• Journal of Sensor Science and Technology
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• v.33 no.1
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• pp.40-47
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• 2024

The creation of vertically aligned one-dimensional (1D) nanostructures through the decoration of n-type tin oxide (SnO₂) on p-type chromium oxide (Cr₂O₃) constitutes an effective strategy for enhancing gas sensing performance. These heterostructures are deposited in multiple stages using a glancing angle deposition technique with an electron beam evaporator, resulting in a reduction in the surface porosity of the nanorods as SnO₂ is incorporated. In comparison to Cr₂O₃ films, the bare Cr₂O₃ nanorods exhibits a response 3.3 times greater to 50 ppm H₂S at 300℃, while the SnO₂-decorated Cr₂O₃ nanorods demonstrate an eleven-fold increase in response. Furthermore, when subjected to various gases (CH₄, H₂S, CO₂, H₂), a notable selectivity toward H₂S is observed. This study paves the way for the development of p-type semiconductor sensors with heightened selectivity and sensitivity towards H₂S, thus advancing the prospects of gas sensor technology.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.162-173
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• 2009

Information on the expected geographical shift of suitable zones for growing crops under future climate is a starting point of adaptation planning in agriculture and is attracting much concern from policy makers as well as researchers. Few practical schemes have been developed, however, because of the difficulty in implementing the site-selection concept at an analytical level. In this study, we suggest site-selection criteria for quality Fuji apple production and integrate geospatial data and information available in public domains (e.g., digital elevation model, digital soil maps, digital climate maps, and predictive models for agroclimate and fruit quality) to implement this concept on a GIS platform. Primary criterion for selecting sites suitable for Fuji apple production includes land cover, topography, and soil texture. When the primary criterion is satisfied, climatic conditions such as the length of frost free season, freezing risk during the overwintering period, and the late frost risk in spring are tested as the secondary criterion. Finally, the third criterion checks for fruit quality such as color and shape. Land attributes related to these factors in each criterion were implemented in ArcGIS environment as relevant raster layers for spatial analysis, and retrieval procedures were automated by writing programs compatible with ArcGIS. This scheme was applied to the A1B projected climates for South Korea in the future normal years (2011-2040, 2041-2070, and 2071-2100) as well as the current climate condition observed in 1971-2000 for selecting the sites suitable for quality Fuji apple production in each period. Results showed that this scheme can figure out the geographical shift of suitable zones at landscape scales as well as the latitudinal shift of northern limit for cultivation at national or regional scales.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.83-98
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• 2021

The purpose of this study to find the factors influencing the fire alarms using IoT firefighting facility management system data of Seoul Fire & Disaster Headquarters, and to present academic implications for establishing an effective prevention system of fire situation. As the number of high and complex buildings increases and former bulidings are advanced, the fire detection facilities that can quickly respond to emergency situations are also increasing. However, if the accuracy of the fire situation is incorrectly detected and the accuracy is lowered, the inconvenience of the residents increases and the reliability decreases. Therefore, it is necessary to improve accuracy of the system through efficient inspection and the internal environment investigation of buildings. The purpose of this study is to find out that false detection may occur due to building characteristics such as usage or time, and to aim of emphasizing the need for efficient system inspection and controlling the internal environment. As a result, it is found that the size(total area) of the building had the greatest effect on the fire alarms, and the fire alarms increased as private buildings, R-type receivers, and a large number of failure or shutoff days. In addition, factors that influencing fire alarms were different depending on the main usage of the building. In terms of time, it was found to follow people's daily patterns during weekdays(9 am to 6 pm), and each peaked around 10 am and 2 pm. This study was claimed that it is necessary to investigate the building environment that caused the fire alarms, along with the system internal inspection. Also, it propose additional recording of building environment data in real-time for follow-up research and system enhancement.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.1 s.6
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• pp.15-29
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• 2005

