• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.243-251
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• 2020

This study is intended to verify the efficiency of the information system by using the navigation application in case of fire. In the demonstration scenario simulation, it was assumed that a fire occurred 6th floor in Korea Institute of Industrial Design Promotion located in C city, K province. Eighty juniors students from K University's department of paramedics of science participated. As a result of the experiment, the demonstration simulation using the navigation application showed that the evacuation time was faster than the case of evacuation guidance in a fire situation. The need for a fire prevention system and fire prevention awareness before and after the implementation of the demonstration scenario simulation increased the need for a fire prevention system and fire prevention awareness score after the experiment.

• Journal of Sensor Science and Technology
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• v.24 no.1
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• pp.10-14
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• 2015

This paper reports the results of a study on the optimization of the etching profile, which is an important factor in deep-reactive-ion etching (DRIE), i.e., dry etching. Dry etching is the key processing step necessary for the development of the Internet of Things (IoT) and various microelectromechanical sensors (MEMS). Large-area etching (open area > 20%) under a high-frequency (HF) condition with nonoptimized processing parameters results in damage to the etched sidewall. Therefore, in this study, optimization was performed under a low-frequency (LF) condition. The HF method, which is typically used for through-silicon via (TSV) technology, applies a high etch rate and cannot be easily adapted to processes sensitive to sidewall damage. The optimal etching profile was determined by controlling various parameters for the DRIE of a large Si wafer area (open area > 20%). The optimal processing condition was derived after establishing the correlations of etch rate, uniformity, and sidewall damage on a 6-in Si wafer to the parameters of coil power, run pressure, platen power for passivation etching, and $SF_6$ gas flow rate. The processing-parameter-dependent results of the experiments performed for optimization of the etching profile in terms of etch rate, uniformity, and sidewall damage in the case of large Si area etching can be summarized as follows. When LF is applied, the platen power, coil power, and $SF_6$ should be low, whereas the run pressure has little effect on the etching performance. Under the optimal LF condition of 380 Hz, the platen power, coil power, and $SF_6$ were set at 115W, 3500W, and 700 sccm, respectively. In addition, the aforementioned standard recipe was applied as follows: run pressure of 4 Pa, $C_4F_8$ content of 400 sccm, and a gas exchange interval of $SF_6/C_4F_8=2s/3s$.

• Journal of Bio-Environment Control
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• v.25 no.1
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• pp.30-41
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• 2016

Korean government has planned to increase the productivity of horticultural crops and to expand supply smart greenhouse for energy saving by modernization of horticultural facilities based on ICT in policy. However, the diversity and linkages of monitoring and control are significantly insufficient in the agricultural sector in the current situation. Therefore, development of a service system with smart-farm based on the internet of things(IoT) for intelligent systemization of all the process of agricultural production through remote control using complex algorithm for diverse monitoring and control is required. In this study, domestic and international research trend related to ICT-based horticultural facilities was briefly introduced and limits were analyzed in the domestic application of the advanced technology. Finally, future core technologies feasible to graft in agricultural field were reviewed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.1009-1015
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• 2017

Recently, the wide spread of IoT (Internet of Things) based technology enables the accumulation of big biometric data on livestock. The availability of big data allows the application of diverse machine learning based algorithm in the field of agriculture, which significantly enhances the productivity of farms. In this paper, we propose an abnormal livestock detection algorithm based on deep learning, which is the one of the most prominent machine learning algorithm. In our proposed scheme, the livestock are divided into two clusters which are normal and abnormal (disease) whose biometric data has different characteristics. Then a deep neural network is used to classify these two clusters based on the biometric data. By using our proposed scheme, the normal and abnormal livestock can be identified based on big biometric data, even though the detailed stochastic characteristics of biometric data are unknown, which is beneficial to prevent epidemic such as mouth-and-foot disease.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.35 no.2
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• pp.119-128
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• 2022

Recent advancement of Internet of Things (IoT) and energy harvesting technology enable realization of flexible thermoelectric energy harvester (f-TEH), with technological prowess for use in biomedical monitoring system integrated applications. To expand a flexible thermoelectric energy harvesting platform, the f-TEH must be required for optimized flexible thermoelectric materials and device structure. In response to these demands related to thermoelectric energy harvesting, many research groups have investigated various f-TEHs applied as a power source for wearable electronics. As a key member of the f-TEH, film-based f-TEHs possess significant applicability in research to realize self-powered wearable electronics, owing to their excellent flexibility, low thermal conductivity, and convenient fabrication process. Thus, based on the rapid growth of thermoelectric film technology, this review aims to overview comprehensively the f-TEH made of various inorganic/organic thermoelectric materials including developed fabrication methods, high thermoelectric performance, and wide-range applications.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.2
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• pp.215-222
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• 2016

