• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.327-330
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• 2006

This paper represents the numerical analysis on effects of radius ratio in a concentric annulus with a rotating inner cylinder. The numerical model consisted of two cylinder which inner cylinder is rotating and outer cylinder is fix, and the axial direction is used the cyclic condition because of the length for axial direction is assumed infinite. The diameter of inner cylinder is assumed 86.8mm, the numerical parameters are angular velocity and radius ratio. Also, the whole walls of numerical model have no-slip and the working fluid is used water at $20^{\circ}C$. The numerical analysis is assumed the transient state to observe the flow variations by time and the 3-D cylindrical coordinate system. The calculation grid adopted a non-constant grid for dense arrangement near the wall side of cylinder, the standard $k-{\omega}$ high Reynolds number model to consider the effect of turbulence flow and wall, the fully implicit method for time term and the quick scheme for momentum equation. The numerical method is compared with the experimental results by Wereley and Lueptow, and the results are very good agreement. As the results, TVF isn't appeared when Re is small because of the initial flow instability is disappear by effect of the centrifugal force and viscosity. The vortex size is from 0.8 to 1.1 for TVF at various $\eta$, and the traveling distance for wavy vortex have the critical traveling distance for each case.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5301-5323
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• 2017

Small cell deployment offers a low-cost solution for the boosted traffic demand in heterogeneous cellular networks (HCNs). Besides improved spatial spectrum efficiency and energy efficiency, future HCNs are also featured with the trend of network architecture convergence and feasibility for flexible mobile applications. To achieve these goals, dual connectivity (DC) is playing a more and more important role to support control/user-plane splitting, which enables maintaining fixed control channel connections for reliability. In this paper, we develop a tractable framework for the downlink SINR analysis of DC assisted HCN. Based on stochastic geometry model, the data-control joint coverage probabilities under multi-frequency and single-frequency tiering are derived, which involve quick integrals and admit simple closed-forms in special cases. Monte Carlo simulations confirm the accuracy of the expressions. It is observed that the increase in mobility robustness of DC is at the price of control channel SINR degradation. This degradation severely worsens the joint coverage performance under single-frequency tiering, proving multi-frequency tiering a more feasible networking scheme to utilize the advantage of DC effectively. Moreover, the joint coverage probability can be maximized by adjusting the density ratio of small cell and macro cell eNBs under multi-frequency tiering, though changing cell association bias has little impact on the level of the maximal coverage performance.

• Nuclear Engineering and Technology
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• v.41 no.7
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• pp.875-884
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• 2009

We present three nuclear/hydrogen-related R&D activities being performed at KAIST: air-ingressed LOCA analysis code development, gas turbine analysis tool development, and hydrogen-production system analysis model development. The ICE numerical technique widely used for the safety analysis of water-reactors is successfully implemented into GAMMA, with which we solve the basic equations for continuity, momentum conservation, energy conservation of the gas mixture, and mass conservation of 6 species (He, N2, O2, CO, CO2, and H2O). GAMMA has been extensively validated using data from 14 test facilities. We developed a tool to predict the characteristics of HTGR helium turbines based on the throughflow calculation with a Newton-Raphson method that overcomes the weakness of the conventional method based on the successive iteration scheme. It is found that the current method reaches stable and quick convergence even under the off-normal condition with the same degree of accuracy. The dynamic equations for the distillation column of HI process are described with 4 material components involved in the HI process: H2O, HI, I2, H2. For the HI process we improved the Neumann model based on the NRTL (Non-Random Two-Liquid) model. The improved Neumann model predicted a total pressure with 8.6% maximum relative deviation from the data and 2.5% mean relative deviation, and liquid-liquid-separation with 9.52% maximum relative deviation from the data.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.644-651
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• 1997

In the water purification plant, chemicals are injected for quick purification of raw water. It is clear that the amount of chemicals intrinsically depends on water quality such as turbidity, temperature, pH and alkalinity. However, the process of chemical reaction to improve water quality (e.g., turbidity) by chemicals is not yet fully clarified nor quantified. The feedback signal in the process of coagulant dosage, which should be measured (through the sensor of the plant) to compute the appropriate amount of chemicals, is also not available. Most traditional methods focus on judging the conditions of purifying reaction and determine the amounts of chemicals through manual operation of field experts using Jar-test data. In this paper, a systematic control strategy is proposed to derive the optimum dosage of coagulant, PAC(Polymerized Aluminium Chloride), using Jar-test results. A neural network model is developed for coagulant dosing and purifying process by means of six input variables (turbidity, temperature, pH, alkalinity of raw water, PAC feed rate, turbidity in flocculation) and one output variable, while considering the relationships to the reaction of coagulation and flocculation. The model is utilized to derive the optimum coagulant dosage (in the sense of minimizing turbidity of water in flocculator). The ability of the proposed control scheme validated through the field test has proved to be of considerable practical value.

