as economic growth and development. Many economic activities, such as international trade and foreign direct investment, rely heavily on contemporary information and communications technologies (FDI). The goal of this study is to look at the dynamic relationship between FDI, ICT, trade openness, and economic growth in the context of BRICS countries from 2000 to 2018, with Gross Domestic Product as the dependent variable and Telephone subscriptions, Mobile subscriptions, Broadband subscriptions, Internet subscribers, Secure internet servers, Trade, and Foreign direct investment as the independent variables.Two variables are used as proxies to manage the macroeconomic environment, while five variables are used as proxies for ICT infrastructures. The outcomes of this study are analyzed using Generalized Methods of Movements (GMM). According to this study, ICT has a positive impact on the economic growth of a few countries. Trade openness and foreign direct investment, on the other hand, have a negative impact on economic growth. As growing countries, the BRICS must participate in economic reform and liberalization measures. This report suggests policy proposals for improving ICT standards, focusing especially on economic growth, trade openness, and increasing foreign investment in the BRICS countries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2976-2990
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• 2022

The adaptive adjustment of reference or weight vectors in decomposition-based methods has been a hot research topic in the evolutionary community over the past few years. Although various methods have been proposed regarding this issue, most of them aim to diversify solutions in the objective space to cover the true Pareto fronts as much as possible. Different from them, this paper proposes a knee point-based reference vector adaptive adjustment strategy to concurrently balance the convergence and diversity. To be specific, the knee point-based reference vector adaptive adjustment strategy firstly utilizes knee points to construct the adaptive reference vectors. After that, a new fitness function is defined mathematically. Then, this paper further designs a many-objective evolutionary algorithm with knee point-based reference vector adaptive adjustment strategy, where the mating operation and environmental selection are designed accordingly. The proposed method is extensively tested on the WFG test suite with 8, 10 and 12 objectives and MPDMP with state-of-the-art optimizers. Extensive experimental results demonstrate the superiority of the proposed method over state-of-the-art optimizers and the practicability of the proposed method in tackling practical many-objective optimization problems.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.208-209
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• 2023

IT(Information Technology) 기술이 고도화됨에 따라 금융 분야에서는 스마트 컨트랙트에 기반하여 자산을 거래할 수 있는 DeFi(Decentralized Finance)가 발전하고 있다. 또한, 다양한 IoT(Internet of Things) 기기들로 구성된 융합환경이 상호 연결되며 IoBE(Internet of Blended Environment)가 조성되고 있다. IoBE의 구성요소 중 의료융합환경인 디지털 헬스케어는 스마트 의료 기기를 통해 진료서비스를 제공한다. 최근에는 디지털 헬스케어 내 자산 거래 수단으로 DeFi를 활용하기 위한 연구가 진행되고 있다. 그러나, 디지털 헬스케어 서비스에 DeFi가 활용될 수 있음에 따라 DeFi 내 보안 위협이 전파될 수 있다. 전파된 보안 위협은 DeFi에서의 디지털 화폐 탈취뿐만 아니라, 디지털 헬스케어 내민감 정보 탈취, 서비스 거부 공격 등 복합 위협으로 이어질 수 있다. 따라서, 본 논문에서는 DeFi의 취약점을 분석하고 이를 기반으로 디지털 헬스케어에서 발생 가능한 공격 시나리오를 도출한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.704-719
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• 2024

