• Title/Summary/Keyword: Software V&V

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POORLY STUDIED ECLIPSING BINARIES IN THE FIELD OF DO DRACONIS: V454 DRA AND V455 DRA

  • Kim, Yonggi;Andronov, Ivan L.;Andrych, Kateryna D.;Yoon, Joh-Na;Han, Kiyoung;Chinarova, Lidia L.
    • Journal of The Korean Astronomical Society
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    • v.53 no.2
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    • pp.43-48
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    • 2020
  • We report an analysis of two poorly studied eclipsing binary stars, GSC 04396-00605 and GSC 04395-00485 (recently named V455 Dra and V454 Dra, respectively). Photometric data of the two stars were obtained using the 1-m Korean telescope of the LOAO operated by KASI while monitoring the cataclysmic variable DO Dra in the frame of the Inter-Longitude Astronomy (ILA) project. We derived periods of 0.434914 and 0.376833 days as well as initial epochs JD 2456480.04281 and JD 2456479.0523, respectively, more accurate than previously published values by factors 9 and 6. The phenomenological characteristics of the mean light curves were determined using the New Algol Variable (NAV) algorithm. The individual times of maxima/minima (ToM) were determined using the newly developed software MAVKA, which outputs accurate parameters using "asymptotic parabola" approximations. The light curves were approximated using phenomenological and physical models. In the NAV algorithm, the phenomenological parameters are well determined. We derived physical parameters using the Wilson-Devinney model. In this model, the best-fit parameters are highly correlated, thus some of them were fixed to reasonable values. For both systems, we find evidence for the presence of a cool spot and estimate its parameters. Both systems can be classified as overcontact binaries of EW type.

Roundabout Signal Metering Operation Methods by Considering Approach Lane's Degree of Saturation (접근로별 포화도를 고려한 Roundabout Signal Metering 운영방법에 관한 연구)

  • Ahn, Woo-Young;Lee, So-Young
    • International Journal of Highway Engineering
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    • v.15 no.5
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    • pp.217-226
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    • 2013
  • PURPOSES : Under the capacity conditions with balanced approach flows, roundabouts give less delay than existing signalized intersections; however, flows over 450 vehicles/hour/lane with unbalanced approach flow conditions, roundabouts efficiency drops due to the short time difference between the critical gap and the follow-up headway. The purpose of this study is developing a roundabout Signal Metering operation method by considering approach lanes degree of saturation. METHODS : A four-way-approach with one-lane roundabout is selected to compare the Signal Metering performance for the case of 16 different unbalanced flow conditions. Based on these traffic conditions, the performance is evaluated for 64 different cases of Signal Metering combinations by using SIDRA software. A degree of saturation(V/C ratio) sum for two adjoined approaches is used for the performance index of choosing Metered Approach and Controlling Approach. RESULTS : When the V/C ratio sum is 0.29~0.81 and Metered Approach flow is less than Controlling Approach flow, the average delay saving per vehicle is about 7 seconds; however, after this rage the delay saving decreases gradually until the V/C ratio sum reaches around 1.0. The range of V/C ratio sum 0.93~1.09 provides average delay saving per vehicle about 3 seconds. In case of V/C ratio sum is grater than 1.0 and the flows of Metered Approach is grater than Controlling Approach, the average delay per vehicle increases 3~11 times respectively. CONCLUSIONS : As expected, the Signal Metering provides substantial improvements in delay saving for the case of V/C ratio sum is 0.3~1.0 under the traffic flow conditions of Metered Approach is less than Controlling Approach.

Reinforcement Learning Based Energy Control Method for Smart Energy Buildings Integrated with V2G Station (강화학습 기반 V2G Station 연계형 스마트 에너지 빌딩 전력 제어 기법)

  • Seok-Min Choi;Sun-Yong Kim
    • The Journal of the Korea institute of electronic communication sciences
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    • v.19 no.3
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    • pp.515-522
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    • 2024
  • Energy consumption is steadily increasing, and buildings in particular account for more than 20% of the total energy consumption around the world. As an effort to cost-effectively manage the energy consumption of buildings, many research groups have recently focused on Smart Building Energy Management Systems (BEMS), which are deepening the research depth by applying artificial intelligence(AI). In this paper, we propose a reinforcement learning-based energy control method for smart energy buildings integrated with V2G station, which aims to reduce the total energy cost of the building. The results of performance evaluation based on the energy consumption data measured in the real-world building shows that the proposed method can gradually reduce the total energy costs of the building as the learning process progresses.

