• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 추계학술대회 논문집 전력기술부문
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• pp.136-138
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• 2007

최근 들어 전력량계는 기계식에서 반도체 소자를 사용하는 전자식으로 점진적으로 교체되고, 외부 통신 장치와의 데이터 통신 방식에 있어 국제 표준 규격인 IEC 62056을 기반으로 표준화하고 있다. 그리하여 표준화된 데이터 통신 방식으로 수집된 전력 정보를 취합하고 통합하는 운영 시스템 구축이 대두하게 되었고 사용자 중심의 HMI(Human Machine Interface) 관점에서 다양한 고객의 요구와 분석 자료 그리고 방대한 데이터 관리를 제공하기 위한 편리한 운영자 환경을 제공해야 한다. 본 논문에서는 전력량계에서 측정된 전력 정보를 저장하고 운영할 수 있는 시스템 개발에 관하여 연구하였다.

• 대한전자공학회논문지TC
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• 제43권9호
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• pp.49-59
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• 2006

운전자 보조시스템은 운전자가 좀 더 편리하고 안전하게 주행할 수 있도록 주행 정보나 위험 경보를 주거나 적극적인 개입을 통해서 안전사고를 방지할 수 있는 시스템이다. 차선이탈경보, 전후방 충돌경보와 같이 특정한 기능을 갖는 현재의 운전자 보조시스템은 비젼과 거리 센서의 가격 대비 처리성능의 향상으로 통합된 기능성과 HMI (Human-Machine Interface)를 갖는 지능형 운전자 보조시스템으로 발전할 것이다. 본 논문은 2대의 카메라와 8대의 초음파센서를 각각 차량의 전후방과 주변에 설치하여 주행 중인 차량의 환경정보인 실선과 점선의 차선 정보, 사각을 제거한 전방향의 차량의 위치정보를 추출하여 운전자가 전방향의 주행상황을 쉽게 인지할 수 있는 조감영상과 음성충돌경보를 제공하는 지능형 운전자 보조시스템을 제안한다.

• International Journal of Computer Science & Network Security
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• 제21권6호
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• pp.245-251
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• 2021

This work aims to focus on the current features and characteristics of Human Element and Artificial intelligence (AI), ask some questions about future information security, and whether we can avoid human errors by improving machine learning and AI or invest in human knowledge more and work them both together in the best way possible? This work represents several related research results on human behavior towards information security, specified with elements and factors like knowledge and attitude, and how much are they invested for ISA (information security awareness), then presenting some of the latest studies on AI and their contributions to further improvements, making the field more securely advanced, we aim to open a new type of thinking in the cybersecurity field and we wish our suggestions of utilizing each point of strengths in both human attributions in software security and the existence of a well-built AI are going to make better future software security.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권7호
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• pp.1705-1720
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• 2013

Human face gender recognition requires fast image processing with high accuracy. Existing face gender recognition methods used traditional local features and machine learning methods have shortcomings of low accuracy or slow speed. In this paper, a new framework for face gender recognition to reach fast face gender recognition is proposed, which is based on Local Ternary Pattern (LTP) and Extreme Learning Machine (ELM). LTP is a generalization of Local Binary Pattern (LBP) that is in the presence of monotonic illumination variations on a face image, and has high discriminative power for texture classification. It is also more discriminate and less sensitive to noise in uniform regions. On the other hand, ELM is a new learning algorithm for generalizing single hidden layer feed forward networks without tuning parameters. The main advantages of ELM are the less stringent optimization constraints, faster operations, easy implementation, and usually improved generalization performance. The experimental results on public databases show that, in comparisons with existing algorithms, the proposed method has higher precision and better generalization performance at extremely fast learning speed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권2호
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• pp.566-579
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• 2012

Ubiquitous computing called pervasive one is based on the thought of pervading ability of computation in daily life applications. In other words, it aims to include computation in devices such as electronic equipment and automobiles. This has led to disengagement of computers from desktop form. Accordingly, the notice in ubiquitous computing being taken of a world steeped in remote and wireless computer-based-services. Handheld and wearable programmed devices such as sense and control appliances are such devices. This advancement is rapidly moving domestic tasks and life from device-and-human communication to the device-and-device model. This model called Machine to Machine (M2M) has led to acceleration of developments in sciences such as nano-science, bio-science, and information science. As a result, M2M led to appearance of applications in various fields such as, environment monitoring, agricultural, health care, logistics, and business. Since it is envisaged that M2M communications will play a big role in the future in all wireless applications and will be emerged as a progressive linkage for next-generation communications, this paper aims to consider how much M2M architectures can realize ubiquitous computing in daily life applications. This is carried out after acquainting and initiating readers with M2M architectures and arguments for M2M. Some of the applications was not achievable before but are becoming viable owing to emergence of M2M communications.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.833-852
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• 2019

