• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.570-590
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• 2024

Breast cancer ranks among the most prevalent forms of malignancy and foremost cause of death by cancer worldwide. It is not preventable. Early and precise detection is the only remedy for lowering the rate of mortality and improving the probability of survival for victims. In contrast to present procedures, thermography aids in the early diagnosis of cancer and thereby saves lives. But the accuracy experiences detrimental impact by low sensitivity for small and deep tumours and the subjectivity by physicians in interpreting the images. Employing deep learning approaches for cancer detection can enhance the efficacy. This study explored the utilization of thermography in early identification of breast cancer with the use of a publicly released dataset known as the DMR-IR dataset. For this purpose, we employed a novel approach that entails the utilization of a pre-trained MobileNetV2 model and fine tuning it through transfer learning techniques. We created three models using MobileNetV2: one was a baseline transfer learning model with weights trained from ImageNet dataset, the second was a fine-tuned model with an adaptive learning rate, and the third utilized early stopping with callbacks during fine-tuning. The results showed that the proposed methods achieved average accuracy rates of 85.15%, 95.19%, and 98.69%, respectively, with various performance indicators such as precision, sensitivity and specificity also being investigated.

• The Journal of Internal Korean Medicine
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• v.45 no.2
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• pp.159-166
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• 2024

Objective: The purpose of this case study is to report the effectiveness of the Korean medicine Beewha-eum as a treatment for functional dyspepsia (FD). Methods: A patient diagnosed with a spleen-stomach deficiency-cold pattern in Korean medicine was treated with herbal medicines, including Beewha-eum. Symptom severity was assessed using the degree of self-reported dyspepsia (%), self-reported energy level, amount of food intake (%), total parenteral nutrition rate (cc/hour), body weight (kg), Nepean dyspepsia index (NDI-K), functional dyspepsia-related quality of life questionnaire (FD-QoL), and short form 36-item health survey (SF-36) score. Results: After treatment, the symptom severity of self-reported dyspepsia decreased from 100% to 10 to 15%, and the self-reported energy level increased from 20 to 80. The amount of food intake increased from 5% to 100%, and the total parenteral nutrition rate started from 60 cc/hour end in week 5. Body weight increased from 53.1 kg to 62 kg. The NDI-K score decreased from 105 to 31. The FD-QoL score increased from 19 to 68. The SF-36 score also increased from 102 to 116. Conclusion: The results suggest that the Korean medicine Beewha-eum could be an effective option for treating FD.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.2
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• pp.119-126
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• 2024

This study aims to evaluate the feasibility of an early warning system for college dropout by machine learning the main patterns that affect college student dropout and to suggest ways to implement a system that can actively prevent it. For this purpose, a performance comparison experiment was conducted using five types of machine learning-based algorithms using data from the Korean Educational Longitudinal Study, 2005, conducted by the Korea Educational Development Institute. As a result of the experiment, the identification accuracy rate of students with the intention to drop out was up to 94.0% when using Random Forest, and the recall rate of students with the intention of dropping out was up to 77.0% when using Logistic Regression. It was measured. Lastly, based on the highest prediction model, we will provide counseling and management to students who are likely to drop out, and in particular, we will apply factors showing high importance by characteristic to the counseling method model. This study seeks to implement a model using IT technology to solve the career problems faced by college students, as dropout causes great costs to universities and individuals.

• Journal of radiological science and technology
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• v.47 no.4
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• pp.287-294
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• 2024

Radiation oncology departments are at high risk for potential radiation safety incidents. This study aimed to identify risk factors for these incidents using the P-mSHEL (Patient, Management, Software, Hardware, Environment, and Liveware) model and to evaluate potential accident types through Failure Mode and Effects Analysis (FMEA). FMEA identified seven accident types with high Risk Priority Number (RPN). A total of 56 detailed risk factors were classified using the P-mSHEL model, and measures to prevent radiation safety incidents were implemented. The effect of these preventive measures on workers' safety perception was confirmed through two indicators (FMEA and safety perception). After implementing the preventive measures, the FMEA analysis showed that the highest reduction in RPN was for A-6 (radiation exposure while other patients/guardians are present) with a reduction rate of 33.3%, followed by B-3 (radiation exposure while staff are present) with a reduction rate of 33.3%. Overall safety perception significantly improved after the preventive measures (4.17±0.35) compared to before (2.76±0.33) (p<0.05), with notable increases in both employee safety culture (3.93±0.51) and patient safety culture (3.73±0.62) (p<0.05). This study identified risk factors in radiation oncology departments. Continuous management, maintenance, and fostering a strong safety culture are crucial for preventing incidents. Regular problem identification and collaboration with relevant departments are essential for maintaining safety standards.

• Microbiology and Biotechnology Letters
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• v.52 no.2
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• pp.141-151
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• 2024

Isochrysis sp. is a sea microalga that has become a species of interest because of the extreme lipid content and rapid growth rate of this organism indicating its potential for efficient biofuel production. Using genome sequencing/genome-scale modeling for the prediction of Isochrysis sp. metabolic utilities there is high scope for the identification of essential pathways for the extraction of byproducts of interest at a higher rate. In our work, we design and present iIsochr964, a genome-scale metabolic model of Isochrysis sp. including 4315 reactions, 934 genes, and 1879 metabolites, which are distributed among fourteen compartments. For model validation, experimental culture, and isolation of Isochrysis sp. were performed and biomass values were used for validation of the genome-scale model. OptFlux was instrumental in uncovering several novel metabolites that influence the organism's metabolism by increasing the flux of interacting metabolites, such as Malonyl-CoA, EPA, Protein and others. iIsochr964 provides a compelling resource of metabolic understanding to revolutionize its industrial applications, thereby fostering sustainable development and allowing estimations and simulations of the organism metabolism under varying physiological, chemical, and genetic conditions. It is also useful in principle to provide a systemic view of Isochrysis sp. metabolism, efficiently guiding research and granting context to omics data.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.6
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• pp.546-552
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• 2007