End to End Model and Delay Performance for V2X in 5G (5G에서 V2X를 위한 End to End 모델 및 지연 성능 평가)

  • Bae, Kyoung Yul;Lee, Hong Woo
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.107-118
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    • 2016
  • The advent of 5G mobile communications, which is expected in 2020, will provide many services such as Internet of Things (IoT) and vehicle-to-infra/vehicle/nomadic (V2X) communication. There are many requirements to realizing these services: reduced latency, high data rate and reliability, and real-time service. In particular, a high level of reliability and delay sensitivity with an increased data rate are very important for M2M, IoT, and Factory 4.0. Around the world, 5G standardization organizations have considered these services and grouped them to finally derive the technical requirements and service scenarios. The first scenario is broadcast services that use a high data rate for multiple cases of sporting events or emergencies. The second scenario is as support for e-Health, car reliability, etc.; the third scenario is related to VR games with delay sensitivity and real-time techniques. Recently, these groups have been forming agreements on the requirements for such scenarios and the target level. Various techniques are being studied to satisfy such requirements and are being discussed in the context of software-defined networking (SDN) as the next-generation network architecture. SDN is being used to standardize ONF and basically refers to a structure that separates signals for the control plane from the packets for the data plane. One of the best examples for low latency and high reliability is an intelligent traffic system (ITS) using V2X. Because a car passes a small cell of the 5G network very rapidly, the messages to be delivered in the event of an emergency have to be transported in a very short time. This is a typical example requiring high delay sensitivity. 5G has to support a high reliability and delay sensitivity requirements for V2X in the field of traffic control. For these reasons, V2X is a major application of critical delay. V2X (vehicle-to-infra/vehicle/nomadic) represents all types of communication methods applicable to road and vehicles. It refers to a connected or networked vehicle. V2X can be divided into three kinds of communications. First is the communication between a vehicle and infrastructure (vehicle-to-infrastructure; V2I). Second is the communication between a vehicle and another vehicle (vehicle-to-vehicle; V2V). Third is the communication between a vehicle and mobile equipment (vehicle-to-nomadic devices; V2N). This will be added in the future in various fields. Because the SDN structure is under consideration as the next-generation network architecture, the SDN architecture is significant. However, the centralized architecture of SDN can be considered as an unfavorable structure for delay-sensitive services because a centralized architecture is needed to communicate with many nodes and provide processing power. Therefore, in the case of emergency V2X communications, delay-related control functions require a tree supporting structure. For such a scenario, the architecture of the network processing the vehicle information is a major variable affecting delay. Because it is difficult to meet the desired level of delay sensitivity with a typical fully centralized SDN structure, research on the optimal size of an SDN for processing information is needed. This study examined the SDN architecture considering the V2X emergency delay requirements of a 5G network in the worst-case scenario and performed a system-level simulation on the speed of the car, radius, and cell tier to derive a range of cells for information transfer in SDN network. In the simulation, because 5G provides a sufficiently high data rate, the information for neighboring vehicle support to the car was assumed to be without errors. Furthermore, the 5G small cell was assumed to have a cell radius of 50-100 m, and the maximum speed of the vehicle was considered to be 30-200 km/h in order to examine the network architecture to minimize the delay.

Assessment of the usefulness of the Machine Performance Check system that is an evaluation tools for the determination of daily beam output (일간 빔 출력 확인을 위한 평가도구인 Machine Performance Check의 유용성 평가)

