• Journal of the Institute of Convergence Signal Processing
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• v.13 no.2
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• pp.83-90
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• 2012

In this paper, an intelligent visual surveillance system based on a NIOS II embedded platform is implemented. By this time, embedded based visual surveillance systems were restricted for a special purpose because of high dependence upon hardware. In order to improve the restriction, we implement a flexible embedded platform, which is available for various purpose of applications. For high speed processing of software based programming, we improved performance of the system which is integrated the SOPC type of NIOS II embedded processor and image processing algorithms by using software programming and C2H(The Altera NIOS II C-To-Hardware(C2H) Acceleration Compiler) compiler in the core of the hardware platform. Then, we constructed a server system which globally manage some devices by the NIOS II embedded processor platform, and included the control function on networks to increase efficiency for user. We tested and evaluated our system at the designated region for visual surveillance.

• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.154-162
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• 2019

Despite the development of information and communication technology, which has a great impact on society and culture, there is no platform that provides a systematic classification and state-of-the-art information retrieval system on the traditional culture. Therefore, this paper developed a traditional culture retrieval system capable of convergence services with systematic classification and retrieval based on automatically generate and visualize the 3D timeline. This system provides the function of collecting traditional culture contents, classifying and storing collected traditional culture contents, and automatically generating 3D digital timeline based on stored traditional culture contents. In addition, a system satisfaction questionnaire was developed to evaluate the usability of the system, and 19 students participated in verifying the system. As a result of the experiment, the satisfaction of the system showed that all items were 'satisfied' on average.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.33-39
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• 2019

As cyber attack methods are becoming more intelligent, incidents such as security breaches and international crimes are increasing. In order to predict and respond to these cyber attacks, the characteristics, methods, and types of attack techniques should be identified. To this end, many security companies are publishing security intelligence reports to quickly identify various attack patterns and prevent further damage. However, the reports that each company distributes are not structured, yet, the number of published intelligence reports are ever-increasing. In this paper, we propose a method to extract structured data from unstructured security intelligence reports. We also propose an automatic intelligence report analysis system that divides a large volume of reports into sub-groups based on their topics, making the report analysis process more effective and efficient.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1381-1390
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• 2021

Smart grid is a representative convergence new technology in the era of the 4th industry revolution that deals with three broad security areas consisting of control system, the power grid, and the consumer. As it is a convergence new technology of the 4th industrial society, it is true that it can have a positive effect on the country's technological development, growth engine, and economic feasibility in the future. However, since the smart grid is expected to cause enormous damage in the event of a security accident, energy-related organizations must prepare various security measures to predict and respond to the latest security incidents. In this paper, the current status of domestic and foreign smart grids, trends in security standards, vulnerabilities and threats, and prospects for smart grid security technologies are to be considered.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.77-87
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• 2021

Environment is an important factor in city life. Environmental elements are a subject that must be discussed in the smart city plan, but there is still a lack of information and data sharing in the urban environment, so improvements are needed. As part of the intelligent of Nanjing, this research has made in-depth investigation into the construction and service demand of environmental information, and has carried out the research on the design and construction of intelligent information platform that conforms to Nanjing intelligent city planning, improves environmental quality and provides environmental information service. The visualization of information is also studied. The result is an important module in the construction of intelligent city in Nanjing.

• Convergence Security Journal
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• v.22 no.2
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• pp.105-114
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• 2022

This paper is presents an intelligent control system that visualizes the direction of arrival for hearing impaired using personal mobility, and aims to recognize and prevent dangerous situations caused by sound such as alarm sounds and crack sounds on roads. The position estimation method of sound source uses a machine learning classification model characterized by generalized correlated phase transformation based on time difference of arrival. In the experimental environment reproducing the road situations, four classification models learned after extracting learning data according to wind speeds 0km/h, 5.8km/h, 14.2km/h, and 26.4km/h were compared with grid search cross validation, and the Muti-Layer Perceptron(MLP) model with the best performance was applied as the optimal algorithm. When wind occurred, the proposed algorithm showed an average performance improvement of 7.6-11.5% compared to the previous studies.

