• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.471-477
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• 2021

In the field of display, a smart factory means more efficient display manufacturing using AI/BIG DATA technology not only for job automation, but also for existing process management, moving facilities, process abnormalities, and defect classification. In the past, when defects appeared in the display manufacturing process, the classification of defects and coping with process abnormalities were different, a lot of time was consumed for this. However, in the field of display manufacturing, advanced process equipment must be used, and it can be said that the competitiveness of the display manufacturing industry is to quickly identify the cause of defects and increase the yield. In this paper, we will summarize the cases in which smart factory AI/BIG DATA technology is applied to domestic display manufacturing, and analyze what advantages can be derived compared to existing methods. This information can be used as prior knowledge for improved smart factory development in the field of display manufacturing using AI/BIG DATA.

• Information Display
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• v.25 no.2
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• pp.10-14
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• 2024

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.844-847
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• 2003

Display devices are becoming increasingly important as an interface between humans and machines in the growing information society. In display devices, PDP (Plasma Display Panel) has many advantages in that it has wide screen, wide viewing angle and is light weight, thin. In PDP driving method, if the brightness of input image is high, applying the fixed sustain pulse to the PDP panel will raise the PDP power consumption and may damages the PDP panel. To overcome these problems, the Plasma AI driving method was introduced by the Matshushita co. in Japan. The Plasma AI driving module calculates the peak value and average value of 1 frame image and adjusts the gradation and sustain pulses for 1 frame sustain. In this paper, the proposed PDP driving module is based on the Plasma AI driving module. The proposed driving module calculates peak value and average value, and the brightness distribution of 1 frame image. Using brightness distribution, the proposed driving module divides 1 frame input image into 15 image patterns. For each image pattern, minimum sustain pulses and sub-frames are used for the brightness of 1 frame image and the sustain weight for 64, 128, 192 gradation is proposed. Therefore, the sustain power consumption can be reduced.

• Information Display
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• v.23 no.4
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• pp.35-44
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• 2022

AI기술의 유용성과 발전 가능성은 다양한 분야에서 확인되어 왔고, 디스플레이 산업에도 AI 기술들이 적극 도입되고 있다. 디스플레이 산업에 도입된 기존의 AI 기술들은 주로 engineer나 불량 검사자의 업무를 자동화하는 목적이었으나, 최근에는 engineer의 업무를 대체하는 고도의 지능화된 AI 기술들이 도입되고 있다. 본 논문에서는 이러한 지능화된 AI 기술 중에서 강화 학습, 자연어 처리, Pattern Matching 기술의 원리와 적용 사례들을 다루어 보았다. 첫번째로 강화 학습의 기본 개념을 설명하고, 설비 control (scheduling), 재료 탐색, 그리고 회로 설계에서의 적용 사례를 살펴보았다. 두번째로는 자연어 처리에서는 기술의 기본 원리 및 다양한 적용 방법론들에 대하여 다루었고, 제조 검사 리포트 분석, 지식재산권 분석, 연구문헌 분석 등에서의 활용 사례를 살펴보았다. 마지막으로 Pattern Matching에서는 기술 개요와 최근의 기술 동향을 기술하였고, Object Detection과 Object Tracking 기술 비교와 함께 패널 설계 도면으로부터 engineer 가 관심을 가져야 할 pattern 탐색에 대한 적용 사례를 살펴보았다.

• International journal of advanced smart convergence
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• v.13 no.3
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• pp.101-108
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• 2024

This paper addresses the implementation of an on-device AI-based metal detection system using a Magneto-Impedance Sensor. Performing calculations on the AI device itself is essential, especially for unmanned aerial vehicles such as drones, where communication capabilities may be limited. Consequently, a system capable of analyzing data directly on the device is required. We propose a lightweight gated recurrent unit (GRU) model that can be operated on a drone. Additionally, we have implemented a real-time detection system on a CPU embedded system. The signals obtained from the Magneto-Impedance Sensor are processed in real-time by a Raspberry Pi 4 Model B. During the experiment, the drone flew freely at an altitude ranging from 1 to 10 meters in an open area where metal objects were placed. A total of 20,000,000 sequences of experimental data were acquired, with the data split into training, validation, and test sets in an 8:1:1 ratio. The results of the experiment demonstrated an accuracy of 94.5% and an inference time of 9.8 milliseconds. This study indicates that the proposed system is potentially applicable to unmanned metal detection drones.

