• 제목/요약/키워드: Intelligence density

검색결과 79건 처리시간 0.026초

유방촬영술에서 인공지능의 적용: 알고리즘 개발 및 평가 관점 (Applications of Artificial Intelligence in Mammography from a Development and Validation Perspective)

  • 김기환;이상협
    • 대한영상의학회지
    • /
    • 제82권1호
    • /
    • pp.12-28
    • /
    • 2021
  • 유방촬영술은 유방암 검진 및 진단을 위한 기본적인 영상 검사이지만, 판독이 어려우며 높은 숙련도를 필요로 한다고 잘 알려져 있다. 이러한 어려움을 극복하기 위해 최근 몇 년 사이에 인공지능을 이용한 유방암 검출 알고리즘들이 활발히 연구되고 있다. 본 종설에서 저자는 고전적인 computer-aided detection 소프트웨어 대비 최근 많이 사용되는 딥러닝의 특징을 알아보고, 딥러닝 알고리즘의 개발 방법과 임상적 검증 방법에 대해서 기술하였다. 또한 딥러닝 기반의 검진 유방촬영술의 판독 방법 분류, 유방 치밀도 평가, 그리고 유방암 위험도 예측 모델 등을 위한 딥러닝 연구들도 소개하였다. 마지막으로 유방촬영술 관련 인공지능 기술들에 대한 영상의학과 전문의의 관심과 의견의 필요성을 기술하였다.

회귀분석이론을 이용한 지하철 역사의 조명부하밀도 분석 (Recommended Practice for Lighting Load Density by Feature Parameters and Regression Analysis depending on Power Consumption Characteristics in Subway Stations)

  • 정현기;김세동
    • 한국조명전기설비학회:학술대회논문집
    • /
    • 한국조명전기설비학회 2006년도 춘계학술대회 논문집
    • /
    • pp.254-259
    • /
    • 2006
  • It is increased electrical energy consumption with the development of intelligence society in the subway station and thus an energy conservation through efficient use of electricity became more important. This paper shows a reasonable design load density in subway stations, that was made by the systematic and statistical way considering actual conditions, such as investigated electric equipment capacity, peak power consumption, demand factor, etc., for 34 subway stations and 10 electrical design offices. In this dissertation, it is necessary to analyse the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, maximum and thus it was carried linear and nonlinear regression analysis.

  • PDF

전기자동차용 리튬이온전지를 위한 양극전극 분말 재료의 연구 동향 (Research Trends of Cathode Materials for Lithium-Ion Batteries used in Electric Vehicles)

  • 신동요;안효진
    • 한국분말재료학회지
    • /
    • 제26권1호
    • /
    • pp.58-69
    • /
    • 2019
  • High performance lithium-ion batteries (LIBs) have attracted considerable attention as essential energy sources for high-technology electrical devices such as electrical vehicles, unmanned drones, uninterruptible power supply, and artificial intelligence robots because of their high energy density (150-250 Wh/kg), long lifetime (> 500 cycles), low toxicity, and low memory effects. Of the high-performance LIB components, cathode materials have a significant effect on the capacity, lifetime, energy density, power density, and operating conditions of high-performance LIBs. This is because cathode materials have limitations with respect to a lower specific capacity and cycling stability as compared to anode materials. In addition, cathode materials present difficulties when used with LIBs in electric vehicles because of their poor rate performance. Therefore, this study summarizes the structural and electrochemical properties of cathode materials for LIBs used in electric vehicles. In addition, we consider unique strategies to improve their structural and electrochemical properties.

인공지능 기술에 관한 가트너 하이프사이클의 네트워크 집단구조 특성 및 확산패턴에 관한 연구 (Structural features and Diffusion Patterns of Gartner Hype Cycle for Artificial Intelligence using Social Network analysis)

