• KNOM Review
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• v.22 no.3
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• pp.20-24
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• 2019

Blockchain is a distributed ledger-based technology where all nodes participating in the blockchain network are connected to the P2P network. When a transaction is created in the blockchain network, the transaction is propagated and validated by the blockchain nodes. The verified transaction is sent to peers connected to each node through P2P network, and the peers keep the transaction in the memory pool. Due to the nature of P2P networks, the number and type of transactions delivered by a blockchain node is different for each node. As a result, all nodes do not have the same memory pool. Research is needed to solve problems such as attack detection. In this paper, we analyze transactions in the memory pool before solving problems such as transaction fee manipulation, double payment problem, and DDos attack detection. Therefore, this study collects transactions stored in each node memory pool of Bitcoin and Ethereum, a cryptocurrency system based on blockchain technology, and analyzes how much common transactions they have using jacquard similarity.

• Convergence Security Journal
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• v.23 no.1
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• pp.97-107
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• 2023

With the popularization of digital devices in the era of the 4th industrial revolution and the increase in cyber crimes targeting them, the importance of securing digital data evidence is emerging. However, the difficulty in securing digital data evidence is due to the use of anti-forensic techniques that increase analysis time or make it impossible, such as manipulation, deletion, and obfuscation of digital data. Such anti-forensic is defined as a series of actions to damage and block evidence in terms of digital forensics, and is classified into data destruction, data encryption, data concealment, and data tampering as anti-forensic techniques. Therefore, in this study, anti-forensic techniques are categorized into data concealment and deletion (obfuscation and encryption), investigate and analyze recent research trends, and suggest future anti-forensic research directions.

• Journal of Industrial Convergence
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• v.21 no.5
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• pp.133-142
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• 2023

In recent years, the problem of academic credential falsification is not simply the manipulation of certificates generated by educational institutions, but also the difficulty of trusting automated relationship verification and verification itself, such as falsely recording completion as graduation while still in school. This is due to the lack of sharing of educational background databases among university institutions and the establishment/operation of independent systems that make it difficult to track educational backgrounds. This study designs and implements an E-AV model for academic credential verification centered on university institutions. It summarizes and stores the linked information on the existing academic background in an encrypted database and implements it with web standard technology considering the compatibility and scalability of the existing system. The results of sample data verification show that it improves safety against forgery and complies with storage space and execution performance. This study aims to contribute to the improvement of online verification services such as academic records management in domestic universities.

• PNF and Movement
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• v.20 no.1
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• pp.73-81
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• 2022

Purpose: The aim of this study was to present specific criteria for setting goals for hand rehabilitation by comparing the degree of difference in grip force, coordination, and dexterity between the dominant and non-dominant hand according to gender. Methods: We recruited 100 healthy adults in their 20s and 30s. A handheld digital dynamometer was used to evaluate the grip force of each of the dominant and non-dominant hand, a chopsticks manipulation test was used to evaluate coordination, and the Purdue Pegboard test was used to evaluate agility. Results: In all subjects, the grip force, coordination, and dexterity showed statistically significant difference (p <0.01) between the dominant and non-dominant hand. In the comparison according to gender, both male and female dominant and non-dominant hands showed statistically significant differences in grip force, coordination, and dexterity (p <0.01). In the comparison according to grip force, there was a statistically significant difference between the dominant and non-dominant hand, and men showed stronger result values in both hands compared to women (p <0.01). In the comparison according to coordination, there was no statistically significant difference between the dominant and non-dominant hand in men and women (p >0.05). In the comparison according to dexterity, there was a statistically significant difference between the dominant and non-dominant hand, and women were shown to be faster in performance time with both hands, compared to men (p <0.01). Conclusion: Differences according to gender exist in grip force and dexterity but not coordination, and differences between dominant and non-dominant hand exists across all measurements. The results suggest setting a recovery goal according to dominance and gender during rehabilitation of hand function.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.509-516
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• 2022

Accurate pose prediction of objects in 3D space is an important visual recognition technique widely used in many applications such as scene understanding in both indoor and outdoor environments, robotic object manipulation, autonomous driving, and augmented reality. Most previous works for object pose estimation have the limitation that they require an exact 3D CAD model for each object. Unlike such previous works, this paper proposes a novel neural network model that can predict the poses of unknown objects based on only their RGB color images without the corresponding 3D CAD models. The proposed model can obtain depth maps required for unknown object pose prediction by using an adaptive depth estimator, AdaBins,. In this paper, we evaluate the usefulness and the performance of the proposed model through experiments using benchmark datasets.

