• 반도체디스플레이기술학회지
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• 제17권4호
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• pp.42-45
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• 2018

As The semiconductor decrease from 10 nanometer to 7 nanometer, It is suggested that "More than Moore" is needed to follow Moore's Law, which has been a guide for the semiconductor industry. Fan-Out Wafer Level Package(FOWLP) is considered as the key to "More than Moore" to lead the next generation in semiconductors, and the reasons are as follows. the fan-out WLP does not require a substrate, unlike conventional wire bonding and flip-chip bonding packages. As a result, the thickness of the package reduces, and the interconnection becomes shorter. It is easy to increase the number of I / Os and apply it to the multi-layered 3D package. However, FOWLP has many issues that need to be resolved in order for mass production to become feasible. One of the most critical problem is the warpage problem in a process. Due to the nature of the FOWLP structure, the RDL is wired to multiple layers. The warpage problem arises when a new RDL layer is created. It occurs because the solder ball reflow process is exposed to high temperatures for long periods of time, which may cause cracks inside the package. For this reason, we have studied warpage in the FOWLP structure using commercial simulation software through the implementation of the reflow process. Simulation was performed to reproduce the experiment of products of molding compound company. Young's modulus and poisson's ratio were found to be influenced by the order of influence of the factors affecting the distortion. We confirmed that the lower young's modulus and poisson's ratio, the lower warpage.

• Advances in nano research
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• 제10권3호
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• pp.221-234
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• 2021

During the previous few years, phenomenon of bioconvection along with the use of nanoparticles showed large number of applications in technological and industrial field. This paper analyzed the bioconvection phenomenon in magnetohydrodynamic boundary layer flow of a Powell-Eyring nanoliquid past a stretchable cylinder with Cattaneo-Christov heat flux. In addition, the impacts of chemical reaction and heat generation/absorption parameter are considered. By the use of appropriate transformation, the governing PDEs (nonlinear) have been transformed and formulated into nonlinear ODEs. The resulting nonlinear ODEs subjected to relevant boundary conditions are solved analytically through homotopy analysis method which is programmed in Mathematica software. Graphical and numerical results versus physical quantities like velocity, temperature, concentration and motile microorganism are investigated under the impact of physical parameters. It is noted that velocity profile enhances as the curvature parameter A and Eyring-Powell fluid parameter M increases but a decline manner for large values of buoyancy ratio parameter Nr and bio-convection Rayleigh number Rb. In the presence of Prandtl number Pr, Eyring-Powell fluid parameter M and heat absorption parameter ��, temperature profile decreases. Nano particle concentration profile increases for increasing values of magnetic parameter Ha and thermophoresis parameter Nt. The motile density profile has revealed a decrement pattern for higher values of bio-convection Lewis number Lb and bio-convection peclet number Pe. This study may find uses in bio-nano coolant systems, advance nanomechanical bio-convection energy conversion equipment's, etc.

• 한국산업융합학회 논문집
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• 제25권2_1호
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• pp.177-184
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• 2022

The automatic defect sorting function of machinery parts is being introduced to the automation of the manufacturing process. In the final stage of automation of the manufacturing process, it is necessary to apply computer vision rather than human visual judgment to determine whether there is a defect. In this paper, we introduce a deep learning method to improve the classification performance of typical mechanical parts, such as welding parts, galvanized round plugs, and electro galvanized nuts, based on the results of experiments. In the case of poor welding, the method to further increase the depth of layer of the basic deep learning model was effective, and in the case of a circular plug, the surrounding data outside the defective target area affected it, so it could be solved through an appropriate pre-processing technique. Finally, in the case of a nut plated with zinc, since it receives data from multiple cameras due to its three-dimensional structure, it is greatly affected by lighting and has a problem in that it also affects the background image. To solve this problem, methods such as two-dimensional connectivity were applied in the object segmentation preprocessing process. Although the experiments suggested that the proposed methods are effective, most of the provided good/defective images data sets are relatively small, which may cause a learning balance problem of the deep learning model, so we plan to secure more data in the future.

