• ETRI Journal
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• v.42 no.2
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• pp.205-216
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• 2020

An arbiter physical unclonable function (APUF) has exponential challenge-response pairs and is easy to implement on field-programmable gate arrays (FPGAs). However, modeling attacks based on machine learning have become a serious threat to APUFs. Although the modeling-attack resistance of an MA-APUF has been improved considerably by architecture modifications, the response generation method of an MA-APUF results in low uniqueness. In this study, we demonstrate three design problems regarding the low uniqueness that APUF-based strong PUFs may exhibit, and we present several foundational principles to improve the uniqueness of APUF-based strong PUFs. In particular, an improved MA-APUF design is implemented in an FPGA and evaluated using a well-established experimental setup. Two types of evaluation metrics are used for evaluation and comparison. Furthermore, evolution strategies, logistic regression, and K-junta functions are used to evaluate the security of our design. The experiment results reveal that the uniqueness of our improved MA-APUF is 81.29% (compared with that of the MA-APUF, 13.12%), and the prediction rate is approximately 56% (compared with that of the MA-APUF (60%-80%).

• Advances in concrete construction
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• v.3 no.2
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• pp.91-102
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• 2015

In this paper, the load-deflection analysis of the Carbon Fiber Reinforced Polymer (CFRP) strengthened Reinforced Concrete (RC) slab using Recurrent Neural Network (RNN) is investigated. Six reinforced concrete slabs having dimension $1800{\times}400{\times}120mm$ with similar steel bar of 2T10 and strengthened using different length and width of CFRP were tested and compared with similar samples without CFRP. The experimental load-deflection results were normalized and then uploaded in MATLAB software. Loading, CFRP length and width were as neurons in input layer and mid-span deflection was as neuron in output layer. The network was generated using feed-forward network and a internal nonlinear condition space model to memorize the input data while training process. From 122 load-deflection data, 111 data utilized for network generation and 11 data for the network testing. The results of model on the testing stage showed that the generated RNN predicted the load-deflection analysis of the slabs in acceptable technique with a correlation of determination of 0.99. The ratio between predicted deflection by RNN and experimental output was in the range of 0.99 to 1.11.

• Journal of the Korea Society for Simulation
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• v.22 no.1
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• pp.41-51
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• 2013

This tutorial paper presents the design methodology of system-level simulators targeted for code division multiple access (CDMA) cellular standards such as EV-DO (Evolution-Data Only) and broadcast multicast service (BCMCS). The basic structure and simulation flow of system-level simulators are delineated, following the procedure of cell layout, mobile drops, channel modeling, received power calculation, scheduling, packet error prediction, and traffic generation. Packet data transmissions on the forward link of CDMA systems and EV-DO BCMCS systems are considered for modeling simulators. System-level simulators for cellular standards are modeled and developed with high-level languages and utilized to evaluate and predict air interface performance metrics including capacity and coverage.

• International Journal of Automotive Technology
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• v.7 no.1
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• pp.9-15
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• 2006

Prediction of the performance of a carbon canister in vehicle evaporative emission control system has become an important aspect of overall fuel system development and design. A vehicle's evaporative emission control system is continuously working, even when the vehicle is not running, due to generation of vapors from the fuel tank during ambient temperature variations. Evaporative emissions from gasoline powered vehicles continue to be a major concern. The objective of this paper is to clarity the flow characteristics and other such fundamental data for the canister during loading and purging are needed, and this data will prove valuable in the development of the canister. This paper is to evaluate the relationship between carbon canister condition and engine performance during engine operation, and the effects of evaporative emissions on the engine performance were investigated.

• Journal of the Korean Society of Safety
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• v.28 no.3
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• pp.18-22
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• 2013

The Co-base super heat resisting alloy ECY768 is employed in gas turbine because of its high temperature strength and oxidation resistance. The prediction of fatigue life for superalloy is important for improving the efficiency. In this paper, low cycle fatigue tests are performed as variables of total strain range and temperature. The relations between strain energy density and number of cycle to failure are examined in order to predict the low cycle fatigue life of ECY768 super alloy. The lives predicted by strain energy methods are found to coincide with experimental data and results obtained from the Coffin-Manson method. The fatigue lives is evaluated using predicted by Coffin-Manson method and strain energy methods is compared with the measured fatigue lives at different temperatures. The microstructure observing was performed for how affect able to low-cycle fatigue life by increasing the temperature.

