• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2481-2490
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• 2015

The issue of PHR is maintained on the server will be in the hospital. PHR information stored on the server, such as a patient's illness and treatment is very sensitive information. Therefore, patients should be guaranteed the protection of privacy. In addition, the PHR should be allowed to group access of it's approach. Therefore, in this paper the proposed group signature using hierarchical identity-based encryption schemes into can guarantee the PHR data privacy. The session key generated by group signature, it is use a tiered approach. The generated session keys safe PHR data transmission is possible. The proposed method is average 80% than the PKI encryption and ID-based encryption rather than average 50% the algorithm processing is more efficient

• Nuclear Engineering and Technology
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• v.48 no.6
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• pp.1360-1367
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• 2016

This paper introduces a boron meter with improved accuracy compared with other commercially available boron meters. Its design includes a new fitting function and a multi-detector. In pressurized water reactors (PWRs) in Korea, many boron meters have been used to continuously monitor boron concentration in reactor coolant. However, it is difficult to use the boron meters in practice because the measurement uncertainty is high. For this reason, there has been a strong demand for improvement in their accuracy. In this work, a boron meter evaluation model was developed, and two approaches were considered to improve the boron meter accuracy: the first approach uses a new fitting function and the second approach uses a multi-detector. With the new fitting function, the boron concentration error was decreased from 3.30 ppm to 0.73 ppm. With the multi-detector, the count signals were contaminated with noise such as field measurement data, and analyses were repeated 1,000 times to obtain average and standard deviations of the boron concentration errors. Finally, using the new fitting formulation and multi-detector together, the average error was decreased from 5.95 ppm to 1.83 ppm and its standard deviation was decreased from 0.64 ppm to 0.26 ppm. This result represents a great improvement of the boron meter accuracy.

• Journal of Korean Society on Water Environment
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• v.37 no.3
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• pp.204-216
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• 2021

It is important to understand the factors influencing the temporal and spatial variability of water quality in order to establish an effective customized management strategy for contaminated aquatic ecosystems. In this study, the spatial diversity of the 5-year (2015 - 2019) average total phosphorus (TP) concentration observed in 40 Total Maximum Daily Loads unit-basins in the Nakdong River watershed was analyzed using 50 predictive variables of watershed characteristics, climate characteristics, land use characteristics, and soil characteristics. Cross-correlation analysis, a two-stage exhaustive search approach, and Bayesian inference were applied to identify predictors that best matched the time-averaged TP. The predictors that were finally identified included watershed altitude, precipitation in fall, precipitation in winter, residential area, public facilities area, paddy field, soil available phosphate, soil magnesium, soil available silicic acid, and soil potassium. Among them, it was found that the most influential factors for the spatial difference of TP were watershed altitude in watershed characteristics, public facilities area in land use characteristics, and soil available silicic acid in soil characteristics. This means that artificial factors have a great influence on the spatial variability of TP. It is expected that the proposed statistical modeling approach can be applied to the identification of major factors affecting the spatial variability of the temporal average state of various water quality parameters.

• Korean Journal of Agricultural Science
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• v.48 no.1
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• pp.59-71
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• 2021

This study investigated the extent to which rice producers from the Ayeyarwaddy Region of Myanmar could improve their productivity if inputs were used efficiently in rice cultivation. To achieve this objective, simple random sampling was used to collect data from 300 rice growers in the study area. Data were analyzed with the translog stochastic frontier approach to understand the production efficiencies. The study further estimated the influencing factors that affect the efficiency levels of rice farmers. The empirical result reveals that the average technical, allocative, and economic efficiencies were at 76.11, 47.85, and 34.15%, respectively. This suggests that there is considerable room for improving rice production by better utilization of the available resources at the current level of technology. This study suggests that strenthening agricultural training programs and adoption of improved rice varieties may reduce overall inefficiencies among rice farmers in Myanmar. Factors like age, household size, education, farming experience, farm size, rice variety, training, and off-farm income have a significant impact on increasing/decreasing farmer's efficiency. Efficiency can be improved by establishing farmer field school programs to increase the scale of operations. The government should encourage young educated people to participate in paddy production and also intervene to reduce input prices and control the quality of seeds.