• 한국정보통신학회논문지
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• 제25권12호
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• pp.1835-1845
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• 2021

본 논문에서는 블랙 아이스를 정확하게 인식하고 도로 노면 정보를 운전자에게 미리 알려줘서 속도를 제어하고 예방 조치를 취할 수 있도록 하기 위해 열화 도로 영상을 기반으로 블랙 아이스 검출하기 위해 lightweight 네트워크를 제안한다. 전이학습을 이용하여 블랙 아이스 인식 실험을 하였고, 블랙 아이스 인식의 정확도 향상을 위해 MobileNetV2 기반의 개선된 lightweight 네트워크를 개발하였다. 계산량을 줄이기 위해 Linear Bottleneck 및 Inverted Residuals를 활용하여 4개의 Bottleneck 그룹을 사용하고 모델의 인식률 향상을 위해 각 Bottleneck 그룹에 3×3 컨볼루션 레이어를 연결하여 지역적 특징 추출을 강화하고 특징 맵의 수를 늘렸다. 마지막으로 구축된 블랙 아이스 데이터 세트 대상으로 블랙 아이스 인식 실험을 진행하였으며, 제안된 모델은 블랙 아이스에 대해 99.07%의 정확한 인식률을 나타내었다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제11권9호
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• pp.371-380
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• 2022

합성곱 신경망은 이미지와 같은 격자 형태로 배열된 데이터를 다루는데 널리 사용되고 있는 신경망이다. 일반적인 합성곱 신경망은 합성곱층과 완전연결층으로 구성되며 각 층은 비선형활성함수를 포함하고 있다. 본 논문은 합성곱 신경망의 성능을 향상시키기 위해 결합된 파라메트릭 활성함수를 제안한다. 결합된 파라메트릭 활성함수는 활성함수의 크기와 위치를 변환시키는 파라미터를 적용한 파라메트릭 활성함수들을 여러 번 더하여 만들어진다. 여러 개의 크기, 위치를 변환하는 파라미터에 따라 다양한 비선형간격을 만들 수 있으며, 파라미터는 주어진 입력데이터에 의해 계산된 손실함수를 최소화하는 방향으로 학습할 수 있다. 결합된 파라메트릭 활성함수를 사용한 합성곱 신경망의 성능을 MNIST, Fashion MNIST, CIFAR10 그리고 CIFAR100 분류문제에 대해 실험한 결과, 다른 활성함수들보다 우수한 성능을 가짐을 확인하였다.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제12권9호
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• pp.399-406
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• 2023

클라우드 컴퓨팅은 에지 서버가 동작하는 포그(fog) 레이어가 결합된 에지(edge) 컴퓨팅 아키텍처로 진화하고 있다. 에지 컴퓨팅 아키텍처가 관심을 받는 이유는 짧은 통신 지연으로 실시간 IoT 응용을 지원할 수 있기 때문이다. 이와 동시에 인공지능 기술을 도입한 많은 클라우드 작업 스케줄링 기법들이 제안되었다. 인공지능 기반의 클라우드 작업 스케줄링 기법은 기존 기법보다 더 좋은 성능을 보이지만 스케줄링 시간이 다소 소요된다는 단점이 있다. 이 논문에서는 에지 컴퓨팅 환경에서 분산 딥러닝 학습 기반의 동적 스케줄링 기법을 제안한다. 제안하는 기법은 기존 기법보다 스케줄링 시간이 짧은 장점이 있다. 또한 멀티 에이전트를 통한 분산 딥러닝 학습의 효과성을 보이기 위해 확장적인 실험 환경에서 제안 기법과 기존 인공지능 기법의 성능일 비교 평가하였다. 성능 실험 결과 기존 인공지능 기반 클라우드 작업 스케줄링 기법보다 짧은 스케줄링 시간을 보여 IoT 실시간 응용에 적합함을 보였으며, 확장적인 실험에서도 제안 기법이 완료된 작업의 수에 대하여 우수한 성능을 보임을 증명하였다.

• 한국시뮬레이션학회논문지
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• 제19권4호
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• pp.161-167
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• 2010

유-헬스케어(U-Healthcare)에서 이동 환자 상태에 대한 모니터링 기술은 필수적이다. 모니터링 기술에서는 이동 환자의 생체 정보가 동적 위치 정보와 함께 정해진 목적지 서버로 전송되어야 하는데 모니터링할 환자의 수가 증가하며 각 환자의 이동성이 불규칙함에 따라 적절한 부하균형 단계가 중간에 필요해진다. 토르소(Torus) 구조를 기반으로 한 이동 환자 상시 모니터링 시스템에서는 이를 반영하여 먼저 환자 생체 정보를 중간노드로 전송한 후 부하균형 기반의 우선순위 정책에 따라 목적지 서버로 연이어 전송된다. 본 논문에서는 계층적이며 객체지향적인 정형화 명세를 기반으로 하는 시스템 명세 기법을 사용하여 이러한 이동 환자 상시 모니터링 시스템의 전체 구조와 구성 노드들의 결합 관계를 정의한 후 각 요소의 기능을 유사코드로 설계함으로써 본 시스템이 효과적인 환자 정보 수집과 전송, 분배 및 판단에 효율적임을 시스템 명세 기법을 통하여 검증한다.

