• 제목/요약/키워드: investigation challenges

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Current status and challenges in disease surveillance and epidemiological investigation systems for companion animals in South Korea

  • Beom Jun Lee;Kyung-Duk Min
    • 대한수의학회지
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    • 제64권2호
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    • pp.18.1-18.5
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    • 2024
  • The surveillance and epidemiological investigation systems for companion animals in South Korea are significantly underdeveloped compared to those for humans and livestock. Recent outbreaks, such as idiopathic neuromuscular syndrome and highly pathogenic avian influenza among cats, have highlighted the need for reliable systems. This short review conducts situation analysis regarding disease surveillance and epidemiological investigation for companion animals in South Korea. The current challenges include an absence of administrative leadership, a lack of legal support, and unreliable medical data. The recommendations for future directions include clear leadership by the Animal and Plant Quarantine Agency, amending the Act on the Prevention of Contagious Animal Diseases to include companion animals, and enhancing the quality of medical data through standardized coding systems, such as Systematized Nomenclature of Medicine Clinical Terms. In addition, sentinel surveillance rather than universal systems should be established to provide adequate incentives for local practitioners to provide data and develop sustainable public-private networks. These recommendations could be important for developing a comprehensive and sustainable system for disease surveillance and epidemiological investigation in the companion animal field.

Clinical Implementation of Deep Learning in Thoracic Radiology: Potential Applications and Challenges

  • Eui Jin Hwang;Chang Min Park
    • Korean Journal of Radiology
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    • 제21권5호
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    • pp.511-525
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    • 2020
  • Chest X-ray radiography and computed tomography, the two mainstay modalities in thoracic radiology, are under active investigation with deep learning technology, which has shown promising performance in various tasks, including detection, classification, segmentation, and image synthesis, outperforming conventional methods and suggesting its potential for clinical implementation. However, the implementation of deep learning in daily clinical practice is in its infancy and facing several challenges, such as its limited ability to explain the output results, uncertain benefits regarding patient outcomes, and incomplete integration in daily workflow. In this review article, we will introduce the potential clinical applications of deep learning technology in thoracic radiology and discuss several challenges for its implementation in daily clinical practice.

Analysis of Cybercrime Investigation Problems in the Cloud Environment

  • Khachatryan, Grigor
    • International Journal of Computer Science & Network Security
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    • 제22권7호
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    • pp.315-319
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    • 2022
  • Cloud computing has emerged to be the most effective headway for investigating crime especially cybercrime in this modern world. Even as we move towards an information technology-controlled world, it is important to note that when innovations are made, some negative implications also come with it, and an example of this is these criminal activities that involve technology, network devices, and networking that have emerged as a result of web improvements. These criminal activities are the ones that have been termed cybercrime. It is because of these increased criminal activities that organizations have come up with different strategies that they use to counter these crimes, and one of them is carrying out investigations using the cloud environment. A cloud environment has been defined as the use of web-based applications that are used for software installation and data stored in computers. This paper examines problems that are a result of cybercrime investigation in the cloud environment. Through analysis of the two components in play; cybercrime and cloud environment, we will be able to understand what are the problems that are encountered when carrying out investigations in cloud forensics. Through the use of secondary research, this paper found out that most problems are associated with technical and legal channels that are involved in carrying out these investigations. Investigator's mistakes when extracting pieces of evidence form the most crucial problems that take a lead when it comes to cybercrime investigation in the cloud environment. This paper not only flags out the challenges that are associated with cybercrime investigation in cloud environments but also offer recommendations and suggested solutions that can be used to counter the problems in question here. Through a proposed model to perform forensics investigations, this paper discusses new methodologies solutions, and developments for performing cybercrime investigations in the cloud environment.

클라우드 환경에서 수사 실무와 법적 과제 (Practical and Legal Challenges of Cloud Investigations)

  • 조슈아 제임스;장윤식
    • 한국인터넷방송통신학회논문지
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    • 제14권6호
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    • pp.33-39
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    • 2014
  • 클라우드 컴퓨팅 서비스의 확산으로 범죄수사를 위한 증거수집의 관점에서 불확실성으로 인한 다양한 실무적이고 법적인 문제가 제기되고 있다. 이 논문은 클라우드 환경에 대한 일반적인 수사상의 논점을 개관하고, 관할과 국제공조를 비롯한 문제점을 진단한다. 실무적으로 직접적으로 수사관이 접속하는 경우와 서비스제공자의 협조를 받는 경우의 장단점을 비교하여 실무적 개선방안을 논의하고 이에 따른 관할의 중복과 서비스 약정 및 포렌식적으로 무결한 데이터 수집 등 법률적 쟁점을 정리한다.

A Journey of Digital Transformation of Small and Medium-Sized Enterprises in Vietnam: Insights from Multiple Cases

  • BUI, Minh Le
    • The Journal of Asian Finance, Economics and Business
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    • 제8권10호
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    • pp.77-85
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    • 2021
  • This study aims to investigate the status quo and identify the challenges and benefits of the digital transformation in the context of small and medium-sized enterprises (SMEs) in Vietnam. The six participating SMEs were purposely contacted, and they were either nominated for, or received the Vietnam Digital Awards in 2018, 2019 and 2020, which were held by the Vietnam Digital Communication Association (http://en.vdca.org.vn/). A qualitative research method is adopted, using a semi-structured interview method and a theoretical triangulation of legitimacy, stakeholder and stewardship theories to facilitate the investigation. This research tries to identify the current challenges and benefits for digital transformation of SMEs in Vietnam, based on perception and experience from business leaders and managers from six SMEs in Vietnam. The findings of this study reveal that besides the recent challenges for digital transformation, participants also experienced and shared their perspectives regarding the benefits received from the digital transformation journey of their organization, which varied from (i) improve operational as well as business functions; (ii) liberate staffs and managers from daily work and allows them to focus on decision-making tasks; (iii) enable solutions to deal with consequences from the COVID-19 pandemic; (iv) enhance value creation process; and (v) help firms to align with the global business standards.

