• 한국전자통신학회논문지
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• 제8권11호
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• pp.1675-1680
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• 2013

최근 저소음, 고속, 고추력의 반송장치가 요구됨에 따라 영구자석 선형동기전동기가 대두되고 있으나 반송경로 전장에 전기자를 설치하는 선형 동기전동기의 특성으로 인해 장거리 반송장치에 적용시 설치비용의 증가를 가져온다. 따라서 우리는 전기자를 분산시켜 배치하는 방법을 제안하여 비용증가의 문제점을 해결하고자 하였다. 하지만 가동자의 진행시 분산배치된 전기자 사이를 통과하게 되면 전기자의 불연속 구간인 단부에 의해 디텐트력이 발생하여 추력 맥동이 발생하고 기기 성능저하와 소음, 진동의 원인이 된다. 따라서 본 논문에서는 단부에 의한 영향을 저감하기 위해 전기자 끝단의 치 높이와 보조치 형상에 따른 디텐트력의 특성을 파악하고 다구찌의 실험계획법을 이용하여 단부 효과를 가장 저감할 수 있는 형상을 제안하였다.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권9호
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• pp.889-897
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• 2010

현대의 대량화된 영상 관리 시스템은 영상의 특징을 표현하는 영상식별자에 대해 왜곡에 강인하며 빠른 검색 속도, 정확성 및 효율적인 저장 등의 기본 성능을 요구한다. 영상식별자 설계 방법은 기하학적 왜곡에 강인한 지역 방식과 빠른 검색 및 적은 저장 용량의 속성을 지닌 전역방식으로 구분 할 수 있다. 본 논문에서는 왜곡에 강하고 지역적 공간적 제약으로 인한 서로간의 차별성이 강화된 지역 기술자들로부터 각각 개개 차원의 특징 분포도를 분석하여, 두 영상간의 유사도를 빠르고 정확하게 측정할 수 있는 지역 기술자 및 전역 기술자의 속성을 가지고 있는 LFH(Local Feature's Histogram)기반 영상식별자를 제안한다. 또한 GPU를 사용하여 LFH를 구현하는 방법을 제시하며, 제안한 LFH와 대표적인 지역, 전역 방식인 SIFT 및 EHD 방식과 저장용량, 추출 시간, 검색 속도 및 정확률에 대한 성능을 비교하였다.

• Restorative Dentistry and Endodontics
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• 제39권4호
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• pp.282-287
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• 2014

Objectives: The aim of the present study was to investigate the bond strength of RelyX Unicem (3M) to root canal dentin when used as an endodontic sealer. Materials and Methods: Samples of 24 single-rooted teeth were prepared with Gates Glidden drills and K3 files. After that, the roots were randomly assigned to three experimental groups (n = 8) according to the filling material, (1) AH Plus (Dentsply De Trey GmbH)/Gutta-Percha cone; (2) Epiphany SE (Pentron)/Resilon cone; (3) RelyX Unicem/Gutta-Percha cone. All roots were filled using a single cone technique associated to vertical condensation. After the filling procedures, each tooth was prepared for a push-out bond strenght test by cutting 1 mm-thick root slices. Loading was performed on a universal testing machine at a speed of 0.5 mm/min. One-way analysis of variance and Tukey test for multiple comparisons were used to compare the results among the experimental groups. Results: Epiphany SE/Resilon showed significantly lower push-out bond strength than both AH Plus/Gutta-Percha and RelyX Unicem/Gutta-Percha (p < 0.05). There was no significant difference in bond strength between AH Plus/Gutta-Percha and RelyX Unicem/Gutta-Percha (p > 0.05). Conclusions: Under the present in vitro conditions, bond strength to root dentin promoted by RelyX Unicem was similar to AH Plus. Epiphany SE/Resilon resulted in lower bond strength values when compared to both materials.

• 자원리싸이클링
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• 제21권1호
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• pp.82-92
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• 2012

텅스텐카바이드는 금속절단 공구, 드릴의 날, 광산공구, 군사무기 재료, 화학원료, 촉매, 내마모성재료, 제트엔진 터빈 블레이드 등 다양한 용도로 사용된다. 요즘 경제적인 측면과 효율적인의 측면에서 텅스텐카바이드 재활용 기술이 넓게 연구되었다. 이 논문에서는 텅스텐카바이드 재활용 기술에 대하여 1969년부터 2011년까지 공개/등록된 미국, 일본, 유럽, 한국의 특허와 SCI급 논문을 조사하였다. 키워드를 이용하여 조사하였고 필터링 하여 특허와 논문을 수집하여 연도별, 국가별, 기관별, 기술별로 분석하였다.

• 한국기계가공학회지
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• 제18권9호
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• pp.29-35
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• 2019

The structure of the machinery industry due to the 4th industrial revolution is changing from precision and durability to intelligent and smart machinery through sensing and interconnection(IoT). There is a growing need for research on prognostics and health management(PHM) that can prevent abnormalities in processing machines and accurately predict and diagnose conditions. PHM is a technology that monitors the condition of a mechanical system, diagnoses signs of failure, and predicts the remaining life of the object. In this study, the vibration generated during machining is measured and a classification algorithm for normal and fault signals is developed. Arbitrary fault signal is collected by changing the conditions of un stable supply cutting oil and fixing jig. The signal processing is performed to apply the measured signal to the learning model. The sampling rate is changed for high speed operation and performed machine learning using raw signal without FFT. The fault classification algorithm for 1D convolution neural network composed of 2 convolution layers is developed.

