• 한국멀티미디어학회논문지
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• 제23권1호
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• pp.31-42
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• 2020

During the 4th Industrial Revolution, service platforms utilizing diverse contents are emerging, and research on recommended systems that can be customized to users to provide quality service is being conducted. hybrid recommendation systems that provide high accuracy recommendations are being researched in various domains, and various filtering techniques, machine learning, and deep learning are being applied to recommended systems. However, in a recommended service environment where data must be analyzed and processed real time, the accuracy of the recommendation is important, but the computational speed is also very important. Due to high level of model complexity, a hybrid recommendation system or a Deep Learning-based recommendation system takes a long time to calculate. In this paper, a Cascade-hybrid recommended algorithm is proposed that can reduce the computational time while maintaining the accuracy of the recommendation. The proposed algorithm was designed to reduce the complexity of the model and minimize the computational speed while processing sequentially, rather than using existing weights or using a hybrid recommendation technique handled in parallel. Therefore, through the algorithms in this paper, contents can be analyzed and recommended effectively and real time through services such as SNS environments or shared economy platforms.

• Journal of Acupuncture Research
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• 제19권5호
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• pp.176-188
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• 2002

Objective : Sono-acupoint (SA) therapy is a new therapeutic technique that combined with acupuncture points, herbal medicine and ultrasound therapy. This study was carried out to investigate the analgesic and anti-inflammatory effects of sono-acupoint therapy. Methods : We performed the tail-flick test with normal rats to examine the tail-flick latency (TFL), and the Freund's adjuvant-induced arthritis rat model to examine the edema, skin temperature and serum concentration of c-reactive protein and rheumatoid factor (RF). Herbal SA (HSA) treatment was performed at bilateral Zusanli (ST36) with the hanbang-gel made of several selected herbal drugs in Sprague-Dawley rats (male, $250{\pm}30g$). General SA (GSA) treatment was performed at bilateral Zusanli (ST36) with the gel used in ultrasound therapy. In arthritis rat model, Freund's adjuvant (50mg/ml) was injected in dorsal part of right foot, and these treatments were performed after 15 days. Results : TFL was lengthened after SA treatments. Skin temperature and RF concentration that were the evidence of arthritis in rats were decreased by HSA treatment (P < 0.05). Conclusion : These results indicate that HSA has the analgesic and anti-inflammatory effects in rats, and further developments will produce the advance of this new therapeutic skill.

• 한국정보통신학회논문지
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• 제18권2호
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• pp.335-344
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• 2014

본 논문은 이전 논문들에서 제안한 고속 홀로그램 생성기 구조의 입출력을 분석하여 가상의 마스터(Virtual Master, VM)를 구현하여 홀로그램 생성기의 입출력 신호 패턴을 생성하고, 이를 이용하여 AXI(Advanced eXtensible Interface)기반의 시스템과 연동하여 메모리 접근에 대한 분석하였다. 또한 메모리에 맵핑방법을 통하여 메모리 접근 시 레이턴시를 줄이는 방법을 제안하고 구현한 시스템을 통하여 메모리 접근에 대하여 분석하였다. 제안한 메모리 맵핑 방법을 통하여 분석하였을 때 약 3배 가량 행 활성화(Activation)을 줄여 레이턴시를 줄일 수 있었다.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1487-1497
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• 2016

Explosively growing service of digital multimedia data increases the need for highly scalable low-cost storage. This paper proposes the new storage architecture based on torus network which does not need network switch and erasure coding for efficient storage usage for high scalability and efficient disk utilization. The proposed model has to compensate for the disadvantage of long network latency and network processing overhead of torus network. The proposed storage model was compared to two most popular distributed file system, GlusterFS and Ceph distributed file systems through a prototype implementation. The performance of prototype system shows outstanding results than erasure coding policy of two file systems and mostly even better results than replication policy of them.

• ETRI Journal
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• 제43권2호
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• pp.357-370
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• 2021

The evolution of blockchain-based systems has enabled researchers to develop nextgeneration e-voting systems. However, the classical consensus method of blockchain, that is, Proof-of-Work, as implemented in Bitcoin, has a significant impact on energy consumption and compromises the scalability, efficiency, and latency of the system. In this paper, we propose a hybrid consensus model (PSC-Bchain) composed of Proof of Credibility and Proof of Stake that work mutually to address the aforementioned problems to secure e-voting systems. Smart contracts are used to provide a trustworthy public bulletin board and a secure computing environment to ensure the accuracy of the ballot outcome. We combine a sharding mechanism with the PSC-Bchain hybrid approach to emphasize security, thus enhancing the scalability and performance of the blockchain-based e-voting system. Furthermore, we compare and discuss the execution of attacks on the classical blockchain and our proposed hybrid blockchain, and analyze the security. Our experiments yielded new observations on the overall security, performance, and scalability of blockchain-based e-voting systems.

