• 융합신호처리학회논문지
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• 제24권1호
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• pp.1-14
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• 2023

Underwater images carry information that is useful in the fields of aquaculture, underwater military security, navigation, transportation, and so on. In this research, we transmitted an underwater image through various underwater mediums in the presence of underwater turbulence and beam attenuation effects using a high-speed visible optical carrier signal. The optical beam undergoes scintillation because of the turbulence and attenuation effects; therefore, distorted images were observed at the receiver end. To understand the behavior of the communication media, we obtained the bit error rate (BER) performance of the system with respect to the average signal-to-noise ratio (SNR). Also, the structural similarity index (SSI) and peak SNR (PSNR) metrics of the received image were evaluated. Based on the received images, we employed suitable nonlinear filters to recover the distorted images and enhance them further. The BER, SSI, and PSNR metrics of the specific nonlinear filters were also evaluated and compared with the unfiltered metrics. These metrics were evaluated using the on-off keying and binary phase-shift keying modulation techniques for the 50-m and 100-m links for beam attenuation resulting from pure seawater, clear ocean water, and coastal ocean water mediums.

• Asia pacific journal of information systems
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• 제34권1호
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• pp.351-371
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• 2024

This study aims to assess the impact of chatbot usability and demographics on continuous intention to use across different sectors. The research employed Braun's Bot Usability Scale (BUS11) to measure chatbot usability, focusing on accessibility, quality, conversation quality, privacy risk, and response time. A total of 187 participants completed a survey as part of this study. Variance-based SEM was utilized to examine relationships and test hypotheses. This study contributes to the ongoing discourse on chatbot adoption and user behaviour. It enhances the understanding of chatbot usability, highlighting the role of age in continued intention to use chatbots. The findings suggest that different age groups may possess specific preferences and expectations regarding chatbot usability. These differing preferences can influence their intention to continue using this technology. The study reveals that chatbot usability significantly impacts continuous intention to use and that age moderates the relationship between perceived conversation quality, information, privacy, security, and continuous intention to use. Based on the study's results, it is recommended that chatbot designers enhance usability to promote long-term adoption and usage.

• Asia pacific journal of information systems
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• 제32권4호
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• pp.803-829
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• 2022

With the advances in technology and the trend towards increased computer-based experiential learning in education settings, business games are being increasingly used by business educators. This article utilizes Toulmin's Sensemaking Framework to investigate the sensemaking process of business professionals to reveal how they consciously reason about the value of business games for learning complex business concepts and principles. Using the analysis of responses from 43 business professionals, our study identifies key areas where business professionals find value in business games and the limitations of using business games. First, business games are found to be an effective tool when teaching practical business skill sets to business professionals. Second, business games enhance the overall learning process in professional business training. Third, despite the advantages, some pitfalls in applying business games to practice are found. We also found sub-themes, claims, and argument patterns of how business professionals evaluate the value of business games through a grounded theory qualitative analysis method. Analysis results show several ground-warrant patterns exist in the arguments on values of business games including general principle - causal reasoning, personal experience - generalization, and personal projection - generalization. With these findings, we believe this paper contributes to the theory and practice of business game design, development, and the game playing and learning process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권4호
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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.

• 신재생에너지
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• 제20권1호
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• pp.88-94
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• 2024

This study explored the potential and implementation of renewable energy sources in Sri Lanka, focusing on the theoretical potential of solar and wind energy to develop self-reliant energy models. Using advanced climate data from the European Centre for Medium-Range Weather Forecasts and Global Solar/Wind Atlas provided by the World Bank, we assessed the renewable energy potential across Sri Lanka. This study proposes off-grid and minigrid systems as viable solutions for addressing energy poverty in rural regions. Rural villages were classified based on solar and wind resources, via which we proposed four distinct energy self-reliance models: Renewable-Dominant, Solar-Dominant, Wind-Dominant, and Diesel-Dominant. This study evaluates the economic viability of these models considering Sri Lanka's current energy market and technological environment. The outcomes highlight the necessity for employing diversified energy strategies to enhance the efficiency of the national power supply system and maximize the utilization of renewable resources, contributing to Sri Lanka's sustainable development and energy security.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2024년도 춘계학술발표대회
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• pp.711-714
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• 2024

In the dynamic landscape of modern machine learning, Federated Learning (FL) has emerged as a compelling paradigm designed to enhance privacy by enabling participants to collaboratively train models without sharing their private data. Specifically, Distillation-based Federated Learning, like Federated Learning with Model Distillation (FedMD), Federated Gradient Encryption and Model Sharing (FedGEMS), and Differentially Secure Federated Learning (DS-FL), has arisen as a novel approach aimed at addressing Non-IID data challenges by leveraging Federated Learning. These methods refine the standard FL framework by distilling insights from public dataset predictions, securing data transmissions through gradient encryption, and applying differential privacy to mask individual contributions. Despite these innovations, our survey identifies persistent vulnerabilities, particularly concerning the susceptibility to logit inversion attacks where malicious actors could reconstruct private data from shared public predictions. This exploration reveals that even advanced Distillation-based Federated Learning systems harbor significant privacy risks, challenging the prevailing assumptions about their security and underscoring the need for continued advancements in secure Federated Learning methodologies.