  • 신선아;강주영
    • 지능정보연구
    • /
    • 제28권1호
    • /
    • pp.107-129
    • /
    • 2022
  • 기술경쟁이 심화되고 있는 오늘날 신기술에 대한 선도적 위치의 선점이 중요하다. 선도적 위치의 선점과 적정시점에 기술 획득·관리를 위해 이해관계자들은 지속적으로 기술에 대한 탐색활동을 수행한다. 이를 위한 참고 자료로서 가트너 하이프 사이클(Gartner Hype Cycle)은 중요한 의미가 있다. 하이프 사이클은 기술수명주기(S-curve)와 하이프 수준(Hype Level)을 결합하여 새로운 기술에 대한 대중의 기대감을 시간의 흐름에 따라 나타낸 그래프이다. 새로운 기술에 대한 기대는 기술사업화뿐만 아니라 연구개발 투자의 정당성, 투자유치를 위한 기회의 발판이 된다는 점에서 연구개발 담당자 및 기술투자자의 관심이 높다. 그러나 산업계의 높은 관심에 비해 실증분석을 시도한 선행연구는 다양하지 못하다. 선행문헌 분석결과 데이터 종류(뉴스, 논문, 주가지수, 검색 트래픽 등)나 분석방법은 한정적이었다. 이에 본 연구에서는 확산의 주요한 채널이 되어가고 있는 소셜네트워크서비스의 데이터를 활용하여 'Gartner Hype Cycle for Artificial Intelligence, 2021'의 단계별 기술들에 대한 집단구조(커뮤니티)의 특성과 커뮤니티 간 정보 확산패턴을 분석하고자 한다. 이를 위해 컴포넌트 응집규모(Component Cohesion Size)를 통해 각 단계별 구조적 특성과 연결중심화(Degree Centralization)와 밀도(Density)를 통해 확산의 방식을 확인하였다. 연구결과 기술을 수용하는 단계별 집단들의 커뮤니케이션 활동이 시간이 지날 수록 분절이 커지며 밀도 역시 감소함을 확인하였다. 또한 새로운 기술에 대한 관심을 촉발하는 혁신태동기 집단의 경우 정보확산을 촉발하는 외향연결(Out-degree) 중심화 지수가 높았으며, 이후의 단계는 정보를 수용하는 내향연결(In-degree) 중심화 지수가 높은 것으로 나타났다. 해당 연구를 통해 하이프 사이클에 관한 이론적 기초를 제공할 것이다. 또한 인공지능기술에 대한 기술관심집단들의 기대감을 반영한 정보확산의 특성과 패턴을 소셜데이터를 통해 분석함으로써 기업의 기술투자 의사결정에 새로운 시각을 제공할 것이다.

원격탐사와 인공지능 모델링을 활용한 제주도 지역의 준맹그로브 탄소 축적량 예측 (Prediction of Carbon Accumulation within Semi-Mangrove Ecosystems Using Remote Sensing and Artificial Intelligence Modeling in Jeju Island, South Korea)

  • 이철호;이종성;김채빈;추연수;이보라
    • Ecology and Resilient Infrastructure
    • /
    • 제10권4호
    • /
    • pp.161-170
    • /
    • 2023
  • 본 연구에서는 제주도에서 자생하는 준맹그로브인 황근 (Hibiscus hamabo)과 갯대추나무 (Paliurus ramosissimus)의 탄소 저장량을 원격탐사로 추정하고 기후요인에 의하여 공간변이를 예측하는 인공지능 모델을 구축하고자 하였다. 준맹그로브의 지상부 탄소 축적량은 Global Ecosystem Dynamics Investigation (GEDI) 라이다에 의하여 제공되는 지상부 생물량 밀도(aboveground biomass density, AGBD)를 Sentinel-2 영상으로부터 추출한 normalized difference vegetation index (NDVI)으로 해상도를 상향하여 추정하였다. 제주도에서 단위면적당 탄소 축적량은 황근이 16.6 t C/ha, 갯대추나무가 21.1 t C/ha이었다. 제주도 전 해안에서 준맹그로브의 탄소 축적량은 11.5 t C로 추정되었다. 환경요인에 따른 준맹그로브의 탄소 축적량을 예측하기 위하여 랜덤 포레스트 기술을 적용하였다. 제주도 준맹그로브림의 분포면적 대비 지상부 생물량의 잔차를 계산하였다. 이 잔차에 영향을 미치는 주요 환경요인으로는 가장 습한 달의 강수량, 가장 더운 달의 최고온도, 등온성 및 가장 습한 달의 평균 온도가 선정되었다. 제주도에서 랜덤 포레스트 분석으로 예측된 준맹그로브의 탄소 축적량은 12.0 t C/ha - 27.6 t C/ha 범위의 공간적 변이를 나타내었다. 본 연구에서 개발된 탄소 축적량의 원격탐사 추정법과 환경요인에 따른 인공지능 예측법은 한반도에서 탄소흡수원으로서 맹그로브의 보전과 조성에 필요한 기초자료로 활용할 수 있을 것이다.

