• International Journal of Advanced Culture Technology
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• v.9 no.1
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• pp.177-182
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• 2021

The fourth industrial revolution based on information and communication technology (ICT) becomes the center of society, and the overall industrial structure is also changing significantly. ICT refers to the hardware of information devices and the software technologies required for the operation and information management of these devices, and any means of collecting, producing, processing, preserving, communicating and utilizing them. ICT is integrated into industries and services or combined with new technologies in various fields such as robotics and nanotechnology to connect all products and services to the network. The development of ICT, which continuously creates new products and services, has spread to all sectors of the industry, affecting not only daily life but also the livestock sector recently. In agriculture, ICT technology can reduce production costs by efficiently managing labor and energy because it can improve quality and yield based on data on environmental and growth information such as temperature, humidity, light and soil. In particular, smart livestock is considered suitable for achieving livestock management goals because it can reduce labor force and improve productivity by remotely and automatically managing accurate information necessary for raising and breeding livestock with ICT devices. The purpose of this study is to propose the need for ICT technology by comparing farm productivity before and after ICT is introduced. The method of the study is to compare the productivity before and after the introduction of ICT in Korean beef farms, pig farms, and poultry farms. The effectiveness of the study proved the excellence of ICT technology through the production results before ICT introduction and the productivity improvement case of livestock farms that efficiently operated manpower management and reduced labor force after ICT introduction. The conclusion of this paper is to present the need for smart livestock through ICT adoption through case study results.

• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.91-96
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• 2022

With the development of the cloud industry, various efforts are being made to improve resource efficiency and environmental continuity in software development and operation methods. However, in constructing a conventional structure of structural scheme, if the functionality is improved and added, it has a problem that the efficiency of full build arrangement is reduced for the changed source. In this paper, if a problem occurs in a solution service company, communication between the development department and the operation department can be facilitated and responded quickly, and the latest source updated during processing of the problem is the management system, provided is a system that can take advantage of CI tools and continuously integrate them. As communication through the proposed system is smooth, it is expected that unnecessary work can be reduced and the speed of development can be improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.668-674
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• 2022

Machine learning techniques using visual data have high usability in fields of industry and service such as scene recognition, fault detection, security and user analysis. Among these, user analysis through the videos from CCTV is one of the practical way of using vision data. Also, many studies about lightweight artificial neural network have been published to increase high usability for mobile and embedded environment so far. In this study, we propose the network combining the object detection and classification for mobile graphic processing unit. This network detects pedestrian and face, classifies age and gender from detected face. Proposed network is constructed based on MobileNet, YOLOv2 and skip connection. Both detection and classification models are trained individually and combined as 2-stage structure. Also, attention mechanism is used to improve detection and classification ability. Nvidia Jetson Nano is used to run and evaluate the proposed system.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.2
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• pp.158-163
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• 2023

Recently, the global demands for high voltage power semiconductors are increasing across various industrial fields. The use of electric cars with high safety and convenience is becoming practical, and IGBT modules of 3.3 kV and 1.2 kA or higher are used for electric locomotives. Delicate design and advanced process technology are required, and research on the optimization of high-voltage IGBT parts is urgently needed in the industry. In this study, we attempted to design a simulation process through TCAD (technology computer-aid design) software to optimize the process conditions of the fielding process among the core unit processes for an especial high yield voltage. As well, the prior circuit technology design and a ring pattern with a large number of ring formation structures outside the wafer similar to the chip structure of other companies were constructed for 3.3 kV NPT-IGBT through a unit process demonstration experiment. The ring pattern was designed with 21 rings and the width of the ring was 6.6 ㎛. By changing the spacing between patterns from 17.4 ㎛ to 35.4 ㎛, it was possible to optimize the spacing from 19.2 ㎛ to 18.4 ㎛.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.230-236
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• 2020

A trash screen is installed in front of the inflow channel of a drainage pumping station, sewage treatment plant, and a power plant to block floating contaminants. The bottleneck phenomenon, which decreases the water inflow, causes damage to the damper as a result of clogging in between the screen if string type obstacles are not removed. In this paper, the apron was removed, and the screen was expanded, to prevent breakage of the bottleneck phenomenon and string type obstacles. This was designed using an extended rake by adding an inner rake in between the screen interspace to remove the bottleneck phenomenon and string type obstacles. To design the inner rake that satisfies the allowable stresses of the existing damper rake, the experiment points were determined according to the experimental design method using the inner rake vertical length and the thickness of the reinforced section as parameters. The use of the ANSYS static structural module and statistical analysis tool R software gives the optimized shape according to the response surface method. The relative error between the response surface analysis results and the simulation results was 1.63% of the determined optimal design-point rake length of 210.2 mm and the reinforcement section thickness of 2 mm. Through empirical experiments, a test rake was constructed to the actual size, and approximately 97% of the bottleneck phenomenon and string type obstacles could be removed.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.193-204
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• 2019

