• Journal of Multimedia Information System
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• v.9 no.1
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• pp.33-42
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• 2022

In this paper, we have recently created self-driving cars and self-parking systems in human-friendly cars that can provide high safety and high convenience functions by recognizing the internal and external situations of automobiles in real time by incorporating next-generation electronics, information communication, and function control technologies. And with the development of connected cars, the ITS (Intelligent Transportation Systems) market is expected to grow rapidly. Intelligent Transportation System (ITS) is an intelligent transportation system that incorporates technologies such as electronics, information, communication, and control into the transportation system, and aims to implement a next-generation transportation system suitable for the information society. By combining the technologies of connected cars and Internet of Things with software features and operating systems, future cars will serve as a service platform to connect the surrounding infrastructure on their own. This study creates a research methodology based on the Enhanced Security Model in Self-Driving Cars model. As for the types of attacks, Availability Attack, Man in the Middle Attack, Imperial Password Use, and Use Inclusive Access Control attack defense methodology are used. Along with the commercialization of 5G, various service models using advanced technologies such as autonomous vehicles, traffic information sharing systems using IoT, and AI-based mobility services are also appearing, and the growth of smart transportation is accelerating. Therefore, research was conducted to defend against hacking based on vulnerabilities of smart cars based on artificial intelligence blockchain.

• Communications of Mathematical Education
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• v.34 no.1
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• pp.1-15
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• 2020

Today's healthcare, intelligent robots, smart home systems, and car sharing are already innovating with cutting-edge information and communication technologies such as Artificial Intelligence (AI), the Internet of Things, the Internet of Intelligent Things, and Big data. It is deeply affecting our lives. In the factory, robots have been working for humans more than several decades (FA, OA), AI doctors are also working in hospitals (Dr. Watson), AI speakers (Giga Genie) and AI assistants (Siri, Bixby, Google Assistant) are working to improve Natural Language Process. Now, in order to understand AI, knowledge of mathematics becomes essential, not a choice. Thus, mathematicians have been given a role in explaining such mathematics that make these things possible behind AI. Therefore, the authors wrote a textbook 'Basic Mathematics for Artificial Intelligence' by arranging the mathematics concepts and tools needed to understand AI and machine learning in one or two semesters, and organized lectures for undergraduate and graduate students of various majors to explore careers in artificial intelligence. In this paper, we share our experience of conducting this class with the full contents in http://matrix.skku.ac.kr/math4ai/.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.368-376
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• 2021

Artificial intelligence clouds help to efficiently develop the autonomous things integrating artificial intelligence technologies and control technologies by sharing the learned models and providing the execution environments. The existing autonomous things development technologies only take into account for the accuracy of artificial intelligence models at the cost of the increment of the complexity of the models including the raise up of the number of the hidden layers and the kernels, and they consequently require a large amount of computation. Since resource-constrained computing environments, could not provide sufficient computing resources for the complex models, they make the autonomous things violate time criticality. In this paper, we propose a digital twin software development framework that selects artificial intelligence models optimized for the computing environments. The proposed framework uses a load estimation DNN model to select the optimal model for the specific computing environments by predicting the load of the artificial intelligence models with digital twin data so that the proposed framework develops the control software. The proposed load estimation DNN model shows up to 20% of error rate compared to the formula-based load estimation scheme by means of the representative CNN models based experiments.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.15-30
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• 2009

As knowledge is now being distributed and shared through the Internet not only in the form of text but also in that of video, UCC (User Created Content) knowledge video sharing services have emerged on the Internet such as Instructables.com. This paper deals with a UCC knowledge video service in real world and reports the case of analyzing its customer model. The knowledge video sharing service can be considered as both a kind of discontinuous innovation, which requires knowledge provider's technical ability of creating and editing UCC video, and a value network, which matches UCC providers and consumers therefore brings network effect, we first adopt the Chasm theory as the base of the customer model and refine the customer model referencing the Technographics, which is also an Internet-refinement of the Chasm model. Finally, non-customer analysis of Blue Ocean strategy is applied for exploring potential customers of the service.

