• KIPS Transactions on Software and Data Engineering
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• v.4 no.3
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• pp.99-110
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• 2015

Internet-of-Things(IoT) is the computing paradigm converged with different technologies, where diverse devices are connected via the wireless network, acquire environmental information from their equipped sensors, and actuated. IoT applications typically provide smart services to users by interacting with multiple devices connected to the network and are designed by integrating multiple technologies such as sensor network, communication technologies, and software engineering. Moreover, since the concept of IoT has been introduced recently, most of the researches are in the beginning step, which is too early to be practically applied. Due to these facts, developing IoT application results in unconventional technical challenges which have not been observed in typical software applications. And, it is not straightforward to apply conventional project guidelines to IoT application development projects. Hence, there can be many difficulties to successfully complete the projects. Therefore, for successful completion of the projects, we analyze technical challenges occurring in all phases of the project lifecycle, i.e. project preparation stage and development stage. And, we propose the effective solutions to overcome the issues. To verify identified issues and presented solutions, we present the result of applying the solutions to an IoT application development. Through the case study, we evaluate how reasonable the unconventional technical issues are generated and analyze effectiveness of applying the solutions to the application.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.8 no.4
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• pp.67-79
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• 2013

A meta-analysis is a statistical literature synthesis method that provides the opportunity to view the research context by combining and analyzing the quantitative results of many empirical studies. The technology acceptance model (TAM) has been the subjects of a great deal of MIS research in the last two decades and now also has been continuously studied. Recently, the convergence of knowledge information society and information telecommunication technologies has a rapid impact on politics, economics and various fields. The biggest issue in the information communication and information systems fields is smart. Therefore, we conducted a meta-analysis research on the behavioral intention of smart phone users based on technology acceptance model. Also, this study was targeted a total of 50 research papers that are setting up the causal relationship in TAM among the research papers published in domestic academic journals since 2005. The result of the meta analysis, showed that the effect size was 0.48 in the path from perceived usefulness to behavioral intention, it showed that the effect size was 0.46 in the path from perceived ease of use to behavioral intention. And, it showed that the effect size was 0.46 in the path from perceived ease of use to perceived usefulness. Also, it showed that the effect size was 0.61 in the path from attitude to behavioral intention. Based on the results, it was discussed the difference through comparative analysis with previous research.

• Spatial Information Research
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• v.17 no.1
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• pp.131-144
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• 2009

Recently, a lot of local autonomous entities are promoting Ubiquitous City(U-City) Construction by integrating Information Communication Technology(ICT) with city development, and also internationally, a lot of cities are making efforts to develop U-City to intensify a city's competitive strength and improve life quality of city dwellers. In keeping with such a stream of the times, each local autonomous entity and project developer are developing a lot of methodologies to establish optimal U-City in corresponding cities and also inquiring into a variety of development procedures, such as connecting existing urban development methods with information establishment methods. The method used usually is to establish Information strategy Plan(ISP) for a city which will be developed through consulting in the stage of city development planning. ISP is to establish vision & strategy for building the ubiquitous city and is a methodology including city vision, strategy, goal, and implementation method, etc. However, due to a lot of variables, such as a variety of city environment, establishment period, budget, information technology, and etc., it is difficult to contain establishment plans for every occasion in a similar method, in reality. Therefore, it is naturally necessary to suggest plans for city vision & strategy, and selection of element technology/service. Thus, this paper suggests models for vision & strategy establishment of U-City and suggests Top-Down Approach and Bottom-Up Approach method as a plan for U-City establishment. In addition, this paper analyzes general promotion methodologies for constructing U-City and analyzes how these two strategic methods [Top-Down Approach and Bottom-Up Approach] for city vision establishment are composed in such a methodology, to define and analyze its constituent plan.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.41-47
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• 2009

Routing through a backbone, which is responsible for performing and managing multipoint communication, reduces the communication overhead and overall energy consumption in wireless sensor networks. However, the backbone nodes will need extra functionality and therefore consume more energy compared to the other nodes. The power consumption imbalance among sensor nodes may cause a network partition and failures where the transmission from some sensors to the sink node could be blocked. Hence optimal construction of the backbone is one of the pivotal problems in sensor network applications and can drastically affect the network's communication energy dissipation. In this paper a distributed algorithm is proposed to generate backbone trees through robust multi-hop clusters in wireless sensor networks. The main objective is to form a properly designed backbone through multi-hop clusters by considering energy level and degree of each node. Our improved cluster head selection method ensures that energy is consumed evenly among the nodes in the network, thereby increasing the network lifetime. Comprehensive computer simulations have indicated that the newly proposed scheme gives approximately 10.36% and 24.05% improvements in the performances related to the residual energy level and the degree of the cluster heads respectively and also prolongs the network lifetime.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.223-229
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• 2018

Recently, the necessity of safety diagnosis of electrical devices has been increasing as the fire caused by electric devices has increased rapidly. This study is concerned with the safety diagnosis of electric equipment using intelligent Fuzzy technology. It is used as a diagnostic input for the multiple electrical safety factors such as the use current, cumulative use time, deterioration and arc characteristics inherent to the equipment. In order to extract these information in real time, a device composed of various sensor circuits, DSP signal processing, and communication circuit is implemented. The fuzzy logic algorithm using the Gaussian function for each information is designed and compiled to be implemented on a small DSP board. The fuzzy logic receives the four diagnostic information, deduces it by the fuzzy engine, and outputs the overall safety status of the device as a 100-step analog fuzzy value familiar to human sensibility. By experiments of a device that combines hardware and fuzzy algorithm implemented in this study, it is verified that it can be implemented in a small DSP board with human-friendly fuzzy value, diagnosing real-time safety conditions during operation of electric equipment. In the future, we expect to be able to study more intelligent diagnostic systems based on artificial intelligent with AI dedicated Micom.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.807-812
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• 2020

