• 한국임상약학회지
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• 제30권4호
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• pp.217-225
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• 2020

The fourth industrial revolution, with its characteristics of "hyper-connectivity", "hyper-intelligence" and "automation", is a hot topic worldwide. It will fundamentally change industry, economy, and business models through technological innovations, such as big data, cloud computing, Internet of Things (IoT), artificial intelligence (AI), and 3D printing. In particular, the development of highly advanced information technology (IT) and AI is expected to replace human roles, thereby changing employment and occupation prospects in the future. Based on this, some predict that the profession of the pharmacist will soon disappear. To counter this, pharmacists' attention and efforts are required to seek innovative transformations in their functions by responding sensitively and promptly to changes of the fourth industrial revolution. It is also necessary to recognize the new roles of pharmacists and to develop the competencies to perform them. The fourth industrial revolution is an inevitable change of the times. At this time, we should take comprehensive and open perspectives on how the future society will change economically, culturally, and socially, and use it as an opportunity to shape the new future of pharmacists.

• Journal of Ginseng Research
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• 제45권2호
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• pp.211-217
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• 2021

The treatments of nervous system diseases (NSDs) have long been difficult issues for researchers because of their complexity of pathogenesis. With the advent of aging society, searching for effective treatments of NSDs has become a hot topic. Ginseng polysaccharides (GP), as the main biologically active substance in ginseng, has various biological properties in immune-regulation, anti-oxidant, anti-inflammation and etc. Considering the association between the effects of GP and the pathogenesis of neurological disorders, many related experiments have been conducted in recent years. In this paper, we reviewed previous studies about the effects and mechanisms of GP on diseases related to nervous system. We found GP play an ameliorative role on NSDs through the regulation of immune system, inflammatory response, oxidative damage and signaling pathway. Structure-activity relationship was also discussed and summarized. In addition, we provided new insights into GP as promising neuroprotective agent for its further development and utilization.

• The Journal of Asian Finance, Economics and Business
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• 제9권4호
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• pp.399-408
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• 2022

Corporate governance and innovation have been a hot topic in recent boardroom talks, whether in the trade or manufacturing industries. Governance innovations are highly significant for the survival of the motor vehicle industry like Honda, Nissan, New General Motors, and Toyota. The study chooses the motor vehicle industry which crosses the age of a century and sufficient corroborative support exists with the perspective of distinctive objectives. Using the population of all the automobile companies listed on the Pakistan stock exchange (PSX), we distill automobile companies to evaluate the firm performance using the panel data regression approach. The results show that there is a significant relationship between gender diversity, audit committees, and firm performance. Further, board size also has a positive impact on firm performance. We identify that the governance mechanism of firms found in default of the frequency of audit committee meetings. By considering results, only limited knowledge of finance directors and also very few numbers of female directors are on the board. Empirical findings of this work might be useful for policymakers in attempting to draft a corporate governance framework better able to monitor the financial performance of firms through female directors and also serve as a catalyst for the regulators of electric vehicles.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2976-2990
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• 2022

The adaptive adjustment of reference or weight vectors in decomposition-based methods has been a hot research topic in the evolutionary community over the past few years. Although various methods have been proposed regarding this issue, most of them aim to diversify solutions in the objective space to cover the true Pareto fronts as much as possible. Different from them, this paper proposes a knee point-based reference vector adaptive adjustment strategy to concurrently balance the convergence and diversity. To be specific, the knee point-based reference vector adaptive adjustment strategy firstly utilizes knee points to construct the adaptive reference vectors. After that, a new fitness function is defined mathematically. Then, this paper further designs a many-objective evolutionary algorithm with knee point-based reference vector adaptive adjustment strategy, where the mating operation and environmental selection are designed accordingly. The proposed method is extensively tested on the WFG test suite with 8, 10 and 12 objectives and MPDMP with state-of-the-art optimizers. Extensive experimental results demonstrate the superiority of the proposed method over state-of-the-art optimizers and the practicability of the proposed method in tackling practical many-objective optimization problems.

• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.459-468
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• 2007

The u-City construction project has become a hot topic in the construction market because it seems economic value-added field for construction firms. However, construction firms don't willingly participate in the u-City construction market because environments of the future business for the u-City are very uncertain. Scenario planning is a very powerful method in managing this uncertain planning situation and is based on scenarios that help each enterprise appropriately adapt itself to its own business environments. Therefore it is based on the main principles of systems thinking and multiple futures. For the purpose of dealing with such uncertainties, this paper attempts to develop the possible market scenarios of the u-City construction market in S.Korea through a scenario planning approach. From this perspective, we considered various aspects of the u-City construction such as market demands, technology development, policy level and management environment. After considering the relevant issues, we identified the main trends and key uncertainties. Finally, we developed three coherent u-City construction market scenarios. Construction firms can use these scenarios as a basic reference for market analysis and business strategy. Therefore, this paper is able to enhance the participation of construction firms in the u-City construction market.