Purpose: In the breast cancer patient, lymphatic mapping and sentinel lymph node biopsy are the most important procedure for axillary lymph node staging. We aimed to compare the three radiocolloids [$^{99m}Tc$-antimony trisulfide colloid (ASC), $^{99m}Tc$-tin colloid (TC), and $^{99m}Tc$-human serum albumin (HSA)] for sentinel lymph node mapping. Subjects and Methods: Totally, 397 patients with clinically N0 stage were enrolled. $^{99m}Tc$-ASC was injected in 202 out of 397 patients, $^{99m}Tc$-TC was injected in 120 patients, and $^{99m}Tc$-HSA was injected in the remaining 75 patients. The sentinel lymph nodes were localized by lymphoscintigraphy and selected using intraoperative gamma probe. All sentinel lymph nodes were investigated by intraoperative pathologic consultation. The axillary lymph nodes which were harvested by the lymph node dissection were also investigated. Results: The patients of each group showed similar clinical characteristics. There were no significant differences (p>0.05) in the identification rate of sentinel lymph nodes (IR), false negative rate (FNR), and negative predictive value (NPV). The axillary lymphadenectomy revealed axillary lymph node metastases in those three groups (ASC-33.2%, TC-31.7%, HSA-22.7%). The IR, FNR, and NPV were not significantly different among those groups. Conclusion: Those three $^{99m}Tc$-labeled radiocolloids showed equivalent results in sentinel lymph node mapping of breast cancer.

• Corrosion Science and Technology
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• v.4 no.4
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• pp.147-154
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• 2005

The creep resistance of geogrids is one of the most significant long-term safety characteristics used as the reinforcement in slopes and embankments. The failure of geogrids is defined as creep strain greater than 10%. In this study, the accelerated creep tests were applied to polyester geogrids at various loading levels of 30, 50% of the yield strengths and temperatures using newly designed test equipment. Also, the new test equipment permitted the creep testing at or above glass transition temperature($T_g$) of 75, 80, $85^{\circ}C$. The time-dependent creep behaviors were observed at various temperatures and loading levels. And then the creep curves were shifted and superposed in the time axis by applying time-temperature supposition principles. The shifting factors(AFs) were obtained using WLF equation. In predicting the lifetimes of geogrids, the underlying distribution for failure times were determined based on identification of the failure mechanism. The results confirmed that the failure distribution of geogrids followed Weibull distribution with increasing failure rate and the lifetimes of geogrids were close to 100 years which was required service life in the field with 1.75 of reduction factor of safety. Using the newly designed equipment, the creep test of geogrids was found to be highly accelerated. Furthermore, the time-temperature superposition with the newly designed test equipment was shown to be effective in predicting the lifetimes of geogrids with shorter test times and can be applied to the other geosynthetics.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.447-450
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• 2007

Positioning technology for moving object is an important and essential component of ubiquitous. Also RFID(Radio Frequency IDentification) is a core technology of ubiquitous wireless communication. In this study we adapted kalman-filter theory to RFID-based Positioning System in order to trace a time-variant moving object and verify the positioning accuracy using RMSE (Roong technology for moving object is an important and essential component of ubiquitous Mean Square Error). The purpose of this study is to verify an effect of kalman-filter on the positioning accuracy and to analyze what does each design factor have an effect on the positioning accuracy by means of simulations and to suggest a standard of optimal design factor of a RFID-based Positioning System. From the results of simulations, Kalman-filer improved the positioning accuracy remarkably; the detection range of RFID tag is not a determining factor. The smaller standard deviation of detection range improves the positioning accuracy. However it accompanies a smaller fluctuation of the positioning accuracy. The larger detection rate of RFID tag yields the smaller fluctuation in the positioning accuracy and has more stable system and improves the positioning accuracy;

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.544-553
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• 2013

In this paper, we propose the pattern classifier of Radial Basis Function Neural Networks(RBFNNs) for diagnosis of 3-phase partial discharge. Conventional methods map the partial discharge/noise data on 3-PARD map, and decide whether the partial discharge occurs or not from 3-phase or neutral point. However, it is decided based on his own subjective knowledge of skilled experter. In order to solve these problems, the mapping of data as well as the classification of phases are considered by using the general 3-PARD map and PA method, and the identification of phases occurring partial discharge/noise discharge is done. In the sequel, the type of partial discharge occurring on arbitrary random phase is classified and identified by fuzzy clustering-based polynomial Radial Basis Function Neural Networks(RBFNN) classifier. And by identifying the learning rate, momentum coefficient, and fuzzification coefficient of FCM fuzzy clustering with the aid of PSO algorithm, the RBFNN classifier is optimized. The virtual simulated data and the experimental data acquired from practical field are used for performance estimation of 3-phase partial discharge pattern classifier.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.423-429
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• 2007

Since the wireless smart card has played a main role in the identification security application for the building access; this research has its purpose to improve the performance of the smart card system and aims to offer more convenient to user. The contactless cards do not require insertion into a card reader and can work up to centimeters away from the reading device. To be able to cope with this performance the controlling of power consumption through the adaptive modulation and error control is needed. This paper addresses a forward error control (FEC) scheme with the adaptive Reed-Solomon code rate and an M-ary frequency shift keying (M-FSK) modulation scheme with the varying symbol size M over the link. The result of comparing energy efficiencies of adaptive error correction and adaptive modulation to other various static schemes shows to save over 50% of the energy consumption.