In order to prevent the national wide spread of the COVID-19 virus, the government enforces to use an electronic access registration system for public facilities to effectively track and manage the spread. Initially, there was a lot of hassle to write a directory, but recently a system for creating an electronic access list using QR codes, what is called KI-Pass, is mainly used. However, the procedure for generating a QR code is somewhat cumbersome. In this paper, we propose a new electronic access registration system that does not require QR code. This system effectively controls the suspicious visitor by using a mask wearing discriminator which has been implemented using deep learning technology, and a non-contact thermometer package. In addition, by linking the beacon, a short-range wireless communication technology, and the visitor's smartphone application, basic information of the facility visitor is automatically registered to KDCA through the server. On the other hand, the user access information registered in the server is encrypted and stored, and is automatically destroyed after up to 4 weeks. This system is expected to be very effective in preventing the spread of other new infectious diseases as well as responding to the coronavirus which is recording a high spread worldwide.

• Journal of vocational education research
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• v.37 no.2
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• pp.77-99
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• 2018

The purpose of this study was to investigate the employment possibility of the humanities college graduates to science and engineering field occupations, and to identify the occupational characteristics related to employability perceived by workers. To do this, basic statistical analysis, correlation analysis, and hierarchical multiple regression analysis were conducted using the data surveyed on 2,600 workers in the science and engineering field in the 'Research on Korean Occupational Index for Career and Employment Service(2017)'. The main results are as follows. First, the employment possibility of the humanities college graduates to science and engineering field was low, except for some occupations in the information communication, manufacturing and processing fields. Second, the occupational characteristics affecting the employment possibilities of the humanities college graduates to science and engineering field are as follows: low importance of the final education, low importance of the major, low importance of qualification, high importance of vocational training, easy to return after the career break, high level of gender equality, high level of pleasant work environment, high employment retention, easy to self-employment or start-up, and increasing number of jobs. Based on the results of this study, to support employment of humanities college graduate from the occupational aspect, it is necessary to find out some detailed jobs or to develop convergence occupations. At this time, it is possible to utilize the occupational characteristics factors that increase the employment possibility of humanities college graduates to science and engineering occupations.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.4
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• pp.101-111
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• 2019

In distance learning, quality of service is an important part of improving customer satisfaction and customer loyalty. However, in verifying the effectiveness of remote education service quality, it has been researched based on fragmentary effects on remote education service quality, and the effect study on the specific target is insufficient. In this study, the effects of remote education service factors on customer satisfaction and customer loyalty were analyzed in the previous study and among job seekers. The survey was conducted from March 2019 and 258 samples of job seekers who experienced remote education were used for empirical analysis. As a result of the analysis, typology, problem solving, interaction, information serviceability, and convenience had a positive effect on customer satisfaction, and satisfaction had a significant influence on customer loyalty. In addition, it was analyzed that characterization, problem-solving, interaction, information serviceability, convenience and customer loyalty were affected in the verification of the mediated effects of satisfaction. In response, the implications of this study were derived from practical research on customer satisfaction and loyalty of educational companies related to eduTech, where education and ICT (Information Communication Technology) were integrated during the 4th Industrial Revolution, which suggested that the quality of a company's remote education service affected customer satisfaction and customer loyalty to entrepreneurs and marketers in the education company's start-up and marketing process. Further, further research will be needed in other areas as well as in the areas of employment education to verify the importance of service quality and assess the various effects.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.6
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• pp.243-250
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• 2019

Because of a moving UAV has a lot of potential/kinetic energy, if the UAV falls to the ground, it may have a lot of impact. Because this can lead to human casualities, in this paper, the population density area on the UAV flight path is defined as a dangerous area. The conventional UAV path flight was a passive form in which a UAV moved in accordance with a path preset by a user before the flight. Some UAVs include safety features such as a obstacle avoidance system during flight. Still, it is difficult to respond to changes in the real-time flight environment. Using public Big Data for UAV path flight can improve response to real-time flight environment changes by enabling detection of dangerous areas and avoidance of the areas. Therefore, in this paper, we propose a method to detect and avoid dangerous areas for UAVs by utilizing the Big Data collected in real-time. If the routh is designated according to the destination by the proposed method, the dangerous area is determined in real-time and the flight is made to the optimal bypass path. In further research, we will study ways to increase the quality satisfaction of the images acquired by flying under the avoidance flight plan.

• The Journal of Bigdata
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• v.6 no.1
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• pp.23-35
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• 2021

In the era of the 4th industrial revolution, smart factories have received great attention, where production and manufacturing technology and ICT converge. With the development of IoT technology and big data, automation of production systems has become possible. In the advanced manufacturing industry, production systems are subject to unscheduled performance degradation and downtime, and there is a demand to reduce safety risks by detecting and reparing potential errors as soon as possible. This study designs a model based on supervised and unsupervised learning for detecting anomalies. The accuracy of XGBoost, LightGBM, and CNN models was compared as a supervised learning analysis method. Through the evaluation index based on the confusion matrix, it was confirmed that LightGBM is most predictive (97%). In addition, as an unsupervised learning analysis method, MD, AE, and LSTM-AE models were constructed. Comparing three unsupervised learning analysis methods, the LSTM-AE model detected 75% of anomalies and showed the best performance. This study aims to contribute to the advancement of the smart factory by combining supervised and unsupervised learning techniques to accurately diagnose equipment failures and predict when abnormal situations occur, thereby laying the foundation for preemptive responses to abnormal situations. do.