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6G 통신에서의 센싱과 통신의 결합 서비스(ISAC) 스크랩

  • 한국전자통신연구원
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  • 전기/전자

Sixth-generation (6G) networks may allow to evolve from everything connected to everything sensed. Integrated sensing and communications (ISAC) requires the higher frequencies, wider bands, and more advanced antenna technology offered by 6G technology. We analyze advanced beamforming techniques to overcome the poor propagation characteristics of millimeter and terahertz waves as well as new waveforms designed to include sensing. This paper is intended to provide communication researchers with short summaries of ISAC, use cases, and standardization initiatives as guidelines for exploring new research and development directions.Ⅰ. 6G 비전과 ISACⅡ. ISAC의 일반 개요Ⅲ. 유스케이스(TR22.837)Ⅳ. 3GPP 기고서 이슈Ⅴ. 결론약어 정리

2023-12-01

주력산업 지능화를 위한 제조 혁신 기술 동향 스크랩

  • 한국전자통신연구원
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  • 전기/전자

Smart manufacturing in Industry 4.0 is developing toward autonomous manufacturing as a last-mile technology. We investigate development trends in manufacturing innovation technologies, review major industrial intelligence projects currently carried out at ETRI, and infer directions of future technology developments.Ⅰ. 서론Ⅱ. 본론Ⅲ. 결론용어해설약어 정리

2023-12-01

뉴로모픽 감각 인지 기술 동향―촉각, 후각을 중심으로 스크랩

  • 한국전자통신연구원
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  • 전기/전자

In response to diverse external stimuli, sensory receptors generate spiking nerve signals. These generated signals are transmitted to the brain along the neural pathway to advance to the stage of recognition or perception, and then they reach the area of discrimination or judgment for remembering, assessing, and processing incoming information. We review research trends in neuromorphic sensory perception technology inspired by biological sensory perception functions. Among the various senses, we consider sensory nerve decoding technology based on sensory nerve pathways focusing on touch and smell, neuromorphic synapse elements that mimic biological neurons and synapses, and neuromorphic processors. Neuromorphic sensory devices, neuromorphic synapses, and artificial sensory memory devices that integrate storage components are being actively studied. However, various problems remain to be solved, such as learning methods to implement cognitive functions beyond simple detection. Considering applications such as virtual reality, medical welfare, neuroscience, and cranial nerve interfaces, neuromorphic sensory recognition technology is expected to be actively developed based on new technologies, including combinatorial neurocognitive cell technology.Ⅰ. 서론Ⅱ. 감각 디코딩 기술Ⅲ. 뉴로모픽 디바이스Ⅳ. 뉴로모픽 인지 기술Ⅴ. 기술 발전 전망Ⅵ. 결론용어해설약어 정리

2023-12-01

Complementary FET로 열어가는 반도체 미래 기술 스크랩

  • 한국전자통신연구원
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  • 전기/전자

With semiconductor scaling approaching the physical limits, devices including CMOS (complementary metal-oxide-semiconductor) components have managed to overcome yet are currently struggling with several technical issues like short-channel effects. Evolving from the process node of 22 nm with FinFET (fin field effect transistor), state-of-the-art semiconductor technology has reached the 3 nm node with the GAA-FET (gate-all-around FET), which appropriately addresses the main issues of power, performance, and cost. Technical problems remain regarding the foundry of GAA-FET, and next-generation devices called post-GAA transistors have not yet been devised, except for the CFET (complementary FET). We introduce a CFET that spatially stacks p- and n-channel FETs on the same footprint and describe its structure and fabrication. Technical details like stacking of nanosheets, special spacers, hetero-epitaxy, and selective recess are more thoroughly reviewed than in similar articles on CFET fabrication.Ⅰ. 트랜지스터 스케일링Ⅱ. Complementary FET(CFET)Ⅲ. Back Side Power Delivery Network(BSPDN) 기술Ⅳ. 결론용어해설약어 정리

2023-12-01

반도체 및 전자패키지의 방열기술 동향 스크랩

  • 한국전자통신연구원
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  • 전기/전자

Heat dissipation technology for semiconductors and electronic packaging has a substantial impact on performance and lifespan, but efficient heat dissipation is currently facing limited improvement. Owing to the high integration density in electronic packaging, heat dissipation components must become thinner and increase their performance. Therefore, heat dissipation materials are being devised considering conductive heat transfer, carbon-based directional thermal conductivity improvements, functional heat dissipation composite materials with added fillers, and liquid-metal thermal interface materials. Additionally, in heat dissipation structure design, 3D printing-based complex heat dissipation fins, packages that expand the heat dissipation area, chip embedded structures that minimize contact thermal resistance, differential scanning calorimetry structures, and through-silicon-via technologies and their replacement technologies are being actively developed. Regarding dry cooling using single-phase and phase-change heat transfer, technologies for improving the vapor chamber performance and structural diversification are being investigated along with the miniaturization of heat pipes and high-performance capillary wicks. Meanwhile, in wet cooling with high heat flux, technologies for designing and manufacturing miniaturized flow paths, heat dissipating materials within flow paths, increasing heat dissipation area, and reducing pressure drops are being developed. We also analyze the development of direct cooling and immersion cooling technologies, which are gradually expanding to achieve near-junction cooling.Ⅰ. 서론Ⅱ. 전도 열전달 방식의 방열기술Ⅲ. 단상 및 상변화 기반 방열기술Ⅳ. 결론용어해설약어 정리

