• KIPS Transactions on Software and Data Engineering
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• v.9 no.5
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• pp.169-176
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• 2020

Recently, deep neural networks (DNNs) have brought revolutions to many mobile and embedded devices by providing human-level machine intelligence for various applications. However, high inference accuracy of such DNNs comes at high computational costs, and, hence, there have been significant efforts to reduce computational overheads of DNNs either by compressing off-the-shelf models or by designing a new small footprint DNN architecture tailored to resource constrained devices. One notable recent paradigm in designing small footprint DNN models is sharing parameters in several layers. However, in previous approaches, the parameter-sharing techniques have been applied to large deep networks, such as ResNet, that are known to have high redundancy. In this paper, we propose a parameter-sharing method for already parameter-efficient small networks such as ShuffleNetV2. In our approach, small templates are combined with small layer-specific parameters to generate weights. Our experiment results on ImageNet and CIFAR100 datasets show that our approach can reduce the size of parameters by 15%-35% of ShuffleNetV2 while achieving smaller drops in accuracies compared to previous parameter-sharing and pruning approaches. We further show that the proposed approach is efficient in terms of latency and energy consumption on modern embedded devices.

• Journal of Korean Society for Geospatial Information Science
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• v.9 no.2 s.18
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• pp.29-36
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• 2001

The purpose of this paper is to describe the Disaster Management System Development of Enterprise GIS at the Kangwon Province in Korea. This project is included into 'the Kangwon Enterprise GIS 21 plan'. The Division of Disaster Management is in the middle of the 2-year project of the Disaster Management System development, appropriate for business performed at the Departments of Forestry, Culture, Environment, Tourism, etc. At the 1st phase of CIS implementation, for more than half a year we focused on the necessity of management of disasters. In the planning process, we needed long-term information on the whole area of Kangwon. In the assessment and response processes, we needed real-time data from Korean Meteorological Administration and other agencies. All the above information was carefully studied and referred to. ESRI's new GIS technologies solve the natural hazard/disaster problems. For example, hazardous materials routing often needs to be found the least expensive path through a roadway network. In the circumstances given, we can choose the departure point and destination of the vehicle, which carries the materials. It's also possible to minimize overall risk and costs of disaster problems by making a plan of people and possessions evacuation from the disaster area in short time limits. We can meet all the above goals using the latest ESRI's technologies.

• Journal of Convergence for Information Technology
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• v.10 no.2
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• pp.39-48
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• 2020

Many studies have been conducted to analyze factors that affect customer satisfaction, and service quality improvement in the parcel delivery industry. Most of these studies have a limited number of respondents using methods such as surveys and interviews. Therefore, this study aims to supplement the shortcomings of previous studies, by searching and analyzing the common major topics related to the complaints pointed out by consumers and suppliers in the parcel delivery service with cases of consumer counseling, and articles that reflect the complaints of workers in the industry. In addition, by analyzing the trend of these topics, we attempted to discover new topics and suggest implications. In conclusion, topics such as delay/lost/wrong deliveries as well as the fierce competition in the parcel delivery industry, turned out to be central aspects. As a result of the topic trend analysis, talks with international couriers have recently increased, and many conflicts related to apartment parcel delivery have been dealt with. The topics presented in this study are mainly focused on the contents of previous studies, but we expect that new and valuable topics can be derived by adding other data and analysis methods, such as internal counseling and academic literature.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.27-40
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• 2016

This paper aims to analyze the business types of 237 IoT based smart home companies in the world (launched during 1999~2014) which got global investment last few years. For this, the previous literatures trying to analze technology and service types of smart home are searched and the typology of the platform is discussed. Based on it, this research conceptualizes an analysis framework that includes three areas of smart home like home automation, home security, and energy efficiency with the three platform types like product, software, and service. This study concludes that the development of business type for IoT based smart home ecosystem is from the product to software and it can be a platform or not. In current status, there are a few platforms of product and software, but in the device management (16%) and thermostat (11%), companies are persuing more platform like. It is difficult to find the service platform in overall areas, for application based service has a few attractions in the investment market due to the lack of cloud infrastructure and data analytics. The following three are the implication to domestic market: 1) More active offering of API and SDK, 2) more active introduction of wireless Intenet network protocols, and 3) more active interoperability efforts and alliance activities are needed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.29-36
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• 2012

In Wireless Sensor Network(WSN)s, the detection of precise location of each node is essential for utilizing sensing data acquired from sensor nodes effectively. Among various location methods, the received signal strength(RSS) based localization scheme is mostly preferable in many applications because it can be easily implemented without any additional hardware cost. Since a RSS-based localization scheme is mainly affected by radio channel or obstacles such as building and mountain between two nodes, the localization error can be inevitable. To enhance the accuracy of localization in RSS-based localization scheme, a number of RSS measurements are needed, which results in the energy consumption. In this paper, a RSS based localization using Bayesian Compressive Sensing(BSS) with path-loss exponent estimation is proposed to improve the accuracy of localization in the energy-efficient way. In the propose scheme, we can increase the adaptative, reliability and accuracy of localization by estimating the path-loss exponents between nodes, and further we can enhance the energy efficiency by the compressive sensing. Through the simulation, it is shown that the proposed scheme can enhance the location accuracy of multiple unknown nodes with fewer RSS measurements and is robust against the channel variation.