• 한국식생활문화학회지
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• 제36권6호
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• pp.633-639
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• 2021

Raphanus sativus var. hortensis f. raphanistroides Makino (Korean wild radish [WR]) are root vegetables belonging to the Brassicaceae family. These radish species mostly grow in sea areas in Asia, where they have been traditionally used as a medicinal food to treat various diseases. To investigate the effect of WR on neuronal cell death in SH-SY5Y cells, beta-amyloid was used to develop the cell death model. WR attenuated neuronal cell death in SH-SY5Y and regulated the mitogen-activated protein kinase (MAPK) signaling. WR extract also inhibited acetylcholinesterase inhibitor activity. Additionally, the WR treatment group ameliorated the behavior of the memory-impaired mice in a scopolamine-induced mouse model. In the behavior test, WR treated mice showed shorter escape latency and swimming distance and improved the platform-crossing number and the swimming time within the target quadrant. Furthermore, WR prevented histological loss of neurons in hippocampal CA1 regions induced by scopolamine. This study shows that WR can prevent memory impairment which may be a crucial way for the prevention and treatment of memory dysfunction and neuronal cell death.

• International journal of advanced smart convergence
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• 제10권2호
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• pp.37-44
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• 2021

At the time of entering the super-aged society, the health problem of the elderly is becoming more prominent due to the rapid digital era caused by COVID-19, but the gap between welfare budgets and welfare benefits according to regional characteristics is still not narrowed and there is a significant difference in emergency medical access. In response, this study proposes an ICT-based New Normal Smart Care System (NNSCS) to bridge the gap I n health and medical problems. This is an integrated system model that links the elderly themselves to health care, self-diagnosis, disease prediction and prevention, and emergency medical services. The purpose is to apply location-based technology and motion recognition technology under smartphones and smartwatches (wearable) environments to detect health care and risks, predict and diagnose diseases using health and medical big data, and minimize treatment latency. Through the New Normal Smart Care System (NNSCS), which links health care, prevention, and rapid emergency treatment with easy and simple access to health care for the elderly, it aims to minimize health gaps and solve health problems for the elderly.

• ETRI Journal
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• 제44권5호
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• pp.849-858
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• 2022

Dynamic voltage frequency scaling (DVFS) has been widely adopted for runtime power management of various processing units. In the case of neural processing units (NPUs), power management of neural network applications is required to adjust the frequency and voltage every layer to consider the power behavior and performance of each layer. Unfortunately, DVFS is inappropriate for layer-wise run-time power management of NPUs due to the long latency of voltage scaling compared with each layer execution time. Because the frequency scaling is fast enough to keep up with each layer, we propose a layerwise dynamic frequency scaling (DFS) technique for an NPU. Our proposed DFS exploits the highest frequency under the power limit of an NPU for each layer. To determine the highest allowable frequency, we build a power model to predict the power consumption of an NPU based on a real measurement on the fabricated NPU. Our evaluation results show that our proposed DFS improves frame per second (FPS) by 33% and saves energy by 14% on average, compared with DVFS.

• Journal of applied mathematics & informatics
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• 제41권4호
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• pp.861-868
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• 2023

Nonlinear network creates complex homotopy structural communication in wireless network medium because of complex distribution approach. Due to this multicast topological connection structure, the queuing probability was non regular principles to create routing structures. To resolve this problem, we propose a Co-cluster homotopy queuing model (Co-CHQT) for Nonlinear Algebraic Topological Structure (NLTS-) for improving poison distribution network communication. Initially this collects the routing propagation based on Nonlinear Distance Theory (NLDT) to estimate the nearest neighbor network nodes undernon linear at x_(a,b)→ax²+bx² = c. Then Quillen Network Decomposition Theorem (QNDT) was applied to sustain the non-regular routing propagation to create cluster path. Each cluster be form with co variance structure based on Two unicast 2(n+1)-Z2(n+1)-Z network. Based on the poison distribution theory X_(a,b) ≠ µ(C), at number of distribution routing strategies weights are estimated based on node response rate. Deriving shorte;'l/st path from behavioral of the node response, Hilbert -Krylov subspace clustering estimates the Cluster Head (CH) to the routing head. This solves the approximation routing strategy from the nonlinear communication depending on Max- equivalence theory (Max-T). This proposed system improves communication to construction topological cluster based on optimized level to produce better performance in distance theory, throughput latency in non-variation delay tolerant.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 춘계학술대회
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• pp.367-370
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• 2017

본 논문은 확률적 DTN 모델 내에서 효율적인 중계 노드를 선택하기 위한 방법을 제안한다. Delay Tolerant Network(DTN)은 효율적인 통신을 위해 묶음 계층(bundle layer)를 생성해 서로 다른 네트워크 및 이기종간의 네트워크 간 중계 노드를 선택하고 메시지를 전달하는 Carry and forward 방식을 사용한다. DTN은 기본적으로 유동적인 노드로 구성되어 고정된 라우팅 루트가 없으며 간헐적인 연결로 인해 긴 지연시간을 가진다. 따라서 DTN을 구성하는 노드들은 필수적으로 메시지를 저장하기 위한 특성을 가지며 저장된 메시지와 노드의 용량은 네트워크의 성능에 영향을 주게 된다. 확률적 DTN 모델은 이러한 DTN의 성능을 분석하기 위해 시간에 따라 무작위적으로 변화하는 Markov 모델을 제안하였다. 하지만 제안된 확률적 DTN 모델에서는 네트워크의 성능을 향상시키기 위한 방법에 대한 연구가 미비하였다. 본 논문은 네트워크의 성능을 향상시키기 위해 확률적 DTN 모델에서 메시지의 생성과 소멸을 통해 분석된 확률적 메시지 분포와 상호 접촉 시간을 이용해 효율적인 중계 노드를 선택하는 알고리즘을 제안한다.