• Title/Summary/Keyword: real-world challenges

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A Data Factorization Study for the Application of Digital Twin Technology to Container Ports (컨테이너 항만의 디지털 트윈 기술 적용을 위한 데이터 요인화 연구)

  • Nam, Jung-Woo;Kim, Yul-Seong;Shin, Young-Ran
    • Journal of Navigation and Port Research
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    • 제46권1호
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    • pp.42-56
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    • 2022
  • Due to the 4th Industrial Revolution announced at the Davos Forum, the World Economic Forum, in 2016, industrial trends around the world are changing rapidly and intelligently. Among them, the digital twin is drawing attention from all industries as a groundbreaking technology that reduces unnecessary costs and trial and error by implementing real objects, systems, and environments in the same way in the real virtual world and using them to perform simulation analysis. In particular, there is a lot of interest in the application of digital twin technology in solving ports safety and efficiency challenges at once. However, there is a lack of in-depth research for the application of digital twin technology in the port, and in particular, there is a lack of research on measurable data for the implementation of the digital twin in ports. The purpose of this study was to increase granularity and connectivity through measurable data investigation for the application of digital twin technology at container ports. Based on the study results, data factors for container port application were classified into crane data, operational data, physical data, and transportation data, and factor composition, correlation with factors, and fitness were confirmed through confirmatory factor analysis.

Proposal of a sustainable K-Culture Festival Strategy (한국문화축제 전략 제언)

  • Kim, Hyejn Joy
    • The Journal of the Convergence on Culture Technology
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    • 제8권4호
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    • pp.213-217
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    • 2022
  • It is a time when a sustainable Korean Culture Festival strategy is needed. The Korean Culture Festival is a Hallyu Culture Festival that comprehensively introduces various Korean cultures such as Korean food, beauty, and fashion with the focus on K content, which has been leading the global craze since 2020. As the core project of the promotion of Neo Hallyu by the Ministry of Culture and Gymnasium, the 2021 Korean Culture Festival, which was based on the World K-Pop concert and the K-Culture Fan Fair, including holding the first face-to-face concert that applied the stage of real-world content after Covid-19, as well as conducting and exhibiting various fan participation challenges, must now make the leap to the global Hallyu Culture Festival. To this end, it can consist of drama, K-pop, K-Culture Fan Fair, K-Meetup, K-Culture Parade, and Awards. This distinction shows a classic festival program centered around the prosumer content that drives the Korean Wave, and in order for this philosophy to be effectively linked to its contemporaries, a Business to Business (B2B) and Business to Consumer (B2C) 'Techtainment Strategy' is needed to acquire potential customers through learned playfulness.

Structural health monitoring of high-speed railway tracks using diffuse ultrasonic wave-based condition contrast: theory and validation

  • Wang, Kai;Cao, Wuxiong;Su, Zhongqing;Wang, Pengxiang;Zhang, Xiongjie;Chen, Lijun;Guan, Ruiqi;Lu, Ye
    • Smart Structures and Systems
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    • 제26권2호
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    • pp.227-239
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    • 2020
  • Despite proven effectiveness and accuracy in laboratories, the existing damage assessment based on guided ultrasonic waves (GUWs) or acoustic emission (AE) confronts challenges when extended to real-world structural health monitoring (SHM) for railway tracks. Central to the concerns are the extremely complex signal appearance due to highly dispersive and multimodal wave features, restriction on transducer installations, and severe contaminations of ambient noise. It remains a critical yet unsolved problem along with recent attempts to implement SHM in bourgeoning high-speed railway (HSR). By leveraging authors' continued endeavours, an SHM framework, based on actively generated diffuse ultrasonic waves (DUWs) and a benchmark-free condition contrast algorithm, has been developed and deployed via an all-in-one SHM system. Miniaturized lead zirconate titanate (PZT) wafers are utilized to generate and acquire DUWs in long-range railway tracks. Fatigue cracks in the tracks show unique contact behaviours under different conditions of external loads and further disturb DUW propagation. By contrast DUW propagation traits, fatigue cracks in railway tracks can be characterised quantitatively and the holistic health status of the tracks can be evaluated in a real-time manner. Compared with GUW- or AE-based methods, the DUW-driven inspection philosophy exhibits immunity to ambient noise and measurement uncertainty, less dependence on baseline signals, use of significantly reduced number of transducers, and high robustness in atrocious engineering conditions. Conformance tests are performed on HSR tracks, in which the evolution of fatigue damage is monitored continuously and quantitatively, demonstrating effectiveness, adaptability, reliability and robustness of DUW-driven SHM towards HSR applications.