Botnet pandemics are becoming more prevalent with the growing use of mobile phone technologies. Mobile phone technologies provide a wide range of applications, including entertainment, commerce, education, and finance. In addition, botnet refers to the collection of compromised devices managed by a botmaster and engaging with each other via a command server to initiate an attack including phishing email, ad-click fraud, blockchain, and much more. As the number of botnet attacks rises, detecting harmful activities is becoming more challenging in handheld devices. Therefore, it is crucial to evaluate mobile botnet assaults to find the security vulnerabilities that occur through coordinated command servers causing major financial and ethical harm. For this purpose, we propose a hybrid analysis approach that integrates permissions and API and experiments on the machine-learning classifiers to detect mobile botnet applications. In this paper, the experiment employed benign, botnet, and malware applications for validation of the performance and accuracy of classifiers. The results conclude that a classifier model based on a simple decision tree obtained 99% accuracy with a low 0.003 false-positive rate than other machine learning classifiers for botnet applications detection. As an outcome of this paper, a hybrid approach enhances the accuracy of mobile botnet detection as compared to static and dynamic features when both are taken separately.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.903-921
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• 2024

Industry 5.0 puts forward higher requirements for smart cities, including low-carbon, sustainable, and people-oriented, which pose challenges to the design of smart cities. In response to the above challenges, this study introduces the cyber-physical-social system (CPSS) and parallel system theory into the design of smart cities, and constructs a smart city framework based on parallel system theory. On this basis, in order to enhance the security of smart cities, a sustainable patrol subsystem for smart cities has been established. The intelligent patrol system uses a drone platform, and the trajectory planning of the drone is a key problem that needs to be solved. Therefore, a mathematical model was established that considers various objectives, including minimizing carbon emissions, minimizing noise impact, and maximizing coverage area, while also taking into account the flight performance constraints of drones. In addition, an improved metaheuristic algorithm based on ant colony optimization (ACO) algorithm was designed for trajectory planning of patrol drones. Finally, a digital environmental map was established based on real urban scenes and simulation experiments were conducted. The results show that compared with the other three metaheuristic algorithms, the algorithm designed in this study has the best performance.

• The Journal of Society for e-Business Studies
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• v.10 no.2
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• pp.1-19
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• 2005

Due to the phenomenal growth in mobile internet users, mobile business as a type of applications of mobile internet has attracted the related industries' and academic researchers' attentions. However, most researchers focus on the issues of Mobile B2C collecting survey questions from consumers or internet users. This paper points out that Mobile B2B has distinct service sector and analyzes the current trend and demand of Mobile B2B in Korea by collecting survey questionnaire from specialists in mobile industries and people in universities and research institutes. Survey fields include business, market, contents/application, research and development and legal system. According to the survey results, Mobile B2B business will rise in distribution, finance, sales, and logistics industries from the beginning of 2005 using wireless PDA and the important preconditions will be security, certification, and standardization.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.49-65
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• 2018

The purpose of the research is to identify the effects of brand evidence, brand personality and negative factors on extended brand trust and customer purchase intention in IoT (Internet of Things) service. Negative factors include scarcity marketing and privacy concern. To achieve this objective, we analyzed the 269 respondents who had used Xiaomi products at least more than once. The results of this study are as follows: First, it was found that core service, self-image congruence of brand evidence and brand personality has a positive influence on extended brand trust. But, perceived price of brand evidence is not related to extended brand trust. Secondly, Scarcity marketing influenced extended brand trust. But, Privacy concern is not related to extended brand trust. Consumers did not realize privacy because of technological innovation of IoT. Thus, the research has a different significance from antecedent research.

• The Journal of the Korea institute of electronic communication sciences
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• v.3 no.4
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• pp.304-312
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• 2008

In this study, the performance analysis was divided into the public sector and private business sector. The four perspectives of the BSC performance analysis for the private business sector can be applied to all of the enterprises as there are Logical Linkages between the four Perspectives. However, these can not be applied in the same way to the public sector. There is no Logical Linkage between public sector and private sectors. Therefore, since there is no Logical Linkage, the KIX project of the public sector has a constrained condition. With the internal and external perspective views, the BSC of the KIX identifies the quality(operation) factor, user(customer) satisfaction factor, and economic costs effects(finance) factor. Based on the linkage model in both the internal and external perspective views and the BSC performance analysis of these views, a performance analysis model was developed and then performance results were analyzed of the whole KIX project.