• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.356-361
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• 1998

Neural Networks, modeled succinctly from the real nervous system of a living body, can be categorized into two folds; artificial neural network(ANN) and biological neural network(BNN). While the former has been developed to solve practical problems using function approximation capability, pattern classification) clustering algorithm, etc, the latter has been focused on verifying the information processing capability to which brain research gives an impetus, by mimicking real biological systems. However, BNN suffers Iron severe nonlinearities dealt with. A bridge between two neural networks is chaotic neural network(CNN), which simply delineate the real nor-vous system and comprises almost all the ANN structures by selecting parameters. Main research theme of this area is to develop an explanation tool to clarify the information processing mechanism in biological systems and its extension to engineering applications. The CNN has a Gaussian-shaped refractory function with hysteresis effect and the chaotic responses of it have been observed fur a wide range of parameter space. Through the examination of the coupling effects of excitatory and inhibitory connections, the secrets of information processing and memory structure will appear.

• Research in Community and Public Health Nursing
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• v.30 no.1
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• pp.38-46
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• 2019

Purpose: The purpose of this study isto identify the mediating effects of interpersonal problems in the relationship between Social Network Service (SNS) use tendency and depression among university students. Methods: Data were collected from April 28 to May 7, 2018 and the participants included 222 university students, who responded to the question regarding SNS use tendency, interpersonal problems and depression. The data were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation coefficients, and multiple regression using the SPSS/WIN 23.0 program. Results: A positive correlation is found between depression and SNS use tendency (r=.24, p<.001), and among interpersonal problems (r=.62, p<.001), SNS use tendency and interpersonal problems (r=.34, p<.001). Interpersonal problems have a full mediating effect on the relationship between SNS use tendency and depression (Sobel test: 5.24, p<.001). Conclusion: These results suggest that it is important to manage interpersonal problems to prevent depression caused by SNS use tendency.

• Journal of Korean Neurosurgical Society
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• v.62 no.1
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• pp.10-26
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• 2019

Magnetic resonance-guided focused ultrasound (MRgFUS) is an emerging new technology with considerable potential to treat various neurological diseases. With refinement of ultrasound transducer technology and integration with magnetic resonance imaging guidance, transcranial sonication of precise cerebral targets has become a therapeutic option. Intensity is a key determinant of ultrasound effects. High-intensity focused ultrasound can produce targeted lesions via thermal ablation of tissue. MRgFUS-mediated stereotactic ablation is non-invasive, incision-free, and confers immediate therapeutic effects. Since the US Food and Drug Administration approval of MRgFUS in 2016 for unilateral thalamotomy in medication-refractory essential tremor, studies on novel indications such as Parkinson's disease, psychiatric disease, and brain tumors are underway. MRgFUS is also used in the context of blood-brain barrier (BBB) opening at low intensities, in combination with intravenously-administered microbubbles. Preclinical studies show that MRgFUS-mediated BBB opening safely enhances the delivery of targeted chemotherapeutic agents to the brain and improves tumor control as well as survival. In addition, BBB opening has been shown to activate the innate immune system in animal models of Alzheimer's disease. Amyloid plaque clearance and promotion of neurogenesis in these studies suggest that MRgFUS-mediated BBB opening may be a new paradigm for neurodegenerative disease treatment in the future. Here, we review the current status of preclinical and clinical trials of MRgFUS-mediated thermal ablation and BBB opening, described their mechanisms of action, and discuss future prospects.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.12
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• pp.105-114
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• 2019

The goal of this study is to quantitatively evaluate the effects of the additional construction of urban railroads. To this end, 1) establish accessibility as a measure of quantitative evaluation of construction effects; 2) select the 'Integration' of Space Syntax as a quantifiable indicator of accessibility; 3) represent the Seoul railroads as a network; 4) calculate the 'Integration' form the network before and after the additional construction of the urban railroads. By calculating the change of the 'Integration' of the individual nodes and the change of the sum of the 'Integration' of given zones, the change in accessibility of a particular node and the change in accessibility of a particular region were calculated. After analyzing the change in accessibility in nodes and areas as well, it was confirmed that the additional construction of urban railroads was improving accessibility as a whole of Seoul. It was also identified that there was a degree of difference in the extent of the accessibility change for the different areas. It is particularly noteworthy that changes occur in the accessibility ranking. While certain regions were improving relative rankings, others fell in rank. With this finding, it could be argued that active consideration of the areas in which the relative decline occurs is needed when the planned urban railroad is being built.

• Korea Trade Review
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• v.44 no.2
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• pp.269-282
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• 2019

This study analyzes the effects of participation in the global production network on the income inequality using panel data from 2005 to 2016 for 63 countries. In this study were used fixed effects model with autocorrelation, random effect model with autocorrelation and the GLS method. Results are as follows: First, the economic development level supports the Kuznets hypothesis. And then, the forward participation in global value chains increased income inequality, and the backward participation decreased income inequality. In order to derive more detailed estimation results, we analyzed OECD countries and non-OECD countries. First, OECD countries featured decreased, but increased beyond a certain level as a U-shaped curve, that did not support the Kuznets hypothesis. In contrast, non-OECD countries followed the Kuznets U-curve. Second, participation in the global production network showed that both OECD and non-OECD countries featured increased income inequality. In contrast, backward participation appears to mitigate income inequality both in OECD and non-OECD countries. Finally, the ratio of labor and capital is significant in mitigating income inequality in non-OECD countries in which they feature backward participation in production networks. This can be interpreted as developing economies participate in the global production network due to increased capital accumulation and increased the labor productivity.

