• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.27 no.7
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• pp.369-374
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• 2015

This study analyzed analyzes the energy performance of six houses in Daejeon completed which were built in 2011. Observed The observed houses, which were all designed and constructed inof the same size and structure, are were highly insulated with triple Low-E coating windows; the insulation level of the walls is was $0.13W/m^2K$ and that of the roof is was $0.10W/m^2K$. As electric houses, all of the energy supplied to the houses, including for cooking, is was supplied by electricity. A and 3~4 kWp of photovoltaic system and a 3~5 kW of ground source heat pump (GSHP) were installed in each house tofor providing provide space heating/and cooling and hot water are installed. We constructed a Web-based remote monitoring system in order to understand energy consumption and the dynamic behavior of the energy system. T, and the results of our metering data analysis of 2013 are as follows. First, the annual residential energy consumption is was 4,400 kWh (${\sigma}=1,209$) and GSHP energy consumption is was 5,182 kWh (${\sigma}=1,164$). Second, residential energy consumption ranked highest in average energy usage, with at 45% of the total, followed by heating with at 30%, hot water supply with at 17% and cooling with at 6%. Third, the average energy independence rate is was 51.8%, the GFA (Gross gross floor area) criteria average energy consumption unit is was $48.7kWh/m^2yr$ (${\sigma}=10.1$), and the net energy consumption unit (except the energy yield of the PV systems) is was $24.7kWh/m^2yr$ (${\sigma}=8.8$).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.288-290
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• 2022

As part of the SOC digitization for smart water management and flood prevention, the government reported that automatic and remote control system for drainage facilities (180 billion won) to 57% of national rivers and established a real-time monitoring system (30 billion won). In addition, they were also planning to establish a smart dam safety management system (15 billion won) based on big data at 11 regions. Therefore, research is needed for smart water management and flood prevention system that can accurately calculate the flow rate through real-time flow rate measurement of rivers. In particular, the most important thing to improve the system implementation and accuracy is to ensure the accuracy of real-time flow rate measurements. To this end, radar sensors for measuring the flow rate of electromagnetic waves in the United States and Europe have been introduced and applied to the system in Korea, but demand for improvement of the system continues due to high price range and performance. Consequently, we would like to propose an improved flow rate measurement and flood forecast system by developing a radar sensor for measuring the electromagnetic surface current meter for real-time flow rate measurement.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.553-562
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• 2017

GPS (Global Positioning System) receiver among various sensors mounted on UAV (Unmanned Aerial Vehicle) helps to perform various functions such as hovering flight and waypoint flight based on GPS signals. GPS receiver can be used in an environment where GPS signals are smoothly received. However, recently, the use of UAV has been diversifying into various fields such as facility monitoring, delivery service and leisure as UAV's application field has been expended. For this reason, GPS signals may be interrupted by UAV's flight in a shadow area where the GPS signal is limited. Multipath can also include various noises in the signal, while flying in dense areas such as high-rise buildings. In this study, we used analytical photogrammetry and auto tracking total station technique for 3D positioning of UAV. The analytical photogrammetry is based on the bundle adjustment using the collinearity equations, which is the geometric principle of the center projection. The auto tracking total station technique is based on the principle of tracking the 360 degree prism target in units of seconds or less. In both techniques, the target used for positioning the UAV is mounted on top of the UAV and there is a geometric separation in the x, y and z directions between the targets. Data were acquired at different speeds of 0.86m/s, 1.5m/s and 2.4m/s to verify the flight speed of the UAV. Accuracy was evaluated by geometric separation of the target. As a result, there was an error from 1mm to 12.9cm in the x and y directions of the UAV flight. In the z direction with relatively small movement, approximately 7cm error occurred regardless of the flight speed.

• 대한공업교육학회지
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• v.32 no.1
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• pp.134-152
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• 2007

This study deals with the development of computer program which can restrict students to access to the unallowable web sites during the Internet based class. Our suggested program can find the student's access list to the unallowable sites, display it on the teacher's computer screen. Through the limitation of the student's access, teacher can enhance the efficiency of class and fulfill his educational purpose for the class. The use of our results leads to the effective and safe utilization of the Internet as the teaching tools in the class. Meanwhile, the typical method is to turn off the LAN (Local Area Network) power in order to limit the student's access to the unallowable web sites. Our program has been developed on the Linux operating systems in the small network environment. The program includes following five functions: the translation function to change the domain name into the IP(Internet Protocol) address, the search function to find the active students' computers, the packet snoop to capture the ongoing packets and investigate their contents, the comparison function to compare the captured packet contents with the predefined access restriction IP address list, and the restriction function to limit the network access when the destination IP address is equal to the IP address in the access restriction list. Our program can capture all passing packets through the computer laboratory in real time and exactly. In addition, it provides teacher's computer screen with the all relation information of students' access to the unallowable sites. Thus, teacher can limit the student's unallowable access immediately. The proposed program can be applied to the small network of the elementary, junior and senior high school. Our research results make a contribution toward the effective class management and the efficient computer laboratory management. The related researches provides teacher with the packet observation and the access limitation for only one host, but our suggested program provides teacher with those for all active hosts.