• Design Convergence Study
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• v.15 no.1
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• pp.37-48
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• 2016

Nowadays, CAD has became an essential tool for designers due to its easy edition and manipulation as well as the capability of communication between designers. Differences between design tool interfaces can cause gaps when visualize designer's ideas. This study is about the differences between various levels of metaphor interface language which is based on the theory of the Hutchins that high-level language interface can reduce the steps of process to visualize the idea of the designers than low-level language interface. This research is based on the assumption that high-level language interface will less interrupt the flow of the design thinking and make more various visual outcomes than the low-level language interface. We verified the hypothesis by analyzing differences of design thinking flow between user groups who used two different animation software. Hopefully, the verification of the hypothesis in this study can be able to guide the use pattern of the CAD tools.

• Annual Conference of KIPS
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• 2020.11a
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• pp.854-857
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• 2020

최근 사람형(Anthropomorphic)로봇손의 사물조작 지능을 개발하기 위하여 행동복제(Behavior Cloning) Deep Reinforcement Learning(DRL) 연구가 진행중이다. 자유도(Degree of Freedom, DOF)가 높은 사람형 로봇손의 학습 문제점을 개선하기 위하여, 행동 복제를 통한 Human Demonstration Augmented(DA)강화 학습을 통하여 사람처럼 사물을 조작하는 지능을 학습시킬 수 있다. 그러나 사물 조작에 있어, 의미 있는 파지를 위해서는 사물의 특정 부위를 인식하고 파지하는 방법이 필수적이다. 본 연구에서는 딥러닝 YOLO기술을 적용하여 사물의 특정 부위를 인식하고, DA-DRL을 적용하여, 사물의 특정 부분을 파지하는 딥러닝 학습 기술을 제안하고, 2 종 사물(망치 및 칼)의 손잡이 부분을 인식하고 파지하여 검증한다. 본 연구에서 제안하는 학습방법은 사람과 상호작용하거나 도구를 용도에 맞게 사용해야하는 분야에서 유용할 것이다.

• Design Convergence Study
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• v.17 no.1
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• pp.17-28
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• 2018

The manipulation of the device by hand while driving is a major factor to increase the risk of accidents, and the design of in-vehicle voice conversational interface that can compensate for this is being actively researched. The purpose of this study is to investigate the effect of the use of the barge-in function of in-vehicle voice interface on user experience. Participants were asked to carry out two tasks, one for navigation and one for music play. We conducted a survey to measure the functional user 's experience after each participant' s tasks, and measured usefulness, usability, satisfaction, and emotion as user experience factors. As a result, Barge-in has been rated as the better choice for most experience factors. There was a significant effect on usability dimension in navigation task and significant effects on usability dimension and emotional dimension in music play task. So it was found that barge-in function had a positive effect on actual user's usability and emotional dimension.

• Journal of Korean Neurosurgical Society
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• v.66 no.4
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• pp.382-392
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• 2023

Objective : The use of indocyanine green videoangiography (ICG-VA) to assess blood flow in the brain during cerebrovascular surgery has been increasing. Clinical studies on ICG-VA have predominantly focused on qualitative analysis. However, quantitative analysis numerical modelling for time profiling enables a more accurate evaluation of blood flow kinetics. In this study, we established a multiple exponential modified Gaussian (multi-EMG) model for quantitative ICG-VA to understand accurately the status of cerebral hemodynamics. Methods : We obtained clinical data of cerebral blood flow acquired the quantitative analysis ICG-VA during cerebrovascular surgery. Varied asymmetric peak functions were compared to find the most matching function form with clinical data by using a nonlinear regression algorithm. To verify the result of the nonlinear regression, the mode function was applied to various types of data. Results : The proposed multi-EMG model is well fitted to the clinical data. Because the primary parameters-growth and decay rates, and peak center and heights-of the model are characteristics of model function, they provide accurate reference values for assessing cerebral hemodynamics in various conditions. In addition, the primary parameters can be estimated on the curves with partially missed data. The accuracy of the model estimation was verified by a repeated curve fitting method using manipulation of missing data. Conclusion : The multi-EMG model can possibly serve as a universal model for cerebral hemodynamics in a comparison with other asymmetric peak functions. According to the results, the model can be helpful for clinical research assessment of cerebrovascular hemodynamics in a clinical setting.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.17-26
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• 2023

Blockchain technology has emerged as one of the most crucial solutions in numerous industries, including healthcare. The combination of blockchain technology and cloud computing results in improving access to high-quality telemedicine and healthcare services. In addition to developments in healthcare, the operational strategy outlined in Vision 2030 is extremely essential to the improvement of the standard of healthcare in Saudi Arabia. The purpose of this survey is to give a thorough analysis of the current state of healthcare technologies that are based on blockchain and cloud computing. We highlight some of the unanswered research questions in this rapidly expanding area and provide some context for them. Furthermore, we demonstrate how blockchain technology can completely alter the medical field and keep health records private; how medical jobs can detect the most critical, dangerous errors with blockchain industries. As it contributes to develop concerns about data manipulation and allows for a new kind of secure data storage pattern to be implemented in healthcare especially in telemedicine fields is discussed diagrammatically.