Deep-Learning-Based Mine Detection Using Simulated Data (시뮬레이션 데이터 기반으로 학습된 딥러닝 모델을 활용한 지뢰식별연구)

  • Buhwan Jeon;Chunju Lee
    • Journal of The Korean Institute of Defense Technology
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    • 제5권4호
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    • pp.16-21
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    • 2023
  • Although the global number of landmines is on a declining trend, the damages caused by previously buried landmines persist. In light of this, the present study contemplates solutions to issues and constraints that may arise due to the improvement of mine detection equipment and the reduction in the number of future soldiers. Current mine detectors lack data storage capabilities, posing limitations on data collection for research purposes. Additionally, practical data collection in real-world environments demands substantial time and manpower. Therefore, in this study, gprMax simulation was utilized to generate data. The lightweight CNN-based model, MobileNet, was trained and validated with real data, achieving a high identification rate of 97.35%. Consequently, the potential integration of technologies such as deep learning and simulation into geographical detection equipment is highlighted, offering a pathway to address potential future challenges. The study aims to somewhat alleviate these issues and anticipates contributing to the development of our military capabilities in becoming a future scientific and technological force.

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Thematic Analysis of the Therapeutic Song Writing Experience of Music Therapy Interns: A Focus Group (음악치료 인턴들의 치료적 노래만들기 경험에 대한 주제분석: 포커스 그룹을 중심으로)

  • Park, Chanyang;Kim, Jinah
    • Journal of Music and Human Behavior
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    • 제17권1호
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    • pp.1-24
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    • 2020
  • The internship is essential for the music therapy curriculum and affords interns the opportunity to apply their classroom-based knowledge and skills to real-world clinical settings. However, challenges associated with the internship can result in interns undergoing trial-and-error learning, interpersonal conflicts, and intrapersonal difficulties. An experiential music therapy group may be useful in helping interns process these incidents and develop their personal and professional skills. We explored the experiences of music therapy interns participating in therapeutic song writing. In this study, five music interns completed two 4-hour sessions of therapeutic song writing. Following the second session, a group interview was conducted with participants to gather data on their experiences. The interview was recorded, transcribed, and analyzed. Six themes and 18 sub-themes were derived from the data. The six themes were preconceptions of therapeutic song writing, meaningful lyric creation, challenges in song composition, structured experiences during song writing process, development of self-awareness through music, and relational experiences resulting from the group process. Participants were able to incorporate their individual internship experiences into a single song by communicating with group members during the step-by-step process. Participation in therapeutic song writing was found to help music therapy interns identify and process challenges encountered during their internship and further their personal and professional development.

Analysis of Autonomous Vehicles Risk Cases for Developing Level 4+ Autonomous Driving Test Scenarios: Focusing on Perceptual Blind (Lv 4+ 자율주행 테스트 시나리오 개발을 위한 자율주행차량 위험 사례 분석: 인지 음영을 중심으로)

  • Seung min Oh;Jae hee Choi;Ki tae Jang;Jin won Yoon
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • 제23권2호
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    • pp.173-188
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    • 2024
  • With the advancement of autonomous vehicle (AV) technology, autonomous driving on real roads has become feasible. However, there are challenges in achieving complete autonomy due to perceptual blind areas, which occur when the AV's sensory range or capabilities are limited or impaired by surrounding objects or environmental factors. This study aims to analyze AV accident patterns and safety issues of perceptual blind area that may occur in urban areas, with the goal of developing test scenarios for Level 4+ autonomous driving. It utilized AV accident data from the California Department of Motor Vehicles (DMV) to compare accident patterns and characteristics between AVs and conventional vehicles based on activation status of autonomous mode. It also categorized AV disengagement data to identify types and real-world cases of disengagements caused by perceptual blind areas. The analysis revealed that AVs exhibit different accident types due to their safe driving maneuvers, and three types of perceptual blind area scenarios were identified. The findings of this study serve as crucial foundational data for developing Level 4+ autonomous driving test scenarios, enabling the design of efficient strategies to mitigate perceptual blind areas in various scenarios. This, in turn, is expected to contribute to the effective evaluation and enhancement of AV driving safety on real roads.

CGRA Compilation Boost up for Acceleration of Graphics (영상처리 가속을 위한 CGRA compilation 속도 향상)

  • Kim, Wonsub;Choi, Yoonseo;Kim, Jaehyun
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 한국방송공학회 2014년도 하계학술대회
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    • pp.166-168
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    • 2014
  • Coarse-grained reconfigurable architectures (CGRAs) present a potential of high compute throughput with energy efficiency. A CGRA consists of an array of functional units (FU), which communicate with each other through an interconnect network containing transmission nodes and register files. To achieve high performance from the software solutions mapped onto CGRAs, modulo scheduling of loops is generally employed. One of the key challenges in modulo scheduling for CGRAs is to explicitly handle routings of operands from a source to a destination operations through various routing resources. Existing modulo schedulers for CGRAs are slow because finding a valid routing is generally a searching problem over a large space, even with the guidance of well-defined cost metrics. Applications in traditional embedded multimedia domains are regarded relatively tolerant to a slow compile time in exchange of a high quality solution. However, many rapidly growing domains of applications, such as 3D graphics, require a fast compilation. Entrances of CGRAs to these domains have been blocked mainly due to its long compile time. We attack this problem by utilizing patternized routes, for which resources and time slots for a success can be estimated in advance when a source operation is placed. By conservatively reserving predefined resources at predefined time slots, future routings originated from the source operation are guaranteed. Experiments on a real-world 3D graphics benchmark suite show that our scheduler improves the compile time up to 6000 times while achieving average 70% throughputs of the state-of-art CGRA modulo scheduler, edge-centric modulo scheduler (EMS).