• 한국기계가공학회지
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• 제20권11호
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• pp.36-42
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• 2021

This study was conducted to analyze the effect of the gear specification and gear quality corresponding to the macro geometry on the gear transmission error. The two pairs of gears with large and small transmission errors were selected for calculation, and two pairs of gears were manufactured with different gear quality. The test gears were manufactured by two different gear specifications with ISO 5 and 8 gear quality, respectively. The transmission error measurement system consists of an input motor, reducer, encoders, gearbox, torque meter, and powder brake. To confirm the repeatability of the test results, repeatability was confirmed by performing three repetitions under all conditions, and the average value was used to compare the transmission error results. The transmission errors of the gears were analyzed and compared with the test results. When the gear quality was high, the transmission error was generally low depending on the load, and the load at which the decreasing transmission error phenomenon was completed was also lower. Even when the design transmission error according to the gear specification was different, the difference of the minimum transmission error was not large. The transmission error at the load larger than the minimum transmission error load increased to a slope similar to the slope of the analysis result.

• 융합보안논문지
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• 제23권1호
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• pp.139-145
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• 2023

한국 육군은 기동화, 지능화, 초연결형 Army TIGER 체계 등 최첨단 미래형 강군 육성을 추진하고 있다. 미래 보병여단은 다영역작전에서 전투수행이 가능하도록 분대 단위 전술차량으로 기동성을 증대시키고, 지상무인로봇, 감시정찰드론 등 다양한 무기체계를 전력화할 예정이다. 또한 무기체계를 통해 수집한 데이터를 초연결 네트워크로 실시간 송·수신하고 학습시키는 지능형 부대를 육성할 것이다. 이러한 군의 발전 계획을 통해 미래의 보병여단은 더 많은 데이터를 유통시킬 것이다. 그러나 현재 육군의 전술정보통신체계는 미래 무기체계의 대용량 정보를 유통하기에 상대적으로 낮은 전송속도와 대역폭, 수동적 네트워크 관리, 기동 간 통신 지원 제한 등 미래의 부대의 전술통신체계로 운용하기에는 한계가 있다. 따라서 본 논문에서는 한국 육군의 미래 보병여단의 무기체계를 분석하고, 보병여단의 기동 상황을 묘사하기 위한 공격작전 시나리오를 바탕으로 지상·공중·위성 계층의 통합 전술통신망 M&S를 통해 미래 보병여단이 갖추어야 할 정보유통능력을 제시한다.

• 산업경영시스템학회지
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• 제46권3호
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• pp.1-6
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• 2023

In the realm of dental prosthesis fabrication, obtaining accurate impressions has historically been a challenging and inefficient process, often hindered by hygiene concerns and patient discomfort. Addressing these limitations, Company D recently introduced a cutting-edge solution by harnessing the potential of intraoral scan images to create 3D dental models. However, the complexity of these scan images, encompassing not only teeth and gums but also the palate, tongue, and other structures, posed a new set of challenges. In response, we propose a sophisticated real-time image segmentation algorithm that selectively extracts pertinent data, specifically focusing on teeth and gums, from oral scan images obtained through Company D's oral scanner for 3D model generation. A key challenge we tackled was the detection of the intricate molar regions, common in dental imaging, which we effectively addressed through intelligent data augmentation for enhanced training. By placing significant emphasis on both accuracy and speed, critical factors for real-time intraoral scanning, our proposed algorithm demonstrated exceptional performance, boasting an impressive accuracy rate of 0.91 and an unrivaled FPS of 92.4. Compared to existing algorithms, our solution exhibited superior outcomes when integrated into Company D's oral scanner. This algorithm is scheduled for deployment and commercialization within Company D's intraoral scanner.

• Geomechanics and Engineering
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• 제37권1호
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• pp.65-72
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• 2024

Water ingress poses a common and intricate geological hazard with profound implications for tunnel construction's speed and safety. The project's success hinges significantly on the precision of estimating water inflow during excavation, a critical factor in early-stage decision-making during conception and design. This article introduces an optimized model employing the gene expression programming (GEP) approach to forecast tunnel water inflow. The GEP model was refined by developing an equation that best aligns with predictive outcomes. The equation's outputs were compared with measured data and assessed against practical scenarios to validate its potential applicability in calculating tunnel water input. The optimized GEP model excelled in forecasting tunnel water inflow, outperforming alternative machine learning algorithms like SVR, GPR, DT, and KNN. This positions the GEP model as a leading choice for accurate and superior predictions. A state-of-the-art machine learning-based graphical user interface (GUI) was innovatively crafted for predicting and visualizing tunnel water inflow. This cutting-edge tool leverages ML algorithms, marking a substantial advancement in tunneling prediction technologies, providing accuracy and accessibility in water inflow projections.

• Current Photovoltaic Research
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• 제12권2호
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• pp.37-40
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• 2024

One of the current innovation trends in the solar industry is the increase in the size of silicon wafers. As the wafer size increases, the series resistance of the module rises, highlighting the need for research on methods for cutting and bonding solar cells. Among these, the Infrared (IR) laser scribing technique has been extensively researched. However, there is still insufficient optimization research regarding the thermal damage caused by lasers on the Transparent Conductive Oxide (TCO) layer of Heterojunction (HJT) solar cells. Therefore, in this study, we systematically varied conditions such as IR laser scribing speed, frequency, power, and the number of scribes to investigate their impact on the performance of cut cells under each condition. Additionally, we conducted a comparative analysis of thermal damage effects on the TCO layer based on varying scribing depths.