• Journal of the Semiconductor & Display Technology
• /
• v.20 no.3
• /
• pp.93-96
• /
• 2021

The desire for a technology that can mechanically acquire 2D images starting with the manual method of drawing has been making possible a wide range of modern image-based technologies and applications over a period. Moreover, this trend of the utilization of image-related technology as well as image-based information is likely to continue. Naturally, as like other technology areas, the function that humans produce and utilize by using images needs to be automated by using computing-based technologies. Surprisingly, technology using images in the future will be able to discover knowledge that humans have never known before through the information-related process that enables new perception, far beyond the scope of use that human has used before. Regarding this trend, the manipulation and configuration of massively distributed image database system is strongly demanded. In this paper, we discuss image identifier production methods based on the utilization of the image hashing technique which especially puts emphasis over an entropy operator.

• Journal of the Semiconductor & Display Technology
• /
• v.21 no.3
• /
• pp.92-97
• /
• 2022

Plastics are classified into 7 types such as PET (PETE), HDPE, PVC, LDPE, PP, PS, and Other for separation and recycling. Recently, large corporations advocating ESG management are replacing them with bioplastics. Incineration and landfill of disposal of plastic waste are responsible for air pollution and destruction of the ecosystem. Because it is not easy to accurately classify plastic materials with the naked eye, automated system-based screening studies using various sensor technologies and AI-based software technologies have been conducted. In this paper, NIR scanning devices considering the NIR wavelength characteristics that appear differently for each plastic material and a system that can identify the type of plastic by learning the NIR spectrum data collected through it. The accuracy of plastic material identification was evaluated through a decision tree-based SVM model for multiclass classification on NIR spectral datasets for 8 types of plastic samples including biodegradable plastic.

• Journal of information and communication convergence engineering
• /
• v.20 no.2
• /
• pp.113-124
• /
• 2022

News in the form of web data generates increasingly large amounts of information as unstructured text. The capability of understanding the meaning of news is limited to humans; thus, it causes information overload. This hinders the effective use of embedded knowledge in such texts. Therefore, Automatic Knowledge Extraction (AKE) has now become an integral part of Semantic web and Natural Language Processing (NLP). Although recent literature shows that AKE has progressed, the results are still behind the expectations. This study proposes a method to auto-extract surface knowledge from English news into a machine-interpretable semantic format (triple). The proposed technique was designed using the grammatical structure of the sentence, and 11 original rules were discovered. The initial experiment extracted triples from the Sri Lankan news corpus, of which 83.5% were meaningful. The experiment was extended to the British Broadcasting Corporation (BBC) news dataset to prove its generic nature. This demonstrated a higher meaningful triple extraction rate of 92.6%. These results were validated using the inter-rater agreement method, which guaranteed the high reliability.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2020.11a
• /
• pp.61-64
• /
• 2020

현재까지 심층 학습을 이용하여 텍스트를 자동으로 분류해주는 연구가 활발히 진행되었으며, 특히 소프트웨어 카테고리를 자동으로 분류해주는 연구가 이루어지고 있다. 최근 심층 신경망의 적절한 구조를 효율적으로 탐색할 수 있는 가중치 공유 기법이 연구되었다. 우리는 이를 응용하여 본 논문에서 가중치 공유를 이용한 소프트웨어 카테고리 분류 방법을 제안하며, 여러 실험을 통해 해당 기법의 성능을 측정하고 논의한다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2023.01a
• /
• pp.485-486
• /
• 2023

4차 산업혁명 이전에도 많은 물류 자동화가 이루어지고 있었다. 그러나 4차 산업혁명이 도래하면서 자동화되는 범위가 더욱 넓어지며 인력이 쓰이는 곳에 로봇이 대거 등장하게 되었다. 그러나 환경이 열악한 중소기업이나 경제성 측면에서의 도입이 어려운 분야에서는 자동 물류 시스템의 적용이 어려운 것이 현실이다. 본 논문에서는 이러한 문제를 해결하기 위해 물건을 옮기는 일에 있어서는 라인트레이서를 이용하여 물품의 수송을 도와주고, 적외선 센서 및 바코드 리더기를 이용하여 물품 개수의 현황 계산을 담당하여 정확한 계산을 도출하여 자동으로 원격 데이터베이스에 저장하여 관리할 수 있는 물류관리 지원 시스템을 제안한다.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.4
• /
• pp.181-189
• /
• 2023

