• Journal of Radiation Industry
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• v.17 no.4
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• pp.345-357
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• 2023

Nuclear forensics has been understood as a mendatory component in the international society for nuclear material control and non-proliferation verification. Radiochronometry of nuclear activities for nuclear forensics are decay series characteristics of nuclear materials and the Bateman equation to estimate when nuclear materials were purified and produced. Radiochronometry values have uncertainty of measurement due to the uncertainty factors in the estimation process. These uncertainties should be calculated using appropriate evaluation methods that are representative of the accuracy and reliability. The IAEA, US, and EU have been researched on radiochronometry and uncertainty of measurement, although the uncertainty calculation method using the Bateman equation is limited by the underestimation of the decay constant and the impossibility of estimating the age of more than one generation, so it is necessary to conduct uncertainty calculation research using computer simulation such as Monte Carlo method. This highlights the need for research using computational simulations, such as the Monte Carlo method, to overcome these limitations. In this study, we have analyzed mathematical models and the LHS (Latin Hypercube Sampling) methods to enhance the reliability of radiochronometry which is to develop an uncertainty algorithm for nuclear material radiochronometry using Bateman Equation. We analyzed the LHS method, which can obtain effective statistical results with a small number of samples, and applied it to algorithms that are Monte Carlo methods for uncertainty calculation by computer simulation. This was implemented through the MATLAB computational software. The uncertainty calculation model using mathematical models demonstrated characteristics based on the relationship between sensitivity coefficients and radiative equilibrium. Computational simulation random sampling showed characteristics dependent on random sampling methods, sampling iteration counts, and the probability distribution of uncertainty factors. For validation, we compared models from various international organizations, mathematical models, and the Monte Carlo method. The developed algorithm was found to perform calculations at an equivalent level of accuracy compared to overseas institutions and mathematical model-based methods. To enhance usability, future research and comparisons·validations need to incorporate more complex decay chains and non-homogeneous conditions. The results of this study can serve as foundational technology in the nuclear forensics field, providing tools for the identification of signature nuclides and aiding in the research, development, comparison, and validation of related technologies.

• Korean Journal of Agricultural Science
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• v.51 no.3
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• pp.315-329
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• 2024

This study was conducted for simulation model development of an electric all-wheel-drive vehicle to adapt the agricultural machinery. Data measurement system was installed on a four-wheel electric driven vehicle using proximity sensor, torque-meter, global positioning system (GPS) and data acquisition (DAQ) device. Axle torque and rotational speed were measured using a torque-meter and a proximity sensor. Driving test was performed on an upland field at a speed of 7 km·h^-1. Simulation model was developed using a multi-body dynamics software, and tire properties were measured and calculated to reflect the similar road conditions. Measured and simulated data were compared to validate the developed simulation model performance, and axle rotational speed was selected as simulation input data and axle torque and power were selected as simulation output data. As a result of driving performance, an average axle rotational speed was 115 rpm for each wheel. Average axle torque and power were 4.50, 4.21, 4.04, and 3.22 Nm and 53.42, 50.56, 47.34, and 38.07 W on front left, front right, rear left, and rear right wheel, respectively. As a result of simulation driving, average axle torque and power were 4.51, 3.9, 4.16, and 3.32 Nm and 55.79, 48.11, 51.62, and 41.2 W on front left, front right, rear left, and rear right wheel, respectively. Absolute error of axle torque was calculated as 0.22, 7.36, 2.97, and 3.11% on front left, front right, rear left, rear right wheel, respectively, and absolute error of axle power was calculated as 4.44, 4.85, 9.04, and 8.22% on front left, front right, rear left, and rear right wheel, respectively. As a result of absolute error, it was shown that developed simulation model can be used for driving performance prediction of electric driven vehicle. Only straight driving was considered in this study, and various road and driving conditions would be considered in future study.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.17-23
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• 2020

Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

• Radiation Oncology Journal
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• v.18 no.2
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• pp.150-156
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• 2000

