• Journal of KIISE:Software and Applications
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• v.33 no.5
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• pp.499-507
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• 2006

Recently human gait has been considered as a useful biometric supporting high performance human identification systems. This paper proposes a view-based pedestrian identification method using the dynamic silhouettes of a human body modeled with the Hidden Markov Model(HMM). Two types of gait models have been developed both with an endless cycle architecture: one is a discrete HMM method using a self-organizing map-based VQ codebook and the other is a continuous HMM method using feature vectors transformed into a PCA space. Experimental results showed a consistent performance trend over a range of model parameters and the recognition rate up to 88.1%. Compared with other methods, the proposed models and techniques are believed to have a sufficient potential for a successful application to gait recognition.

• Journal of Korea Multimedia Society
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• v.14 no.9
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• pp.1182-1189
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• 2011

We named the system Visual Path Map which visualizes the distribution of clusters according to characteristics and entire process about exercise prescription, and we purpose to visualize a process according to exercise prescription. Visual Path Map visualizes the distribution of clusters according to characteristics, current and object distribution, and changed distribution for prescription. So it visualizes paths from current distribution to object distribution according to prescription. We used SOM in order to express properties along subjects in Visual Path map, and visualized distribution of clusters about physical characteristics, body mass index, and age information of 1,500 ordinary people. Also we visualize practical exercise prescription according to real data of expert of exercise prescription.

• Journal of IKEEE
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• v.24 no.4
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• pp.1039-1049
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• 2020

Neural decoding is important to recognize the user's intention for controlling a neuro-prosthetic hand. This paper proposes a real-time decoding method for multi-channel peripheral neural activity. Peripheral nerve signals were measured from the median and radial nerves, and motion artifacts were removed based on locally fitted polynomials. Action potentials were then classified using a k-means algorithm. The firing rate of action potentials was extracted as a feature vector and its dimensionality was reduced by a self-organizing feature map. Finally, a multi-layer perceptron was used to classify hand motions. In monkey experiments, all processes were completed within a real-time constrain, and the hand motions were recognized with a high success rate.

• Journal of Intelligence and Information Systems
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• v.13 no.2
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• pp.69-80
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• 2007

The preferences of customers change over time. However, existing collaborative filtering (CF) systems are static, since they only incorporate information regarding whether a customer buys a product during a certain period and do not make use of the purchase sequences of customers. Therefore, the quality of the recommendations of the typical CF could be improved through the use of information on such sequences. In this study, we propose a new methodology for enhancing the quality of CF recommendation that uses customer purchase sequences. The proposed methodology is applied to a large department store in Korea and compared to existing CF techniques. Various experiments using real-world data demonstrate that the proposed methodology provides higher quality recommendations than do typical CF techniques with better performance.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2017.05a
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• pp.133-133
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• 2017

[서론] Pure Ti 및 Ti합금의 양극산화법에 의해 만들 수 있는 자기조직화된 나노튜브피막은 광촉매, 태양전지 등 다양한 분야에서 많은 연구가 되고 있다. 양극산화법에 의해 생성되는 산화피막층의 성장거동에 대해서 지금까지 용액의 pH, 온도 및 인가전압 등 양극산화조건의 영향에 대해 많은 연구가 보고 되었다. 하지만, 양극산화에 사용되는 기판의 특성에 대해서는 많은 연구가 이루어지지 않고 있다. 본 연구에서는 pure Ti 및 Ti-Ni합금에 양극산화법에 의해 생성하는 나노튜브 피막층의 성장거동에 대해 기판의 특성(Ni농도 변화 및 phase변화)이 피막층의 형태 및 성장거동에 미치는 영향에 대해서 조사 하였다. [실험방법] Sample은 pure Ti 및 Ti-xNi(x=49.0, 51.1, 52.2, 52.5 at.%)를 이용하였다. Ti-Ni합금은 아크용해로 제작 후 $1000^{\circ}C$ 에서 24시간 균질화 처리 후 20% 냉간압연을 하였다. 합금의 조성 및 결정구조 분석은 EPMA 및 XRD를 통해 조사 하였고, 양극산화는 미량의 물 및 불화암모늄을 포함한 에틸렌글리콜 용액에서 20, 35, 50V 20분간 실시하였다. 양극산화법에 의해 형성한 산화피막층은 FE-SEM 및 TEM을 통해 관찰 하였다. [결론] Pure Ti의 경우 모든 조건에서 나노튜브형태의 산화막이 형성되는 것을 알 수 있었다. 하지만, Ti-Ni 합금의 경우 20V, 35V에서는 sponge 형태의 산화막이 형성되고, 50V에서만 나노튜브형태의 산화막이 형성 되었다. 또한, 모든 시편에서 양극산화 시간이 증가함에 따라 나노튜브형태의 산화막은 sponge 형태로 구조적 변화가 일어나는 것을 알 수 있었다. 그리고, 기판 Ni농도가 증가 함에 따라 형성되는 산화막의 형태 변화는 가속화 되는 것을 알 수 있었다. 이러한 결과는 양극산화 초기 Ti의 우선적 산화에 의해 Ti과잉의 나노튜브층이 생성되고, 동시에 산화막과 합금계면에 Ni과잉층이 형성되는 것을 알 수 있었다. 산화막과 합금계면에 생성된 Ni과잉층에 의해 양극산화 시간이 증가함에 따라 sponge형태의 산화막이 생성되는 것을 알 수 있었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.9
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• pp.762-771
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• 2012

