• Title/Summary/Keyword: Parameter Analysis

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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.

A Study on Efficient AI Model Drift Detection Methods for MLOps (MLOps를 위한 효율적인 AI 모델 드리프트 탐지방안 연구)

  • Ye-eun Lee;Tae-jin Lee
    • Journal of Internet Computing and Services
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    • v.24 no.5
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    • pp.17-27
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    • 2023
  • Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

Study on the Free Roll Decay and Resistance Performances of Fishing Vessels by Varying Appendages (어선 부가물 별 자유 횡 동요 감쇠 및 저항성능에 관한 연구)

  • Mijin Yoon;Janghoon Seo;Dong-Woo Park;Chanjae Lee;Intae Kim;Dong Nam
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.6
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    • pp.688-696
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    • 2023
  • In the present study, free roll decay and resistance performances of fishing vessels were evaluated with the combinations and variations of in the parameters of appendages which are attached to improve motion performance of fishing vessels. Computational Ffluid Ddynamics was used to perform free roll decay and resistance analysis. The roll period and decay coefficient were derived by the variations in the combination and dimensions of the primary appendages of the bilge keel and the under keel. It was observed thatThe variations of in the length of the under keel did not significantly impact to the roll damping coefficient. Conversely, for the bilge keel, an increase in the length and angle resulted in an increase in the roll damping coefficient. Comparison of resistance performance was additionally assessed among the selected hulls with the appendages and bare hull. The resistance of the hull with the appendages was higher than that of the bare hull due owing to the changes of in the pressure on the surface of the hull and trim angle. Throughout the present study, the impact of appendage parameter and arrangement on the free roll decay and resistance performance of fishing vessels were was assessed,. which This will be beneficial for the application of appendages to fishing vessels.

Two-Dimensional Shear Wave Elastography Predicts Liver Fibrosis in Jaundiced Infants with Suspected Biliary Atresia: A Prospective Study

  • Huadong Chen;Luyao Zhou;Bing Liao;Qinghua Cao;Hong Jiang;Wenying Zhou;Guotao Wang;Xiaoyan Xie
    • Korean Journal of Radiology
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    • v.22 no.6
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    • pp.959-969
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    • 2021
  • Objective: This study aimed to evaluate the role of preoperative two-dimensional (2D) shear wave elastography (SWE) in assessing the stages of liver fibrosis in patients with suspected biliary atresia (BA) and compared its diagnostic performance with those of serum fibrosis biomarkers. Materials and Methods: This study was approved by the ethical committee, and written informed parental consent was obtained. Two hundred and sixteen patients were prospectively enrolled between January 2012 and October 2018. The 2D SWE measurements of 69 patients have been previously reported. 2D SWE measurements, serum fibrosis biomarkers, including fibrotic markers and biochemical test results, and liver histology parameters were obtained. 2D SWE values, serum biomarkers including, aspartate aminotransferase to platelet ratio index (APRi), and other serum fibrotic markers were correlated with the stages of liver fibrosis by METAVIR. Receiver operating characteristic (ROC) curves and area under the ROC (AUROC) curve analyses were used. Results: The correlation coefficient of 2D SWE value in correlation with the stages of liver fibrosis was 0.789 (p < 0.001). The cut-off values of 2D SWE were calculated as 9.1 kPa for F1, 11.6 kPa for F2, 13.0 kPa for F3, and 15.7 kPa for F4. The AUROCs of 2D SWE in the determination of the stages of liver fibrosis ranged from 0.869 to 0.941. The sensitivity and negative predictive value of 2D SWE in the diagnosis of ≥ F3 was 93.4% and 96.0%, respectively. The diagnostic performance of 2D SWE was superior to that of APRi and other serum fibrotic markers in predicting severe fibrosis and cirrhosis (all p < 0.005) and other serum biomarkers. Multivariate analysis showed that the 2D SWE value was the only statistically significant parameter for predicting liver fibrosis. Conclusion: 2D SWE is a more effective non-invasive tool for predicting the stage of liver fibrosis in patients with suspected BA, compared with serum fibrosis biomarkers.

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.