• Geomechanics and Engineering
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• v.29 no.4
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• pp.391-405
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• 2022

A newly proposed grouting simulation method, the sequential diffusion solidification method was introduced into the numerical simulation of combined bi-borehole grouting. The traditional, critical and difficult numerical problem for the temporal and spatial variation simulation of the slurry is solved. Thus, numerical simulation of grouting and blocking of flowing water in karst conduits is realized and the mechanism understanding of the combined bi-borehole technology is promoted. The sensitivity analysis of the influence factors of combined bi-borehole grouting was investigated. Through orthogonal experiment, the influences of proximal and distal slurry properties, the initial flow velocity of the conduit and the proximal and distal slurry injection rate on the blocking efficiency are compared. The velocity variation, pressure variation and slurry deposition phenomenon were monitored, and the flow field characteristics and slurry outflow behavior were analyzed. The interaction mechanism between the proximal and distal slurries in the combined bi-borehole grouting is revealed. The results show that, under the orthogonal experiment conditions, the slurry injection rate has the greatest impact on blocking. With a constant slurry injection rate, the blocking efficiency can be increased by more than 30% when using slurry with weak time-dependent viscosity behavior in the distal borehole and slurry with strong time-dependent viscosity behavior in the proximal borehole respectively. According to the results of numerical simulation, the grouting scheme of "intercept the flow from the proximal borehole by quick-setting slurry, and grout cement slurry from the distal borehole" is put forward and successfully applied to the water inflow treatment project of China Resources Cement (Pingnan) Limestone Mine.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.186-192
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• 2023

Malwares are becoming a major problem nowadays all around the world in android operating systems. The malware is a piece of software developed for harming or exploiting certain other hardware as well as software. The term Malware is also known as malicious software which is utilized to define Trojans, viruses, as well as other kinds of spyware. There have been developed many kinds of techniques for protecting the android operating systems from malware during the last decade. However, the existing techniques have numerous drawbacks such as accuracy to detect the type of malware in real-time in a quick manner for protecting the android operating systems. In this article, the authors developed a hybrid model for android malware detection using a decision tree and KNN (k-nearest neighbours) technique. First, Dalvik opcode, as well as real opcode, was pulled out by using the reverse procedure of the android software. Secondly, eigenvectors of sampling were produced by utilizing the n-gram model. Our suggested hybrid model efficiently combines KNN along with the decision tree for effective detection of the android malware in real-time. The outcome of the proposed scheme illustrates that the proposed hybrid model is better in terms of the accurate detection of any kind of malware from the Android operating system in a fast and accurate manner. In this experiment, 815 sample size was selected for the normal samples and the 3268-sample size was selected for the malicious samples. Our proposed hybrid model provides pragmatic values of the parameters namely precision, ACC along with the Recall, and F1 such as 0.93, 0.98, 0.96, and 0.99 along with 0.94, 0.99, 0.93, and 0.99 respectively. In the future, there are vital possibilities to carry out more research in this field to develop new methods for Android malware detection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.163-169
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• 2020

Recently, research on automation and unmanned operation of machines in the industrial field has been conducted with the advent of AI, Big data, and the IoT, which are the core technologies of the Fourth Industrial Revolution. The machines for these automation processes are controlled based on the data collected from the sensors attached to them, and further, the processes are managed. Conventionally, the abnormalities of sensors are periodically checked and managed. However, due to various environmental factors and situations in the industrial field, there are cases where the inspection due to the failure is not missed or failures are not detected to prevent damage due to sensor failure. In addition, even if a failure occurs, it is not immediately detected, which worsens the process loss. Therefore, in order to prevent damage caused by such a sudden sensor failure, it is necessary to identify the failure of the sensor in an embedded system in real-time and to diagnose the failure and determine the type for a quick response. In this paper, a deep neural network-based fault diagnosis system is designed and implemented using Raspberry Pi to classify typical sensor fault types such as erratic fault, hard-over fault, spike fault, and stuck fault. In order to diagnose sensor failure, the network is constructed using Google's proposed Inverted residual block structure of MobilieNetV2. The proposed scheme reduces memory usage and improves the performance of the conventional CNN technique to classify sensor faults.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3A
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• pp.129-139
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• 2003