2023-12-01

지능형 Self-Organizing Network를 위한 설명 가능한 기계학습 연구 동향 스크랩

  • 한국전자통신연구원
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  • 전기/전자

As artificial intelligence has become commonplace in various fields, the transparency of AI in its development and implementation has become an important issue. In safety-critical areas, the eXplainable and/or understandable of artificial intelligence is being actively studied. On the other hand, machine learning have been applied to the intelligence of self-organizing network (SON), but transparency in this application has been neglected, despite the critical decision-makings in the operation of mobile communication systems. We describes concepts of eXplainable machine learning (ML), along with research trends, major issues, and research directions. After summarizing the ML research on SON, research directions are analyzed for explainable ML required in intelligent SON of beyond 5G and 6G communication.Ⅰ. 서론Ⅱ. 설명 가능한 기계학습 연구 동향Ⅲ. SON에서의 기계학습 연구 동향Ⅳ. 지능형 SON에서 XML 연구 방향Ⅴ. 결론약어 정리

2023-12-01

인공지능에서 저작권과 라이선스 이슈 분석 스크랩

  • 한국전자통신연구원
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  • 전기/전자

Open source has many advantages and is widely used in various fields. However, legal disputes regarding copyright and licensing of datasets and learning models have recently arisen in artificial intelligence developments. We examine how datasets affect artificial intelligence learning and services from the perspective of copyrighting and licensing when datasets are used for training models. The licensing conditions of datasets can lead to copyright infringement and license violation, thus determining the scope of disclosure and commercialization of the trained model. In addition, we examine related legal issues.Ⅰ. 서론Ⅱ. 인공지능 학습과 추론 과정의 이슈Ⅲ. 관련 사례들Ⅳ. 데이터세트의 쟁점Ⅴ. 학습모델 쟁점Ⅵ. 추론/서비스 쟁점Ⅶ. 이슈에 대한 견해Ⅷ. 결론 및 향후 과제용어해설약어 정리

2023-12-01

자율주행차량 운전자 모니터링에 대한 동향 및 시사점 스크랩

  • 한국전자통신연구원
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  • 전기/전자

Given recent accidents involving autonomous vehicles, driver monitoring technology related to the transition of control in autonomous vehicles is gaining prominence. Driver status monitoring systems recognize the driver’s level of alertness and identify possible impairments in the driving ability owing to conditions including drowsiness and distraction. In autonomous vehicles, predictive factors for the transition to manual driving should also be included. During traditional human driving, monitoring the driver’s status is relatively straightforward owing to the consistency of crucial cues, such as the driver’s location, head orientation, gaze direction, and hand placement. However, monitoring becomes more challenging during autonomous driving because of the absence of direct manual control and the driver’s engagement in other activities, which may obscure the accurate assessment of the driver’s readiness to intervene. Hence, safety-ensuring technology must be balanced with user experience in autonomous driving. We explore relevant global and domestic regulations, the new car assessment program, and related standards to extract requirements for driver status monitoring. This kind of monitoring can both enhance the autonomous driving performance and contribute to the overall safety of autonomous vehicles on the road.Ⅰ. 서론Ⅱ. 자율주행 제어권 관련 안전기준Ⅲ. EuroNCAPⅣ. ISO 표준 동향Ⅴ. 결론용어해설약어 정리각주

2023-12-01

비디오 시각적 관계 이해 기술 동향 스크랩

  • 한국전자통신연구원
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  • 전기/전자

Visual relationship understanding in computer vision allows to recognize meaningful relationships between objects in a scene. This technology enables the extraction of representative information within visual content. We discuss the technology of visual relationship understanding, specifically focusing on videos. We first introduce visual relationship understanding concepts in videos and then explore the latest existing techniques. Next, we present benchmark datasets commonly used in video visual relationship understanding. Finally, we discuss future research directions in video visual relationship understanding.Ⅰ. 서론Ⅱ. 비디오 시각적 관계 이해 기술 개요Ⅲ. 비디오 시각적 관계 이해 기술 동향Ⅳ. 벤치마크 데이터셋Ⅴ. 결론용어해설

2023-12-01

인공지능 기술을 활용한 데이터 관리 기술 동향 스크랩

  • 한국전자통신연구원
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  • 전기/전자

Recently, artificial intelligence has been in the spotlight across various fields. Artificial intelligence uses massive amounts of data to train machine learning models and performs various tasks using the trained models. For model training, large, high-quality data sets are essential, and database systems have provided such data. Driven by advances in artificial intelligence, attempts are being made to improve various components of database systems using artificial intelligence. Replacing traditional complex algorithm-based database components with their artificial-intelligence-based counterparts can lead to substantial savings of resources and computation time, thereby improving the system performance and efficiency. We analyze trends in the application of artificial intelligence to database systems.Ⅰ. 서론Ⅱ. 워크로드 기반 지도 학습 기술Ⅲ. 데이터 기반 비지도 학습 기술Ⅳ. 제로샷(Zero-shot) 학습 기반 모델Ⅴ. 데이터베이스 시스템을 위한 ETRI 인공지능 활용 기술Ⅵ. 결론용어해설약어 정리

2023-12-01