• Korean Journal of Veterinary Research
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• v.64 no.2
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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.

• Korean Journal of Radiology
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• v.21 no.5
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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.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.33-39
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• 2014

An area presenting new opportunities for both legitimate business, as well as criminal organizations, is Cloud computing. This work gives a strong background in current digital forensic science, as well as a basic understanding of the goal of Law Enforcement when conducting digital forensic investigations. These concepts are then applied to digital forensic investigation of cloud environments in both theory and practice, and supplemented with current literature on the subject. Finally, legal challenges with digital forensic investigations in cloud environments are discussed.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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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.

• The Journal of Industrial Distribution & Business
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• v.12 no.6
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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.

• Journal of Drive and Control
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• v.17 no.4
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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.

• Current Optics and Photonics
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• v.8 no.4
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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.

• Asia Marketing Journal
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• v.11 no.2
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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.

• International Journal of Contents
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• v.9 no.4
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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.