• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1414-1416
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• 2016

In this paper, a SWB (Super-WideBand) dipole antenna with self-complementary structure is proposed for signal intelligence. The proposed antenna consists of a self-complementary dipole antenna and a tapered balun for balanced feeding. The measured -10 dB reflection bandwidth of the proposed antenna is more than 28:1 (0.73-20 GHz) and 3 dB axial ratio bandwidth is 3.25:1 (1.91-6.22 GHz) with RHCP (Right Hand Circular Polarization) at +z direction. The measured radiation patterns are omni-directional in lower frequency band and bi-directional in higher frequency band. The measured peak gain within -10 dB reflection bandwidth varies from 2.83 dBi to 7.66 dBi.

• Journal of the Korean Society of Radiology
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• v.81 no.6
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• pp.1305-1333
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• 2020

Deep learning has recently achieved remarkable results in the field of medical imaging. However, as a deep learning network becomes deeper to improve its performance, it becomes more difficult to interpret the processes within. This can especially be a critical problem in medical fields where diagnostic decisions are directly related to a patient's survival. In order to solve this, explainable artificial intelligence techniques are being widely studied, and an attention mechanism was developed as part of this approach. In this paper, attention techniques are divided into two types: post hoc attention, which aims to analyze a network that has already been trained, and trainable attention, which further improves network performance. Detailed comparisons of each method, examples of applications in medical imaging, and future perspectives will be covered.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.211-213
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• 2013

In these days, the delusions of Big Data and apprehension about them are coming into the picture in many business fields. General techniques for preservation, analysis, and utilization of Big Data are falling short of useful techniques for the volume of fast-increasing data. However, there are some assertions that the power of analysis and prediction of Artificial Intelligence would intensify the power of Big Data analysis. This paper studies on business cases to try to graft the Artificial Intelligence technique onto Big Data analysis. We first research on various techniques of Artificial Intelligence and relations between Artificial Intelligence and Big Data. And then, we perform case studies of Big Data with using Artificial Intelligence and propose some roles of Big Data in the future.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1207-1210
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• 2021

본 본문은 사람의 걸음걸이를 분석을 하여 사람을 인식하는 시스템을 개발한다. mmWave 레이다 센서를 사용하여 사람의 걸음걸이를 인식하고 인식한 데이터를 바탕으로 어떤 사용자인지 분석한다. 데이터를 분석하여 등록된 사용자가 왔을 경우 개방하는 방식으로 출입을 통제하는 개폐 시스템을 사용하고 통신을 사용하여 스마트폰과 통신하여 문이 열리면 실시간으로 사용자가 볼 수 있게 한다.

• Journal of Physiology & Pathology in Korean Medicine
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• v.35 no.5
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• pp.132-138
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• 2021

Artificial intelligence technology sheds light on new ways of innovating acupuncture research. As acupoint selection is specific to target diseases, each acupoint is generally believed to have a specific indication. However, the specificity of acupoint selection may be not always same with the specificity of acupoint indication. In this review, we propose that the specificity of acupoint indication can be inferred from clinical data using reverse inference. Using forward inference, the prescribed acupoints for each disease can be quantified for the specificity of acupoint selection. Using reverse inference, targeted diseases for each acupoint can be quantified for the specificity of acupoint indication. It is noteworthy that the selection of an acupoint for a particular disease does not imply the acupoint has specific indications for that disease. Electronic medical record includes various symptoms and chosen acupoint combinations. Data mining approach can be useful to reveal the complex relationships between diseases and acupoints from clinical data. Combining the clinical information and the bodily sensation map, the spatial patterns of acupoint indication can be further estimated. Interoperable medical data should be collected for medical knowledge discovery and clinical decision support system. In the era of artificial intelligence, machine learning can reveal the associations between diseases and prescribed acupoints from large scale clinical data warehouse.

• Korean System Dynamics Review
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• v.11 no.2
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• pp.77-102
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• 2010

This paper examines a mechanism of the Electronic Territory Expansion and the Information-oriented Society. Especially, a strategy for the territory development based on intelligence is suggested. The strategy is divided into a strategy for the domestic electronic territory and a plan for the global electronic territory. To examine the strategy and the plan, this paper is using the causal map analysis based on the System Thinking Approach. The causal map of the mechanism is characterized by a positive feedback loop. The paper has concluded that it is important to make the positive loops as a virtuous circle. It means that when a society dominates the advantageous position firstly in the field of intelligent and electronic territory, the competitiveness can grow in arithmetical progression.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.103-111
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• 2023

Implementing conventional DFT solution for arrays of DNN accelerators having large number of processing elements (PEs), without considering architectural characteristics of PEs may incur overwhelming test overheads. Recent DFT based techniques have utilized the homogeneity and dataflow of arrays at PE-level and Core-level for obtaining reduction in; test pattern volume, test time, test power and ATPG runtime. This paper reviews these contemporary test solutions for ASIC based DNN accelerators. Mainly, the proposed test architectures, pattern application method with their objectives are reviewed. It is observed that exploitation of architectural characteristic such as homogeneity and dataflow of PEs/ arrays results in reduced test overheads.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.928-929
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• 2023

도로 교통 사고 및 교통 정체는 도로 상황의 비정상적인 요인으로 인해 발생하는 심각한 문제이다. 이러한 문제를 해결하기 위해 도로 상황을 실시간으로 감지하고 사용자에게 알리는 시스템이 필요하다고 판단된다. 본 연구는 도로 상황 감지 및 예방을 위한 새로운 접근 방식을 제안하며, 이에 대한 배경과 필요성, 그리고 프로젝트의 특장점을 소개한다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.4
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• pp.283-292
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• 2020

Artificial intelligence, which is one of the representative images of the 4th industrial revolution, has been highly recognized since 2016. This paper analyzed domestic paper trends for 'Artificial Intelligence', 'Machine Learning', and 'Deep Learning' among the domestic papers provided by the Korea Academic Education and Information Service. There are approximately 10,000 searched papers, and word count analysis, topic modeling and semantic network is used to analyze paper's trends. As a result of analyzing the extracted papers, compared to 2015, in 2016, it increased 600% in the field of artificial intelligence, 176% in machine learning, and 316% in the field of deep learning. In machine learning, a support vector machine model has been studied, and in deep learning, convolutional neural networks using TensorFlow are widely used in deep learning. This paper can provide help in setting future research directions in the fields of 'artificial intelligence', 'machine learning', and 'deep learning'.

• ETRI Journal
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• v.46 no.1
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• pp.7-10
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• 2024