• Title/Summary/Keyword: Information and Communication Technology

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Determinants of Hotel Customers' Use of the Contactless Service: Mixed-Method Approach (호텔 고객의 비대면 서비스 이용의도의 영향요인에 대한 연구)

  • Chung, Hee Chung;Koo, Chulmo;Chung, Namho
    • Knowledge Management Research
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    • v.22 no.3
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    • pp.235-252
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    • 2021
  • The development of information and communication technology and COVID-19 have caused an unusual change in the hotel industry, and the demand for the contactless services such as service robots from hotel customers has surged. Therefore, this study investigates the perception of hotel customers on contactless services by applying a mixed-method analysis. Specifically, this study identified the causal correlations between variables through the structural equation model, and further applied the fuzzy set qualitative comparison analysis to derive patterns of variables that form the intention to use the non-face-to-face services. As a result of the analysis, it was shown that service experience co-creation, palyfulness, personalization, and trust had a significant effect on intention to use through the contactless service use desire. On the other hand, in the results of fuzzy-set qualitative comparison analysis, playfulness was derived as a core factor in all patterns. Based on these analysis results, this study provides academic basis for in-depth understanding of hotel customers' perception of contactless service and specific guidelines for hotel managers on the contactless service strategies in the era of COVID-19 pandemic.

A Study on the Analysis of Miles Training Effect (마일즈 훈련효과 분석에 관한 연구)

  • Lee, Yong-Yeon;Lee, Ho Jun;Kim, Yong-Pil
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.4
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    • pp.353-359
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    • 2021
  • The Army is constructing a training system using Miles equipment that applies the latest science and technology to carry out military training. The Miles training system is a system that uses Miles equipment to simulate the damage situation of combat personnel and equipment in the same way as an actual battlefield by conducting practiced maneuvers in the field. Through this, the training force can experience conditions similar to an actual battle. In particular, the training effects of the warriors participating in the training can be maximized by establishing an integrated system that utilizes cutting-edge science technologies, such as information communication and computer simulation. This study analyzed the effects of Miles training in the army using scientific techniques targeted at the mid-range Miles. In particular, the effect index for analyzing the training effect was derived from a literature survey and expert opinions. The weight of each effect index was calculated by applying the Swing method. The final training effect was calculated by combining the results of the survey from train-experienced people. The Miles training effect was 2.6 times more effective than previous training without using Miles, and the satisfaction rate with Miles training according to status was high through variance analysis, and the difference was statistically significant.

Machine Learning for Predicting Entrepreneurial Innovativeness (기계학습을 이용한 기업가적 혁신성 예측 모델에 관한 연구)

  • Chung, Doo Hee;Yun, Jin Seop;Yang, Sung Min
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.16 no.3
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    • pp.73-86
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    • 2021
  • The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.

Multi-Path Routing Algorithm for Cost-Effective Transactions in Automated Market Makers (자동화 마켓 메이커에서 비용 효율적인 거래를 위한 다중 경로 라우팅 알고리즘)

  • Jeong, Hyun Bin;Park, Soo Young
    • KIPS Transactions on Computer and Communication Systems
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    • v.11 no.8
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    • pp.269-280
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    • 2022
  • With the rise of a decentralized finance market (so called, DeFi) using blockchain technology, users and capital liquidity of decentralized finance applications are increasing significantly. The Automated Market Maker (AMM) is a protocol that automatically calculates the asset price based on the liquidity of the decentralized trading platform, and is currently most commonly used in the decentralized exchanges (DEX), since it can proceed the transactions by utilizing the liquidity pool of the trading platform even if the buyers and sellers do not exist at the same time. However, Automated Market Maker have some disadvantages since the cost efficiency of each transaction using Automated Market Maker depends on the liquidity size of some liquidity pools used for the transaction, so the smaller the size of the liquidity pool and the larger the transaction size, the smaller the cost efficiency of the trade. To solve this problem, some platforms are adopting Transaction Path Routing Algorithm that bypasses transaction path to other liquidity pools that have relatively large size to improve cost efficiency, but this algorithm can be further improved because it uses only a single transaction path to proceed each transaction. In addition to just bypassing transaction path, in this paper we proposed a Multi-Path Routing Algorithm that uses multiple transaction paths simultaneously by distributing transaction size, and showed that the cost efficiency of transactions can be further improved in the Automated Market Maker-based trading environment.

