• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.406-412
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• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.4
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• pp.214-224
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• 2022

It is necessary to estimate manoeuvring characteristics of submerged bodies at the design stage in order to ensure the safe operations. In this study, added mass coefficients in the mathematical model of submerged bodies are estimated by captive model tests and numerical calculations. Two kinds of models, MARIN 'BB2'submarine model and AUV (Autonomous unmanned vehicle) model are utilized in the forced oscillation tests. Compared to BB2 submarine, AUV with cylindrical type hull form shows relatively small added masses in roll, pitch, and yaw directions. Next, numerical calculations based on potential theory are performed under the assumption that viscous effects on inertia forces are negligible. Added masses obtained by numerical calculations are in good agreements with forced oscillation test results. And if slow manoeuvres of submerged bodies are presumed, some of velocity coupled terms can be approximated by combinations of added mass coefficients.

• Design & Manufacturing
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• v.16 no.3
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• pp.9-15
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• 2022

In order to reduce the manufacturing costs of the glass lens, it is necessary to manufacture a lens using a UV curable resin or a thermosetting resin, which is a curable material, in order to replace a glass lens. In the case of forming a lens using a thermosetting material, it is necessary to form several lenses at once using the wafer-level lens manufacturing technologies due to the long curing time of the material. When a lens is manufactured using a curable material, an error in the shape of the lens due to the shrinkage of the material during the curing process is an important cause of defects. The major factors for these shape errors and deformations are the shrinkage and the change of mechanical properties in the process of changing from a liquid material during curing to a solid state after complete curing. Therefore, it is necessary to understand the curing process of the material and to examine the shrinkage rate and change of physical properties according to the degree cure. In addition, it is necessary to proceed with CAE for lens molding using these and to review problems in lens manufacturing in advance. In this study, the viscoelastic properties of the material were measured during the curing process using a rheometer. Using the results, Rheological investigation of cure kinetics was performed. At the same time, The shrinkage of the material was measured and simple mathematical models were created. And using the results, the molding process of a single lens was analyzed using Comsol, a commercial S/W. In addition, the experiment was conducted to compare and verify the CAE results. As a result, it was confirmed that the shrinkage rate of the material had a great influence on the shape precision of the final product.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2789-2802
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• 2020

Small Modular Reactors (SMRs) are attracting wide attention due to their outstanding performance, extensive studies have been carried out for lead-based fast reactors (LFRs) that cooled with Lead or Lead-bismuth (LBE), and small modular natural circulation LFR is one of the promising candidates for SMRs and LFRs development. One of the challenges for the design small modular natural circulation LFR is to master the natural circulation thermal-hydraulic performance in the reactor primary circuit, while the natural circulation characteristics is a coupled thermal-hydraulic problem of the core thermal power, the primary loop layout and the operating state of secondary cooling system etc. Thus, accurate predicting the natural circulation LFRs thermal-hydraulic features are highly required for conducting reactor operating condition evaluate and Thermal hydraulic design optimization. In this study, a thermal-hydraulic analysis code is developed for small modular natural circulation LFRs, which is based on several mathematical models for natural circulation originally. A small modular natural circulation LBE cooled fast reactor named URANUS developed by Korea is chosen to assess the code's capability. Comparisons are performed to demonstrate the accuracy of the code by the calculation results of MARS, and the key thermal-hydraulic parameters agree fairly well with the MARS ones. As a typical application case, steady-state analyses were conducted to have an assessment of thermal-hydraulic behavior under nominal condition, and several parameters affecting natural circulation were evaluated. What's more, two characteristics parameters that used to analyze natural circulation LFRs natural circulation capacity were established. The analyses show that the core thermal power, thermal center difference and flow resistance is the main factors affecting the reactor natural circulation. Improving the core thermal power, increasing the thermal center difference and decreasing the flow resistance can significantly increase the reactor mass flow rate. Characteristics parameters can be used to quickly evaluate the natural circulation capacity of natural circulation LFR under normal operating conditions.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.73-80
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• 2009

G protein-coupled receptors(GPCRs) family is a cell membrane protein, and plays an important role in a signaling mechanism which transmits external signals through cell membranes into cells. But, GPCRs each are known to have various complex control mechanisms and very unique signaling mechanisms. Structural features, and family and subfamily of GPCRs are well known by function. and accordingly, the most fundamental work in studies identifying the previous GPCRs is to classify the GPCRs with given protein sequences. Studies for classifying previously identified GPCRs more easily with mathematical models have been mainly going on. In this paper Considering that functions of proteins are determined by their stereoscopic structures, the present paper proposes a method to compare secondary structures of two GPCRs having different amino acid sequences, and then detect an unknown GPCRs assumed to have a same function in databases of previously identified GPCRs.

• Journal of the Korean Society of Food Culture
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• v.25 no.6
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• pp.779-787
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• 2010

The principal objective of this study was to determine the optimal mixing conditions for three amounts of onion powder, sugar, and butter to prepare onion powder cookies. The experimental design was based on the central composite design methodology of response surface, which included 16 experimental points including two replicates for onion powder, sugar, and butter. The mechanical and sensory properties of the cookies were measured, and these values were applied to the mathematical models. A canonical form and perturbation plot showed the influence of each ingredient on the mixed final product. The results of the spread ratio did not show significant results, but hardness increased with increasing quantities of onion powder and sugar but decreased with butter (p<0.01). The color lightness "L" value increased with increasing quantities of sugar and butter but decreased with added onion powder. In contrast, the redness color "a" value increased with increasing quantities of onion powder and sugar. Sugar did not affect the yellowness color "b" value, but the color b value increased with increasing onion powder and sugar. The results of a sensory evaluation using the predicted model showed significant values for flavor (p<0.01), texture (p<0.05), taste (p<0.05), and overall quality (p<0.01). As a result, the optimum formulation by numerical and graphical methods was calculated as 12.58 g onion powder, 35 g sugar, and 52.38 g butter.

