• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2005년도 한국컴퓨터종합학술대회 논문집 Vol.32 No.1 (A)
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• pp.412-414
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• 2005

Because a sensor node must operate on a tiny battery, the goal to eliminate energy inefficiencies leads the current researchers excavating for new techniques to advocate. As sensor networks edge closer towards wide spread deployment, security issues become a central concern. So far much research has focused on making sensor networks feasible and useful, and has not concentrated much on security issues especially computationally inexpensive techniques. In this paper we introduce a simple scheme relying on one-way hash-functions that greatly enhances location privacy by changing traceable identifiers on every read getting by with only a single, unreliable message exchange. Thereby the scheme is safe from many threats like eavesdropping, message interception, spoofing, and replay attacks.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.1146-1148
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• 2007

This paper proposes a method to improve the charging speed and discharging performance of a high voltage capacitor used in a portable medical device. The improvement of the charging speed was achieved by duty cycle control. The discharging performance was carried out by varying the phase duration and the leading edge voltage of the output according to the transthoracic impdedance of the patient. As a result, the improvement in the charging speed and the performance of the discharging parameters shorten the patient treatment time.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2009년도 제38회 동계학술대회 초록집
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• pp.374-374
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• 2010

Charge transfer mechanism of poly(4,4'-aminotriphenylene hexafluoroisopropylidenediphthalimide) (TP6F PI) which exhibits bistable ON and OFF switching has been studied using photoemission electron spectroscopy (PES) and near-edge x-ray absorption fine structure (NEXAFS). Here, we demonstrate novel set-up in which holes are injected by photoemission process instead of direct charge carrier injection via metal electrode. The accumulated charges on the PI surface in the OFF state abruptly flow across the PI film when the bias voltage of a back electrode reaches a specific value, indicating that the film is changed to the ON state. Core level and x-ray absorption spectra probed at charge injection region via photoemission process do not show any evidences implying structural modification of TP6F PI during the phase change. Whereas, in valence band spectra, the highest occupied molecular orbital (HOMO) is shifted toward Fermi level, responsible for improved hole-mobility of TP6F PI of ON state.

• Journal of Information Processing Systems
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• 제14권6호
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• pp.1301-1306
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• 2018

Artificial intelligence is one of the key technologies of the Fourth Industrial Revolution. This paper introduces the diverse kinds of approaches to subjects that tackle diverse kinds of research fields such as model-based MS approach, deep neural network model, image edge detection approach, cross-layer optimization model, LSSVM approach, screen design approach, CPU-GPU hybrid approach and so on. The research on Superintelligence and superconnection for IoT and big data is also described such as 'superintelligence-based systems and infrastructures', 'superconnection-based IoT and big data systems', 'analysis of IoT-based data and big data', 'infrastructure design for IoT and big data', 'artificial intelligence applications', and 'superconnection-based IoT devices'.

• Current Applied Physics
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• 제18권11호
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• pp.1182-1184
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• 2018

The combination of angular spin momentum with electronics is a promising successor to charge-based electronics. The conduction bands in GaAs may become spin-polarized via optical spin pumping, doping with magnetic ions, or induction of a moment with an external magnetic field. We investigated the spin populations in GaAs with x-ray magnetic circular dichroism for each of these three cases. We find strong anti-symmetric lineshapes at the Ga $L_3$ edge indicating conduction band spin splitting, with differences in line width and amplitude depending on the source of spin polarization.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.25-31
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• 2023

Fog computing diversifies cloud computing by using edge devices to provide computing, data storage, communication, management, and control services. As it has a decentralised infrastructure that is capable of amalgamating with cloud computing as well as providing real-time data analysis, it is an emerging method of using multidisciplinary domains for a variety of applications; such as the IoT, Big Data, and smart cities. This present study provides an overview of the security and privacy concerns of fog computing. It also examines its fundamentals and architecture as well as the current trends, challenges, and potential methods of overcoming issues in fog computing.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송∙미디어공학회 2020년도 하계학술대회
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• pp.26-27
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• 2020

본 논문에서는 서로 다른 특성을 갖기 때문에 표준화가 어려운 엣지 플랫폼에서 동일한 머신 러닝 모델로도 확장 가능한 분석 서비스를 하기 위해, 마이크로서비스 기반으로 협업 분석 하는 설계 방법을 소개한다. 이를 위해 실제 사용자 분석 결과 적응적인 컨텐츠 서비스 시나리오를 고려하였다. 서로 다른 성능을 갖는 엣지가 협업하기 위해서 클라우드에서 제공 받는 어플리케이션을 마이크로 서비스화 하고 다수의 엣지에 해당 서비스를 분산 분포하여 연결한다. 해당 방법은 전체 서비스를 상호 독립적인 최소 구성 요소로 분할하고 모든 요소가 독립적으로 연동되어 타스크를 수행하게 하며 유사한 프로세스는 공유함으로서 상대적으로 성능이 떨어지는 엣지들간 협력으로 효율적인 분석 서비스 제공이 가능하도록 할 것이다.

• ETRI Journal
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• 제45권4호
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• pp.666-677
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• 2023

In the last few years, convolutional neural networks (CNNs) have demonstrated good performance while solving various computer vision problems. However, since CNNs exhibit high computational complexity, signal processing is performed on the server side. To reduce the computational complexity of CNNs for edge computing, a lightweight algorithm, such as a MobileNet, is proposed. Although MobileNet is lighter than other CNN models, it commonly achieves lower classification accuracy. Hence, to find a balance between complexity and accuracy, additional hyperparameters for adjusting the size of the model have recently been proposed. However, significantly increasing the number of parameters makes models dense and unsuitable for devices with limited computational resources. In this study, we propose a novel MobileNet architecture, in which the number of parameters is adaptively increased according to the importance of feature maps. We show that our proposed network achieves better classification accuracy with fewer parameters than the conventional MobileNet.

• 스마트미디어저널
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• 제13권2호
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• pp.85-94
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• 2024

Artificial Intelligence of Things (AIoT), which combines AI and the Internet of Things (IoT), has recently gained popularity. Deep neural networks (DNNs) have achieved great success in many applications. Deploying complex AI models on embedded boards, nevertheless, may be challenging due to computational limitations or intelligent model complexity. This paper focuses on an AIoT-based system for smart sewing automation using edge devices. Our technique included developing a detection model and a decision tree for a sufficient testing scenario. YOLOv5 set the stage for our defective sewing stitches detection model, to detect anomalies and classify the sewing patterns. According to the experimental testing, the proposed approach achieved a perfect score with accuracy and F1score of 1.0, False Positive Rate (FPR), False Negative Rate (FNR) of 0, and a speed of 0.07 seconds with file size 2.43MB.

• 전자통신동향분석
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• 제39권4호
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• pp.82-92
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• 2024

This paper introduces the technological development trends in on-device SLMs (Small Language Models). Large Language Models (LLMs) based on the transformer model have gained global attention with the emergence of ChatGPT, providing detailed and sophisticated responses across various knowledge domains, thereby increasing their impact across society. While major global tech companies are continuously announcing new LLMs or enhancing their capabilities, the development of SLMs, which are lightweight versions of LLMs, is intensely progressing. SLMs have the advantage of being able to run as on-device AI on smartphones or edge devices with limited memory and computing resources, enabling their application in various fields from a commercialization perspective. This paper examines the technical features for developing SLMs, lightweight technologies, semiconductor technology development trends for on-device AI, and potential applications across various industries.