• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.103-114
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• 2022

The Internet of Things (IoT) is one of the fastest technologies that are used in various applications and fields. The concept of IoT will not only be limited to the fields of scientific and technical life but will also gradually spread to become an essential part of our daily life and routine. Before, IoT was a complex term unknown to many, but soon it will become something common. IoT is a natural and indispensable routine in which smart devices and sensors are connected wirelessly or wired over the Internet to exchange and process data. With all the benefits and advantages offered by the IoT, it does not face many security and privacy challenges because the current traditional security protocols are not suitable for IoT technologies. In this paper, we presented a comprehensive survey of the latest studies from 2018 to 2021 related to the security of the IoT and the use of machine learning (ML) and deep learning and their applications in addressing security and privacy in the IoT. A description was initially presented, followed by a comprehensive overview of the IoT and its applications and the basic important safety requirements of confidentiality, integrity, and availability and its application in the IoT. Then we reviewed the attacks and challenges facing the IoT. We also focused on ML and its applications in addressing the security problem on the IoT.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.175-180
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• 2022

Data is an important resource to expect new value as 21st-century crude oil. In the shipping industry, despite the existence of numerous maritime data accumulated through ship operations, it was negligent in developing a business model with the data. This paper identified major demand sources and demand types based on the type and availability of maritime data surveyed through interviews with experts in the shipping industry and academia. Considering the characteristics and demands of these maritime data, this paper presented a private-type and public-interest business model. In the case of the private-type model, it creates additional added value by using maritime data and uses mainly ship internal data. The public-type model is to seek public safety and social benefits and mainly uses external data. A great synergy effect can be expected when combined with public services such as maritime survey, vessel traffic service, maritime environment management, and meteorological service. This study is expected to contribute greatly to the spread of the proposed business models throughout the shipping industry.

• Journal of the Korean Society of Food Culture
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• v.38 no.4
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• pp.191-202
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• 2023

Food upcycling has emerged as an effective approach to sustainably utilize the food waste generated within the food supply chain. This review article examines upcycled food with respect to its definition, consumers' knowledge and perception on it, and the process by which by-products from the food supply chain are utilized for the creation of upcycled food products. The definition of upcycled food varied among manufacturers, research institutions, and the Upcycled Food Association, depending on the specific values and objectives of each sector. This has resulted in the use of different keywords to highlight the distinctive characteristics of their respective interpretations of upcycled food. This review also summarizes the various consumer traits that can influence the awareness and acceptance of upcycled food, encompassing functional, empirical and emotional, symbolic and self-expressive, and economic benefits. Additionally, the review presents strategies to utilize by-products produced in large quantities in Korea, while also addressing the control of hazardous components to ensure biological or chemical safety and the changes in nutritional value that may occur during the utilization of these byproducts.

• Journal of Smart Tourism
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• v.2 no.1
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• pp.5-19
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• 2022

Smart tourism is seen as a revolution in the tourism industry, involving innovative and transformative theoretical-practical approaches for the sector. As a result of its application in the tourist context, benefits can be seen such as more sustainable practices, greater mobility and better accessibility in destinations, evolution of processes and experiences of tourists. Much of this is achieved through the support of technological solutions. However, despite the immense expectations, and the many researches carried out on it, a literature summary regarding the dimensions that can be observed in each application of this smart tourism has not yet been proposed. Therefore, supported by the PRISMA recommendation, this research proposed to carry out an integrative review of the literature on smart tourism (in its different levels of application, such as the city, the destination and the smart tourism region), with the objective of mapping the dimensions that underlie it. Thus, from an initial scope of 833 intellectual productions obtained, inputs were found for the dimensions in 363 of them after a thorough analysis. The compilation of data obtained from these productions supported the proposition of 14 operational dimensions of smart tourism, namely: collaboration, technology, sustainability, experience, accessibility, knowledge management, innovation management, human capital, marketing, customized services, transparency, safety, governance and mobility. With this set of dimensions, it is envisaged that the implementation of smart tourism projects can present more comprehensive and assertive results. In addition, shortcomings and opportunities for new research that support the evolution of the theory and practice of smart tourism are highlighted.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.72-81
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• 2023