CAC is a very important issue in CDMA system in order to protect the required QoS(quality of service) and increase the system's capacity. In this paper, we proposed and analyzed a call admission control scheme using multiple thresholds, which can provide quick processing time and better performance. There are two effective thresholds used to decide call admission. One is the number of active users, and the other is the signal to interference ratio(SIR). If the threshold of active users are lower than the low number of users threshold, we accept the new call without any other conditions. Otherwise, we check the current SIR to guarantee the quality of our service. System then accepts the new call when the SIR satisfies system requirement. Otherwise, the call will be rejected. Multiple threshold schemes are investigated and their performance is compared with the number of user and power based CAC's. simulation results are provided to evaluate the performance.

• Journal of Nutrition and Health
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• v.42 no.2
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• pp.119-127
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• 2009

Malnutrition of hospitalized patients can adversely affect clinical outcomes and cost. Several nutritional screening tools have been developed to identify patients with malnutrition risk. However, many of those possess practical pitfalls of requiring much time and labor to administer and may not be highly applicable to a Korean population. This study sought to develop and evaluate a Nutrition Risk Screening Tool (NRST) which is simple and quick to administer and widely applicable to Korean hospitalized patients with various diseases. The study was also designed to generate a screening tool predictable of various clinical outcomes and to validate it against the Nutritional Risk Screening 2002 (NRS 2002). Electronic medical records of 424 patients hospitalized at a general hospital in Seoul during a 14-month period were abstracted for anthropometric, medical, biochemical, and clinical outcome variables. The study employed a 4-step process consisting of selecting NRST components, searching a scoring scheme, validating against a reference tool, and confirming clinical outcome predictability. NRST components were selected by stepwise multiple regression analysis of each clinical outcome (i.e., hospitalization period, complication, disease progress, and death) on several readily available patient characteristics. Age and serum levels of albumin, hematocrit (Hct), and total lymphocyte count (TLC) remained in the last model for any of 4 dependent variables were decided as NRST components. Odds ratios of malnutrition risk based on NRS 2002 according to levels of the selected components were utilized to frame a scoring scheme of NRST. A NRST score higher than 3.5 was set as a cut-off score for malnutrition risk based on sensitivity and specificity levels against NRS 2002. Lastly differences in clinical outcomes by patients' NRST results were examined. The results showed that the NRST can significantly predict the in-hospital clinical outcomes. It is concluded that the NRST can be useful to simply and quickly screen patients at high-nutritional risk in relation to prospective clinical outcomes.

• Research in Plant Disease
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• v.8 no.3
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• pp.146-161
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• 2002

Incidence of soilborne diseases, as a major cause of failure of continuous monocropping becomes severe in recent years. For examples, recent epidemics of club root of chinese cabbage, white rot of garlic, bacterial wilt of potato, pepper phytophthora blight, tomato fusarium wilt and CGMMV of watermelon are the diseases that require urgent control measures. Reasons for the severe incidence of soilborne diseases are the simplified cropping system or continuous monocropping associated with allocation of major production areas of certain crop and year-round cultivation system that results in rapid degradation of soil environment. Neglect of breeding for disease resistance relative to giving much emphasis on high yield and good quality, and cultural methods putting first on the use of chemical fertilizers are thought to be the reason. Counter-measures against soilborne disease epidemics would become most effective when the remedies are seeded for individual causes. As long-term strategies, development of rational cropping system which fits local cropping and economic condition, development and supply of cultivars resistant to multiple diseases, and improvement of soil environment by soil conditioning are suggested. In short-term strategies, simple and economical soil-disinfestation technology, and quick and accurate forecasting methods for soilborne diseases are urgent matter far development. for these, extensive supports are required in governmental level for rearing soilborne disease specialists and activation of collaborating researches to solve encountering problems of soilborne diseases.