In real time applications, due to their effective cost and small size, wireless networks play an important role in receiving particular data and transmitting it to a base station for analysis, a process that can be easily deployed. Due to various internal and external factors, networks can change dynamically, which impacts the localisation of nodes, delays, routing mechanisms, geographical coverage, cross-layer design, the quality of links, fault detection, and quality of service, among others. Conventional methods were programmed, for static networks which made it difficult for networks to respond dynamically. Here, machine learning strategies can be applied for dynamic networks effecting self-learning and developing tools to react quickly and efficiently, with less human intervention and reprogramming. In this paper, we present a wireless networks survey based on different machine learning algorithms and network lifetime parameters, and include the advantages and drawbacks of such a system. Furthermore, we present learning algorithms and techniques for congestion, synchronisation, energy harvesting, and for scheduling mobile sinks. Finally, we present a statistical evaluation of the survey, the motive for choosing specific techniques to deal with wireless network problems, and a brief discussion on the challenges inherent in this area of research.

• 대한원격탐사학회지
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• 제40권2호
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• pp.123-139
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• 2024

Forest vertical structure is vital for comprehending ecosystems and biodiversity, in addition to fundamental forest information. Currently, the forest vertical structure is predominantly assessed via an in-situ method, which is not only difficult to apply to inaccessible locations or large areas but also costly and requires substantial human resources. Therefore, mapping systems based on remote sensing data have been actively explored. Recently, research on analyzing and classifying images using machine learning techniques has been actively conducted and applied to map the vertical structure of forests accurately. In this study, Sentinel-2 and digital surface model images were obtained on two different dates separated by approximately one month, and the spectral index and tree height maps were generated separately. Furthermore, according to the acquisition time, the input data were separated into cases 1 and 2, which were then combined to generate case 3. Using these data, forest vetical structure mapping models based on random forest, support vector machine, and extreme gradient boost(XGBoost)were generated. Consequently, nine models were generated, with the XGBoost model in Case 3 performing the best, with an average precision of 0.99 and an F1 score of 0.91. We confirmed that generating a forest vertical structure mapping model utilizing bi-seasonal data and an appropriate model can result in an accuracy of 90% or higher.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.403-406
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• 1996

Since most human activities in a nuclear power plant are perfirmed in the main control room (MCR), it is important to have its design well human-engineered, both physically and cognitively. Much research efforts have been given for better, operator-centered designs of human-machine interface in MCR capitalizing today's advanced information technology. Korea is among those who are actively expending such research for the next-generation nuclear plants. This paper analyzes two forerunners among the emerging MCR designs, namely Nuplex 80+ and N4, from the perspective of cognitive systems engineering. Since the two show some fundamental differences in their design concepts, the principles with their pros and cons must be enumerated to benefit our own design of new control rooms. This paper also lists many other decision-making points that emerged due to the new availability of cognitively based on cognitive engineering principles. The future scope and directions of related research are suggested.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2424-2441
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• 2012

In this paper, we propose a fake iris detection method that combines the optical and textural features of the human eye. To extract the optical features, we used dual Purkinje images that were generated on the anterior cornea and the posterior lens surfaces based on an analytic model of the human eye's optical structure. To extract the textural features, we measured the amount of change in a given iris pattern (based on wavelet decomposition) with regard to the direction of illumination. This method performs the following two procedures over previous researches. First, in order to obtain the optical and textural features simultaneously, we used five illuminators. Second, in order to improve fake iris detection performance, we used a SVM (Support Vector Machine) to combine the optical and textural features. Through combining the features, problems of single feature based previous works could be solved. Experimental results showed that the EER (Equal Error Rate) was 0.133%.

• 산업경영시스템학회지
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• 제17권30호
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• pp.25-34
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• 1994

Mental workload has a improtant place in modern work environment such as human-computer interaction. Designing man-machine system requires knowledge and evaluation of the human cognitive process which controls information flow during our works. Many studies estimate reaction time as a index of menatal workload. This paper investigates what reflacts the workload of human information handling when the informations grow its degree. Experiment result introuce the memory time that explain the information-load more sensitive than react time. And react time shows learning effect but memory time does'nt show that effect So it can be concluded that cognitive learning or work schema needs more time to achieve dexterity than motor skill.