In this paper, we propose an adaptive power control scheme employing a self-optimization concept in femtocell systems, in order to improve system capacity, thereby reducing call-drop probability. In the proposed scheme, each femto base station(FBS) controls individual channel's transmission power base on two parameters; the neighboring cell's transmission power for each individual channel which is delivered from a femto-gateway and the received power strength from neighboring cells which is periodically measured by means of a spectrum sensing. Adaptive adjustment of individual channel's transmission power in accordance with femto mobile station(FMS) mobility features can also reduce undesirable handovers and evenly distribute traffic load over all femtocells. In addition, the manipulative control of channel's transmission power is able to keep the system coverage and the call-drop probability within an acceptable range, regardless of density of femtocells. Computer simulation shows that the proposed scheme outperforms existing schemes in terms of the system coverage and the call-drop probability.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.185-192
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• 2013

The purpose of this study is to set the relationship between each parts that forms the engine of an automobile based on the 3D visualization technology which is able to be learned according to the skill of the operator in the industry field and to recommend the auto parts using a task ontology. A visualization method was proposed by structuring the complex knowledge by signifying the link and the node in forms of a network and using SOM which can be shown in the form of 3 dimension. In addition, by using is-a Relationship-based hierarchical Taxonomy setting the relationship between each of the parts that forms the engine of an automobile, to allow a recommendation using a weighted value possible. By providing and placing the complex knowledge in the 3D space to the user for an opportunity of more realistic and intuitive navigation, when randomly selecting the automobile parts, it allows the recommendation of the parts having a close relationship with the corresponding parts for easy assembly and to know the importance of usage for the automobile parts without any special expertise.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.181-188
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• 2011

With the rapid proliferation of wireless networks and mobile computing applications, the landscape of the network security has greatly changed recently. Especially, Vehicular Ad Hoc Networks maintaining network topology with vehicle nodes of high mobility are self-organizing Peer-to-Peer networks that typically have short-lasting and unstable communication links. VANETs are formed with neither fixed infrastructure, centralized administration, nor dedicated routing equipment, and vehicle nodes are moving, joining and leaving the network with very high speed over time. So, VANET-security is very vulnerable for the intrusion of malicious and misbehaving nodes in the network, since VANETs are mostly open networks, allowing everyone connection without centralized control. In this paper, we propose a weighted intrusion detection method using rough set that can identify malicious behavior of vehicle node's activity and detect intrusions efficiently in VANETs. The performance of the proposed scheme is evaluated by a simulation study in terms of intrusion detection rate and false alarm rate for the threshold of deviation number ${\epsilon}$.

• Smart Media Journal
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• v.1 no.2
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• pp.12-22
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• 2012

Today we are witnessing an increasingly widespread use of cameras in our lives for video surveillance, robot vision, and mobile phones. This has led to a renewed interest in computer vision in general and an on-going boom in human activity recognition in particular. Although not particularly fancy per se, human gait is inarguably the most common and frequent action. Early on this decade there has been a passing interest in human gait recognition, but it soon declined before we came up with a systematic analysis and understanding of walking motion. This paper presents a set of DBN-based models for the analysis of human gait in sequence of increasing complexity and modeling power. The discussion centers around HMM-based statistical methods capable of modeling the variability and incompleteness of input video signals. Finally a novel idea of extending the discrete state Markov chain with a continuous density function is proposed in order to better characterize the gait direction. The proposed modeling framework allows us to recognize pedestrian up to 91.67% and to elegantly decode out two independent gait components of direction and posture through a sequence of experiments.

• Cross-Cultural Studies
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• v.52
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• pp.277-312
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• 2018

First-order cybernetics during the 1940s and 1950s aimed for control of an observed system, while second-order cybernetics during the mid-1970s aspired to address the mechanism of an observing system. The former pursues an objective, subjectless, approach to a system, whereas the latter prefers a subjective, personal approach to a system. Second-order observation must be noted since a human observer is a living system that has its unique cognition. Maturana and Varela place the autopoiesis of this biological system at the core of second-order cybernetics. They contend that an autpoietic system maintains, transforms and produces itself. Technoscientific recreation of biological autopoiesis opens up to a new step in cybernetics: what I describe as third-order cybernetics. The formation of technoscientific autopoiesis overlaps with the Fourth Industrial Revolution or what Erik Brynjolfsson and Andrew McAfee call the Second Machine Age. It leads to a radical shift from human centrism to posthumanity whereby humanity is mechanized, and machinery is biologized. In two versions of the novel Demon Seed, American novelist Dean Koontz explores the significance of technoscientific autopoiesis. The 1973 version dramatizes two kinds of observers: the technophobic human observer and the technology-friendly machine observer Proteus. As the story concludes, the former dominates the latter with the result that an anthropocentric position still works. The 1997 version, however, reveals the victory of the techno-friendly narrator Proteus over the anthropocentric narrator. Losing his narrational position, the technophobic human narrator of the story disappears. In the 1997 version, Proteus becomes the subject of desire in luring divorcee Susan. He longs to flaunt his male egomaniac. His achievement of male identity is a sign of technological autopoiesis characteristic of third-order cybernetics. To display self-producing capabilities integral to the autonomy of machinery, Koontz's novel demonstrates that Proteus manipulates Susan's egg to produce a human-machine mixture. Koontz's demon child, problematically enough, implicates the future of eugenics in an era of technological autopoiesis. Proteus creates a crossbreed of humanity and machinery to engineer a perfect body and mind. He fixes incurable or intractable diseases through genetic modifications. Proteus transfers a vast amount of digital information to his offspring's brain, which enables the demon child to achieve state-of-the-art intelligence. His technological editing of human genes and consciousness leads to digital standardization through unanimous spread of the best qualities of humanity. He gathers distinguished human genes and mental status much like collecting luxury brands. Accordingly, Proteus's child-making project ultimately moves towards technologically-controlled eugenics. Pointedly, it disturbs the classical ideal of liberal humanism celebrating a human being as the master of his or her nature.