Sintering behavior and electrical properties of transition metal (Ni, Co, Mn) based spinel oxides for temperature sensor applications (복합전이금속(Ni, Co, Mn) 기반 스피넬계 산화물의 소결 거동 및 온도센서 특성 연구)

  • Younghee So;Eunseo Lee;Jinyoung Lee;Sungwook Mhin;Bin Lee;Hyung Tae Kim
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.34 no.2
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    • pp.73-77
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    • 2024
  • The spinel-type oxide (Nix, Mny, Co3-x-y)O4 (NMC) is widely utilized as a material for temperature sensors with a negative temperature coefficient (NTC), finding applications across various industries including electric vehicle battery management systems. Typically, NMC is manufactured using solid-state reaction methods employing powders of Ni, Mn, and Co compounds, with the densification process through sintering recognized as a crucial factor determining the electrical properties of the temperature sensor material. In this study, NMC pellets were synthesized via solid-state reaction and their crystallographic and microstructural characteristics were investigated. Also, the activation energy for densification behavior during the sintering process was determined. According to the analysis results, the room temperature resistance of the NMC pellets was measured at 10.03 Kohm, with the sensitivity parameter, B-value, recorded at 3601.8 K, indicating their potential applicability as temperature sensors across various industrial fields. Furthermore, the activation energy for densification was found to be 273.3 ± 0.4 kJ/mol, providing valuable insights into the thermodynamic aspects of the sintering process of the NMC.

Establishment of a quality index of surfactin production during cheonggukjang fermentation (청국장 발효 중 surfactin 생산량 품질지표 설정)

  • Chang-Geun Ji;Jeong-Hwa Hong;Sang-Hyun Lee
    • Food Science and Preservation
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    • v.30 no.2
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    • pp.311-320
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    • 2023
  • Surfactin, one of the most powerful biosurfactants, can be widely applied in agriculture, food, and pharmaceutics. The purpose of the present study was to establish suitable indicators for a rapid detection method that can confirm the surfactin productivity of cheonggukjang. In the present study, changes in the total number of bacteria were quantified according to the fermentation time of chenggukjang. Furthermore, physicochemical factors, such as pH, color value, surface tension, refractive index, absorbance, and protein contents, were assessed in chenggukjang viscous substances, and a correlation analysis between the physicochemical factors and surfactin contents was performed. We found that the protein contents gradually increased up to 48 h (4.21±0.11 mg/mL) without a change in the surface tension. Furthermore, the refractive index, absorbance at 280 nm, and color value were significantly increased as the fermentation time increased; however, there were no statistically significant differences after 36 h of fermentation. Interestingly, this result exhibited a tendency similar to the surfactin content according to fermentation time. These findings suggest that surfactin can be used as a suitable quality indicator and may provide an experimental basis for the fermented food industry.

Process Optimization for the Industrialization of Transparent Conducting Film (투명 전도막의 산업화를 위한 공정 최적화)

  • Nam, Hyeon-bin;Choi, Yo-seok;Kim, In-su;Kim, Gyung-jun;Park, Seong-su;Lee, Ja Hyun
    • Industry Promotion Research
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    • v.9 no.1
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    • pp.21-29
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    • 2024
  • In the rapidly advancing information society, electronic devices, including smartphones and tablets, are increasingly digitized and equipped with high-performance features such as flexible displays. This study focused on optimizing the manufacturing process for Transparent Conductive Films (TCF) by using the cost-effective conductive polymer PEDOT and transparent substrate PET as alternatives to expensive materials in flexible display technology. The variables considered are production speed (m/min), coating maximum temperature (℃), and PEDOT supply speed (rpm), with surface resistivity (Ω/□) as the response parameter, using Response Surface Methodology (RSM). Optimization results indicate the ideal conditions for production: a speed of 22.16 m/min, coating temperature of 125.28℃, and PEDOT supply at 522.79 rpm. Statistical analysis validates the reliability of the results (F value: 18.37, P-value: < 0.0001, R2: 0.9430). Under optimal conditions, the predicted surface resistivity is 145.75 Ω/□, closely aligned with the experimental value of 142.97 Ω/□. Applying these findings to mass production processes is expected to enhance production yields and decrease defect rates compared to current practices. This research provides valuable insights for the advancement of flexible display manufacturing.