• Smart Structures and Systems
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• v.30 no.1
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• pp.17-34
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• 2022

For steel structures, fatigue cracks are critical damage induced by long-term cycle loading and distortion effects. Vision-based crack detection can be a solution to ensure structural integrity and performance by continuous monitoring and non-destructive assessment. A critical issue is to distinguish cracks from other features in captured images which possibly consist of complex backgrounds such as handwritings and marks, which were made to record crack patterns and lengths during periodic visual inspections. This study presents a parametric study on image-based crack identification for orthotropic steel bridge decks using captured images with complicated backgrounds. Firstly, a framework for vision-based crack segmentation using the atrous convolution-based Deeplapv3+ network (ACDN) is designed. Secondly, features on crack images are labeled to build three databanks by consideration of objects in the backgrounds. Thirdly, evaluation metrics computed from the trained ACDN models are utilized to evaluate the effects of obstacles on crack detection results. Finally, various training parameters, including image sizes, hyper-parameters, and the number of training images, are optimized for the ACDN model of crack detection. The result demonstrated that fatigue cracks could be identified by the trained ACDN models, and the accuracy of the crack-detection result was improved by optimizing the training parameters. It enables the applicability of the vision-based technique for early detecting tiny fatigue cracks in steel structures.

• 한국정보통신설비학회:학술대회논문집
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• 2007.08a
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• pp.247-250
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• 2007

There are three main kinds of service standards for 3G(Third-Generation) wireless communication as WCDMA, CDMA2000 and TD-SCDMA(Time Division-Synchronous Code Division Multiple Access). Compare with WCDMA and CDMA2000, TD-SCDMA system has distinguished technical characters. It is a TDD(Time Division Duplexing) based technology and deploys several advanced but in some respects complex technologies such as smart antenna, joint-detection and baton-handoff, etc. Therefore to analyze and design TD-SCDMA wireless network, it needs more efficient and systematic simulation tool. General simulation tool has so many analysis functions including path loss prediction, capacity and coverage analysis. For more suitable for TD-SCDMA, new additional technologies have to be implemented in simulation tool. Especially as the wireless network highly advancing focused on data service, it more needs to research and develop on the reliability of the simulation tool. In this paper, to give the concrete process and skill about how to implement TD-SCDMA simulation tool, we define the kinds of simulation tool and list basic analysis functions available for TD-SCDMA network design at first. And then we explain how to consider the effects of new technologies of TD-SCDMA and give the solutions about theses considerations.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.35-46
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• 2013

As a rapid increase of mobile network usage, many studies on solution for network traffic's demand problem have been done. Especially network environment measurement area provides basis for solving network traffic's demand problem by finding causes of problems through accurate network analysis. However, as increase of demand for smartphone, we should consider effects of mobile platform's property measuring mobile network. In this paper, we design a network traffic measurement system considering mobile platform. Through the information from packets, this system calculates packet transmission delay and throughput. We minimize computation cost required for a mobile device that is a client in this system. When fully using network resources, we found that Wi-Fi has shorter transmission delay, higher maximum throughput and lower loss rate than 3G, Android has shorter transmission delay and higher maximum throughput than iOS, and UDP has longer transmission delay and higher maximum throughput through this system.

• The Journal of the Acoustical Society of Korea
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• v.20 no.8
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• pp.12-18
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• 2001

In this paper, we propose the Recurrent Neural Predictive HMM (RNPHMM). The RNPHMM is the hybrid network of the recurrent neural network and HMM. The predictive recurrent neural network trained to predict the future vector based on several last feature vectors, and defined every state of HMM. This method uses the prediction value from the predictive recurrent neural network, which is dynamically changing due to the effects of the previous feature vectors instead of the stable average vectors. The models of the RNPHMM are Elman network prediction HMM and Jordan network prediction HMM. In the experiment, we compared the recognition abilities of the RNPHMM as we increased the state number, prediction order, and number of hidden nodes for the isolated digits. As a result of the experiments, Elman network prediction HMM and Jordan network prediction HMM have good recognition ability as 98.5% for test data, respectively.

• Management & Information Systems Review
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• v.31 no.4
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• pp.517-538
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• 2012

The purpose of this study is to explore key factors that influence the intention of continuous use of social network service users in the online environment. Since the intention of continuous use is one of the most critical factors in the profit model of social network service, the findings of this study should be useful to the SNS firms. This study use the personal and network aspects as major behavior intention of that influence user's attachment to a social network service. The results are summarized as follows. First, use motivation in self-determination have effects on emotional attachment, information sharing intention, loyalty. The world's most leading social network services now, the social network service has developed very fast as a kind of new online service. During the past few years, the number of Twitter's registered users around the world has already exceeded 170 million. Not only have the United Sates, many countries around the world have also been hit by the wave of SNS, including those in Korea. Since the intention of continuous use is one of the most critical factors in the profit model of social network service, the findings of this study should be useful to the SNS firms. We need to continue the study of social network.