• Nuclear Engineering and Technology
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• v.54 no.9
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• pp.3488-3493
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• 2022

Accelerator driven subcritical systems have long been discussed as facilities which can be used for solving the nuclear waste problem. The physics of these systems is very different from conventional reactors and new techniques had to be developed for reactivity monitoring. One such technique is the Area Ratio Method which studies the response of a subcritical system upon insertion of a large number of neutron pulses. An issue associated with this technique is the spatial dependence of measured reactivity which is intrinsic to the sub criticality of the system since the reactor does not operate on the fundamental mode and measured reactivity depends on the detector position. This is generally addressed by defining Bell-Glasstone spatial correction factor. This factor upon multiplication with measured reactivity gives the correct reactivity which is independent of detector location. Monte Carlo Methods are used for evaluating these factors. This paper presents a complete three dimensional map of spatial correction factors for BRAHMMA subcritical system. In addition, the dataset obtained also helps in identifying detector locations where the correction factor is close to unity, thereby implying no correction if the detector is used at those locations.

• Geomechanics and Engineering
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• v.30 no.4
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• pp.363-372
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• 2022

One of the most frequent issues in tunnel excavation is the collapse of rock blocks and the dropping of rock fragments from the tunnel face. The tunnel face can be reinforced using a number of techniques. One of the most popular and affordable solutions is the use of face longitudinal dowels, which has benefits including high strength, flexibility, and ease of cutting. In order to examine the reinforced face, this work shows the longitudinal deformation profile and ground response curve for a tunnel face. This approach is based on assumptions made during the analysis phase of problem solving. By knowing the tunnel face response and dowel behavior, the interaction of two elements can be solved. The rock element equation derived from the rock bolt method is combined with the dowel differential equation to solve the reinforced ground response curve (GRC). With a straightforward and accurate analytical equation, the new differential equation produces the reinforced displacement of the tunnel face at each stage of excavation. With simple equations and a less involved computational process, this approach offers quick and accurate solutions. The FLAC3D simulation has been compared with the suggested analytical approach. A logical error is apparent from the discrepancies between the two solutions. Each component of the equation's effect has also been described.

• Journal of the Korean Dietetic Association
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• v.8 no.1
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• pp.1-8
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• 2002

The purpose of this study is to clarify success factors for desirable relationship between buyer and supplier in elementary school. Therefore, the survey questionnaire consisted of general background, past success, success difference, buyer-supplier relationship characteristics(trust, supporting status, communication behavior, conflict resolution techniques, supplier selection process). The subjects were 66 dieticians of elementary school in Inchon. The statistical analysis of data was completed using SPSS program. The results were summarized as follows : Average total cost/day per one person ￦1,156. The number of suppliers per one school were 6. 92.3% of the subjects were in favor of private contract, regarding contract methods of purchasing food materials. For the past success, degree of satisfaction about past their supplier showed 3.49 score. The present success difference was shown higher than the past success. There was significant correlation between the past success and the present success difference. Trust about suppliers showed 3.40score. Supplying companies hardly support for buying school. Among information quality(timely, accurate, adequate, complete, credible), timely and complete showed lower score than the other kind of elements. Among the buyer-supplier relationship characteristic elements, only trust correlated with satisfaction about suppliers significantly. Among the conflict resolution techniques, joint problem solving and persuasive attempts were often made use of by subjects. The supplier selection criteria were shown quality(7.47), supplier's capabilities(6.46), management plan(6.00), price(5.73), scale(5.48), assets(5.27), considers delivery(4.76) and technology(2.39). As results, trust was needed for the desirable relationship between buyers and suppliers. This study has some limitations. The data in this study were collected from only buyer. It is more desired to acquire data from suppliers also.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.792-796
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• 2005