Deep CNN based Pilot Allocation Scheme in Massive MIMO systems

  • Kim, Kwihoon;Lee, Joohyung
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • 제14권10호
    • /
    • pp.4214-4230
    • /
    • 2020
  • This paper introduces a pilot allocation scheme for massive MIMO systems based on deep convolutional neural network (CNN) learning. This work is an extension of a prior work on the basic deep learning framework of the pilot assignment problem, the application of which to a high-user density nature is difficult owing to the factorial increase in both input features and output layers. To solve this problem, by adopting the advantages of CNN in learning image data, we design input features that represent users' locations in all the cells as image data with a two-dimensional fixed-size matrix. Furthermore, using a sorting mechanism for applying proper rule, we construct output layers with a linear space complexity according to the number of users. We also develop a theoretical framework for the network capacity model of the massive MIMO systems and apply it to the training process. Finally, we implement the proposed deep CNN-based pilot assignment scheme using a commercial vanilla CNN, which takes into account shift invariant characteristics. Through extensive simulation, we demonstrate that the proposed work realizes about a 98% theoretical upper-bound performance and an elapsed time of 0.842 ms with low complexity in the case of a high-user-density condition.

Pygidiopsis summa (Digenea: Heterophyidae): Status of Metacercarial Infection in Mullets from Coastal Areas in the Republic of Korea

  • Sohn, Woon-Mok;Na, Byoung-Kuk;Cho, Shin-Hyeong;Lee, Won-Ja;Park, Mi-Yeoun;Lee, Soon-Won;Choi, Seung-Bong;Huh, Beom-Nyung;Seok, Won-Seok
    • Parasites, Hosts and Diseases
    • /
    • 제54권4호
    • /
    • pp.497-502
    • /
    • 2016
  • To know the infection status of zoonotic trematode metacercariae in brackish water fish, we surveyed mullets collected from 18 coastal areas in the Republic of Korea. The metacercariae of Pygidiopsis summa were detected in 236 (68.2%) out of 346 mullets examined. They were found in mullets from 15 areas except for those from Boseong-gun (Jeollanam-do), Pohang-si, and Uljin-gun (Gyeongsangbuk-do). Especially in mullets from Taean-gun (Chungcheongnam-do) and Geoje-si (Gyeongsangnam-do), their prevalences were 100% and 95.5%, and the average metacercarial density was more than 1,000 per fish. They were also detected in mullets from 3 coastal lakes, Gyeongpoho, Songjiho, and Hwajinpoho, in Gangwon-do, and their average densities were 419, 147, and 672 per infected fish, respectively. The metacercariae of 5 other heterophyid species, including Heterophyes nocens, Heterophyopsis continua, Metagonimus sp., Stictodora fuscata, and Stictodora lari, were found in the mullets examined. The metacercariae of H. nocens were detected in 66.7, 100, 28.6, 81.6, 3.9, 61.5, and 27.3% of mullets from Muan-gun, Shinan-gun, Haenam-gun, Gangjin-gun, and Boseong-gun (Jeollanam-do), Hadong-gun, and Geoje-si (Gyeongsangnam-do), and their metacercarial intensities were 64, 84, 119, 99, 1, 24, and 24 per fish infected, respectively. From the above results, it has been confirmed that P. summa metacercariae are heavily infected in mullets from coastal areas of Korea. It is suggested that residents who frequently consume raw mullet dish can be easily infected with heterophyid flukes.