• Journal of Digital Convergence
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• v.18 no.1
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• pp.137-146
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• 2020

NLP means the technology that mechanically analyzes a language spoken by a human and makes it into a form that can be understood by a computer. This is important because it is a core technology for communication between humans and devices, which is the basis of artificial intelligence. In this paper, I analyzed patent information of US and Korea in order to identify technical trends related to NLP, especially semantic analysis. and the purpose of this study is to provide meaningful information for future research on NLP. In conclusion, the number of Korea patents is 7.9% compared to the USA and the different frequencies of the major keywords were found to differ from country to country in technical direction. In addition, the upward or downward keywords are twice as many in the U.S. as in Korea, and reflect the trend of the times relatively more. Based on these results, in future study, I will analysis how upward trending keywords are described in actual patents for concrete technology prediction.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.6
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• pp.53-67
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• 2002

The multimedia synchronization is one of the key issues to be resolved in order to provide a good quality of multimedia related services, such as Video on Demands(VoD), Lecture on Demands(LoD), and tele-conferences. In this paper, we introduce an adaptive multimedia synchronization algorithm using the level of buffers and load of servers, which are modeled and analyzed by ExSpect, a Petri net based simulation tool. In the proposed algorithm, the audio and video buffers are divided to 5 different levels, and the pre-defined play-out speed controller tries to make the buffer level to be normal in different temporal relations between multimedia streams using buffer levels and server loads. Because each multimedia packet is played by the pre-defined play-out speed, the media data can be reproduced within the permissible limit of errors while preserving the level of buffers to be normal. The proposed algorithm is able to handle and support various communication restrictions between providers and users, and offers little jitter play-out to many users in networks with the limited transmission capability. The performance of the developed algorithm is analyzed in various network conditions using a Petri net simulation tool.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.123-136
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• 2005

We propose a recognition system for superimposed patterns based on selective attention model and SVM which produces better performance than artificial neural network. The proposed selective attention model includes attention layer prior to SVM which affects SVM's input parameters. It also behaves as selective filter. The philosophy behind selective attention model is to find the stopping criteria to stop training and also defines the confidence measure of the selective attention's outcome. Support vector represents the other surrounding sample vectors. The support vector closest to the initial input vector in consideration is chosen. Minimal euclidean distance between the modified input vector based on selective attention and the chosen support vector defines the stopping criteria. It is difficult to define the confidence measure of selective attention if we apply common selective attention model, A new way of doffing the confidence measure can be set under the constraint that each modified input pixel does not cross over the boundary of original input pixel, thus the range of applicable information get increased. This method uses the following information; the Euclidean distance between an input pattern and modified pattern, the output of SVM, the support vector output of hidden neuron that is the closest to the initial input pattern. For the recognition experiment, 45 different combinations of USPS digit data are used. Better recognition performance is seen when selective attention is applied along with SVM than SVM only. Also, the proposed selective attention shows better performance than common selective attention.

• Journal of the Korean Chemical Society
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• v.18 no.5
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• pp.329-340
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• 1974

Sulfadiazine, $C_{10}H_{10}N_4O_2S$, forms monoclinic crystals of space group $P21}c$ from a mixture of acetone and ethanol with $a=13.71{\pm}0.04,\;b=5.84{\pm}0.03,\;c=15.11{\pm}0.05{\AA},\;{\beta}=115.0{\pm}0.3^{\circ}$, and four molecules per cell. Three dimensional photographic data were collected with $CuK\alpha$ radiation. The structure was determined using Patterson and Fourier synthesis methods and refined by block diagonal least-squares methods with isotropic thermal parameter for all non-hydrogen atoms. The final R value was 0.15 for the 1517 observed independent reflections. The dihedral angle between the planes through the benzene ring and the pyrimidine ring is $76^{\circ}$. The conformational angle formed by the projection of the S-C(5) bond with that of N(1)-C(1) where the projection is taken along the S-N(1) bond is $77^{\circ}$. The imino nitrogen atom, N(1), and pyrimidine nitrogen atom, N(3), form intermolecular $N-H{\cdots}N$ hydrogen bond between the molecules related by center of symmetry. Amino nitrogen atom, N(4), forms two intermolecular $N-H{\cdots}O$ hydrogen bonds, with O(1) and O(2) atoms of different molecules separated by b. A two dimensional network of hydrogen bonds form infinite molecular sheets parallel to the (100) plane. Adjacent sheets are bound together by van der Waals forces.

• The Korean Journal of Financial Management
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• v.26 no.3
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• pp.103-138
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• 2009

In this article we examine a unique data set of intraday fair disclosure(FD) releases to shed light on market efficiency within the trading day. Specifically, this paper analyze the response of stock prices on fair disclosure disseminated in real-time through KIND(Korea Investor's Network for Disclosure) on Korea stock exchange during the period from January 2003 to September 2004. We find that the prices of stock experiences a statistically and economically significant increase beginning seconds after the fair disclosure is initially announced and lasting approximately two minutes. The stock price responds more strongly to fair disclosure on smaller firm but the response to fair disclosure on the largest firm stock is more gradual, lasting five minutes. We also examine the profitability of a short-term trading strategy based on dissemination of fair disclosure. After controlling for trading costs we find that trader who execute a trade following initial disclosure generate negative profits, but trader buying stock before initial disclosure realize statistically significant positive profit after two minute of disclosure. Summarizing overall results, our evidence supports that security prices on Korea stock exchange reflects all available information within two minutes and the Korea stock market is semi-strongly efficient enough that a trader cannot generate profits based on widely disseminated news unless he acts almost immediately.