Truck Shipment Safety Information, which is a part of the development of NERIS is divided into Optimal Route Guidance System and Emergency Response System. This research is for establishing an advance warning system, which aims for preventing damages(fire, explosion, gas-escape etc.) and detecting incidents that are able to happen during transporting hazardous materials in advance through monitoring the position of moving vehicles and the state of hazardous materials in real-time. This research is peformed to confirm the practical possibility of application of the advance warning system that monitors whether the hazardous materials transport vehicles move the allowed routes, finds the time and the location of incidents of the vehicles promptly and develops the emergency system that is able to respond to the incidents as well by using the technologies of CPS, CDMA and CIS with testing the ability of performance. As the results of the test, communication accuracies are 99$\%$ in freeway, 96$\%$ in arterial, 97$\%$ in hilly sections, 99$\%$ in normal sections, 96$\%$ in local sections, 99$\%$ in urban sections and 98$\%$ in tunnels. According to those results, the system has been recorded a high success rate of communication that enough to apply to the real site. However, the weak point appeared through the testing is that the system has a limitation of communication that is caused in the rural areas and certain areas where are fewer antennas that make communication possible between on-board unit and management server. Consequently, for the practical use of this system, it is essential to develop the exclusive en-board unit for the vehicles and find the method that supplements the receiving limitation of the GPS coordinates inside tunnels. Additionally, this system can be used to regulate illegal acts automatically such as illegal negligence of hazardous materials. And the system can be applied to the study about an application scheme as a guideline for transporting hazardous materials because there is no certain management system and act of toxic substances in Korea.

• Korean Security Journal
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• no.31
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• pp.73-100
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• 2012

Republic of Korea for the last 2012 nuclear security summit in Seoul in three days from March 26, has held great success. This industry watchers at home and abroad through professional meetings and private organizations to promote global nuclear security was intended to draw, for the preparation of this event the most important one of the things that should be addressed at the meeting was over the top guard. The national guard of heads of state and nationally significant as the important issues should be dealt with. So who is responsible for national security summit national guard for a successful guard against participants should have a higher understanding, these stories ever to be dealt with important security subjects is the psychological state of cognition. This study is currently a source of honor to escort the psychological state of subjects, and whether the search as I looked at cognition. Qualitative research methods to conduct research in-depth interview technique was used for one of the transcribed data analysis program, a non-quantitative data were analyzed using NVivo 8. As a result of this study, analysis of the problem compared with the usual methods 39 (72.2%), fine-grained observation and 15 (27.7%), through the media how cognition 41 (73.2%), marginal help of 15 (26.7%) were. The usual comparison with how honored Issue sources to detect security of those words and actions and facial expressions, etc. Security of subjects over the state of mind cognition that he, detailed observation of the national guard to security subjects the psychological state of cognition which are pre-Thorough Information subjects that can have all the information about security and the state can be obtained by saying that. Media coverage through a cognitive approach national guard of the media coverage to understand the security subjects of the political situation to understand the prerequisite that were marginal for help through the cognitive approach of security subjects surrounding the execution of security workers, Secretary in charge of protocol and security, and be propagated through the selection techniques to be utilized was that.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10B
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• pp.946-961
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• 2008