• 대기
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• 제33권4호
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• pp.423-440
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• 2023

The updated version of Global Ocean Data Assimilation and Prediction System (GODAPS) in the NIMS/KMA (National Institute of Meteorological Sciences/Korea Meteorological Administration), which has been in operation since December 2021, is being introduced. This technical note on GODAPS2 describes main progress and updates to the previous version of GODAPS, a software tool for the operating system, and its improvements. GODAPS2 is based on Forecasting Ocean Assimilation Model (FOAM) vn14.1, instead of previous version, FOAM vn13. The southern limit of the model domain has been extended from 77°S to 85°S, allowing the modelling of the circulation under ice shelves in Antarctica. The adoption of non-linear free surface and variable volume layers, the update of vertical mixing parameterization, and the adjustment of isopycnal diffusion coefficient for the ocean model decrease the model biases. For the sea-ice model, four vertical ice layers and an additional snow layer on top of the ice layers are being used instead of previous single ice and snow layers. The changes for data assimilation include the updated treatment for background error covariance, a newly added bias scheme combined with observation bias, the application of a new bias correction for sea level anomaly, an extension of the assimilation window from 1 day to 2 days, and separate assimilations for ocean and sea-ice. For comparison, we present the difference between GODAPS and GODAPS2. The verification results show that GODAPS2 yields an overall improved simulation compared to GODAPS.

• Restorative Dentistry and Endodontics
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• 제48권1호
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• pp.1.1-1.11
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• 2023

Objectives: This study evaluated the dentinal penetration depth of 2.5% sodium hypochlorite (NaOCl) in root canals with and without preparation and different irrigant activation protocols. Materials and Methods: Sixty-three bovine mandibular incisors were randomly allocated to 6 groups (n = 10): G1, preparation + conventional needle irrigation (CNI); G2, preparation + passive ultrasonic irrigation (PUI); G3, preparation + Odous Clean (OC); G4, no preparation + CNI; G5, no preparation + PUI; G6, no preparation + OC; and CG (negative control; n = 3). Samples were filled with crystal violet for 72 hours. Irrigant activation was performed. Samples were sectioned perpendicularly along the long axis, 3 mm and 7 mm from the apex. Images of the root thirds of each block were captured with a stereomicroscope and analyzed with an image analysis software. One-way analysis of variance, followed by the Tukey post hoc test, and the Student's t-test were used for data analysis, with a significance level of 5%. Results: The NaOCl penetration depth was similar when preparation was performed, regardless of the method of irrigation activation (p > 0.05). In the groups without preparation, G6 showed greater NaOCl penetration depth (p < 0.05). The groups without preparation had a greater NaOCl penetration depth than those with preparation (p = 0.0019). Conclusions: The NaOCl penetration depth was similar in groups with root canal preparation. Without root canal preparation, OC allowed deeper NaOCl penetration. The groups without preparation had greater NaOCl penetration than those undergoing root canal preparation.

• Journal of Radiation Protection and Research
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• 제48권4호
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• pp.184-196
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• 2023

Background: Radiation protection is crucial in various fields due to the harmful effects of radiation. Shielding is used to reduce radiation exposure, but gamma radiation poses challenges due to its high energy and penetration capabilities. Materials and Methods: This work investigates the radiation shielding properties of polyvinylidene fluoride (PVDF) samples containing different weight fraction of tungsten carbide (WC), tungsten trioxide (WO₃), and tungsten disulfide (WS₂). Parameters such as the mass attenuation coefficient (MAC), half-value layer (HVL), mean free path (MFP), effective atomic number (Z_eff), and macroscopic effective removal cross-section for fast neutrons (Σ_R) were calculated using the Phy-X/PSD software. EpiXS simulations were conducted for MAC validation. Results and Discussion: Increasing the weight fraction of the additives resulted in higher MAC values, indicating improved radiation shielding. PVDF-xWC showed the highest percentage increase in MAC values. MFP results indicated that PVDF-0.20WC has the lowest values, suggesting superior shielding properties compared to PVDF-0.20WO₃ and PVDF-0.20WS₂. PVDF-0.20WC also exhibited the highest Z_eff values, while PVDF-0.20WS₂ showed a slightly higher increase in Z_eff at energies of 0.662 and 1.333 MeV. PVDF-0.20WC has demonstrated the highest Σ_R value, indicating effective shielding against fast neutrons, while PVDF-0.20WS₂ had the lowest Σ_R value. The Monte Carlo N-Particle Transport version 5 (MCNP5) simulations showed that PVDF-xWC attenuates gamma radiation more than pure PVDF, significantly decreasing the dose equivalent rate. Conclusion: Overall, this research provides insights into the radiation shielding properties of PVDF mixtures, with PVDF-xWC showing the most promising results.