A Case Study on ESG Management in the Age of the Fourth Industrial Revolution - Focused on ESG management of appraisers and Korea Association of Property Appraisers (제4차 산업혁명시대에 있어서 ESG 경영 사례연구 -감정평가사와 한국감정평가협회 ESG 경영 활동을 중심으로)

  • Jeon, Gwang Seop
    • Smart Media Journal
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    • v.11 no.7
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    • pp.28-38
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    • 2022
  • The term 'fourth industrial revolution' was mentioned at the World Economic Forum (WEF) in 2016 and has become a term representing a new industrial era based on information and communication technology (ICT). In the environment of the 4th industrial revolution, ESG management activities are becoming a very important factor in business activities. With the emergence of a new paradigm of organizational operation in the post Covid19 era, the demands for ESG (Environment, Social, Governance) investment related to the environment, social responsibility are increasing. This study examines the role that can support ESG management by utilizing the expertise of appraisers. Real estate is one of the fields of high public interest, and since most ESGs have been conducted centered on the role of private companies, the role of the expert group or the role of public corporations and public institutions is relatively insufficient. If a company or general company engaged in the real estate investment business establishes the role of the Korea Appraisers Association to revitalize ESG management using appraisers, such as ESG appraisers, when investing in real estate, it is believed that it will be possible to promote efficient and sound development of the real estate industry. It was judged that a study on a group of experts was also necessary. In addition, even if the impact of Covid-19 is excluded, it is necessary to gradually introduce an appraisal using non-face-to-face or various advanced technologies (the 4th industry). This study differs from previous studies in that it focused on the role of ESG by the Korea Association of Property Appraisers while research on the role of ESG in public institutions or expert groups is being actively conducted in recent years.

Efficient Stack Smashing Attack Detection Method Using DSLR (DSLR을 이용한 효율적인 스택스매싱 공격탐지 방법)

  • Do Yeong Hwang;Dong-Young Yoo
    • KIPS Transactions on Computer and Communication Systems
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    • v.12 no.9
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    • pp.283-290
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    • 2023
  • With the recent steady development of IoT technology, it is widely used in medical systems and smart TV watches. 66% of software development is developed through language C, which is vulnerable to memory attacks, and acts as a threat to IoT devices using language C. A stack-smashing overflow attack inserts a value larger than the user-defined buffer size, overwriting the area where the return address is stored, preventing the program from operating normally. IoT devices with low memory capacity are vulnerable to stack smashing overflow attacks. In addition, if the existing vaccine program is applied as it is, the IoT device will not operate normally. In order to defend against stack smashing overflow attacks on IoT devices, we used canaries among several detection methods to set conditions with random values, checksum, and DSLR (random storage locations), respectively. Two canaries were placed within the buffer, one in front of the return address, which is the end of the buffer, and the other was stored in a random location in-buffer. This makes it difficult for an attacker to guess the location of a canary stored in a fixed location by storing the canary in a random location because it is easy for an attacker to predict its location. After executing the detection program, after a stack smashing overflow attack occurs, if each condition is satisfied, the program is terminated. The set conditions were combined to create a number of eight cases and tested. Through this, it was found that it is more efficient to use a detection method using DSLR than a detection method using multiple conditions for IoT devices.

Prediction of the Following BCI Performance by Means of Spectral EEG Characteristics in the Prior Resting State (뇌신호 주파수 특성을 이용한 CNN 기반 BCI 성능 예측)

  • Kang, Jae-Hwan;Kim, Sung-Hee;Youn, Joosang;Kim, Junsuk
    • KIPS Transactions on Computer and Communication Systems
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    • v.9 no.11
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    • pp.265-272
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    • 2020
  • In the research of brain computer interface (BCI) technology, one of the big problems encountered is how to deal with some people as called the BCI-illiteracy group who could not control the BCI system. To approach this problem efficiently, we investigated a kind of spectral EEG characteristics in the prior resting state in association with BCI performance in the following BCI tasks. First, spectral powers of EEG signals in the resting state with both eyes-open and eyes-closed conditions were respectively extracted. Second, a convolution neural network (CNN) based binary classifier discriminated the binary motor imagery intention in the BCI task. Both the linear correlation and binary prediction methods confirmed that the spectral EEG characteristics in the prior resting state were highly related to the BCI performance in the following BCI task. Linear regression analysis demonstrated that the relative ratio of the 13 Hz below and above the spectral power in the resting state with only eyes-open, not eyes-closed condition, were significantly correlated with the quantified metrics of the BCI performance (r=0.544). A binary classifier based on the linear regression with L1 regularization method was able to discriminate the high-performance group and low-performance group in the following BCI task by using the spectral-based EEG features in the precedent resting state (AUC=0.817). These results strongly support that the spectral EEG characteristics in the frontal regions during the resting state with eyes-open condition should be used as a good predictor of the following BCI task performance.