• 농업과학연구
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• 제49권4호
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• pp.971-978
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• 2022

Fertigation, which has been introduced in agricultural fields since 1990, has been widely practiced in upland fields as well as in plastic film houses as part of the crop production system. In accordance with demands in the agricultural sector, a huge number of scientific studies on fertigation have been conducted worldwide. Moreover, with a combination of advanced technologies such as big-data, machine learning, etc., fertigation is positioned as an indispensable tool to achieve sustainable crop production and to enhance nutrient and water use efficiency. In this review, we focused on providing valuable information in terms of crop production and nutrient/water use efficiency. A variety of fertigation studies have described that enhancement of crop production did not differ relative to conventional method or slightly increased. In contrast, fertigation significantly improved nutrient/water use efficiency, with a reduction in use ranging from 20 to 50%. Water-soluble organic resources such as livestock manure and agricultural byproducts also have been identified as useful resources like chemical fertilizers. Furthermore, the initial irrigation point was generally recommended in a range of -10 - -40 kPa, although the point differed according to the crop and crop growth stage. From this review, we suggest that fertigation, which is closely integrated with advanced technology, could be a leading technology to attain not only food security but also carbon neutrality via improvement of nutrient/water use efficiency.

• 품질경영학회지
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• 제52권3호
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• pp.509-527
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• 2024

Purpose: This study aims to investigate the factors influencing the adoption of Generative AI in the workplace, focusing on both enablers and inhibitors. By employing the dual factor theory, this research examines how knowledge support, customization, entertainment, perceived risk, realistic threat, and identity threat impact the intention to adopt Generative AI technologies such as ChatGPT. Methods: Data were collected from 192 participants via MTurk, all of whom had experience using Generative AI. The survey was conducted in June 2024, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to ensure the validity and reliability of the measurement model. Attention-check questions were used to ensure data quality, and participants provided demographic information at the end of the survey. Results: : The findings reveal that knowledge support and entertainment significantly enhance the intention to adopt Generative AI, whereas realistic threat poses a substantial barrier. Customization, perceived risk, and identity threat did not significantly affect adoption intentions. Conclusion: This study contributes to the literature by addressing the gap in understanding the adoption mechanisms of Generative AI in professional settings. It highlights the importance of promoting AI's knowledge support and entertainment capabilities while addressing employees' concerns about job security. Organizations should emphasize these benefits and proactively mitigate perceived threats to foster a positive reception of Generative AI technologies. The findings offer practical implications for enhancing user acceptance and provide a foundation for future research in this area.

• 한국조경학회지
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• 제41권4호
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• pp.56-67
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• 2013

