• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.208-214
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• 2021

Recently, much of the intelligent security scenario and criminal investigation demands for matching photo and non-photo. Existing face recognition system can not sufficiently guarantee these needs. In this paper, we propose an algorithm to improve the performance of heterogeneous face recognition systems by reducing the different modality between sketches and photos of the same person. The proposed algorithm extracts each image's texture features through texture descriptors (gray level co-occurrence matrix, multiscale local binary pattern), and based on this, generates a transformation matrix through eigenfeature regularization and extraction techniques. The score value calculated between the vectors generated in this way finally recognizes the identity of the sketch image through the score normalization methods.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.225-236
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• 2014

Productivity of public organizations was far older due to issue more difficult to measure than private organizations. Unlike the private sector, the public sector is a diverse and sometimes conflicting objectives (efficiency, effectiveness, equity, democracy, etc.) exist, it is difficult to measure productivity in a single index. Many departments of government is intricately interrelated and sometimes produced by the joint efforts, it is difficult to allocate performance, incentives and accountability to among departments. And there is the difficulty of collecting data on the productivity indicators of public organizations. Despite these difficulties, we developed a productivity index system and measuring method to systematically introduce the concept of productivity in the local administration. In this paper, the productivity and the productivity index measurement practices of local governments conducted annually from 2011 on was deep into research. First, the report found examples of the governments of the developed countries, productivity measurement, then the way MOPAS(Ministry of Public Administration and Security) measure productivity index of local governments, success factors, the implications were in-depth analysis. Finally, in order to enhance productivity and competitiveness municipalities studied ways to take advantage of the productivity index.

• Journal of Multimedia Information System
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• v.9 no.1
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• pp.51-60
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• 2022

This paper raised the need to examine how the online education environment triggered by COVID-19 and the smart learning environment can be established in consideration of the improvement of education and learning through learning analysis. Many studies are being conducted in Korea, and the Ministry of Education is continuously striving to build a smart school by promoting strategies for promoting smart education on the way to a talent powerhouse. Nevertheless, there is no unified definition of smart learning, and it can be seen as customized (individualized) learning using smart devices. However, most of the discussions on the construction of smart schools so far have limitations in that they are limited to physical spaces. Accordingly, the opinions of teachers and learners were not sufficiently reflected in the establishment of the facility. This study intends to study smart learning in various departments. In addition, the subjects students in charge of the co-researcher of this study were analyzed. The total number of subjects was 951, and 434 responded to this study survey. In addition, students were well accepting the online environment, and in the future, regardless of COVID-19, research will be presented to improve mutual communication between professors and students in smart learning.

• Journal of Preventive Medicine and Public Health
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• v.54 no.3
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• pp.208-217
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• 2021

Objectives: In spite of the importance of green space for reducing obesity-related problems, there has been little exploration of whether access to green space (e.g., parks and recreational facilities) influences the obesity rate of adults in the United States. The purpose of the study was to investigate the relationships among accessibility of green space, obesity rates, and socioeconomic and demographic variables among adults living in the State of Indiana, United States. Methods: We conducted a secondary data analysis to investigate the relationships among accessibility to green space, obesity rates, and socio-demographic variables with employing Geographic Information System in order to measure the accessibility of green space. Results: This study found that accessibility of green space served as a strong predictor of reduced obesity rates among adults (β=-2.478; p<0.10). In addition, adults with higher education levels, as well as better access to green space, were found to have even lower obesity rates (β=-0.188; p<0.05). Other control variables such as unemployment rates, food security, and physical inactivity are additional factors that influence obesity rates among adults. Conclusions: Accessibility of green space may play an important role in facilitating physical activity participation and reducing obesity rates.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.59-69
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• 2021

Malfunctions and failures linked to medical devices may result in significant damage for human being. Thus, in order to ensure that safety of medical device is achieved, it should be established and applied the international standard. It is required to integrate and customize activities at standards, owing to reference relationship between standards, especially, activities based safety analysis is too expensive. This paper proposes a integration process that integrate activities of development lifecycle and safety process. Additionally, we derived a guidance based on STPA for integration process. As a result, we can be performed systematically from early stage of the development and increased effectiveness of integration process by the guidance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.213-220
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• 2023

Face recognition is a very important process in video monitoring and is a type of biometric technology. It is mainly used for identification and security purposes, such as ID cards, licenses, and passports. The recognition process has many variables and is complex, so development has been slow. In this paper, we proposed a face recognition method using CNN, which has been re-examined due to the recent development of computers and algorithms, and compared with the feature comparison method, which is an existing face recognition algorithm, to verify performance. The proposed face search method is divided into a face region extraction step and a learning step. For learning, face images were standardized to 50×50 pixels, and learning was conducted while minimizing unnecessary nodes. In this paper, convolution and polling-based techniques, which are one of the deep learning technologies, were used for learning, and 1,000 face images were randomly selected from among 7,000 images of Caltech, and as a result of inspection, the final recognition rate was 98%.