Development and Validation of a Model Using Radiomics Features from an Apparent Diffusion Coefficient Map to Diagnose Local Tumor Recurrence in Patients Treated for Head and Neck Squamous Cell Carcinoma

  • Minjae Kim;Jeong Hyun Lee;Leehi Joo;Boryeong Jeong;Seonok Kim;Sungwon Ham;Jihye Yun;NamKug Kim;Sae Rom Chung;Young Jun Choi;Jung Hwan Baek;Ji Ye Lee;Ji-hoon Kim
    • Korean Journal of Radiology
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    • v.23 no.11
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    • pp.1078-1088
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    • 2022
  • Objective: To develop and validate a model using radiomics features from apparent diffusion coefficient (ADC) map to diagnose local tumor recurrence in head and neck squamous cell carcinoma (HNSCC). Materials and Methods: This retrospective study included 285 patients (mean age ± standard deviation, 62 ± 12 years; 220 male, 77.2%), including 215 for training (n = 161) and internal validation (n = 54) and 70 others for external validation, with newly developed contrast-enhancing lesions at the primary cancer site on the surveillance MRI following definitive treatment of HNSCC between January 2014 and October 2019. Of the 215 and 70 patients, 127 and 34, respectively, had local tumor recurrence. Radiomics models using radiomics scores were created separately for T2-weighted imaging (T2WI), contrast-enhanced T1-weighted imaging (CE-T1WI), and ADC maps using non-zero coefficients from the least absolute shrinkage and selection operator in the training set. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of each radiomics score and known clinical parameter (age, sex, and clinical stage) in the internal and external validation sets. Results: Five radiomics features from T2WI, six from CE-T1WI, and nine from ADC maps were selected and used to develop the respective radiomics models. The area under ROC curve (AUROC) of ADC radiomics score was 0.76 (95% confidence interval [CI], 0.62-0.89) and 0.77 (95% CI, 0.65-0.88) in the internal and external validation sets, respectively. These were significantly higher than the AUROC values of T2WI (0.53 [95% CI, 0.40-0.67], p = 0.006), CE-T1WI (0.53 [95% CI, 0.40-0.67], p = 0.012), and clinical parameters (0.53 [95% CI, 0.39-0.67], p = 0.021) in the external validation set. Conclusion: The radiomics model using ADC maps exhibited higher diagnostic performance than those of the radiomics models using T2WI or CE-T1WI and clinical parameters in the diagnosis of local tumor recurrence in HNSCC following definitive treatment.

Genetic diversity and population structure in five Inner Mongolia cashmere goat populations using whole-genome genotyping

  • Tao Zhang;Zhiying Wang;Yaming Li;Bohan Zhou;Yifan Liu;Jinquan Li;Ruijun Wang;Qi Lv;Chun Li;Yanjun Zhang;Rui Su
    • Animal Bioscience
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    • v.37 no.7
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    • pp.1168-1176
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    • 2024
  • Objective: As a charismatic species, cashmere goats have rich genetic resources. In the Inner Mongolia Autonomous Region, there are three cashmere goat varieties named and approved by the state. These goats are renowned for their high cashmere production and superior cashmere quality. Therefore, it is vitally important to protect their genetic resources as they will serve as breeding material for developing new varieties in the future. Methods: Three breeds including Inner Mongolia cashmere goats (IMCG), Hanshan White cashmere goats (HS), and Ujimqin white cashmere goats (WZMQ) were studied. IMCG were of three types: Aerbas (AEBS), Erlangshan (ELS), and Alashan (ALS). Nine DNA samples were collected for each population, and they were genomically re-sequenced to obtain high-depth data. The genetic diversity parameters of each population were estimated to determine selection intensity. Principal component analysis, phylogenetic tree construction and genetic differentiation parameter estimation were performed to determine genetic relationships among populations. Results: Samples from the 45 individuals from the five goat populations were sequenced, and 30,601,671 raw single nucleotide polymorphisms (SNPs) obtained. Then, variant calling was conducted using the reference genome, and 17,214,526 SNPs were retained after quality control. Individual sequencing depth of individuals ranged from 21.13× to 46.18×, with an average of 28.5×. In the AEBS, locus polymorphism (79.28) and expected heterozygosity (0.2554) proportions were the lowest, and the homologous consistency ratio (0.1021) and average inbreeding coefficient (0.1348) were the highest, indicating that this population had strong selection intensity. Conversely, ALS and WZMQ selection intensity was relatively low. Genetic distance between HS and the other four populations was relatively high, and genetic exchange existed among the other four populations. Conclusion: The Inner Mongolia cashmere goat (AEBS type) population has a relatively high selection intensity and a low genetic diversity. The IMCG (ALS type) and WZMQ populations had relatively low selection intensity and high genetic diversity. The genetic distance between HS and the other four populations was relatively high, with a moderate degree of differentiation. Overall, these genetic variations provide a solid foundation for resource identification of Inner Mongolia Autonomous Region cashmere goats in the future.