도시 오픈 스페이스의 기능과 역할이 다양해지면서 도시 오픈 스페이스는 도시 엔터테인먼트 목적지(Urban Entertainment Destination, UED)로서 기능이 주목받고 있다. 본 연구는 엔터테인먼트형 도시 오픈 스페이스(EUOS)에 대한 개념을 정립하고, UED 구성요소를 기반으로 EUOS 요소를 구분하고, 이를 국내 도시 오픈 스페이스에 적용시켜 분석하였다. 또한 이용객 설문조사를 통해 이용자가 EUOS로서 대상지를 선택하는 선택속성을 도출하였다. 대상지는 청계천, 서울숲공원, 선유도공원, 반포한강공원으로 하였고, 조사방법으로는 관찰조사, 문헌조사, 설문조사를 수행하였다. 분석방법은 SPSS 18.0을 이용하여 ANOVA 분석과 회귀분석을 실시하였다. 분석결과는 다음과 같다. 첫째, 국내 도시 오픈 스페이스는 EUOS 관점에서 볼 때 8가지 요소를 갖추고 있었다. 8가지 요소는 경관성(Landscape), 핵심시설의 다양성(Multi anchoring), 주변지역 연계성(Contextual links), 프로그램 다양성(Programmability), 커뮤니티성(Community) 브랜드 정체성(Branded identity), 안전성(Security), 이용 편의성(Service)으로 구분되었다. 둘째, 국내 도시 오픈 스페이스를 이용하는 이용객의 이동거리, 이용시간, 이동수단 등의 행태를 분석한 결과, 근린 이용보다는 광역적 이용으로 활용되고 있음을 알 수 있었다. 셋째, 도시 오픈 스페이스를 EUOS로서 이용하는 이용객들은 경관성(Landscape)과 안전성(Security), 이용 편의성(Service)을 가장 중요하게 생각하고 있었으며, 반면에 핵심시설의 다양성(Multi anchoring), 프로그램 다양성(Programmability)과 커뮤니티성(Community)은 상대적으로 중요도를 낮게 생각하고 있었다. 넷째, 재방문이나 전체만족도에 영향을 미치는 요인으로 경관성(Landscape)이 공통적인 요소로 도출되었으며, 재방문에는 안전성(Security)이 전체만족도에는 핵심시설의 다양성(Multi anchoring), 주변지역 연계성(Contextual links)이 경관성(Landscape)과 함께 영향을 미치는 것으로 나타났다. 종합해 보면, 도시 오픈 스페이스가 EUOS로서 기능을 강화하기 위해서는 경관성(Landscape)에 대한 비중을 높혀야 한다. 경관성(Landscape)을 높이기 위해서는 도시 오픈 스페이스의 시설 및 프로그램 향상뿐만 아니라, 이용자의 활동을 통합적으로 고려하여 조성하는 것이 필요하다. 그리고 EUOS로서 활용되는 도시 오픈 스페이스는 집약적 활동과 이용집중이 높은 곳으로 안전이나 조명, 범죄, 장애인 시설 등과 같은 공공서비스에 대한 투자가 이루어져야 한다. 마지막으로 도시 오픈 스페이스의 만족도를 높이기 위해 매력시설의 질적 양적 향상과 주변지역이 연계될 수 있는 광역적 접근의 투자와 개발이 필요한 것으로 판단된다.

• 시큐리티연구
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• 제48호
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• pp.147-176
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• 2016

한반도는 삼면이 바다로 둘러싸여 있는 지정학적 특성으로 인해 수출입 물동량의 97% 이상을 해양을 통하여 교류하고 있으며, 세계화 국제화 추세에 따라 외국적 선박 및 국제 여객선을 통한 외국여행객들의 출입이 증가하는 추세에 있다. 또한 국민소득 향상과 해양에 대한 관심도 높아짐에 따라 해양 레저객이 급증하고 있어 해양에서의 사건, 사고가 연간 끊임없이 발생하고 있다. 해양에서 치안을 담당하는 해양경비안전본부의 관할 면적은 국토의 약4.5배에 달하며, 해안선의 길이는 도서지역 포함하여 14,963km, 안전센터 1개소 당 94km를 관장하고 있으며, 경비함정 1척당 $24,068km^2$를 담당하고 있어 효율적인 순찰 및 방범활동이 이루어지지 않고 있다. 본 연구에서는 이러한 문제 인식아래 해양경비안전본부에서 취급하는 해양 범죄의 현황과 추세를 분석하여 보다 효율적인 순찰, 방범 방안을 제시하고자 한다. 증가하는 해양 범죄에 효율적으로 대응하기 위한 방안으로 1900년대 초 미국에서 개발되어 활용하고 있는 지리적 프로파일링 기법의 도입을 제안하였다. 지리적 프로파일링은 공간분석과 지도화를 응용하여 범죄 위험 지역을 예측하고 상습적으로 발생하는 지역에 대해 특별관리 하는 핫스팟 분석 등 다양한 기법으로 활용되고 있으며, 국내에서도 경찰청에서 2008년부터 도입하여 죄종별, 시간대별, 지역별, 범죄 다발지, 범죄 발생 우려지 등으로 구분하여 일상화된 순찰 개념이 아닌 고도화된 분석에 의한 순찰과 방범활동에 활용하고 있다. 이러한 지리적 프로파일링을 해양에서도 도입하여 해양 범죄를 유형별, 장소별, 시기별, 기간별 등으로 세분화하여 분석, "해양 범죄 지도"를 작성하고, 이를 토대로 살인, 강도, 절도, 실종, 변사, 충돌 등 중요범죄에 대한 위험발생 지역을 "범죄 지점" 일명, 크리미널 포인트(Criminal Point)로 지정 하고 이 지역을 중심으로 시기별, 시간대별로 구분하여 경비함정을 배치하고 정기 또는 수시 경비활동과 방범활동 등을 전개한다면 해양 범죄 및 해양 사고 대응력이 향상될 것으로 기대한다.