• Title/Summary/Keyword: Performance parameter and evaluation

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Application of peak based-Bayesian statistical method for isotope identification and categorization of depleted, natural and low enriched uranium measured by LaBr3:Ce scintillation detector

  • Haluk Yucel;Selin Saatci Tuzuner;Charles Massey
    • Nuclear Engineering and Technology
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    • v.55 no.10
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    • pp.3913-3923
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    • 2023
  • Todays, medium energy resolution detectors are preferably used in radioisotope identification devices(RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(241Am, 57Co, 137Cs, 54Mn, 60Co), and then applied to five standard nuclear materials(0.32-4.51% at.235U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5-74.4% for 238U and 4.7-10.5% for 235U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify 235U and 238U isotopes in LEU or natural U-Th samples if a medium energy resolution detector is was in the measurements.

Evaluation of Static and Fatigue Performances of Decks Reinforced with GFRP Rebar for Reinfocement Ratio (GFRP 보강근으로 보강된 바닥판의 보강비에 따른 정적 및 피로성능 평가)

  • You, Young-Jun;Park, Young-Hwan;Choi, Ji-Hun;Kim, Jang-Ho Jay
    • Journal of the Korea Concrete Institute
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    • v.26 no.4
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    • pp.491-497
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    • 2014
  • The corrosion of steel reinforcement in reinforced concrete bridge decks significantly affects the degradation of the capacity. Due to the advantageous characteristics such as high tensile strength and non-corrosive property, fiber reinforced polymer (FRP) has been gathering much interest from designers and engineers for possible usage as a alternative reinforcement for a steel reinforcing bar. However, its application has not been widespread, because there data for short- and long-term performance data of FRP reinforced concrete members are insufficient. In this paper, seven full-scale decks with dimensions of $4000{\times}3000{\times}240mm$ were prepared and tested to failure in the laboratory. The test parameter was the bottom reinforcement ratio in transverse direction. The decks were subjected to various levels of concentrated cyclic load with a contact area of $577{\times}231mm$ to simulate the vehicle loading of DB-24 truck wheel loads acting on the center span of the deck. It was observed that the glass FRP (GFRP) reinforced deck on a restraint girder is strongly effected to the level of the applied load rather than the bottom reinforcement ratio. The study results showed that the maximum load less than 58% of the maximum static load can be applied to the deck to resist a fatigue load of 2 million cycles. The fatigue life of the GFRP decks from this study showed the lower and higher fatigue performance than that of ordinary steel and CFRP rebar reinforced concrete deck. respectively.

Fuzzy Control for the Obstacle Avoidance of Remote Control Mobile Robot (원격제어 이동로봇의 장애물 회피를 위한 퍼지 제어)

  • Yeo, Hee-Joo;Sung, Mun-Hyun
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.1
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    • pp.47-54
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    • 2011
  • The remote control mobile robot is the robot accomplishing a task according to the orders giving by a user through departed communication system using a joystick. Basically, to supply a lot of information, as this type of robot uses visual information, the user can check the transmitted information by eyes and give orders to the robot. But the weak point of this type of robot is that it has a possibility to come into a collision with an obstacle not be seen to the user because of the communication delay occurring in a communication system and dead zone happening in visual information. To solve the problem, in this paper, we try to suggest a system applying a fuzzy control system to the robot to avoid collision with an obstacle by an immediate order of the user. The fuzzy control system has better performance than any other existing control methods in the change of noise and parameter. And it is more efficient than any other since it solves easy the complexity of the system analysis occurring because of the nonlinear feature of the mobile robot system. In this paper, we made experiments how the mobile robot controlled by the fuzzy control system avoids an obstacle, tracks the path and avoids the obstacle in the path, to prove the performance and to check the evaluation and the application possibility of the fuzzy control system.

Accelerated Life Prediction on Tensile Strength of Oil Resistance HNBR (내유성 HNBR 고무의 인장강도 성능에 대한 가속수명예측)

  • Kim, Kyung Pil;Lee, Yong Seok;Yeo, Yong Heon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.11
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    • pp.233-238
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    • 2020
  • Although the interest in NBR has been increasing due to the recent developments of the aerospace sector, there are few reports on HNBR's aeronautical oil, particularly evaluations of the accelerated life of harsh factors. In this study, the tensile strength was adopted as a performance evaluation factor to evaluate the accelerated life of HNBR used in the aviation field. The accelerated stress factor affecting the performance-aging characteristics was defined as temperature. The acceleration stress factor was determined to be temperature, and the result of measuring the tensile strength change over time. The sample for the acceleration condition was taken out of the oven for a certain period and left at room temperature for 24 hours. The dumbbell type 3 specimens were manufactured according to the standard specified in KS M 6518 and were measured the tensile strength, a factor in accelerated life evaluations. The activation energy was 0.895, and the shape parameter was 1.152 using the Arrhenius model. The characteristic life obtained from the tensile strength of the HNBR specimen immersed in aviation oil at 20℃ was 272,256 hours; the average life was 258,965 hours, and the B10 life was 38,624 hours.