• Structural Engineering and Mechanics
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• v.85 no.4
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• pp.433-443
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• 2023

The current paper discusses the dynamic and stability responses of cross-ply composite laminated plates by employing a refined quasi-3D trigonometric shear deformation theory. The proposed theory takes into consideration shear deformation and thickness stretching by a trigonometric variation of in-plane and transverse displacements through the plate thickness and assures the vanished shear stresses conditions on the upper and lower surfaces of the plate. The strong point of the new formulation is that the displacements field contains only 4 unknowns, which is less than the other shear deformation theories. In addition, the present model considers the thickness extension effects (ε_z≠0). The presence of the Winkler-Pasternak elastic base is included in the mathematical formulation. The Hamilton's principle is utilized in order to derive the four differentials' equations of motion, which are solved via Navier's technique of simply supported structures. The accuracy of the present 3-D theory is demonstrated by comparing fundamental frequencies and critical buckling loads numerical results with those provided using other models available in the open literature.

• Computers and Concrete
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• v.31 no.2
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• pp.111-121
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• 2023

The influence of material composition such as aggregate types, addition of supplementary cementitious materials as well as exposed temperature levels have significant impacts on concrete residual mechanical strength properties when exposed to elevated temperature. This study is based on data obtained from literature for fly ash blended concrete produced with natural and recycled concrete aggregates to efficiently develop prediction models for estimating its residual compressive strength after exposure to high temperatures. To achieve this, an extensive database that contains different mix proportions of fly ash blended concrete was gathered from published articles. The specific design variables considered were percentage replacement level of Recycled Concrete Aggregate (RCA) in the mix, fly ash content (FA), Water to Binder Ratio (W/B), and exposed Temperature level. Thereafter, a simplified mathematical equation for the prediction of concrete's residual compressive strength using Gene Expression Programming (GEP) was developed. The relative importance of each variable on the model outputs was also determined through global sensitivity analysis. The GEP model performance was validated using different statistical fitness formulas including R², MSE, RMSE, RAE, and MAE in which high R² values above 0.9 are obtained in both the training and validation phase. The low measured errors (e.g., mean square error and mean absolute error are in the range of 0.0160 - 0.0327 and 0.0912 - 0.1281 MPa, respectively) in the developed model also indicate high efficiency and accuracy of the model in predicting the residual compressive strength of fly ash blended concrete exposed to elevated temperatures.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.67-75
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• 2023

This paper deals with the operation of air taxis, which is one of the latest innovative technologies aimed at solving the issue of traffic congestion in cities. A key challenge for the successful introduction of the technology and efficient operation is a vertiport location problem. This paper employs a discrete choice model to calculate choice probabilities of transportation modes for each route, taking into account factors such as cost and travel time associated with different modes. Based on this probability, a mathematical formulation to maximize the utilization rate for air taxi is proposed. However, the proposed model is NP-hard, effective and efficient solution methodology is required. Compared to previous studies that simply proposed the optimization models, this study presents a solution methodology using the cross-entropy algorithm and confirms the effectiveness and efficiency of the algorith through numerical experiments. In addition to the academic excellence of the algorithm, it suggests that decision-making that considers actual data and air taxi utilization plans can increase the practial usability.

• Journal of Biomedical Engineering Research
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• v.44 no.5
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• pp.303-314
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• 2023

This study aimed to assess the practical feasibility of advanced deformable image registration (DIR) algorithms in radiotherapy by employing two distinct datasets. The first dataset included 14 4D lung CT scans and 31 head and neck CT scans. In the 4D lung CT dataset, we employed the DIR algorithm to register organs at risk and tumors based on respiratory phases. The second dataset comprised pre-, mid-, and post-treatment CT images of the head and neck region, along with organ at risk and tumor delineations. These images underwent registration using the DIR algorithm, and Dice similarity coefficients (DSCs) were compared. In the 4D lung CT dataset, registration accuracy was evaluated for the spinal cord, lung, lung nodules, esophagus, and tumors. The average DSCs for the non-learning-based SyN and NiftyReg algorithms were 0.92±0.07 and 0.88±0.09, respectively. Deep learning methods, namely Voxelmorph, Cyclemorph, and Transmorph, achieved average DSCs of 0.90±0.07, 0.91±0.04, and 0.89±0.05, respectively. For the head and neck CT dataset, the average DSCs for SyN and NiftyReg were 0.82±0.04 and 0.79±0.05, respectively, while Voxelmorph, Cyclemorph, and Transmorph showed average DSCs of 0.80±0.08, 0.78±0.11, and 0.78±0.09, respectively. Additionally, the deep learning DIR algorithms demonstrated faster transformation times compared to other models, including commercial and conventional mathematical algorithms (Voxelmorph: 0.36 sec/images, Cyclemorph: 0.3 sec/images, Transmorph: 5.1 sec/images, SyN: 140 sec/images, NiftyReg: 40.2 sec/images). In conclusion, this study highlights the varying clinical applicability of deep learning-based DIR methods in different anatomical regions. While challenges were encountered in head and neck CT registrations, 4D lung CT registrations exhibited favorable results, indicating the potential for clinical implementation. Further research and development in DIR algorithms tailored to specific anatomical regions are warranted to improve the overall clinical utility of these methods.