This research proposes a novel approach to tackle the challenge of categorizing unstructured customer complaints in the automotive industry. The goal is to identify potential vehicle defects based on the findings of our algorithm, which can assist automakers in mitigating significant losses and reputational damage caused by mass claims. To achieve this goal, our model uses the Word2Vec method to analyze large volumes of unstructured customer complaint data from the National Highway Traffic Safety Administration (NHTSA). By developing a score dictionary for eight pre-selected criteria, our algorithm can efficiently categorize complaints and detect potential vehicle defects. By calculating the score of each complaint, our algorithm can identify patterns and correlations that can indicate potential defects in the vehicle. One of the key benefits of this approach is its ability to handle a large volume of unstructured data, which can be challenging for traditional methods. By using machine learning techniques, we can extract meaningful insights from customer complaints, which can help automakers prioritize and address potential defects before they become widespread issues. In conclusion, this research provides a promising approach to categorize unstructured customer complaints in the automotive industry and identify potential vehicle defects. By leveraging the power of machine learning, we can help automakers improve the quality of their products and enhance customer satisfaction. Further studies can build upon this approach to explore other potential applications and expand its scope to other industries.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.877-885
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• 2022

Vision-based activity recognition has been widely attempted at construction sites to estimate productivity and enhance workers' health and safety. Previous studies have focused on extracting an individual worker's postural information from sequential image frames for activity recognition. However, various trades of workers perform different tasks with similar postural patterns, which degrades the performance of activity recognition based on postural information. To this end, this research exploited a concept of human-object interaction, the interaction between a worker and their surrounding objects, considering the fact that trade workers interact with a specific object (e.g., working tools or construction materials) relevant to their trades. This research developed an approach to understand the context from sequential image frames based on four features: posture, object, spatial features, and temporal feature. Both posture and object features were used to analyze the interaction between the worker and the target object, and the other two features were used to detect movements from the entire region of image frames in both temporal and spatial domains. The developed approach used convolutional neural networks (CNN) for feature extractors and activity classifiers and long short-term memory (LSTM) was also used as an activity classifier. The developed approach provided an average accuracy of 85.96% for classifying 12 target construction tasks performed by two trades of workers, which was higher than two benchmark models. This experimental result indicated that integrating a concept of the human-object interaction offers great benefits in activity recognition when various trade workers coexist in a scene.

• The Journal of Health Technology Assessment
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• v.1 no.1
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• pp.22-26
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• 2013

Objectives: Balancing benefits and risks through the drug life cycle has been discussed for many decades. The objective of this study was to review the processes and tools currently proposed for benefit-risk assessment of medicinal drugs. It aimed to establish scientific and efficient drug safety management system based on the synthetic analysis of benefit-risk evidence. Methods: We conducted a review of exiting literatures published by regulatory agencies or initiatives. Not only quantitative methodologies but also qualitative method were compared to understand their key characteristics for the benefit and risk assessment of drugs. Results: Recently, benefit-risk assessments have more structured approaches to decision making as part of regulatory science. Regulatory agencies such as European Medicines Agency, FDA have prepared plans to apply benefit-risk assessment to regulatory decision making. Also many initiatives such as IMI (Innovative Medicine Initiative) have conducted research and published reports about benefit-risk assessment. For benefit-risk assessment, four kinds of methods are necessary. Frameworks such as BRAT (Benefit Risk Action Team) framework, PrOACT-URL provide guidance for the whole process of decision-making. Metrics are measurements of risk benefit. The estimation techniques are methods to synthesis and combine evidences from various sources. The utility survey techniques are necessary to explicit preferences of various outcome from stakeholders. Conclusion: There is the lack of widely accepted, validated model for benefit-risk assessment. Nor there is an agreement among academia, industry, and government on methods for the quantitative valuation. It is also limited by available evidence and underlying assumptions. Nevertheless, benefit-risk assessment is fundamental to improve transparency, consistency and predictability for decision making through the structured systematic approaches.