• Transactions of Materials Processing
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• v.17 no.6
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• pp.393-400
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• 2008

Springback is one of the most difficult phenomena to analyze and control in sheet forming. Most of traditional springback control methods rely on experiences of skilled workers in industrial fields. This study focuses on prediction and generation of optimum reconfigurable die surfaces to control shape errors originated by springback. For this purpose, a deformation transfer function(DTF) was combined with finite element analysis of the springback in the 2D sheet forming model of elastic-perfectly plastic materials under the condition without blank holder. The results showed shape errors within 1% of the objective shape, which were comparable with analytically predicted errors. In addition to this theoretical analysis, DTF method was also applied to 2D and 3D sheet forming experiments. The experimental results showed ${\pm}0.5$ mm and ${\pm}1.0$ mm shape error distribution respectively, demonstrating that reconfigurable die surfaces were predicted well by the DTF method. Irrespective of material properties and sheet thickness, the DTF method was applicable not only to FEM simulation but also to 2D and 3D elasto-reconfigurable die forming. Consequently, this study shows that springback can be controlled effectively in the elasto-RDF system by using the DTF method.

• Korean Journal of Materials Research
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• v.19 no.6
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• pp.337-343
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• 2009

In this study, we optimized Pb-free Sn/Ni plating thickness and conditions were optimized to counteract the environmental regulations, such as RoHS and ELV(End-of Life Vehicles). The $B_{10}$ life verification method was also suggested to have been successful when used with the accelerated life test(ALT) for assessing Pb-free solder joint life of piezoelectric (PZT) ceramic resonator. In order to evaluate the solder joint life, a modified Norris-Landzberg equation and a Coffin-Manson equation were utilized. Test vehicles that were composed of 2520 PZT ceramic resonator on FR-4 PCB with Sn-3.0Ag-0.5Cu for ALT were manufactured as well. Thermal shock test was conducted with 1,500 cycles from $(-40{\pm}2)^{\circ}C$ to $(120{\pm}2)^{\circ}C$, and 30 minutes dwell time at each temperature, respectively. It was discovered that the thermal shock test is a very useful method in introducing the CTE mismatch caused by thermo-mechanical stress at the solder joints. The resonance frequency of test components was measured and observed the microsection views were also observed to confirm the crack generation of the solder joints.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.139-148
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• 1998

Internal and external heat sources will cause to deform to machine elements in the contact joint of structure, which results in the change of contact pressure distribution different from initial assembly. Heat induced variations of contact pressure will change the static and dynamic properties such as contact stiffness, damping as well as contact heat conduction in the structure In order to design and control the intelligent machine tool operating in variant conditions more sophisticatedly, the good prediction for the changes of prescribed properties are strongly required especially in the contact elements adjacent to the rotational or linear bearing. This paper presents some computational and experimental results in regard to static and dynamic characteristics of the press-fitted bush and shaft assembly which is a model of the bearing innerrace and shaft assembly. In the condition of heat generation on the outer surface of the bush, the effects of changes in the negative clearance and the heat flux on pressure distribution and dynamic properties are investigated. Results of this study show that the edge effect of the bush and the initial clearance have effects on the transient dynamic characteristics significantly.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1023-1025
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• 2019

Coal and Natural gas are two biggest contributors to a generation of energy throughout the world. Most of these resources create environmental pollution while making energy affecting the natural habitat. Many approaches have been proposed as alternatives to these sources. One of the leading alternatives is Solar Energy which is usually harnessed using solar farms. In artificial intelligence, the most researched area in recent times is machine learning. With machine learning, many tasks which were previously thought to be only humanly doable are done by machine. Neural networks have two major subtypes i.e. Convolutional neural networks (CNN) which are used primarily for classification and Recurrent neural networks which are utilized for time-series predictions. In this paper, we predict energy generated by solar fields and optimal angles for solar panels in these farms for the upcoming seven days using environmental and historical data. We experiment with multiple configurations of RNN using Vanilla and LSTM (Long Short-Term Memory) RNN. We are able to achieve RSME of 0.20739 using LSTMs.

• Wind and Structures
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• v.17 no.4
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• pp.361-377
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• 2013

Wall functions have been widely used in computational fluid dynamics (CFD) simulations and can save significant computational costs compared to other near-wall flow treatment strategies. However, most of the existing wall functions were based on the asymptotic characteristics of near-wall flow quantities, which are inapplicable in complex and non-equilibrium flows. A modified wall function is thus derived in this study based on flow over a plate at zero-pressure gradient, instead of on the basis of asymptotic formulations. Turbulent kinetic energy generation ($G_P$), dissipation rate (${\varepsilon}$) and shear stress (${\tau}_{\omega}$) are composed together as the near-wall expressions. Performances of the modified wall function combined with the nonlinear realizable k-${\varepsilon}$ turbulence model are investigated in homogeneous equilibrium atmosphere boundary layer (ABL) and flow around a 6 m cube. The computational results and associated comparisons to available full-scale measurements show a clear improvement over the standard wall function, especially in reproducing the boundary layer flow. It is demonstrated through the two case studies that the modified wall function is indeed adaptive and can yield accurate prediction results, in spite of its simplicity.