• Journal of Convergence for Information Technology
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• v.8 no.1
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• pp.201-206
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• 2018

Recently, as technologies for realizing artificial intelligence have become more common, machine learning is widely used. Machine learning provides insight into collecting large amounts of data, batch processing, and taking final action, but the effects of the work are not immediately integrated into the learning process. In this paper proposed an adaptive learning model to improve the performance of real-time stream analysis as a big business issue. Adaptive learning generates the ensemble by adapting to the complexity of the data set, and the algorithm uses the data needed to determine the optimal data point to sample. In an experiment for six standard data sets, the adaptive learning model outperformed the simple machine learning model for classification at the learning time and accuracy. In particular, the support vector machine showed excellent performance at the end of all ensembles. Adaptive learning is expected to be applicable to a wide range of problems that need to be adaptively updated in the inference of changes in various parameters over time.

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.1-10
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• 2020

The performance of the personalized product recommendation system for offline shopping malls is poor compared with the one using online environment information since it is difficult to obtain visitors' characteristic information. In this paper, a mobile robot platform is suggested capable of recommending personalized advertisement using customers' sex and age information provided by Face API of MS Azure Cloud service. The performance of the developed robot is verified through locomotion experiments, and the performance of API used for our robot is tested using sampled images from open Asian FAce Dataset (AFAD). The developed robot could be effective in marketing by providing personalized advertisements at offline shopping malls.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.121-124
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• 2001

충돌회피 시스템은 선박의 안전 항해에 중요한 역할을 한다. 충돌회피 시스템은 선박이 장애물을 만났을 때 영역전문가인 항해사를 대신하여 피항 행위를 하도륵 지시하는 시스템으로 자선에서 이루어지는 해상 장애물들에 대한 피항 시 그 판단 기준을 각 장애물에 대한 충돌위험도에 둔다. 따라서 본 연구에서는 선박의 충돌회피 시스템의 보다 안전한 충돌회피를 도모하기 위해 충돌회피를 위한 충돌위험도 결정 시스템을 제안한다. 충돌위험도 결정 시스템은 장애물 모델링과 장애물의 충돌위험도 결정의 두 부분으로 구성된다. 장애물 모델링은 선박의 센서에서 나오는 저수준의 자료를 지능형 선박의 타 시스템에서 이용하기 쉽도록 구하는 과정이다. 충돌위험도 결정 시스템의 출력으로 산출되는 충돌위험도는 충돌회피 시스템의 피항 행위 결정에 정보로 사용된다. 본 연구에서는 DCPA와 TCPA를 이용한 기존의 기법에 VCD의 개념을 추가한 새로운 충돌위험도 결정 기법을 제안한다. 입력변수가 되는 DCPA, TCPA, VCD의 퍼지 소속함수를 산출하고 이를 기반으로 퍼지 추론을 이용하여 세부적인 충돌위험도를 결정한다. 본 연구에서 제안하는 기법은 기존의 DCPA와 TCPA만으로 충돌위험도를 결정한 경우보다 상세한 충돌위험도 결정이 가능하다는 장점과 국제해상충돌예방규칙의 내용이 적용되었다는 장점을 지닌다. 제안된 기법은 DCPA와 TCPA 만으로 충돌위험도를 결정한 기법과 비교.평가하여 성능을 검증한다.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1956_1957
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• 2009

전 세계적인 에너지 확보 위기와 $CO_2$ 과다 배출로 인한 지구 온난화 문제에 당면한 현재의 전력산업이 다음 세기에도 지속적으로 성장해 가기 위해서는 에너지 효율 향상과 신 재생에너지에 바탕을 둔 분산전원의 활성화를 통한 환경과의 조화와 더불어 미래 디지털 시대의 에너지 조건을 충족시키기 위한 IT기술과 전력기술의 융합을 통한 자동화되고 지능화된 전력시스템 즉, 스마트그리드로의 변화가 절실히 요구되고 있다. 스마트그리드의 주요 분야 중에서 AMI(Advanced Metering Infrastructure)는 최종 전력 소비자와 전력회사 사이의 전력서비스인프라로, 지능형 전력망(Smart Grid) 구현에 필수적인 핵심 인프라 시스템이며, 공급-수요 상호 인지 기반 수요반응(Demand Response) 실현을 위한 중요 수단이라 할 수 있으며, 다양한 유형의 분산전원체계, 배전지능화시스템 등과 정보 연계 등 미래 지능형 전력망 운용을 위해 요구되는 최우선 지능화 전력망 인프라로 인식되고 있다. 본 논문에서는 AMI 시스템의 해외 구축 동향과 관련 기술 그리고 국내 적용을 위한 방안에 대하여 기술하고자 한다.