• Journal of Dental Anesthesia and Pain Medicine
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• v.23 no.6
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• pp.293-302
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• 2023

This review paper delves into the comparative study of epinephrine and phenylephrine as vasoconstrictors in dental anesthesia, exploring their histories, pharmacological properties, and clinical applications. The study involved a comprehensive literature search, focusing on articles that directly compared the two agents in terms of efficacy, safety, and prevalence in dental anesthesia. Epinephrine, with its broad receptor profile, has been a predominant choice, slightly outperforming in the context of prolonging dental anesthesia and providing superior hemostasis, which is crucial for various dental procedures. However, the stimulation of beta-adrenergic receptors caused by epinephrine poses risks, especially to patients with cardiovascular conditions. Phenylephrine, a selective alpha-1 adrenergic agonist, emerges as a safer alternative for such patients, avoiding the cardiovascular risks associated with epinephrine. Moreover, its vasoconstrictive effect may not be as deleterious as that of epinephrine, due to its selective action. This review reveals that despite the potential benefits of phenylephrine, epinephrine continues to dominate in clinical settings, due to its historical familiarity, availability, and cost-effectiveness. The lack of commercially available pre-made phenylephrine dental carpules in most countries, except Brazil, and a knowledge gap within dental academia regarding phenylephrine, contribute to its limited use. This review concludes that while both agents are effective, the choice between them should be based on individual patient conditions, availability, and the practitioner's knowledge and familiarity with the agents. The underuse of other vasoconstrictors like levonordefrin and the unavailability of phenylephrine in pre-mixed dental cartridges in many countries highlights the need for further exploration and research in this field. Furthermore, we also delve into the role of levonordefrin and examine the rationale behind the exclusion of phenylephrine from commercially available pre-mixed local anesthetic carpules, suggesting a need for a responsive approach from pharmaceutical manufacturers to the distinct needs of the dental community.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.49 no.6
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• pp.332-338
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• 2023

Objectives: This study aimed to compare the effectiveness of a hybrid arch bar (hAB) with the conventional Erich arch bar (EAB) for the management of jaw fractures, focusing on their use for temporary fixation in patients undergoing open reduction and internal fixation (ORIF). Materials and Methods: Patients presenting with maxillary and mandibular fractures at our institution were included in this prospective, comparative study. Placement time and ease of occlusal reproducibility were recorded intraoperatively for Group A (hAB patients) and Group B (EAB patients). The primary outcome was comparison of the postoperative stability of the two arch bars. Postoperative measurements also included mucosal overgrowth, screw loosening or wire retightening, and replacement rates. The data were tabulated and computed with a P<0.05 considered statistically significant. Results: The study included 41 patients. A statistically significant difference was observed in postoperative stability scores (3) between Group A and Group B (85.0% vs 9.5%, P=0.001). The mean placement time in Group A (23.3 minutes) significantly differed from that in Group B (86.4 minutes) (P<0.001). The ease of intraoperative occlusion was not different between the two groups (P=0.413). Mucosal overgrowth was observed in 75.0% of patients (15 of 20) in Group A. Conclusion: The hAB was superior to EAB in clinical efficiency, maxillomandibular fixation time reduction, stability, versatility, and safety. Despite temporary mucosal overgrowth, the benefits of hAB outweigh the disadvantages. The choice between hAB and EAB should be based on specific clinical requirements.

• Journal of Dairy Science and Biotechnology
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• v.41 no.4
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• pp.179-190
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• 2023

Currently, various probiotics are being used to improve the nutrition of companion animals. They are widely sold as additives in companion animal foods because of the numerous gastrointestinal and immune health benefits for dogs and cats. Therefore, extensive research is being conducted to improve quality and safety during manufacturing and to extend the shelf life of companion animal foods by adding probiotics. The manufacturing process must be conducted such that the characteristics and efficacy of probiotics added to food are optimally beneficial for companion animals. Therefore, this review aims to address the overall characteristics of the probiotic strains used and to examine the various methods through which probiotics are added to companion animal foods.