Research on gait recognition and its use is actively underway. This study suggests a method to recognize abnormal gaits of pedestrians. The purposes of the existing research to recognize normal steps are to measure physical activities and to validate people by their walks, but the purpose to recognize abnormal steps in this study is to insure the safe life of pedestrians. There are situations in which pedestrians are unaware of themselves vulnerable and can not ask for help. The purpose of this research is that even if pedestrians are unaware of themselves and there are no spontaneous requests for helps, it is intended for them to escape from dangers and difficulties by adopting the recent IOT technology. Hence, this study analyzes normal pace of pedestrians using the triaxial acceleration sensors, and takes ranges of their normal walking. And then, the steps of pedestrians are measured using the triaxial acceleration sensors, contrasted with their normal walking ranges, and determine whether their steps are normal or not. When it is out of the state for normal paces, a method to determine as abnormal paces is suggested.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.11-20
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• 2018

Recently companies have increased the new projects to improve and innovate the business process in order to adopt the advanced technologies such as IoT (Internet of Things), Big Data Analysis, Cloud Computing, mobile and artificial intelligence technologies for sustainable competitive advantages under rapid technological and socioeconomic external environmental changes. However, there are obstacles to achieve the project goals, corporate's strategy and objectives due to various kind of risks based on characteristics of projects and conflicts of stakeholders participated on projects. Hence, the solutions are required to resolve the various kind of risks and conflicts of stakeholders. The objectives of this study are to investigate the impact of the project governance, agency conflicts on the project success based on agency theory by using the statistical hypothesis testing the relationship among those variables. As a result of hypothesis testing, we could find that the project governance impacts positively on project success and negatively on the agency conflicts. Further, the agency conflicts impacts negatively on the project success. Finally, we could find that the agency conflicts such as goal conflict, different risk attitude and information asymmetry between project manager and team members impact negatively on the project success. Meanwhile, the project governance impact positively on the project success, negatively impact on the agency conflicts such as goal conflict, different risk attitude and information asymmetry between project manager and project team members. In order to increase the project success rate, the project governance institutions such as PGB (Project Governance Board), EPMO (Enterprise Project Management Office), PSC (Project Steering Committee) are needed to prevent or reduce the agency conflicts between project manager and team members.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2015-2021
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• 2017

Recently, a lot of attention is fallen to IoT(Internet of Things) for hyper-connected society and the number of unlicensed wireless device has been increasing. Thus, this paper analyzed the impact of unlicensed wireless device on the basis of 802.11ah on licensed LTE user equipment in 900 MHz frequency band for efficient frequency use. As the interference analysis method, Minimum Coupling Loss (MCL) method and Monte Carlo (MC) method were used. In case of one interferer, minimum separation distance between interferer and victim was calculated as about 22 m through the MCL method under the assumption of the worst case. The maximum number of interferer to meet the interference probability of 5% below within a cell radius of the victim was computed as about 3000 by using MC method based on statistical technique. The analysis method and results in this paper are expected to be used for the coexistence between unlicensed wireless device and licensed wireless device.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.6
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• pp.83-88
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• 2016

Over the last five years, 568 people have died while hiking according to 2015 statistics from the public safety ministry. Among those deaths, approximately 33% were due to loss of footing or falling. In this respect, the highly advanced functions of hiking boots should be considered to prevent these unfortunate accidents. For example, by utilizing the Internet of Things (IoT) and Information and Communications Technology (ICT), hiking boots equipped with a Global Positioning System (GPS) or vital signs monitoring systems should be considered. In addition, many challenges remain for the production of 3D printed hiking boots, because the functions of hiking boots are variable, which is important when handling changing terrains and situations. The design of customized hiking boots was introduced in this paper, and 3D printing applications for midsoles using a Porous Polymer Printing (PPP) method was also suggested to verify the possibility of manufacturing hiking boots.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.92-98
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• 2017

Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.