Design and Performance Evaluation of Offset Time Decision Algorithm for Guaranteeing the QoS in Optical Burst Switching Networks (광 버스트 스위칭 망에서 QoS 보장을 위한 Offset 시간 결정 알고리즘 설계 및 성능 평가)

  • So, Won-Ho;Cha, Yun-Ho;Roh, Sun-Sik;Kim, Young-Chon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.1C
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    • pp.1-10
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    • 2002
  • With the explosive growth of the number of Internet users and Internet-related services, the research on construction of broadband Optical Internet by using WDM technologies is actively is actively progressed. In this paper, we design the offset time decision (OTD) algorithm for supporting the QoS in optical networks based on optical burst switching (OBS), which is the new switching paradigm, and evaluate the performance of it. The proposed algorithm determines a reasonable offset time considering traffic load of network and the number of wavelengths to guarantee the burst loss rate (BLR) of high priority Internet traffic as a QoS parameter. In order to design the proposed OTD algorithm, firstly we make the new burst loss formula, which includes the effect of offset time. The decision of offset time corresponding to the requested BLR, however, should use the reverse formula of proposed one, thus we are not able to use it without any changes. In this paper, we define the heuristic loss formula (HLF) that can be changed into reversed formula by using the proposed formula and proportional equation considering its characteristics. Finally we show the OTD algorithm to decide the offset time by using HLF. We show that the requested BLR is guaranteed under various traffic load with the determinded offset time by using the proposed OTD algorithm.

Study on Enhancement of TRANSGUIDE Outlier Filter Method under Unstable Traffic Flow for Reliable Travel Time Estimation -Focus on Dedicated Short Range Communications Probes- (불안정한 교통류상태에서 TRANSGUIDE 이상치 제거 기법 개선을 통한 교통 통행시간 예측 향상 연구 -DSRC 수집정보를 중심으로-)

  • Khedher, Moataz Bellah Ben;Yun, Duk Geun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.3
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    • pp.249-257
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    • 2017
  • Filtering the data for travel time records obtained from DSRC probes is essential for a better estimation of the link travel time. This study addresses the major deficiency in the performance of TRANSGUIDE in removing anomalous data. This algorithm is unable to handle unstable traffic flow conditions for certain time intervals, where fluctuations are observed. In this regard, this study proposes an algorithm that is capable of overcoming the weaknesses of TRANSGUIDE. If TRANSGUIDE fails to validate sufficient number of observations inside one time interval, another process specifies a new validity range based on the median absolute deviation (MAD), a common statistical approach. The proposed algorithm suggests the parameters, ${\alpha}$ and ${\beta}$, to consider the maximum allowed outlier within a one-time interval to respond to certain traffic flow conditions. The parameter estimation relies on historical data because it needs to be updated frequently. To test the proposed algorithm, the DSRC probe travel time data were collected from a multilane highway road section. Calibration of the model was performed by statistical data analysis through using cumulative relative frequency. The qualitative evaluation shows satisfactory performance. The proposed model overcomes the deficiency associated with the rapid change in travel time.

Calibration and Validation of the Hargreaves Equation for the Reference Evapotranspiration Estimation in Gyeonggi Bay Watershed (경기만 유역의 기준 증발산량 산정을 위한 Hargreaves 공식의 보정 및 검정)

  • Lee, Khil-Ha;Cho, Hong-Yeon;Oh, Nam-Sun
    • Journal of Korea Water Resources Association
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    • v.41 no.4
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    • pp.413-422
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    • 2008
  • It is essential to locally adjust the Hargreaves parameter for estimating reference evapotranspiration with short data as a substitute of Penman-Monteith equation. In this study, evaluation of daily-based reference evapotranspiration is computed with Hargreaves equation. in Gyeonggi bay area including Ganghwa, Incheon, Suwon, Seosan, and Cheonan station for the time period of 1997-2004. Hargreaves coefficient is adjusted to give the best fit with Penman-Monteith evapotranspiration, being regarded as a reference. Then, the preferred parameters are validated for the same stations for the time period of 2005-2006. The optimization-based correction in calibration for 1997-2004 shows improved performance of the Hargreaves equation, giving 0.68-0.77 to 0.92-0.98 in Nash-Sutcliffe coefficient of efficiency (NSC) and 14.63-23.30 to 5.23-11.75 in RMSE. The validation for 2005-2006 shows improved performance of the Hargreaves equation, giving 0.43-0.85 to 0.93-0.97 in NSC and 14.43-26.81 to 6.48-9.09 in RMSE.