Purpose : Stereotactic radiation therapy (SRT) can deliver highly focused radiation to a small and spherical target lesion with very high degree of mechanical accuracy. For non-spherical and large lesions, however, inclusion of the neighboring normal structures within the high dose radiation volume is inevitable in SRT This is to report the beam shaping using the partial closure of the independent jaw in SRT and the verification of dose calculation and the dose display using a home-made soft ware. Materials and Methods : Authors adopted the idea to partially close one or more independent collimator jaw(5) in addition to the circular collimator cones to shield the neighboring normal structures while keeping the target lesion within the radiation beam field at all angles along the arc trajectory. The output factors (OF's) and the tissue-maximum ratios (TMR's) were measured using the micro ion chamber in the water phantom dosimetry system, and were compared with the theoretical calculations. A film dosimetry procedure was peformed to obtain the depth dose profiles at 5 cm, and they were also compared with the theoretical calculations, where the radiation dose would depend on the actual area of irradiation. Authors incorporated this algorithm into the home-made SRT software for the isodose calculation and display, and was tried on an example case with single brain metastasis. The dose-volume histograms (DVH's) of the planning target volume (PTV) and the normal brain derived by the control plan were reciprocally compared with those derived by the plan using the same arc arrangement plus the independent collimator jaw closure. Results : When using 5.0 cm diameter collimator, the measurements of the OF's and the TMR's with one independent jaw set at 30 mm (unblocked), 15.5 mm, 8.6 mm, and 0 mm from th central beam axis showed good correlation to the theoretical calculation within 0.5% and 0.3% error range. The dose profiles at 5 cm depth obtained by the film dosimetry also showed very good correlation to the theoretical calculations. The isodose profiles obtained on the home-made software demonstrated a slightly more conformal dose distribution around the target lesion by using the independent jaw closure, where the DVH's of the PTV were almost equivalent on the two plans, while the DVH's for the normal brain showed that less volume of the normal brain receiving high radiation dose by using this modification than the control plan employing the circular collimator cone only. Conclusions : With the beam shaping modification using the independent jaw closure, authors have realized wider clinical application of SRT with more conformal dose planning. Authors believe that SRT, with beam shaping ideas and efforts, should no longer be limited to the small spherical lesions, but be more widely applied to rather irregularly shaped tumors in the intracranial and the head and neck regions.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.99-124
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• 2012

Our society has long been talking about necessity for innovation. Since companies in particular need to carry out business innovation in their overall processes, they have attempted to apply many innovation factors on sites and become to pay more attention to their innovation. In order to achieve this goal, companies has applied various information technologies (IT) on sites as a means of innovation, and consequently IT have been greatly developed. It is natural for the field of IT to have faced another revolution which is called cloud computing, which is expected to result in innovative changes in software application via the Internet, data storing, the use of devices, and their operations. As a vehicle of innovation, cloud computing is expected to lead the changes and advancement of our society and the business world. Although many scholars have researched on a variety of topics regarding the innovation via IT, few studies have dealt with the issue of could computing as IT. Thus, the purpose of this paper is to set the variables of innovation attributes based on the previous articles as the characteristic variables and clarify how these variables affect "Performance Expectancy" of companies and the intention of using cloud computing. The result from the analysis of data collected in this study is as follows. The study utilized a research model developed on the innovation diffusion theory to identify influences on the adaptation and spreading IT for cloud computing services. Second, this study summarized the characteristics of cloud computing services as a new concept that introduces innovation at its early stage of adaptation for companies. Third, a theoretical model is provided that relates to the future innovation by suggesting variables for innovation characteristics to adopt cloud computing services. Finally, this study identified the factors affecting expectation and the intention to use the cloud computing service for the companies that consider adopting the cloud computing service. As the parameter and dependent variable respectively, the study deploys the independent variables that are aligned with the characteristics of the cloud computing services based on the innovation diffusion model, and utilizes the expectation for performance and Intention to Use based on the UTAUT theory. Independent variables for the research model include Relative Advantage, Complexity, Compatibility, Cost Saving, Trialability, and Observability. In addition, 'Acceptance for Adaptation' is applied as an adjustment variable to verify the influences on the expected performances from the cloud computing service. The validity of the research model was secured by performing factor analysis and reliability analysis. After confirmatory factor analysis is conducted using AMOS 7.0, the 20 hypotheses are verified through the analysis of the structural equation model, accepting 12 hypotheses among 20. For example, Relative Advantage turned out to have the positive effect both on Individual Performance and on Strategic Performance from the verification of hypothesis, while it showed meaningful correlation to affect Intention to Use directly. This indicates that many articles on the diffusion related Relative Advantage as the most important factor to predict the rate to accept innovation. From the viewpoint of the influence on Performance Expectancy among Compatibility and Cost Saving, Compatibility has the positive effect on both Individual Performance and on Strategic Performance, while it showed meaningful correlation with Intention to Use. However, the topic of the cloud computing service has become a strategic issue for adoption in companies, Cost Saving turns out to affect Individual Performance without a significant influence on Intention to Use. This indicates that companies expect practical performances such as time and cost saving and financial improvements through the adoption of the cloud computing service in the environment of the budget squeezing from the global economic crisis from 2008. Likewise, this positively affects the strategic performance in companies. In terms of effects, Trialability is proved to give no effects on Performance Expectancy. This indicates that the participants of the survey are willing to afford the risk from the high uncertainty caused by innovation, because they positively pursue information about new ideas as innovators and early adopter. In addition, they believe it is unnecessary to test the cloud computing service before the adoption, because there are various types of the cloud computing service. However, Observability positively affected both Individual Performance and Strategic Performance. It also showed meaningful correlation with Intention to Use. From the analysis of the direct effects on Intention to Use by innovative characteristics for the cloud computing service except the parameters, the innovative characteristics for the cloud computing service showed the positive influence on Relative Advantage, Compatibility and Observability while Complexity, Cost saving and the likelihood for the attempt did not affect Intention to Use. While the practical verification that was believed to be the most important factor on Performance Expectancy by characteristics for cloud computing service, Relative Advantage, Compatibility and Observability showed significant correlation with the various causes and effect analysis. Cost Saving showed a significant relation with Strategic Performance in companies, which indicates that the cost to build and operate IT is the burden of the management. Thus, the cloud computing service reflected the expectation as an alternative to reduce the investment and operational cost for IT infrastructure due to the recent economic crisis. The cloud computing service is not pervasive in the business world, but it is rapidly spreading all over the world, because of its inherited merits and benefits. Moreover, results of this research regarding the diffusion innovation are more or less different from those of the existing articles. This seems to be caused by the fact that the cloud computing service has a strong innovative factor that results in a new paradigm shift while most IT that are based on the theory of innovation diffusion are limited to companies and organizations. In addition, the participants in this study are believed to play an important role as innovators and early adapters to introduce the cloud computing service and to have competency to afford higher uncertainty for innovation. In conclusion, the introduction of the cloud computing service is a critical issue in the business world.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.3
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• pp.464-477
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• 2013