• Journal of Biomedical Engineering Research
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• v.45 no.3
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• pp.118-127
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• 2024

Commonly deep learning methods for enhancing the quality of medical images use unpaired dataset due to the impracticality of acquiring paired dataset through commercial imaging system. In this paper, we propose a supervised learning method to enhance the quality of ultrasound images. The U-net model is designed by incorporating a divide-and-conquer approach that divides and processes an image into four parts to overcome data shortage and shorten the learning time. The proposed model is trained using paired dataset consisting of 828 pairs of low-quality and high-quality images with a resolution of 512x512 pixels obtained by varying the number of channels for the same subject. Out of a total of 828 pairs of images, 684 pairs are used as the training dataset, while the remaining 144 pairs served as the test dataset. In the test results, the average Mean Squared Error (MSE) was reduced from 87.6884 in the low-quality images to 45.5108 in the restored images. Additionally, the average Peak Signal-to-Noise Ratio (PSNR) was improved from 28.7550 to 31.8063, and the average Structural Similarity Index (SSIM) was increased from 0.4755 to 0.8511, demonstrating significant enhancements in image quality.

• Journal of Veterinary Clinics
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• v.40 no.1
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• pp.25-30
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• 2023

The ventral midline approach (VMA) and right flank approach (RFA) are common procedures for the sterilization of bitches. This study compared the different parameters viz. total duration of surgery, recovery time, and length of the incision as well as body temperature, heart rate, respiration rate, and SpO2 in each approach. Twenty (20) bitches were divided randomly for the RFA and VMA. Meloxicam (0.2 mg/kg) was administered subcutaneously half an hour before the induction to provide preemptive analgesia. Diazepam and ketamine were administered intravenously at dose rates of 0.25 mg/kg and 2.5 mg/kg, and 0.17 mg/kg and 3.33 mg/kg, respectively to produce and maintain anesthesia. Each parameter was recorded at the pre-operative, operative and post-operative times. The average duration of surgery and length of incision of RFA (16.1 ± 5.13 min and 2.44 ± 0.83 cm) were significantly lower (p < 0.05) than the VMA (21.3 ± 5.48 min and 3.53 ± 0.7 cm). The operated bitches showed hypothermia (p < 0.05) at 1 hour compared to baseline and 24 hours of surgery. Heart and respiration rates increased significantly (p < 0.05) during traction and severing of ovarian ligaments in bitches within the RFA group, but there was no significant difference within VMA approaches. The sedation score was significantly higher (p < 0.05) at 1 hour after surgery in both approaches. Based on the duration of surgery and length of incision RFA approach was quick and minimal skin wound. Further studies on bitches considering molecular investigations of surgical stress are imperative.

• Journal of Multimedia Information System
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• v.5 no.3
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• pp.147-154
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• 2018

Natural language processing (NLP) is an emerging research area in which we study how machines can be used to perceive and alter the text written in natural languages. We can perform different tasks on natural languages by analyzing them through various annotational tasks like parsing, chunking, part-of-speech tagging and lexical analysis etc. These annotational tasks depend on morphological structure of a particular natural language. The focus of this work is part-of-speech tagging (POS tagging) on Hindi language. Part-of-speech tagging also known as grammatical tagging is a process of assigning different grammatical categories to each word of a given text. These grammatical categories can be noun, verb, time, date, number etc. Hindi is the most widely used and official language of India. It is also among the top five most spoken languages of the world. For English and other languages, a diverse range of POS taggers are available, but these POS taggers can not be applied on the Hindi language as Hindi is one of the most morphologically rich language. Furthermore there is a significant difference between the morphological structures of these languages. Thus in this work, a POS tagger system is presented for the Hindi language. For Hindi POS tagging a hybrid approach is presented in this paper which combines "Probability-based and Rule-based" approaches. For known word tagging a Unigram model of probability class is used, whereas for tagging unknown words various lexical and contextual features are used. Various finite state machine automata are constructed for demonstrating different rules and then regular expressions are used to implement these rules. A tagset is also prepared for this task, which contains 29 standard part-of-speech tags. The tagset also includes two unique tags, i.e., date tag and time tag. These date and time tags support all possible formats. Regular expressions are used to implement all pattern based tags like time, date, number and special symbols. The aim of the presented approach is to increase the correctness of an automatic Hindi POS tagging while bounding the requirement of a large human-made corpus. This hybrid approach uses a probability-based model to increase automatic tagging and a rule-based model to bound the requirement of an already trained corpus. This approach is based on very small labeled training set (around 9,000 words) and yields 96.54% of best precision and 95.08% of average precision. The approach also yields best accuracy of 91.39% and an average accuracy of 88.15%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.1890-1910
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• 2013