저온 및 고전류밀도 조건에서 전기도금된 구리 박막 간의 열-압착 직접 접합 (Thermal Compression of Copper-to-Copper Direct Bonding by Copper films Electrodeposited at Low Temperature and High Current Density)

  • 이채린;이진현;박기문;유봉영
    • 한국표면공학회:학술대회논문집
    • /
    • 한국표면공학회 2018년도 춘계학술대회 논문집
    • /
    • pp.102-102
    • /
    • 2018
  • Electronic industry had required the finer size and the higher performance of the device. Therefore, 3-D die stacking technology such as TSV (through silicon via) and micro-bump had been used. Moreover, by the development of the 3-D die stacking technology, 3-D structure such as chip to chip (c2c) and chip to wafer (c2w) had become practicable. These technologies led to the appearance of HBM (high bandwidth memory). HBM was type of the memory, which is composed of several stacked layers of the memory chips. Each memory chips were connected by TSV and micro-bump. Thus, HBM had lower RC delay and higher performance of data processing than the conventional memory. Moreover, due to the development of the IT industry such as, AI (artificial intelligence), IOT (internet of things), and VR (virtual reality), the lower pitch size and the higher density were required to micro-electronics. Particularly, to obtain the fine pitch, some of the method such as copper pillar, nickel diffusion barrier, and tin-silver or tin-silver-copper based bump had been utillized. TCB (thermal compression bonding) and reflow process (thermal aging) were conventional method to bond between tin-silver or tin-silver-copper caps in the temperature range of 200 to 300 degrees. However, because of tin overflow which caused by higher operating temperature than melting point of Tin ($232^{\circ}C$), there would be the danger of bump bridge failure in fine-pitch bonding. Furthermore, regulating the phase of IMC (intermetallic compound) which was located between nickel diffusion barrier and bump, had a lot of problems. For example, an excess of kirkendall void which provides site of brittle fracture occurs at IMC layer after reflow process. The essential solution to reduce the difficulty of bump bonding process is copper to copper direct bonding below $300^{\circ}C$. In this study, in order to improve the problem of bump bonding process, copper to copper direct bonding was performed below $300^{\circ}C$. The driving force of bonding was the self-annealing properties of electrodeposited Cu with high defect density. The self-annealing property originated in high defect density and non-equilibrium grain boundaries at the triple junction. The electrodeposited Cu at high current density and low bath temperature was fabricated by electroplating on copper deposited silicon wafer. The copper-copper bonding experiments was conducted using thermal pressing machine. The condition of investigation such as thermal parameter and pressure parameter were varied to acquire proper bonded specimens. The bonded interface was characterized by SEM (scanning electron microscope) and OM (optical microscope). The density of grain boundary and defects were examined by TEM (transmission electron microscopy).

  • PDF

감정표현불능증 : 그 개념과 치료적 함의 (Alexithymia : Concept and Implications for Treatment)

  • 함병주;김린
    • 수면정신생리
    • /
    • 제9권1호
    • /
    • pp.18-23
    • /
    • 2002
  • Alexithymia represents deficits in the cognitive processing and regulation of emotions. It is observed in many cases of psychosomatic disease, anorexia nervosa, panic disorder, depression etc. Many studies have shown that alexithymia is associated with maladaptive styles of emotion regulation, low emotional intelligence, interhemispheric transfer deficit, and reduced rapid eye movement density. Psychotherapies that enhance emotional awareness may be effective in alleviating the difficulties of alexithymic individuals. Aexithymia is useful for constructing the role of personality and emotions in the pathogenesis of psychiatric disorders. It may serve as a bridge between neurobiology and psychology. We review recent alexithymia theory and research and their implications for treatment of psychosomatic disorders.

  • PDF

실시간 영상분석을 이용한 합성곱 신경망 기반의 실내 연기 감지 연구 (A Study on Indoor Smoke Detection Based on Convolutional Neural Network Using Real Time Image Analysis)

  • 류진규;곽동걸;이봉섭;김대환
    • 전력전자학회:학술대회논문집
    • /
    • 전력전자학회 2019년도 전력전자학술대회
    • /
    • pp.537-539
    • /
    • 2019
  • Recently, large-scale fires have been generated as urban buildings have become more and more density. Especially, the expansion of smoke in buildings due to high-rise is an problem, and the smoke is the main cause of death in fires. Therefore, in this paper, the image-based smoke detection is proposed through deep learning-based artificial intelligence techniques to prevent possible damage if existing detectors are not detected. In addition, the detection model was not configured simply through only the smoke data set, but the data set in the haze form was additionally composed together to compensate for the accuracy.

  • PDF