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Online Community Design: Review of Frameworks and Developing Online Community Construct

  • Oh Ki-Tae;Lee Kun-Pyo
    • Archives of design research
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    • 제19권3호
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    • pp.131-142
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    • 2006
  • The purpose of this study is to develop an online community construct, which proposes an inclusive illustration of the structure of online communities, for online community designers. This study reviewed researches from psychology, sociology, management engineering, and practical reports to understand the characteristics and dynamics of online communities. The proposed online community construct visualizes the cognitive, affective, and behavioral aspects of online community. As the notion of community originates from geographical groups, and with the assumption that geographical community shares identical characteristics with online community, this study reviewed researches about geographical communities as a starting-point. Then the study went through three main perspectives (1) online community attributes, (2) sense of online community and (3) challenges of online community. Then this study proposed an online community construct that encompasses the reviewed frameworks. The online community can be seen as a congregation of members from two sources. One is from the 'Shared Goal' that meets the personal needs. Given the shared goal, members gather into the community without personal relationship and have more chances to feel the sense of belonging to their needs fulfillment or benefit. This befitting tendency leads to strengthening of membership. Public online forums fall under this classification. The other source is from the emotional connections that are already initiated by personal and casual contacts in the real world. The network of emotional connection can evolve into an online congregation of people under faint boundaries. Although there is no (or weak) shared goal, members are strongly bound to other members. Personal homepage or web log (blog) can be classified as an example of relationship-oriented community.

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A Survey on Smart Internet of Things - Trend Issues, Cognitive Computing Frameworks (지능형 IoT에 대한 조사 - Cognitive Computing Frameworks, 트렌드 이슈)

  • Landry, Moungala Alban;Kabulo, Nday Sinai;Yum, Sun-Ho;Namgung, Jung-Il;Shin, Soo-Young;Park, Soo-Hyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 한국정보처리학회 2018년도 춘계학술발표대회
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    • pp.604-607
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    • 2018
  • From the last past decade, the Internet of Thing (IoT) area has attracted a lot of attention from researchers. It is said to be a promising technology with great impact in people life, since it redefines the relationship objects have with Human and between themselves. It allows objects to gather data from the real world and communicate with others through the internet. This enabled many opportunities for service providers, companies, factories, environmental monitoring, healthcare, smart cities, and soon. Therefore, today, IoT is densely used in various domains of life, and knows an exponential growth. However, although many advancements have been achieved, several challenges keep causing issues and still need to be overcome. This paper gives an overview on the current trend issues in IoT on which researchers are focusing. It's also explores different proposed frameworks to allow the application of cognitive computing as an integrated process of an Internet of things (IoT) systems, to bring a great advanced in the way machine may communicate with human and their surroundings. This is known as cognitive IoT (CIoT), which allows machines to produce a human-like behavior, then providing enhanced level of capabilities to IoT.

Optimization of Data Placement using Principal Component Analysis based Pareto-optimal method for Multi-Cloud Storage Environment

  • Latha, V.L. Padma;Reddy, N. Sudhakar;Babu, A. Suresh
    • International Journal of Computer Science & Network Security
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    • 제21권12호
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    • pp.248-256
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    • 2021
  • Now that we're in the big data era, data has taken on a new significance as the storage capacity has exploded from trillion bytes to petabytes at breakneck pace. As the use of cloud computing expands and becomes more commonly accepted, several businesses and institutions are opting to store their requests and data there. Cloud storage's concept of a nearly infinite storage resource pool makes data storage and access scalable and readily available. The majority of them, on the other hand, favour a single cloud because of the simplicity and inexpensive storage costs it offers in the near run. Cloud-based data storage, on the other hand, has concerns such as vendor lock-in, privacy leakage and unavailability. With geographically dispersed cloud storage providers, multicloud storage can alleviate these dangers. One of the key challenges in this storage system is to arrange user data in a cost-effective and high-availability manner. A multicloud storage architecture is given in this study. Next, a multi-objective optimization problem is defined to minimise total costs and maximise data availability at the same time, which can be solved using a technique based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions known as the Pareto-optimal set.. When consumers can't pick from the Pareto-optimal set directly, a method based on Principal Component Analysis (PCA) is presented to find the best answer. To sum it all up, thorough tests based on a variety of real-world cloud storage scenarios have proven that the proposed method performs as expected.