There is a great need to develop a training program proven to change behavior and improve knowledge. The purpose of this study was to evaluate employee hygiene knowledge, hygiene practice, and cleanliness, before and after HACCP system implementation at one small-size restaurant. The efficiency of the system was analyzed using time-temperature control after implementation of u-HACCP$^{(R)}$. The employee hygiene knowledge and practices showed a significant improvement (p<0.05) after HACCP system implementation. In non-heating processes, such as seasoned lettuce, controlling the sanitation of the cooking facility and the chlorination of raw ingredients were identified as the significant CCP. Sanitizing was an important CCP because total bacteria were reduced 2~4 log CFU/g after implementation of HACCP. In bean sprouts, microbial levels decreased from 4.20 logCFU/g to 3.26 logCFU/g. There were significant correlations between hygiene knowledge, practice, and microbiological contamination. First, personnel hygiene had a significant correlation with 'total food hygiene knowledge' scores (p<0.05). Second, total food hygiene practice scores had a significant correlation (p<0.05) with improved microbiological qualities of lettuce salad. Third, concerning the assessment of microbiological quality after 1 month, there were significant (p<0.05) improvements in times of heating, and the washing and division process. On the other hand, after 2 months, microbiological was maintained, although only two categories (division process and kitchen floor) were improved. This study also investigated time-temperature control by using ubiquitous sensor networks (USN) consisting of an ubi reader (CCP thermometer), an ubi manager (tablet PC), and application software (HACCP monitoring system). The result of the temperature control before and after USN showed better thermal management (accuracy, efficiency, consistency of time control). Based on the results, strict time-temperature control could be an effective method to prevent foodborne illness.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.137-147
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• 2014