  • Lee, Sang Hyeon;Ahn, Woo Sang;Lee, Woo Seok;Choi, Jin Hyeok;Kim, Seon Yeon
    • The Journal of Korean Society for Radiation Therapy
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    • v.29 no.2
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    • pp.65-73
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    • 2017
  • Purpose: Machine Performance Check (MPC) is a self-checking software based on the Electronic Portal Imaging Device (EPID) to measure daily beam outputs without external installation. The purpose of this study is to verify the usefulness of MPC by comparing and correlating daily beam output of QA Beamchecker PLUS. Materials and Methods: Linear accelerator (Truebeam 2.5) was used to measure 10 energies which are composed of photon beams(6, 10, 15 MV and 6, 10 MV-FFF) and electron beams(6, 9, 12, 16 and 20 MeV). A total of 80 cycles of data was obtained by measuring beam output measurement before treatment over five months period. The Pearson correlation coefficient was used to evaluate the consistency of the beam output between the MPC and the QA Beamchecker PLUS. In this study, if the Pearson correlation coefficient is; (1) 0.8 or higher, the correlation is very strong (2) between 0.6 and 0.79, the correlation is strong (3) between 0.4 and 0.59, the correlation is moderate (4) between 0.2 and 0.39, the correlation is weak (5) lower than 0.2, the correlation is very weak. Results: Output variations observed between MPC and QA Beamchecker PLUS were within 2 % for photons and electrons. The beam outputs variations of MPC were $0.29{\pm}0.26%$ and $0.30{\pm}0.26%$ for photon and electron beams, respectively. QA Beamchecker PLUS beam outputs were $0.31{\pm}0.24%$ and $0.33{\pm}0.24%$ for photon and electron beams, respectively. The Pearson correlation coefficient between MPC and QA Beamchecker PLUS indicated that photon beams were very strong at 15 MV, and strong at 6 MV, 10 MV, 6 MV-FFF and 10 MV-FFF. For electron beams, the Pearson correlation coefficient were strong at 16 MeV and 20 MeV, moderate at 9 MeV and 12 MeV, and very weak at 6 MeV. Conclusion: MPC showed significantly strong correlation with QA Beamchecker PLUS when testing with photon beams and high-energy electron beams in the evaluation of daily beam output, but the correlation when testing with low-energy electron beams (6 MeV) appeared to be low. However, MPC and QA Beamchecker PLUS are considered to be suitable for checking daily beam output, as they performed within 2 % of beam output consistency during the observation. MPC which can perform faster than the conventional daily beam output measurement tool, is considered to be an effective method for users.

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Prognostic Value of CD44 Variant exon 6 Expression in Non-Small Cell Lung Cancer: a Meta-analysis

  • Zhao, Shuang;He, Jin-Lan;Qiu, Zhi-Xin;Chen, Nian-Yong;Luo, Zhuang;Chen, Bo-Jiang;Li, Wei-Min
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.16
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    • pp.6761-6766
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    • 2014
  • Background: CD44v6 (CD44 variant exon 6) is the chief CD44 variant isoform regulating tumor invasion, progression, and metastasis. The prognostic value of CD44v6 expression in non small cell lung cancer (NSCLC) has been evaluated in many studies, but the results have remained controversial. Thus, we performed a meta-analysis of currently available studies to investigate the prognostic value of CD44v6 expression in NSCLC patients and the relationship between the expression of CD44v6 and clinicopathological features. Materials and Methods: Two independent reviewers searched the relevant literature in Pubmed, Medline and Embase from 1946 to January 2014. Overall survival (OS) and various clinicopathological features were collected from included studies. This meta-analysis was accomplished using STATA 12.0 and Revman 5.2 software. Pooled hazard ratios (HRs) with 95% confidence intervals (95%CIs) were calculated to estimate the effects. Results: A total of 921 NSCLC patients from ten studies met the inclusion criteria. The results showed that CD44v6 high expression was a prognostic factor for poor survival (HR=1.91, 95%CI=1.12-3.26, p<0.05). With respect to clinicopathological features, CD44v6 high expression was related to histopathologic type (squamous cell carcinoma versus adenocarcinoma: OR=2.72, 95%CI=1.38-5.38, p=0.004), and lymph node metastasis (OR=3.02, 95%CI=1.93-4.72, p<0.00001). Conclusions: Our results suggested CD44v6 high expression as a poor prognostic factor for NSCLC, and CD44v6 expression is associated with lymph node metastasis and histopathologic type. Therefore, CD44v6 expression can be used as a novel prognostic marker in NSCLC cases.