Routing overlay offers an ideal methodology to improve the end-to-end communication performance by deriving a backup path for any node pair. This paper focuses on a challenging issue of selecting a proper backup path to bypass the failures on the default path with high probability for any node pair. For existing backup path selection approaches, our trace-driven evaluation results demonstrate that the backup and default paths for any node pair overlap with high probability and hence usually fail simultaneously. Consequently, such approaches fail to derive a robust backup path that can take over in the presence of failure on the default path. In this paper, we propose a three-phase RBPS approach to identify a proper and robust backup path. It utilizes the traceroute probing approach to obtain the fine-grained topology information, and systematically employs the grid quorum system and the Bloom filter to reduce the resulting communication overhead. Two criteria, delay and fault-tolerant ability on average, of the backup path are proposed to evaluate the performance of our RBPS approach. Extensive trace-driven evaluations show that the fault-tolerant ability of the backup path can be improved by about 60%, while the delay gain ratio concentrated at 14% after replacing existing approaches with ours. Consequently, our approach can derive a more robust and available backup path for any node pair than existing approaches. This is more important than finding a backup path with the lowest delay compared to the default path for any node pair.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.3
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• pp.29-42
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• 2023

Universal Soil Loss Equation (USLE) is suggested and employed in the policy to conserve soil resources and to manage the impact of development, since soil loss is very essential to nonpoint source pollution management. The equation requires only five factors to estimate average annual potential soil loss, USLE is simplicity provides benefits in use of the equation. However, it is also limitation of the model, since the estimated results are very sensitive to the five factors. There is a need to examine the application procedures. Three approaches to estimate potential soil loss were examined, In the first approach, all factors were prepared with raster data, soil loss were computed for each cell, and sum of all cell values was determined as soil loss for the watersheds. In the second approach, the mean values for each factor were defined as representing USLE factors, and then the five factors were multiplied to determine soil loss for the watersheds. The third approach was same as the second approach, except that the Vegetative and Mechanical measure was used instead of the Cover and management factor and Support practice factor. The approaches were applied in 38 watersheds, they displayed significant difference, moreover no trends were detected for the soil loss at watersheds with the approaches. Therefore, it was concluded that there is a need to be developed and provided a typical guideline or public systems so that soil loss estimations have consistency with the users.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.451-459
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• 2017

There are many researches showing that when a process change has occurred, variable sampling intervals (VSI) control chart is better than the fixed sampling interval (FSI) control chart in terms of reducing the required time to signal. When the process engineers use VSI control procedure, frequent switching between different sampling intervals can be a complicating factor. However, average number of samples to signal (ANSS), which is the amount of required samples to signal, and average time to signal (ATS) do not provide any control statistics about switching performances of VSI charts. In this study, we evaluate numerical switching performances of multivariate VSI EWMA chart including average number of switches to signal (ANSW) and average switching rate (ASWR). In addition, numerical study has been carried out to examine how to improve the performance of considered chart with accumulate-combine approach under several different smoothing constant and sample size. In conclusion, process engineers, who want to manage the correlation coefficients of related quality variables, are recommended to make sample size as large and smoothing constant as small as possible under permission of process conditions.