Digital Forensic: Challenges and Solution in the Protection of Corporate Crime

  • CHOI, Do-Hee
    • 산경연구논집
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    • 제12권6호
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    • pp.47-55
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    • 2021
  • Purpose: Organizational crime is an offense committed by an individual or an official in a corporate entity for organizational gain. This study aims to explore the literature on challenges facing digital forensics and further discuss possible solutions to such challenges as far as the protection of corporate crime is concerned. Research design, data and methodology: Qualitative textual methodology matches the interpretative approach since it is a quality method meant to consider the inductivity of strategies. Also, a qualitative approach is vital because it is distinct from the techniques used in optimistic paradigms linked to science laws. Results: For achieving justice through the investigation of digital forensic, there is a need to eradicate corporate crimes. This study suggests several solutions to reduce corporate crime such as 'Solving a problem to Anti-forensic Techniques', 'Cloud computing technique', and 'Legal Framework' etc. Conclusion: As corporate crime increases in rate, the data collected by digital forensics increases. The challenge of analyzing chunks of data requires digital forensic experts, who need tools to analyze them. Research findings shows that a change of the operating system and digital evidence interpretation is becoming a challenge as the new computer application software is not compatible with older software's structure.

Independent Metering Valve: A Review of Advances in Hydraulic Machinery

  • Nguyen, Thanh Ha;Do, Tri Cuong;Ahn, Kyoung Kwan
    • 드라이브 ㆍ 컨트롤
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    • 제17권4호
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    • pp.54-71
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    • 2020
  • In light of the environmental challenges, energy-saving strategies are currently under investigation in the construction industry. This paper focuses on the energy-saving method used in the hydraulic system based on independent metering (IM) technologies, which can overcome the lost energy at the main control valve of the conventional electrohydraulic servo system. By scientifically arranging the proportional valves, the IM system can individually control the flow rate of the inlet and the outlet ports of the actuators. In addition, the IMV system can be used to effectively regenerate energy under different operating modes, thereby saving more energy than conventional hydraulic systems. Therefore, the IMV system has a great potential to improve the energy efficiency of hydraulic machinery. The overall IMV system, including the configuration, proportional valve, operation mode, and the control strategy is introduced via state-of-the-art hydraulic technologies. Finally, the challenges of IM systems are discussed to provide researchers with directions for future development.

Utilizing Optical Phantoms for Biomedical-optics Technology: Recent Advances and Challenges

  • Ik Hwan Kwon;Hoon-Sup Kim;Do Yeon Kim;Hyun-Ji Lee;Sang-Won Lee
    • Current Optics and Photonics
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    • 제8권4호
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    • pp.327-344
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    • 2024
  • Optical phantoms are essential in optical imaging and measurement instruments for performance evaluation, calibration, and quality control. They enable precise measurement of image resolution, accuracy, sensitivity, and contrast, which are crucial for both research and clinical diagnostics. This paper reviews the recent advancements and challenges in phantoms for optical coherence tomography, photoacoustic imaging, digital holographic microscopy, optical diffraction tomography, and oximetry tools. We explore the fundamental principles of each technology, the key factors in phantom development, and the evaluation criteria. Additionally, we discuss the application of phantoms used for enhancing optical-image quality. This investigation includes the development of realistic biological and clinical tissue-mimicking phantoms, emphasizing their role in improving the accuracy and reliability of optical imaging and measurement instruments in biomedical and clinical research.

Nepali Consumer Perceptions of Country-of-Origin and Brand Trust: An Initial Investigation

  • Al Rosenbloom
    • Asia Marketing Journal
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    • 제11권2호
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    • pp.193-215
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    • 2009
  • This paper reports the country of origin and brand trust perceptions of 102 Nepali consumers living in Kathmandu. The paper also explores these Nepali consumers' perceptions of global brands. Three major findings are reported: (1) For these Nepali consumers, the importance of buying a global brand is exceptionally important in their purchase decisions. (2) Nepali women consistently rate the importance of buying a global brand higher than Nepali men. (3) The set of global brands most trusted by these Nepali consumers show strong regional, Asian preferences. The paper also discusses the challenges of market research in Nepal.

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Protein Disorder Prediction Using Multilayer Perceptrons

  • Oh, Sang-Hoon
    • International Journal of Contents
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    • 제9권4호
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    • pp.11-15
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    • 2013
  • "Protein Folding Problem" is considered to be one of the "Great Challenges of Computer Science" and prediction of disordered protein is an important part of the protein folding problem. Machine learning models can predict the disordered structure of protein based on its characteristic of "learning from examples". Among many machine learning models, we investigate the possibility of multilayer perceptron (MLP) as the predictor of protein disorder. The investigation includes a single hidden layer MLP, multi hidden layer MLP and the hierarchical structure of MLP. Also, the target node cost function which deals with imbalanced data is used as training criteria of MLPs. Based on the investigation results, we insist that MLP should have deep architectures for performance improvement of protein disorder prediction.