Purpose : The purpose of this study is to verify the accuracy of dose delivery according to the patient's breathing cycle in Gated Volumetric Modulated Arc Therapy Materials and Methods : TrueBeam STxTM(Varian Medical System, Palo Alto, CA) was used in this experiment. The Computed tomography(CT) images that were acquired with RANDO Phantom(Alderson Research Laboratories Inc. Stamford. CT, USA), using Computerized treatment planning system(Eclipse 10.0, Varian, USA), were used to create VMAT plans using 10MV FFF with 1500 cGy/fx (case 1, 2, 3) and 220 cGy/fx(case 4, 5, 6) of doserate of 1200 MU/min. The regular respiratory period of 1.5, 2.5, 3.5 and 4.5 sec and the patients respiratory period of 2.2 and 3.5 sec were reproduced with the $QUASAR^{TM}$ Respiratory Motion Phantom(Modus Medical Devices Inc), and it was set up to deliver radiation at the phase mode between the ranges of 30 to 70%. The results were measured at respective respiratory conditions by a 2-Dimensional ion chamber array detector(I'mRT Matrixx, IBA Dosimetry, Germany) and a MultiCube Phantom(IBA Dosimetry, Germany), and the Gamma pass rate(3 mm, 3%) were compared by the IMRT analysis program(OmniPro I'mRT system software Version 1.7b, IBA Dosimetry, Germany) Results : The gamma pass rates of Case 1, 2, 3, 4, 5 and 6 were the results of 100.0, 97.6, 98.1, 96.3, 93.0, 94.8% at a regular respiratory period of 1.5 sec and 98.8, 99.5, 97.5, 99.5, 98.3, 99.6% at 2.5 sec, 99.6, 96.6, 97.5, 99.2, 97.8, 99.1% at 3.5 sec and 99.4, 96.3, 97.2, 99.0, 98.0, 99.3% at 4.5 sec, respectively. When a patient's respiration was reproduced, 97.7, 95.4, 96.2, 98.9, 96.2, 98.4% at average respiratory period of 2.2 sec, and 97.3, 97.5, 96.8, 100.0, 99.3, 99.8% at 3.5 sec, respectively. Conclusion : The experiment showed clinically reliable results of a Gamma pass rate of 95% or more when 2.5 sec or more of a regular breathing period and the patient's breathing were reproduced. While it showed the results of 93.0% and 94.8% at a regular breathing period of 1.5 sec of Case 5 and 6, it could be confirmed that the accurate dose delivery could be possible on the most respiratory conditions because based on the results of 100 patients's respiratory period analysis as no one sustained a respiration of 1.5 sec. But, pretreatment dose verification should be precede because we can't exclude the possibility of error occurrence due to extremely short respiratory period, also a training at the simulation and careful monitoring are necessary for a patient to maintain stable breathing. Consequently, more reliable and accurate treatments can be administered.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.25-34
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• 2020

In the current medical information system, a system environment is constructed in which Biometric data generated by using IoT or medical equipment connected to a patient can be stored in a medical information server and monitored at the same time. Also, the patient's biometric data, medical information, and personal information after simple authentication using only the ID / PW via the mobile terminal of the medical staff are easily accessible. However, the method of accessing these medical information needs to be improved in the dimension of protecting patient's personal information, and provides a quick authentication system for first aid. In this paper, we implemented an automatic authentication system based on the patient's situation and evaluated its performance. Patient's situation was graded into normal and emergency situation, and the situation of the patient was determined in real time using incoming patient biometric data from the ward. If the patient's situation is an emergency, an emergency message including an emergency code is send to the mobile terminal of the medical staff, and they attempted automatic authentication to access the upper medical information of the patient. Automatic authentication is a combination of user authentication(ID/PW, emergency code) and mobile terminal authentication(medical staff's role, working hours, work location). After user authentication, mobile terminal authentication is proceeded automatically without additional intervention by medical staff. After completing all authentications, medical staffs get authorization according to the role of medical staffs and patient's situations, and can access to the patient's graded medical information and personal information through the mobile terminal. We protected the patient's medical information through limited medical information access by the medical staff according to the patient's situation, and provided an automatic authentication without additional intervention in an emergency situation. We performed performance evaluation to verify the performance of the implemented automatic authentication system.

• Progress in Medical Physics
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• v.10 no.2
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• pp.63-71
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• 1999

For the purpose of utilization in 3-D conformal radiotherapy and whole body radiosurgery, the Whole Body 3-Dimensional Topographic Radiation Therapy System has been developed. Whole body frame was constructed in order to be installed on the couch. Radiopaque catheters were engraved on it for the dedicated coordinate system and a MeV-Green immobilizer was used for the patient setup by the help of side panels and plastic rods. By designing and constructing the whole body frame in this way, geometrical limitation to the gantry rotation in 3-D conformal radiotherapy could be minimized and problem which radiation transmission may be altered in particular incident angles was solved. By analyzing CT images containing information of patient setup with respect to the whole body frame, localization and coordination of the target is performed so that patient setup error may be eliminated between simulation and treatment. For the verification of setup, the change of patient positioning is detected and adjusted in order to minimize the setup error by means of comparison of the body outlines using 3 CCTV cameras. To enhance efficiency of treatment procedure, this work can be done in real time by watching the change of patient setup through the monitor. The method of image subtraction in IDL (Interactive Data Language) was used to visualize the change of patient setup. Rotating X-ray system was constructed for detecting target movement due to internal organ motion. Landmark screws were implanted either on the bones around target or inside target, and variation of target location with respect to markers may be visualized in order to minimize internal setup error through the anterior and the lateral image information taken from rotating X-ray system. For CT simulation, simulation software was developed using IDL on GUI(Graphic User Interface) basis for PC and includes functions of graphic handling, editing and data acquisition of images of internal organs as well as target for the preparation of treatment planning.