• Journal of Food Hygiene and Safety
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• v.30 no.1
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• pp.1-12
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• 2015

This study was performed to determine risk ranking of the combination of pathogen-livestock or livestock products to identify the most significant public health risks and to prioritize risk management strategies. First, we reviewed foodborne outbreak data related to livestock products and determined main vehicles and pathogens according to the number of outbreak and case. Second, expert's opinion about management priority of pathogen-livestock product pairing was surveyed with 19 livestock experts in the university, research center, and government agency. Lastly, we used the outcome of Risk Ranger (semi-quantitative risk ranking tool) of 14 combinations of pathogen and livestock or livestock products. We have classified the combination of pathogen-livestock products into group I (high risk), II (medium risk), and III (low risk) according to their risk levels and management priority. Group I, which is the highest risk for foodborne outbreak, includes Salmonella spp./egg and egg products, Campylobacter spp./poultry, pathogenic E. coli/meat and processed ground meat. In conclusion, the results of this study will provide the specific guideline of mid- and long-term planning for risk assessment and risk management prioritization of the combination of pathogen and livestock, or livestock product.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.2
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• pp.163-174
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• 2020

Particulate matter levels are rapidly increasing daily, and this can affect human health. Therefore, air pollutant emissions from sea vessels require management. This study evaluates the status of air pollutants, focusing on air pollutant emissions from the vessels of the Korea Coast Guard (KCG), and proposes national management measures to reduce emissions. According to a report recently released (2018) by the National Institute of Environmental Research (NIER), emissions from vessels constituted 6.4 % of the total domestic emissions, including 13.1 % NO_x, 10.9 % SO_x, and 9.6 % particulate matter (PM10/PM2.5). Among the rates of pollutant emission from vessels, the emission rates of domestic and overseas cargo vessels were the highest (50.6 %); the ratio of fishing boats was 42.6 %. With respect to jurisdictional sea area, 44.1 % of the emissions are from the south sea, including the Busan and Ulsan ports, and 24.8 % of the emissions are from the west sea, including the Gwangyang and Yeosu ports. The KCG inspects boarding lines to manage emission conditions and regulate air pollutant emissions, but it takes time and effort to operate various discharge devices and measure fuel oil standards. In addition, owing to busy ship schedules, inspection documents are limited in terms of management. Therefore, to reduce the air pollutant emissions of such vessels, regulations will be strengthened to check for air pollutants, and a monitoring system based on actual field data using KCG patrol ships will be established, for each sea area, to manage the emissions of such vessels. Furthermore, there is a need for technological development and institutional support for the introduction of environmentally friendly vessels.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.322-331
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• 2003

As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.

• Journal of the Korean Society of Marine Environment & Safety
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• v.15 no.2
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• pp.79-89
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• 2009

For preliminary diagnosis on current fishing ground environment and basic information for establishment of effective and rational management policy in fisheries resources protection area, water and sediment quality and changes of total area in the 10 marine protection areas designated for fisheries resources management in Korea were assessed. Results showed that environmental quality in these areas has been degraded by pollution sources, coastal utilization and development stress, etc. The pattern and degree of contamination differed by protection areas, suggesting that it is necessary for optimum environmental management plan considering the regional characteristics. The total designated area of protection areas in 2003 changed by $-22.9{\sim}2.4%$, on average -6.4%, compared with the first year of designation; Wando-Doam Bay showd the highest increase rate (2.4%), and Hansan Bay has the highest decrease rate (-22.9%) Decrease rate of land and sea in total area showd 6.1% and 6.6%. An integrated management of environmental data in protection areas is required for systematic assessment. Therefore, the suitable environmental and information management is needed specifically considering the environment characteristics such as development and utilization conditions of land and sea area Furthermore, bemuse urbanization and industrialization threats the junctions of the protection areas, authorized ministry (MIFAFF) should develope and establish monitoring and management procedures based on the related laws.

• Pediatric Infection and Vaccine
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• v.23 no.3
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• pp.202-208
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• 2016

Purpose: Rotavirus vaccine (RV) was introduced in Korea since 2007, and intussusception (IS) remains an important safety concern. This study investigated the trend of IS occurrence related to RV as well as the temporal relevance between vaccination and IS in children. Methods: We collected data of the patient aged ${\leq}18$ years with IS admitted to Gachon University Gil Medical Center, 2003 to 2015. For the patients that have occurred since 2008, the immunization records of RV were collected. The proportion of cases <1 year was calculated by the year and the temporal relationship between vaccination and IS occurrence was analyzed. Results: A total of 696 IS cases were noted. The cases <1 year were 30.7% (214/696). Although the incidence of all IS has increased over the 13-year period (from 74.1 in 2003 to 89.5 in 2015, linear by linear association, P=0.003), the incidence of IS <1 year has not increased (from 56.9 in 2003 to 53.3 in 2015, P=0.910), and the proportion of cases <1 year has decreased (from 35.4 in 2003 to 18.8 in 2015, P=0.000). Of 128 cases <1 year since 2008, 53.9% received RV. In the vaccinated group, 10 cases of IS occurred within 30 days, and eight cases did within 31 to 60 days. Numbers of IS after first, second, and third dose were three, 10, and five cases, respectively. Conclusions: Occurrence of IS in children <1 year of age did not increase since the introduction of RV. Further monitoring is essential for evaluation of vaccine safety.