• The Journal of Industrial Distribution & Business
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• v.9 no.3
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• pp.57-68
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• 2018

Purpose - The purpose of this study is to classify that the quality factors for comparing the Visegrard Group with the Nordic Council have historical similarities against Germany and the Soviet Union. However, this is because in the integrated European market, the competitiveness possessed by the two groups of countries is invested in the priority order to grow. Research design, data, and methodology - The study was conducted on the research design, and the reason for trying to compare the competence of the automobile industry in the assessment of industrial capability is that the Visegrard Group focuses on automotive production and the Nordic Association focuses on the commercialization of the automobile(market). In this study, searching and quantifying indirect evidence was made through standards are more complementary in Europe since each country acts like the role of the European automotive industry for example, which is different from the realistic evaluation criteria, are more important than those of the United States(first in the world) or Germany(first in Europe). Results - The results of this study are as follows: In the global EV market U.S.(export: $ 2.62 billion /share: 36.7%), Germany($ 1.29 billion /18.1%), France($ 390 million /5.4%), United Kingdom($ 380 million /5.4%), and South Korea($ 320 million/ 4.4%). South Korea's share of the EV market is 4.4%, while TSI reaches at +0.9 which measures the comparative advantage of a specific commodity in the world trade market. There is great potential for evaluated as products processing in export competition. But, commercialization, standardization, and overall market expansion did not have a positive impact on global satisfaction. Conclusions - EVs put importance on various utilities. So this suggests that Korea's exports to the EU, including the Visegrard Group, should be more focused on marketability when illuminating with a sharing industrial system under the European Union. It is necessary to specialize in manufacturing and commercialization by country(region) to prepare sharing economy and blockchain in order to create a smart-sharing city linked on artificial intelligence, as the commercialization of electric vehicles, which will have a larger growth rate than that of manufacturing in the fourth revolutionary era.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.272-277
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• 2001

In this paper, we describe a new method for selecting information sources in a distributed environment. Recently, there has been much research on distributed information retrieval, that is information retrieval (IR) based on a multi-database model in which the existence of multiple sources is modeled explicitly. In distributed IR, a method is needed that would enable selecting appropriate sources for users\` queries. Most existing methods use statistical data such as document frequency. These methods may select inappropriate ate sources if a query contains polysemous words. In this paper, we describe an information-source selection method using two types of thesaurus. One is a thesaurus automatically constructed from documents in a source. The other is a hand-crafted general-purpose thesaurus(e.g. WordNet). Terms used in documents in a source differ from one another and the meanings of a term differ depending on th situation in which the term is used. The difference is a characteristic of the source. In our method, the meanings of a term are distinguished between by the relationship between the term and other terms, and the relationship appear in the co-occurrence-based thesaurus. In this paper, we describe an algorithm for evaluating a usefulness of a source for a query based on a thesaurus. For a practical application of our method, we have developed Papits, a multi-agent-based in formation sharing system. An experiment of selection shows that our method is effective for selecting appropriate sources.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.120-128
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• 2010

Web development and digital technology enable users not only to consume contents but also to produce and share it through using various media. Thus, since personal needs for contents are increased, the interest in environment and technology for creating digital contents is growing. Because of existing digital contents technology such as writing tool or digital storyboard have focused on the individual creation, it is hard to induce participation and collaboration of other users and sharing and reusing contents. Therefore, we suggest a new form of collaborate digital storytelling using the concept of the collective intelligence through contest. Most of all, we develop writing tool and storyboard tool in order to facilitate participants to produce online contents. Also, distinguished from previous contest, this contest considers not only content output but also collaborative process for making it.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.5
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• pp.169-176
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• 2020

