• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.227-228
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• 2022

The slowdown of the global economic market due to the pandemic is causing the global construction market to stagnate, and the use of smart construction technology is drawing attention as one of the main alternatives to overcome this problem. In fact, a number of previous studies have been published that smart construction technologies such as building information modeling and drones can contribute to project performance improvement, such as productivity improvement and cost reduction. However, previous studies focus on the application direction and technical effectiveness of smart construction technology, so the analysis in terms of the contribution that the application of the technology has to the project performance is insufficient. Therefore, the purpose of this study is to focus on the effectiveness aspect of the application of smart construction technology on the project performance. The results of this study are expected to be able to be used as basic data for establishing policies related to the activation of smart construction technology promoted by the government and setting the direction for the use of smart construction technology by stakeholders.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.113-124
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• 2019

Recently, Omni Channel Services has been considered the most innovative business strategy. Omni-Channel sees a variety of channels from all channels viewpoints, organically combining each channel to provide a seamless experience for consumers. In other words, Omni-Channel is not simply a systematic integration of channels, but a means of delivering consistent services to consumers in all processes through a strategy to an organic connection. The aim of this study is to provide a comprehensive insight into the decision factors affecting the adoption of Omni-channel. For this purpose, an empirical analysis is conducted on the course of acceptanceof the Omni-channel service based on the Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-technology fit (TTF), an effective model frequently selected to describe the acceptance of service in the introduction phase of new information technology. As a result of the study, it was confirmed that the task characteristics and the technical characteristics had a positive effect on the task-technology fit, and the task-technology fit had a positive effect on the performance expectancy. In addition, task-technology fit, performance expectancy, and social influence have a positive effect on the intention to use the Omni-Channel. This study is intended to deliver an experimental meaning by proposing a strategical measure to understand the behaviorsand uses of consumers in the Omni-channel service environment and increase the customer satisfaction for the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3447-3469
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• 2019

It is well-known that the cooperative communication and error control technology can improve the network performance, but most existing cooperative MAC protocols have not focused on how to cope with the contention process caused by cooperation and how to reduce the bad influence of channel packet error rate on the system performance. Inspired by this, this paper first modifies and improves the basic rules of the IEEE 802.11 Medium Access Control (MAC) protocol to optimize the contention among the multi-relay in a cooperative ARQ scheme. Secondly, a hybrid ARQ protocol with soft combining is adopted to make full use of the effective information in the error data packet and hence improve the ability of the receiver to decode the data packet correctly. The closed expressions of network performance including throughput and average packet transmission delay in a saturated network are then analyzed and derived by establishing a dedicated two-dimensional Markov model and solving its steady-state distribution. Finally, the performance evaluation and superiority of the proposed protocol are validated in different representative study cases through MATLAB simulations.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1996.10a
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• pp.29-48
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• 1996

Previous studies on user training have largely focused on assessing models which describe the determinants of information technology usage or examined theeffects of training, on user satisfaction, productivity, performance and so on. Scant research efforts have been made, however, to examine those effects of training by using theoretical models. This study presented a conceptural model to predict intention to use information technology and conducted an experimentto understand how training for computer skill acquisition affects primary variables of the model. The data were obtained from 32 student subjects of an experimental group and 31 students of a control group, and the information technology employed for this study was a university's electronic mail system. The study results revealed that attitude toward usage and perceived behavioral control helped to predict user intentions ; outcome expectations were positively related to attitude toward usage ; and self-efficacy was positively related to perceived behavioral control. Thd hands-on training for the experimental group led to increases in perceived ease of use, self-efficacy and perceived behaviroal control. The changes in those variables suggest more causal effects of user training than other survey studies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.785-790
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• 2017

Network scanning tools typically use port scans to steal information from network terminals and identify vulnerabilities. In particular, Shodan and Censys use a network scanning tool to gather a wide range of terminal information, store it in their database and provide it to the users. In order to prevent such information gathering, it is required to know the scanning methods of Shodan and Censys. However, the scanning model used by Shodan and Censys is not known exactly. Therefore, this paper estimates scanning models of Shodan and Censys and analyzes the performance of each models.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.991-992
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• 2006