A Comparative Study on Virtual Try-on Systems using Body Measurement Input

  • Lim, Ho-Sun;Istook, Cynthia
    • The International Journal of Costume Culture
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    • v.13 no.2
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    • pp.118-129
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    • 2010
  • Digital technology introduced into the clothing and fashion industry is evolving to digital virtual fashions and consumer-centered mass-customized production systems. Today the application of such 3D virtual try-on systems is being expanded gradually in the clothing industry. This study purposed to make virtual avatars and virtual garments using OptiTex and V-stitcher virtual software and compared the appearance of the virtual garments put on the virtual avatars. For this, we created virtual avatars and virtual garments using body measurements obtained from jive subjects of top jive body shapes, respectively, using $[TC]^2$ body scanner. According to the results of comparing the outcomes of the two different virtual software systems, virtual avatar II of V-Stitcher tended to have a more round and lifted hip and the waist line at a higher position. In addition, the body curves and shapes of a virtual avatar affect the appearance of virtual garments. This study applied the same body measurements to virtual avatars and the same pattern to virtual garments, but when different kinds of virtual software were used, the virtual avatars and virtual garments showed different appearance and fit. This result may mean that when customers buy apparel products using different kinds of virtual try-on systems, their evaluation of appearance can vary depending on the virtual try-on system. Therefore, research needs to be made actively for the development and use of linkage programs that can reflect actual body measurements between virtual software systems and 3D body scanning systems.

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A Study of Security Vulnerability of Iriscode (홍채코드의 보안 취약성에 대한 연구)

  • Youn, Soung-Jo;Anusha, B.V.S;Kim, Gye-Young
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.10a
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    • pp.193-195
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    • 2018
  • 홍채코드는 홍채의 정보를 이진코드로 표현함으로써 홍채정보를 보호하는 방법이다. 이러한 방법은 현재 홍채인식 시스템에서 표준으로 채택된 기술이다. 본 논문에서는 1-D 가버 필터를 사용하여 홍채 코드로부터 역공학적 방법을 사용하여 홍채영상을 복원하고, 복원된 홍채 영상과 기존의 홍채영상의 인식 결과를 통해 홍채 인식에 대한 취약성을 연구한다.

Dash Box AI-based Pedestrian danger Notification System (블랙박스형 AI 기반의 보행자 위험 알림 시스템)

  • Hyun-Woo Kim;Ji-Seob Kim;Seong-Mo Yang;Kyu-Chan Kim;Chul-Woo Park;Joon-Ho Park
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2023.01a
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    • pp.239-240
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    • 2023
  • 교통사고는 차량 운전자의 부주의 및 보행자의 안전 불감증 등 여러 가지 이유로 다양한 형태의 교차로에서 사고가 발생한다. 이것을 개선하고자 본 논문에서는 보행자 위험 알림 시스템을 구현하였다. 이 시스템은 YOLO v4 tiny 알고리즘 사용해 약 8,000장의 보행자와 차량의 사진을 학습시켜 객체 인식의 정확도를 높이고 웹캠과 스피커를 사용하여 보행자에게 위험을 알릴 뿐만 아니라, 사고 발생 등의 경우에 대해서 블랙박스 역할을 할 수 있도록 구현하였다.

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Realtime Apple Quality Monitoring System Based on Deep Learning (딥러닝 기반의 사과 품질 실시간 모니터링 시스템)

  • Chan-seok Bae;Woo-hyuk Jung;Geun-jae Lee;Gyu-ryang Hong;Ji-hyun Kwon;Hongseok Yoo
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2024.01a
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    • pp.297-298
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    • 2024
  • 펜데믹, 전쟁 등을 포함한 국제 정세 변화에 따른 물류대란, 원자재가격 상승 및 환율 급등으로 인해 2023년 기준 대한민국의 물가는 크게 오르고 있는 추세이다. 물가 상승은 사업장의 인건비 부담 증가로 이어지고 있고 특히 노동 집약 산업인 농업 분야에서의 인건비 부담 문제는 더욱 심각한 실정이다. 외국인 근로자 고용이 대안이 될 수 있지만 인건비 절감 효과는 미미하기에 농업계 관계자들은 자동화 시스템 도입에 관심이 집중되고 있다. 따라서, 본 논문에서는 사과 분류 작업 자동화 체계의 핵심 요소에 해당하는 사과 품질 실시간 모니터링 시스템을 제안한다. 제안한 방식에서는 딥러닝 기반의 영상 분석 기법 및 무게 센서 데이터 분석을 통해 사과의 품질에 따른 등급 책정을 자동화 한다.

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