Recently, deep neural networks (DNNs) have brought revolutions to many mobile and embedded devices by providing human-level machine intelligence for various applications. However, high inference accuracy of such DNNs comes at high computational costs, and, hence, there have been significant efforts to reduce computational overheads of DNNs either by compressing off-the-shelf models or by designing a new small footprint DNN architecture tailored to resource constrained devices. One notable recent paradigm in designing small footprint DNN models is sharing parameters in several layers. However, in previous approaches, the parameter-sharing techniques have been applied to large deep networks, such as ResNet, that are known to have high redundancy. In this paper, we propose a parameter-sharing method for already parameter-efficient small networks such as ShuffleNetV2. In our approach, small templates are combined with small layer-specific parameters to generate weights. Our experiment results on ImageNet and CIFAR100 datasets show that our approach can reduce the size of parameters by 15%-35% of ShuffleNetV2 while achieving smaller drops in accuracies compared to previous parameter-sharing and pruning approaches. We further show that the proposed approach is efficient in terms of latency and energy consumption on modern embedded devices.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.1-27
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• 2021

The entire tourism industry is being hit hard by the COVID-19 as a global pandemic. Accommodation sharing services such as Airbnb, which have recently expanded due to the spread of the sharing economy, are particularly affected by the pandemic because transactions are made based on trust and communication between consumer and supplier. As the pandemic situation changes individuals' perceptions and behavior of travel, strategies for the recovery of the tourism industry have been discussed. However, since most studies present macro strategies in terms of traditional lodging providers and the government, there is a significant lack of discussion on differentiated pandemic response strategies considering the peculiarity of the sharing economy centered on peer-to-peer transactions. This study discusses the marketing strategy for individual hosts of Airbnb during COVID-19. We empirically analyze the effect of changes in listing descriptions posted by the Airbnb hosts on listing performance after COVID-19 was outbroken. We extract nine aspects described in the listing descriptions using the Attention-Based Aspect Extraction model, which is a deep learning-based aspect extraction method. We model the effect of aspect changes on listing performance after the COVID-19 by observing the frequency of each aspect appeared in the text. In addition, we compare those effects across the types of Airbnb listing. Through this, this study presents an idea for a pandemic crisis response strategy that individual service providers of accommodation sharing services can take depending on the listing type.

• Korean Security Journal
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• no.61
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• pp.59-85
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• 2019

In the reality that the boundary between the real world and the virtual world disappears with the 4th Industrial Revolution, cyber crimes that occur beyond time and space have clear limitations in fulfilling their duties only with the police force of government organizations established under the real law system. The research method of this thesis is based on the literature research and the experience of security work. The purpose of this paper is to establish a social system where collective intelligence of each social field can participate voluntarily to respond to cyber crimes occurring beyond the time and space before the law and institutionalization. In addition, the social system in which collective intelligence in each social sector can participate voluntarily was established to define crime types in cyberspace in real time and to prevent crimes defined by the people themselves and the counter-measures had been proposed in order to form social consensus. First, it is necessary to establish a collective intelligent network-type cyberpolice volunteer system. The organization consists of professors of security and security related departments at universities nationwide, retired public officials from the National Intelligence Service, the National Police Agency, and the National Emergency Management Agency, security companies and the organizations, civilian investigators, security & guard, firefighting, police, transportation, intelligence, security, national security, and research experts. Second, private sector regulation should be established newly under the Security Business Act. Third, the safety guard of the collective intelligent cyberpolice volunteer system for the stability of the people's lives should strengthen volunteer work. Fourth, research lessons and legal countermeasures against cybercrime in advanced countries should be introduced. Fifth, the Act on the Protection of Personal Information, the Act on Promotion of Information and Communication Network Utilization and Information Protection, the Act on the Utilization and Protection of Credit Information, and the Special Act on the Materials and Parts Industry should be amended. Sixth, police officers should develop cybercrime awareness skills for proactive prevention activities.