The methods of times series analysis have been recognized as important tools for assisting in solving problems related to the management of water resources. Especially, After more than 40 years the so-called Hurst effect remains an open problem in stochastic hydrology. Until now, its existence has been explained fly R/S analysis that roots in early work of the British hydrologist H.E. Hurst(1951). Today, the Hurst analysis is mostly used for the hydrological studies for memory and characteristics of time series and many methodologies have been developed for the analysis. So, there are many different techniques for the estimation of the Hurst exponent(H). However, the techniques can produce different characteristics for the persistence of a time series each other. We found that DFA is the most appropriate technique for the Hurst exponent estimation for both the shot term memory and long term memory. We analyze the SOI(Southern Oscillations Index) and 6 tree-ring series for USA sites by means of DFA and the BDS statistic is used for nonlinearity test of the series. From the results, we found that SOI series is nonlinear time series which has a long term memory of H=0.92. Contrary to earlier work of Rao(1999), all the tree- ring series are not random from our analysis. A certain tree ring series show a long term memory of H=0.97 and nonlinear property. Therefore, we can say that the SOI and tree-ring series may show long memory and nonlinearity.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.5
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• pp.1233-1246
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• 2018

With the proliferation of smart mobiles, disassembly techniques for position-independent code (PIC) composed of ARM architecture instructions in computer security are becoming more important. However, existing techniques have been studied on x86 architecture and are focused on solving problems of non-PIC and generality. Therefore, the accuracy of the collected address information is low to apply to advanced security technologies such as binary measurement. In this paper, we propose a disassembly technique that reflects the characteristics of PIC composed of ARM instructions. For accuratly collecting traceable addresses, we designed value-set analysis having symbol-form domain. To solve the main problem of disassembly, we devised a heuristic using the characteristics of the code generated by the compiler. To verify the accuracy and effectiveness of our technique, we tested 669 shared libraries and executables in the Android 8.1 build, resulting in a total disassembly rate of 91.47%.

• The Journal of the Acoustical Society of Korea
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• v.34 no.6
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• pp.479-486
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• 2015

A triplet line array has a capability for solving left/right ambiguity problem and high directivity of line array. For this, high computational powers and correlation between nearby sensors must be considered. Hardware powers are dramatically increased, so various adaptive beamforming techniques and signal processing techniques can be adopted for large triplet line array. To investigate the optimum signal processing method and improve the target detection capability, we need to analyze the noise correlation among the triplet line array sensors in real environment. In this paper we analyze the experimental data in the East Sea, investigate noise correlation between three hydrophones in triplet sensors, among the triplet sensors and time varying properties. Based on the acquired results, it is possible to verify some information for beamforming and signal processing methods with considering the properties of the triplet line array.

• Journal of the Korean Society of Safety
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• v.28 no.3
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• pp.107-113
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• 2013

Problem solving and/or decision making process usually encountered in human living consists of a sequence of human behaviors based upon his/her knowledge. Thus, Rasmussen introduced Skill-Rule-Knowledge paradigm to countermeasure human errors that can occur in Nuclear Power Plants. Unfortunately however, it was not so easy as expected since objective evidence have not been obtainable with conventional research techniques. With the help of EEG band pawer ratio techniques, this study tried to get psycho-physiological symptoms of human errors, if any, while human beings perform knowledge-based behaviors such as simple arithmetic computations with different difficulty level. A set of simulated works was carried out with a computer station. Four kinds of arithmetic computation tasks were given to 10 health male under-graduate students on different day individually, and during the experiment, EEG and ECG was measured continuously for objective psycho-physiological analysis. According to the results, ${\alpha}$/(${\alpha}+{\beta}$) as well as ${\alpha}/{\beta}$ band power ratio were sensitive to task difficulty level which consistently decreased both. However, any one of them failed to reveal the influence of tasks with different difficulty level in the aspect of task duration time. On the contrary, Heart Rate Variability was more suggestive than expected. To make a conclusion, it can be said that band power of EEG waves will be helpful in not only assessment of work difficulty level but also assessment of workers' skill development if supported by cardiac function such as HRV.