• Journal of Platform Technology
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• 제11권1호
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• pp.72-84
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• 2023

With the rise of the Internet of Things, the security of such lightweight computing environments has become a hot topic. Lightweight block ciphers that can provide efficient performance and security by having a relatively simpler structure and smaller key and block sizes are drawing attention. Due to these characteristics, they can become a target for new attack techniques. One of the new cryptanalytic attacks that have been attracting interest is Neural cryptanalysis, which is a cryptanalytic technique based on neural networks. It showed interesting results with better results than the conventional cryptanalysis method without a great amount of time and cryptographic knowledge. The first work that showed good results was carried out by Aron Gohr in CRYPTO'19, the attack was conducted on the lightweight block cipher SPECK-/32/64 and showed better results than conventional differential cryptanalysis. In this paper, we first apply the Differential Neural Distinguisher proposed by Aron Gohr to the block ciphers HIGHT and GOST to test the applicability of the attack to ciphers with different structures. The performance of the Differential Neural Distinguisher is then analyzed by replacing the neural network attack model with five different models (Multi-Layer Perceptron, AlexNet, ResNext, SE-ResNet, SE-ResNext). We then propose a Related-key Neural Distinguisher and apply it to the SPECK-/32/64, HIGHT, and GOST block ciphers. The proposed Related-key Neural Distinguisher was constructed using the relationship between keys, and this made it possible to distinguish more rounds than the differential distinguisher.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1066-1079
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• 2023

Multi-target tracking based on the detector is a very hot and important research topic in target tracking. It mainly includes two closely related processes, namely target detection and target tracking. Where target detection is responsible for detecting the exact position of the target, while target tracking monitors the temporal and spatial changes of the target. With the improvement of the detector, the tracking performance has reached a new level. The problem that always exists in the research of target tracking is the problem that occurs again after the target is occluded during tracking. Based on this question, this paper proposes a DeepSORT model based on SIFT features to improve ship tracking. Unlike previous feature extraction networks, SIFT algorithm does not require the characteristics of pre-training learning objectives and can be used in ship tracking quickly. At the same time, we improve and test the matching method of our model to find a balance between tracking accuracy and tracking speed. Experiments show that the model can get more ideal results.

• 분석과 대안
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• 제2권1호
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• pp.71-106
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• 2018

The 19th CPC National Congress has a key historical significance in the development of China's constitution. It will also play a decisive role in the history of the seventy years'constitutional change in New China. XiJinping's new socialist thought with Chinese characteristics established in the report of 19th CPC National Congress will be written in the preface of the March 2018 National People's Congress's constitutional amendment. The fifth revision of 1982 Constitution will touch on many issues such as the leadership of the CPC into the constitution, the abolition of the tenure of the president, the constitutional oath system, and the reform of the national supervisory system. In addition, the constitutionality review system, the establishment of the National Security Council, the constitutional status of socialist public property and private property and the adjustment of major economic system has become a hot topic in the theory field. In the history node towards a socialist country ruled by law, the theory and practice of the China indeed have the academic ideas, value position and path model differences, which will delay the Chinese constitutional development, but also is the necessary pain in the process of moving towards the rule of law in China. Indeed, how to the development and where to go in the future of Chinese constitutionalism itself has sample value, which deserves rational attention and in-depth inquiry from Chinese and Western academics.

• 정보보호학회논문지
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• 제33권3호
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• pp.561-575
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• 2023

정보보안 산업은 지난 수십 년간 매우 다양한 성장을 거듭해왔다. 특히 기술적, 관리적, 제도적 측면에서 다양한 해법을 제시해왔다. 그럼에도 불구하고 매년 보안사고는 지속해서 발생하고 있는데 주목해야 한다. 이는기존의 보안이 지나치게 기술 중심, 예방 중심의 정책으로 추진되고 있어서 디지털 시대의 다양한 비즈니스 변화에 한계가 있음을 증명하고 있다. 따라서 최근에 전통적인 보안 접근 방식의 한계를 벗어나고자 인간중심 보안(PCS:People-Centric Security)이 화두가 되고 있다. 본 연구에서는 정보보안 위반의 개념, PCS 전략적원칙, 전문가 인터뷰를 통해 인간이 유발할 수 있는 취약점을 크게 5가지로 구분하고 21개의 세부 구성요소로 분류함으로써 근본적인 보안 사고 대응 방안을 제시하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권12호
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• pp.3416-3435
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• 2023

Task offloading in vehicular networks is hot topic in the development of autonomous driving. In these scenarios, due to the role of vehicles and pedestrians, task characteristics are changing constantly. The classical deep learning algorithm always uses a pre-trained neural network to optimize task offloading, which leads to system performance degradation. Therefore, this paper proposes a neural network fine-tuning task offloading algorithm, combining with location prediction for pedestrians and vehicles by the Payne model of fluid dynamics and the car-following model, respectively. After the locations are predicted, characteristics of tasks can be obtained and the neural network will be fine-tuned. Finally, the proposed algorithm continuously predicts task characteristics and fine-tunes a neural network to maintain high system performance and meet low delay requirements. From the simulation results, compared with other algorithms, the proposed algorithm still guarantees a lower task offloading delay, especially when congestion occurs.