Generating Sponsored Blog Texts through Fine-Tuning of Korean LLMs (한국어 언어모델 파인튜닝을 통한 협찬 블로그 텍스트 생성)

  • Bo Kyeong Kim;Jae Yeon Byun;Kyung-Ae Cha
    • Journal of Korea Society of Industrial Information Systems
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    • v.29 no.3
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    • pp.1-12
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    • 2024
  • In this paper, we fine-tuned KoAlpaca, a large-scale Korean language model, and implemented a blog text generation system utilizing it. Blogs on social media platforms are widely used as a marketing tool for businesses. We constructed training data of positive reviews through emotion analysis and refinement of collected sponsored blog texts and applied QLoRA for the lightweight training of KoAlpaca. QLoRA is a fine-tuning approach that significantly reduces the memory usage required for training, with experiments in an environment with a parameter size of 12.8B showing up to a 58.8% decrease in memory usage compared to LoRA. To evaluate the generative performance of the fine-tuned model, texts generated from 100 inputs not included in the training data produced on average more than twice the number of words compared to the pre-trained model, with texts of positive sentiment also appearing more than twice as often. In a survey conducted for qualitative evaluation of generative performance, responses indicated that the fine-tuned model's generated outputs were more relevant to the given topics on average 77.5% of the time. This demonstrates that the positive review generation language model for sponsored content in this paper can enhance the efficiency of time management for content creation and ensure consistent marketing effects. However, to reduce the generation of content that deviates from the category of positive reviews due to elements of the pre-trained model, we plan to proceed with fine-tuning using the augmentation of training data.

Modified AWSSDR method for frequency-dependent reverberation time estimation (주파수 대역별 잔향시간 추정을 위한 변형된 AWSSDR 방식)

  • Min Sik Kim;Hyung Soon Kim
    • Phonetics and Speech Sciences
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    • v.15 no.4
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    • pp.91-100
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    • 2023
  • Reverberation time (T60) is a typical acoustic parameter that provides information about reverberation. Since the impacts of reverberation vary depending on the frequency bands even in the same space, frequency-dependent (FD) T60, which offers detailed insights into the acoustic environments, can be useful. However, most conventional blind T60 estimation methods, which estimate the T60 from speech signals, focus on fullband T60 estimation, and a few blind FDT60 estimation methods commonly show poor performance in the low-frequency bands. This paper introduces a modified approach based on Attentive pooling based Weighted Sum of Spectral Decay Rates (AWSSDR), previously proposed for blind T60 estimation, by extending its target from fullband T60 to FDT60. The experimental results show that the proposed method outperforms conventional blind FDT60 estimation methods on the acoustic characterization of environments (ACE) challenge evaluation dataset. Notably, it consistently exhibits excellent estimation performance in all frequency bands. This demonstrates that the mechanism of the AWSSDR method is valuable for blind FDT60 estimation because it reflects the FD variations in the impact of reverberation, aggregating information about FDT60 from the speech signal by processing the spectral decay rates associated with the physical properties of reverberation in each frequency band.

Evaluation of Robustness of Deep Learning-Based Object Detection Models for Invertebrate Grazers Detection and Monitoring (조식동물 탐지 및 모니터링을 위한 딥러닝 기반 객체 탐지 모델의 강인성 평가)

  • Suho Bak;Heung-Min Kim;Tak-Young Kim;Jae-Young Lim;Seon Woong Jang
    • Korean Journal of Remote Sensing
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    • v.39 no.3
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    • pp.297-309
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    • 2023
  • The degradation of coastal ecosystems and fishery environments is accelerating due to the recent phenomenon of invertebrate grazers. To effectively monitor and implement preventive measures for this phenomenon, the adoption of remote sensing-based monitoring technology for extensive maritime areas is imperative. In this study, we compared and analyzed the robustness of deep learning-based object detection modelsfor detecting and monitoring invertebrate grazersfrom underwater videos. We constructed an image dataset targeting seven representative species of invertebrate grazers in the coastal waters of South Korea and trained deep learning-based object detection models, You Only Look Once (YOLO)v7 and YOLOv8, using this dataset. We evaluated the detection performance and speed of a total of six YOLO models (YOLOv7, YOLOv7x, YOLOv8s, YOLOv8m, YOLOv8l, YOLOv8x) and conducted robustness evaluations considering various image distortions that may occur during underwater filming. The evaluation results showed that the YOLOv8 models demonstrated higher detection speed (approximately 71 to 141 FPS [frame per second]) compared to the number of parameters. In terms of detection performance, the YOLOv8 models (mean average precision [mAP] 0.848 to 0.882) exhibited better performance than the YOLOv7 models (mAP 0.847 to 0.850). Regarding model robustness, it was observed that the YOLOv7 models were more robust to shape distortions, while the YOLOv8 models were relatively more robust to color distortions. Therefore, considering that shape distortions occur less frequently in underwater video recordings while color distortions are more frequent in coastal areas, it can be concluded that utilizing YOLOv8 models is a valid choice for invertebrate grazer detection and monitoring in coastal waters.