A Study on the Function Overlap and Irrational Hierarchy System of Logistics Complexes of Inland Base: Focusing on the Case of the Integrated Freight Terminal in the Yeongnam Area (내륙 거점 물류단지 기능중첩 및 연계체계 불합리성에 관한 연구: 영남권 복합물류 터미널을 사례로)

  • JUNG, Jin Uk;PARK, Woonho;JOH, Chang-Hyeon;PARK, Dongjoo
    • Journal of Korean Society of Transportation
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    • v.34 no.4
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    • pp.304-317
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    • 2016
  • The advancement in technology including transportation and information communication has accelerated the flow of supplies, and the importance of the national logistics policy has increased following the expansion of the regional range of logistics to a national range. The rapid growth of the domestic logistics market results in the deficit of logistics facilities, inefficient operation of logistics facilities, and a complicated distribution structure. It has precipitated a plan aimed at efficiency improvement by building base logistics facilities, but this market is now undergoing difficulties due to low performance. Many studies on the revitalization of base logistics facilities have been conducted, but a causal analysis focusing on the function overlap of private logistics businesses has been absent. Therefore, this study has analyzed the function overlap of logistics facilities and the irrationality of the system, which resulted from the lost function of Inland Freight bases in the Yeongnam region. By suggesting the cause of disuse of base logistics complexes from the function overlap in the ground transportation of domestic freight, the study can provide the policy implication for the national logistics infrastructure.

Conceptual Design of Networking Node with Real-time Monitoring for QoS Coordination of Tactical-Mesh Traffic (전술메쉬 트래픽 QoS 조율을 위한 네트워킹 노드의 개념 설계 및 실시간 모니터링)

  • Shin, Jun-Sik;Kang, Moonjoong;Park, Juman;Kwon, Daehoon;Kim, JongWon
    • Smart Media Journal
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    • v.8 no.2
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    • pp.29-38
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    • 2019
  • With the advancement of information and communication technology, tactical networks are continuously being converted to All-IP future tactical networks that integrate all application services based on Internet protocol. Futuristic tactical mesh network is built with tactical WAN (wide area network) nodes that are inter-connected by a mesh structure. In order to guarantee QoS (quality of service) of application services, tactical service mesh (TSM) is suggested as an intermediate layer between infrastructure and application layers for futuristic tactical mesh network. The tactical service mesh requires dynamic QoS monitoring and control for intelligent QoS coordination. However, legacy networking nodes used for existing tactical networks are difficult to support these functionality due to inflexible monitoring support. In order to resolve such matter, we propose a tactical mesh WAN node as a hardware/software co-designed networking node in this paper. The tactical mesh WAN node is conceptually designed to have multi-access networking interfaces and virtualized networking switches by leveraging the DANOS whitebox server/switch. In addition, we explain how to apply eBPF-based traffic monitoring to the tactical mesh WAN node and verify the traffic monitoring feasibility for supporting QoS coordination of tactical-mesh traffic.

The Effect of Rearing Knowledge on Rearing Satisfaction in Companion Animals (반려동물의 양육지식이 양육만족도에 미치는 영향)

  • Kim, Seok-Eun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.1
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    • pp.333-337
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    • 2021
  • Companion animals are physically, mentally, and socially beneficial to humans, giving us great comfort in living in the Corona19 (COVID-19) era. It is also an era of the Fourth Industrial Revolution, featuring the convergence of information and communication technology. Korea, which is facing a super-aged society, has the highest suicide rate among OECD countries, and companion animals that are effective in emotional stability can be the answer. This study is about companion animals that are effective in stabilizing the emotions of the elderly, one of the major problems in the Republic of Korea, which is about to solve in a super-aged society with more than 20 percent of the elderly aged 65 or older, needs to solve. The impact of knowledge of raising companion animals on the satisfaction level of the elderly was investigated through the management and awareness of infectious diseases. Although the level of care of companion animals had a very significant (p<0.001) effect on the satisfaction of the companion animals, the recognition of infectious diseases has no statistical significance (p>0.05). Raising companion animals with knowledge of rearing increases the satisfaction level and can lead to a happier life. While personal learning is important, it is also believed that supporting education will be necessary as a policy consideration.