In this paper, we present a case study of developing MVIS (Machine Vision Inspection System) designed for exterior quality inspection of stamping dies used in the production of automotive exterior components in a small to medium-sized factory. While the primary processes within the factory, including machining, transportation, and loading, have been automated using PLCs, CNC machines, and robots, the final quality inspection process still relies on manual labor. We implement the MVIS with general-purpose industrial cameras and Python-based open-source libraries and frameworks for rapid and low-cost development. The MVIS can play a major role on improving throughput and lead time of stamping dies. Furthermore, the processed inspection images can be leveraged for future process monitoring and improvement by applying deep learning techniques.

• Water for future
• /
• v.28 no.2
• /
• pp.115-124
• /
• 1995

A GIS is capable of extracting various hydrological factors from DEM(digital elevation model). One of important tasks for hydrological analysis is the division of watershed. It can be an essential factor among various geometric characteristics of watershed. In this study, watershed itself and other geometric factors of watershed are extracted from DEM by using GIS technique. The manual process of tasks to obtain geometric characteristics of watershed is automated by using the functions of ARC/INFO software as GIS package. Scanned data was used for this study and it is converted to DEM data. Various forms of representation of spatial data are handled in main module and GRID module of ARC/INFO. GRID module is used on a stream in order to define watershed boundary, so it would be possible to obtain the watersheds. Also, a flow direction, stream networks and orders are generated. The results show that GIS can aid watershed management and research and surveillance. Also the geometric characteristics parameters of watershed can be quantified with ease using GIS technique and the hardsome process can be automated.

• Journal of the Korean Institute of Gas
• /
• v.22 no.2
• /
• pp.1-20
• /
• 2018

Despite many measures, still from time to time catastrophic events occur, even after reviewing potential scenarios with HAZID tools. Therefore, it is evident that in order to prevent such events, answering the question: "What can go wrong?" requires more enhanced HAZID tools. Recently, new system based approaches have been proposed, such as STPA (system-theoretic process analysis) and Blended Hazid, but for the time being for several reasons their availability for general use is very limited. However, by making use of available advanced software and technology, traditional HAZID tools can still be improved in degree of completeness of identifying possible hazards and in work time efficiency. The new HAZID methodology proposed here, the Data-based semi-Automatic HAZard IDentification (DAHAZID), seeks to identify possible scenarios with a semi-automated system approach. Based on the two traditional HAZID tools, Hazard Operability (HAZOP) Study and Failure Modes, Effects, and Criticality Analysis (FMECA), the new method will minimize the limitations of each method. This will occur by means of a thorough systematic preparation before the tools are applied. Rather than depending on reading drawings to obtain connectivity information of process system equipment elements, this research is generating and presenting in prepopulated work sheets linked components together with all required information and space to note HAZID results. Next, this method can be integrated with proper guidelines regarding process safer design and hazard analysis. To examine its usefulness, the method will be applied to a case study.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.2
• /
• pp.180-189
• /
• 2017

Some people who take a driver's license test retake it again because of license cancellation, but most of them take the test for the first time to drive the car. Driving a car is directly linked to life, and the initial correct driving habits are more important than anything else. In particular, it is very important to obtain a license by evaluating the correct driving ability based on objective and fair standards when learning the first driving, because many people acquire a driving license while entering the society for the first time. In this paper, we propose the S / W design and its main functions that can emit high quality drivers through efficient, fair and accurate automated scoring. Through this, it is proposed to improve the automatic grading driver's license system, to prevent traffic accidents, and to reduce traffic accidents through proper driving.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.12 no.4
• /
• pp.671-678
• /
• 2017

Recent advances in Internet of Things (IoT) encourage us to use IoT devices in daily living areas. However, as IoT devices are being ubiquitously used, concerns onsecurity and privacy of IoT devices are getting grown. Key management is an important and fundamental task to provide security services. For better security, we should restrict reusing a same key in sequential authentication sessions, but it is difficult to manually update and memorize keys. In this paper, we propose a hardware security module(HSM) for automated key management in IoT devices. Our HSM is attached to an IoT device and communicates with the device. It provides an automated, secure key update process without any user intervention. The secure keys provided by our HSM can be used in the user and device authentications for any internet services.