The explosion of data due to the improvement of sensor technology and computing performance has become the basis for analyzing the situation in the industrial fields, and various attempts to detect events based on such data are increasing recently. In particular, sound signals collected from sensors are used as important information to classify events in various application fields as an advantage of efficiently collecting field information at a relatively low cost. However, the performance of sound-event classification in the field cannot be guaranteed if noise can not be removed. That is, in order to implement a system that can be practically applied, robust performance should be guaranteed even in various noise conditions. In this study, we propose a system that can classify the sound event after generating the enhanced sound signal based on the deep learning algorithm. Especially, to remove noise from the sound signal itself, the enhanced sound data against the noise is generated using SEGAN applied to the GAN with a VAE technique. Then, an end-to-end based sound-event classification system is designed to classify the sound events using the enhanced sound signal as input data of CNN structure without a data conversion process. The performance of the proposed method was verified experimentally using sound data obtained from the industrial field, and the f1 score of 99.29% (railway industry) and 97.80% (livestock industry) was confirmed.

• Korean Journal of Construction Engineering and Management
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• v.19 no.2
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• pp.15-24
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• 2018

Despite the recognition of the need for productivity information and its importance, the feedback of productivity information is not well-established in the construction industry. Effective use of productivity information is required to improve the reliability of construction planning. However, in many cases, on-site productivity information is hardly management effectively, but rather it relies on the experience and/or intuition of project participants. Based on the literature review and expert interviews, the authors recognized that one of the possible solutions is to develop a systematic approach in dealing with productivity information of the construction job-sites. It is required that the new system should not be burdensome to users, purpose-oriented information management, easy-to follow information structure, real-time information feedback, and productivity-related factor recognition. Based on the preliminary investigations, this study proposed a framework for a novel system that facilitate the effective management of construction productivity information. This system has utilized Sketchup software which has good user accessibility by minimizing additional data input and related workload. The proposed system has been designed to input, process, and output the pertinent information through a four-stage process: preparation, input, processing, and output. The inputted construction information is classified into Task Breakdown Structure (TBS) and Material Breakdown Structure (MBS), which are constructed by referring to the contents of the standard specification of building construction, and converted into productivity information. In addition, the converted information is also graphically visualized on the screen, allowing the users to use the productivity information from the job-site. The productivity information management system proposed in this study has been pilot-tested in terms of practical applicability and information availability in the real construction project. Very positive results have been obtained from the usability and the applicability of the system and benefits are expected from the validity test of the system. If the proposed system is used in the planning stage in the construction, the productivity information and the continuous information is accumulated, the expected effectiveness of this study would be conceivably further enhanced.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.10
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• pp.920-929
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• 2014

Recently, embedded system which demand is explosively increasing in the fields of communication, traffic, medical and industry facilities, expands to cyber physical system (CPS) which monitors and controls the networked embedded systems. In addition, internet of things(IoT) technology using wearable devices such as Google Glass, Samsung Galaxy Gear and Sony Smart Watch are gaining attention. In this situation, Samsung Smart Home and LG Home Chat are released one after another. However, since these services can be available only between smart phones and home appliances, there is a disadvantage that information cannot be passed to other terminals without commercial global messaging server. In this paper, to solve above issues, we propose the structure of an indoor location network based on unit space, which prevents the information of the devices or each individual person from leaking to outside and can selectively communicate to all existent terminals in the network using IoT chatting. Also, it is possible to control general devices and prevent external leakage of private information.

• Korean Journal of Agricultural Science
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• v.43 no.4
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• pp.650-655
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• 2016

Gears are components of transmission which transmit the power of an engine to a machine and offer numerous speed ratios, a compact structure, and high efficiency of power transmission. Gear train design in the automotive industry uses simulation software. However, PTO (Power Take-Off) gear design for agricultural applications uses the empirical method because of the wide range of load fluctuations in agricultural fields. The PTO is an important part of agricultural tractors which transmits the power to various tractor implements. Therefore, a simulation was essential to the optimal design of the PTO. When the PTO gear is optimally designed, there are many advantages such as low cost, reduced size, and light weight. In this study, we conducted the bending and contact safety factor simulation for the PTO gear of an agricultural tractor. The bending and contact safety factors were calculated on ISO 6336 : 2006 by decreasing the face widths of the PTO pinion and wheel gear from 18 mm at an interval of 1 mm. The safety factor of the PTO gear decreased as the face width decreased. The contact safety factors of the pinion and wheel gear were 1.45 and 1.53, respectively, when the face width was 18 mm. The simulation results showed that the face width of the PTO gear should be greater than 9 mm to maintain the bending and contact safety factors higher than 1. It would be possible to reduce the weight of the PTO gear for different uses and working conditions. This study suggests that the possibility of designing an optimal PTO gear decreases as its face width decreases.