• Journal of Information Display
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• v.10 no.1
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• pp.37-44
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• 2009

AiPi technology incorporates an embedded clock and control scheme with a point-to-point bus topology, thereby having the smallest possible number of interface lines between a timing controller and column drivers. A point-to-point architecture boosts the data rate and reduces the number of interface lines, because impedance matching can be easily achieved. An embedded clock and control scheme is implemented by means of multi-level signalling, which results in a simple clock/data recovery circuitry. A 46" AiPi-based 10-bit FHD prototype requires only 20 interface lines, compared to 38 lines for mini-LVDS. The measured maximum data rate per data pair is more than 800 Mbps.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.790-791
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• 2023

본 논문은 스마트 미러를 활용한 스마트팜 디스플레이 장치의 중요성과 잠재적인 활용 가능성을 논의하며, 농업 분야의 혁신과 정보 기술의 융합이 농업 생산성을 향상하는 역할을 강조한다. 스마트 미러를 통해 제공되는 실시간 정보와 데이터는 농업 종사자들에게 생산성 향상 및 농작물의 품질을 향상 시키며, 지속 가능한 농업을 실현하는 데 도움을 줄 것으로 기대된다.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2005.09a
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• pp.89-92
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• 2005

The AIN/AI thin films were prepared at various conditions, such as $N_2$ gas flow rate [$N_2(N_2+Ar)$] from 0.6 to 0.9, a substrate temperature ranging from room temperature to $300^{\circ}C$ and working pressure 1mTorr. We estimated crystallographic characteristics and c-axis preferred orientations of AIN/AI thin films as function of AI electrode surface roughness. The optimal processing conditions for AI electrode were found at substrate temperature of $300^{\circ}C$ sputtering power of 100W and a working pressure of 2mTorr. In these conditions, we obtained the c-axis preferred orientation of $AIN/AI/SiO_2/Si$ thin film about 4 degree.

• Journal of Information Technology Services
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• v.20 no.4
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• pp.81-93
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• 2021

In the era of artificial intelligence, the use of 'artificial intelligence-based services' has been diversified by combining various smart devices, big data, and voice recognition technology with artificial intelligence. From the perspective of IT services, these services are important technology that cause a paradigm shift from display-centered to voice-centered, and from passive to active IT-based services. This study seeks to find a solution to the current situation where AI assistant service is still in its beginning stage, despite having been ten years since its release and having a growing number of consumer touch points. Accordingly, we categorized the functions of AI assistant services and identified the degree of importance and satisfaction of services recognized by actual users. In order to define the 'ideal' services of AI assistant, seven experts from AI assistant-related industry have participated in the interview. Based on this result, we investigated the importance and satisfaction of services perceived by actual users of AI assistant services. As a result of IPA (Importance Performance Analysis). we find out which services are potentially 'keep', 'concentrate', 'low priority', or 'overkill' and provide various implications from the findings.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.110-113
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• 2022

Non-playable game character plays an important role in improving the concentration of the game and the interest of the user, and recently implementation of NPC with reinforcement learning has been in the spotlight. In this paper, we estimate an AI target tracking method via reinforcement learning, and implement an AI-based tracking agency of specific target object with avoiding traps through Unity ML-Agents Toolkit. The implementation is built in Unity game engine, and simulations are conducted through a number of experiments. The experimental results show that outstanding performance of the tracking target with avoiding traps is shown with good enough results.