• Annual Conference of KIPS
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• 2009.11a
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• pp.139-140
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• 2009

양성자 기반 공학 기술 개발 사업단은 20MeV 양성자 가속기를 운전 중이며, 진공, 빔 계측, 전원 등의 장치에 대한 제어 시스템을 개발 운영 중이다. 대형 입자 가속기를 위한 제어 시스템의 전체 네트워크는 사용자 인터페이스와 제어계가 단일 네트워크를 공유하고 있으며 EPICS(Experimental Physics and Industrial Control System) CA(Channel Access)통신을 이용하여 데이터를 상호 교환한다. 그러나 단일 네트워크를 사용함으로서 관리자만이 제어해야 할 데이터는 많은 클라이언트에게 노출되는 문제점이 있다. 그러므로 클라이언트의 접근을 제어하여 제어계로부터 전달되는 신호들의 안정성과 보안성을 유지할 수 있는 방법이 요구된다. 본 논문에서는 제어시스템에 보안성과 안정성을 유지하기 위하여 클라이언트를 Control Network, 제어계를 Machine Network로 분산시키고 통신 중계기 역할을 하는 CA Gateway를 적용하여 클라이언트에게 접근 권한을 주는 기법을 제시하고 구현 및 그 결과를 보고한다.

• Annual Conference of KIPS
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• 2022.11a
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• pp.1068-1070
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• 2022

우리나라의 무역 활동을 처리하는 항만은 국가 주요시설로 보안에 만전을 기하고 있다. 그러나 항만의 면적이 넓고 복잡하기 때문에 사각지대가 존재하고 사각지대에서의 불법행위 단속 건수는 매년 증가하고 있다. 이에 항만의 보안 강화를 위한 대책이 필요하다. 본 논문은 항만의 상황을 이동형 CCTV에 부착된 IoT 센서들로 인식하여 YOLOv5 딥러닝 모델로 분석한 후 웹 대시보드에 시각화하는 항만 보안 시스템을 제안한다. 이동형 CCTV는 특정 위치로 직접 이동할 수 있어 거리에 따라 해상도가 낮아지는 기존 CCTV의 단점을 보완할 수 있다. 또한 해당 시스템은 주변에서 쉽게 구할 수 있는 장비들과 오픈소스 라이브러리를 활용하기 때문에 다른 보안장비들에 비해 효율적인 비용으로 높은 보안 효과를 얻을 수 있다는 강점을 지닌다. 본 시스템은 항만시설뿐 아니라 군사시설, 물류시설 등 보안을 중요시하는 다른 분야에 확대 적용될 수 있다는 점에서 의의가 있다.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.458-463
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• 2023

This study presents a paper on the implementation of a Raspberry Pi-based educational smart farm system. It confirms that in a real smart farm environment, the control of temperature, humidity, soil moisture, and light intensity can be smoothly managed. It also includes remote monitoring and control of sensor information through a web service. Additionally, information about intruders collected by the Pi camera is transmitted to the administrator. Although the cost of existing smart farms varies depending on the location, material, and type of installation, it costs 400 million won for polytunnel and 1.5 billion won for glass greenhouses when constructing 0.5ha (1,500 pyeong) on average. Nevertheless, among the problems of smart farms, there are lax locks, malfunctions to automation, and errors in smart farm sensors (power problems, etc.). We believe that this study can protect crops at low cost if it is complementarily used to improve the security and reliability of expensive smart farms. The cost of using this study is about 100,000 won, so it can be used inexpensively even when applied to the area. In addition, in the case of plant cultivators, cultivators with remote control functions are sold for more than 1 million won, so they can be used as low-cost plant cultivators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.494-510
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• 2024

Internet users are exposed to sophisticated cyberattacks that intrusion detection systems have difficulty detecting. Therefore, research is increasing on intrusion detection methods that use artificial intelligence technology for detecting novel cyberattacks. Unsupervised learning-based methods are being researched that learn only from normal data and detect abnormal behaviors by finding patterns. This study developed an anomaly-detection method based on unsupervised machines and deep learning for a network intrusion detection system (NIDS). We present a hybrid anomaly detection approach based on unsupervised learning techniques using the autoencoder (AE), Isolation Forest (IF), and Local Outlier Factor (LOF) algorithms. An oversampling approach that increased the detection rate was also examined. A hybrid approach that combined deep learning algorithms and traditional machine learning algorithms was highly effective in setting the thresholds for anomalies without subjective human judgment. It achieved precision and recall rates respectively of 88.2% and 92.8% when combining two AEs, IF, and LOF while using an oversampling approach to learn more unknown normal data improved the detection accuracy. This approach achieved precision and recall rates respectively of 88.2% and 94.6%, further improving the detection accuracy compared with the hybrid method. Therefore, in NIDS the proposed approach provides high reliability for detecting cyberattacks.