Multiprocessor system is efficient and high performance architecture to overcome a limitation of single core SoC. In this paper, we propose a multiprocessor SoC (MPSoC) architecture which provides the low complexity and the high performance. The dynamic routing scheme has a serious problem in which the complexity of routing increases exponentially. We solve this problem by making a cluster with several PEs (Processing Element). In inter-cluster network, we use deterministic routing scheme and in intra-cluster network, we use dynamic routing scheme. In order to control the hierarchical network, we propose efficient router architecture by using smart crossbar switch. We modeled 2-D mesh topology and used simulator based on C/C++. The results of this routing scheme show that our approach has less complexity and improved throughput as compared with the pure deterministic routing architecture and the pure dynamic routing architecture.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.633-635
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• 2016

Convolutional Networks (ConvNets) are powerful models that learn hierarchies of visual features, which could also be used to obtain image representations for transfer learning. The basic pipeline for transfer learning is to first train a ConvNet on a large dataset (source task) and then use feed-forward units activation of the trained ConvNet as image representation for smaller datasets (target task). Our key contribution is to demonstrate superior performance of multiple ConvNet layer features over single ConvNet layer features. Combining multiple ConvNet layer features will result in more complex feature space with some features being repetitive. This requires some form of feature selection. We use AdaBoost with single stumps to implicitly select only distinct features that are useful towards classification from concatenated ConvNet features. Experimental results show that using multiple ConvNet layer activation features instead of single ConvNet layer features consistently will produce superior performance. Improvements becomes significant as we increase the distance between source task and the target task.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.490-496
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• 2005

In this paper, we propose a self-constructed clustering algorithm based on inference information of the fuzzy model. This method makes it possible to automatically detect and optimize the number of cluster and parameters by using input-output data. The propose method improves the performance of clustering by extended supervised learning technique. This technique uses the output information as well as input characteristics. For effect the similarity measure in clustering, we use the TSK fuzzy model to sent the information of output. In the conceptually, we design a learning method that use to feedback the information of output to the clustering since proposed algorithm perform to separate each classes in input data space. We show effectiveness of proposed method using simulation than previous ones

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.57-65
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• 2019

In this paper, we propose a Rights Management Information(RMI) expression systems for individual sites are integrated and the performance evaluation is performed to find out an efficient comparing and updating method of RMI through various image feature point search techniques. In addition, we proposed a weighted scoring model for both public domain sites and posts in order to use the most latest RMI based on reliable data. To solve problem that most public domain sites are exposed to copyright infringement by providing inconsistent RMI(Rights Management Information) expression system and non-up-to-date RMI information. The weighted scoring model proposed in this paper makes it possible to use the latest RMI for duplicated images that have been verified through the performance evaluation experiments of SIFT and CNN techniques and to improve the accuracy when applied to search engines. In addition, there is an advantage in providing users with accurate original public domain images and their RMI from the search engine even when some modified public domain images are searched by users.

• Journal of Communications and Networks
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• v.13 no.4
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• pp.319-326
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• 2011

Beamforming techniques have been successfully utilized for traffic channels in order to solve the interference problem. However, their use for control channels has not been sufficiently investigated. In this paper, a (semi-) centralized beamforming strategy that adaptively changes beam patterns and controls the total transmit power of cells is proposed for the performance enhancement of the common channel in hierarchical cell structure (HCS) networks. In addition, some examples of its practical implementation with low complexity are presented for two-tier HCS networks consisting of macro and pico cells. The performance of the proposed scheme has been evaluated through multi-cell system-level simulations under optimistic and pessimistic interference scenarios. The cumulative distribution function of user geometry or channel quality has been used as a performance metric since in the case of common control channel the number of outage users is more important than the sum rate. Simulation results confirm that the proposed scheme provides a significant gain compared to the random beamforming scheme as well as conventional systems that do not use the proposed algorithm. Finally, the proposed scheme can be applied simultaneously to several adjacent macro and pico cells even if it is designed primarily for the pico cell within macro cells.