This study aims to provide guidelines on future policy for restructuring the scheme of aid programs associated with If small and medium-sized enterprises (i.e. SME) in Korea. For this purpose, we investigate an empirical dataset of recent aid programs deployed by Ministry of Information and Communication (i.e. MIC) for the last four years First, it is examined that the programs are practiced in accordance with their own policy objective by comparing matching samples between two groups such as program beneficiary and non-beneficiary companies. Second, positioning transition of programs within a same category is visualized in terms of two business portfolio analysis matrices. Third, an affiliation network matrix of (he programs is newly developed and then we attempt to analyze the programs relationship by the application of multidimensional scaling method to the affiliation network matrix. The empirical dataset is composed of two different kinds of corporate datasets. One is a corporate dataset of 8,994 beneficiary companies that are aided by MIC during the year of '03-'06. The other is also a corporate dataset of 18,354 non-beneficiary companies that have no records of the program supports during the years at all. Particularly, the matching samples of non-beneficiary companies are prepared in order to have comparable corporate age years (i.e. CAY) against beneficiary companies' CAY. Results show that; 1) up-to-date, the programs are properly assigned to IT SME conforming to their own policy objective; 2) however, as the year goes on, the following two distinct positioning transitions are revealed such as (1) both CAY and corporate sales (i.e. SAL) are increased simultaneously, (2) ratio of intangible assets (i.e. RIA) is decreased and ratio of operating gain to revenue (i.e. ROR) is increased. Hence, the role of the programs gets weakened with regard to providing seed money to technology innovation-typed IT SME so that a managerial adjustment of the programs is required consequently; 3) even though the model adequacy is not satisfactory through the analysis of multidimensional scaling method, the relationship of indirect-typed programs can relatively be stronger than that of direct-typed programs.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.144-149
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• 2018

The eggs are incubated for 18 days through the generator and incubated in the developing incubator. During the developmental period, the weight loss of the fetus is correlated with the ventricular formation, and the proper ventricular formation is also associated with the healthy embryonic hatching and the egg hatching rate. However, in the incubator period of the domestic hatchery, it is a reality to acquire the resultant side by the Iranian standard weight measurement with the experience of the hatchery and the person concerned and the development period without the apparatus for measuring the present weight. As a result, prevalence of early mortality, hunger and illness during hatching are frequent. Monitoring the reduction of weaning weight is crucial to obtaining chick quality and hatching performance with weight changes within the development machine. Water loss is different depending on the size of eggs, egg shell, and elder group. We can expect to increase the hatching rate by measuring the weight change in real time and optimizing the ventilation change accordingly. There is a need to develop a real-time measurement system that can control 10 to 13% reduction of the total weight during hatching. The system through this study is a way to check the one - time directly when moving the existing egg, and it is impossible to control the measurement of the fetal water evaporation within the development period. Unlike systems that do not affect the hatching rate, four load cells are connected in parallel on the Arduino sketch board and the AT-command command is used to connect the mobile phone and computer in real time. The communication speed of Bluetooth was set to 15200 to match the communication speed of Arduino and Hyper-terminal program. The real - time monitoring system was designed to visually check the change of the weight of the fetus in the artificial incubator. In this way, we aimed to improve the hatching rate and health condition of the hatching eggs.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.2
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• pp.82-96
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• 2019

This study evaluated the status of watershed health in Geum River Basin by SWAT (Soil and Water Assessment Tool) hydrology and water quality. The watershed healthiness from watershed hydrology and stream water quality was calculated using multivariate normal distribution from 0(poor) to 1(good). Before evaluation of watershed healthiness, the SWAT calibration for 11 years(2005~2015) of streamflow(Q) at 5 locations with 0.50~0.77 average Nash-Sutcliffe model efficiency and suspended solid (SS), total nitrogen(T-N), and total phosphorus(T-P) at 3 locations with 0.67~0.94, 0.59~0.79, and 0.61~0.79 determination coefficient($R^2$) respectively. For 24 years (1985~2008) the spatiotemporal change of watershed healthiness was analyzed with calibarted SWAT and 5 land use data of 1985, 1990, 1995, 2000, and 2008. The 2008 SWAT results showed that the surface runoff increased by 40.6%, soil moisture and baseflow decreased by 6.8% and 3.0% respectively compared to 1985 reference year. The stream water quality of SS, T-N, and T-P increased by 29.2%, 9.3%, and 16.7% respectively by land development and agricultural activity. Based on the 1985 year land use condition. the 2008 watershed healthiness of hydrology and stream water quality decreased from 1 to 0.94 and 0.69 respectively. The results of this study be able to detect changes in watershed environment due to human activity compared to past natural conditions.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.