• Steel and Composite Structures
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• v.25 no.6
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• pp.663-670
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• 2017

The problem of layup optimization of the composite laminates involves a very complex multidimensional solution space which is usually non-exhaustively explored using different heuristic computational methods such as genetic algorithms (GA). To ensure the convergence to the global optimum of the applied heuristic during the optimization process it is necessary to evaluate a lot of layup configurations. As a consequence the analysis of an individual layup configuration should be fast enough to maintain the convergence time range to an acceptable level. On the other hand the mechanical behavior analysis of composite laminates for any geometry and boundary condition is very convoluted and is performed by computational expensive numerical tools such as finite element analysis (FEA). In this respect some studies propose very fast FEA models used in layup optimization. However, the lower bound of the execution time of FEA models is determined by the global linear system solving which in some complex applications can be unacceptable. Moreover, in some situation it may be highly preferred to decrease the optimization time with the cost of a small reduction in the analysis accuracy. In this paper we explore some machine learning techniques in order to estimate the failure of a layup configuration. The estimated response can be qualitative (the configuration fails or not) or quantitative (the value of the failure factor). The procedure consists of generating a population of random observations (configurations) spread across solution space and evaluating using a FEA model. The machine learning method is then trained using this population and the trained model is then used to estimate failure in the optimization process. The results obtained are very promising as illustrated with an example where the misclassification rate of the qualitative response is smaller than 2%.

• Journal of Engineering Education Research
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• v.21 no.3
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• pp.56-65
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• 2018

With rapid advance of technologies including information and communication technologies, jobs are evolving faster than ever. Architectural engineering is no exception in this regard, and the green architectural engineering is emerging fast as a promising new field. In this study, a Delphi study of expert architectural engineers are conducted to find out (1) near future prospects of the field, (2) near future emerging jobs, (3) competencies needed for these jobs, and (4) educational content necessary to build these competencies with regards to the green architectural engineering. Initial Delphi survey consisting of open-ended questions in the above four areas were conducted and came out with 65 items after duplicate removal and semantic refinements. Further refinements via second and third wave of Delphi results into 40 items that the 13 architectural engineering experts may largely agree upon as future prospects with regards to the green architectural engineering. Findings indicate that it is expected that the demand for green architectural engineering and needs for automatic energy control system increase. Also, collaborations with other fields is becoming more and more important in green architectural engineering. The professional work management skills such as knowledge convergence, problem solving, collaboration skills, and creativity linking components from various related areas seem to also be on the increasing need. Near future ready critical skills are found to be the building environment control techniques (thermal, light, sound, and air), the data processing techniques like data mining, energy monitoring, and the control and utilization of environmental analysis software. Experts also agree on new curriculum for green building architecture to be developed with more of converging subjects across disciplines for future ready professional skills and experiences. Major topics to be covered in the near future includes building environment studies, building energy management, energy reduction systems, indoor air quality, global environment and natural phenomena, and machinery and electrical facility. Architectural engineering community should be concerned with building up the competencies identified in this Delphi preparing for fast advancing future.

• Journal of Broadcast Engineering
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• v.27 no.5
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• pp.808-811
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• 2022

Display under strong ambient lighting is perceived darker than it really is. Existing techniques for solving the problem in terms of software show limitations in that image enhancement techniques are applied regardless of ambient lighting or chrominance is not improved compared to luminance. Therefore, this paper proposes a visibility enhancement algorithm using deep learning to adaptively respond to ambient lighting values and an equation to restore optimal chrominance for luminance. The algorithm receives an ambient lighting value with the input image, and then applies a deep learning model and chrominance restoration equation to generate an image to minimize the difference between the degradation modeling of enhanced image and the input image. Qualitative evaluation proves that the algorithm shows excellent performance in improving visibility under strong ambient lighting through comparison of images applied with degradation modeling.