• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.500-506
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• 2018

In this paper, we considered the one-shot alignment using master inertial navigation system (MINS) and slave inertial navigation system (SINS) in the missile to find the exact posture of a missile. In order to perform one-shot alignment, the tilt angle between MINS and SINS must be obtained, which can be compensated by obtaining the tilt angle between missile round and SINS. The tilt angle was calculated by using the roll rotation of missile round, jig for rotating the missile round and interface structure to measure the horizontal state by using a horizontal angle meter were constructed. As a result of the tilt angle save (TAS) inspection, the tilt angle ${\alpha}$, ${\beta}$, ${\gamma}$ is normal range and it is possible to perform one-shot alignment by compensating this value.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.968-976
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• 2019

This paper presents a number of verification case studies for a recently developed sensitivity/uncertainty code package. The code package, ROMUSE (Reduced Order Modeling based Uncertainty/Sensitivity Estimator) is an effort to provide an analysis tool to be used in conjunction with reactor core simulators, in particular the Virtual Environment for Reactor Applications (VERA) core simulator. ROMUSE has been written in C++ and is currently capable of performing various types of parameter perturbations and associated sensitivity analysis, uncertainty quantification, surrogate model construction and subspace analysis. The current version 2.0 has the capability to interface with the Design Analysis Kit for Optimization and Terascale Applications (DAKOTA) code, which gives ROMUSE access to the various algorithms implemented within DAKOTA, most importantly model calibration. The verification study is performed via two basic problems and two reactor physics models. The first problem is used to verify the ROMUSE single physics gradient-based range finding algorithm capability using an abstract quadratic model. The second problem is the Brusselator problem, which is a coupled problem representative of multi-physics problems. This problem is used to test the capability of constructing surrogates via ROMUSE-DAKOTA. Finally, light water reactor pin cell and sodium-cooled fast reactor fuel assembly problems are simulated via SCALE 6.1 to test ROMUSE capability for uncertainty quantification and sensitivity analysis purposes.

• Geomechanics and Engineering
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• v.17 no.1
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• pp.1-9
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• 2019

This paper proposes a new numerical approach to model geocell reinforced soils, where the geocell is described as membrane elements and the complex interaction between geocell and soil is realized by coupling their degrees of freedom. The effectiveness and robustness of this approach are demonstrated using two examples, i.e., a geocell-reinforced foundation and a large scale retaining wall project. The first example validates the approach against established solutions through a comprehensive parametrical study to understand the influence of geocell on the improvement of bearing capacity of foundations. The study results show that reducing the geocell pocket size has a strong effect on improving the bearing capacity. In addition, when the aspect ratio maintains the same value, the bearing capacity improvement with increasing geocell height is insignificant. Comparing with the field monitoring and measurement in the project, the second example investigates the application of the approach to practical engineering projects. This paper provides a practically feasible and efficient modelling approach, where no explicit interface or contact is required. This allows geocell reinforced soils in large scale project can be effectively modelled where the mechanism for complex geocell-soil interaction can be explicitly observed.

• Advances in concrete construction
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• v.7 no.4
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• pp.241-247
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• 2019

In this paper the effect of bedding layer on the failure mechanism of rock in direct shear test has been investigated using particle flow code, PFC. For this purpose, firstly calibration of pfc2d was performed using Brazilian tensile strength. Secondly direct shear test consisting bedding layer was simulated numerically. Thickness of layers was 10 mm and rock bridge length was 10 mm, 40 mm and 60 mm. In each rock bridge length, bedding layer angles changes from $0^{\circ}$ to $90^{\circ}$ with increment of $15^{\circ}$. Totally 21 models were simulated and tested. The results show that two types of cracks develop within the model. Shear cracks and tensile cracks. Also failure pattern is affected by bridge length while shear strength is controlled by failure pattern. It's to be noted that bedding layer has not any effect on the failure pattern because the layer interface strength is too high.

• Food Science and Industry
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• v.51 no.2
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• pp.127-135
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• 2018

The action of antioxidants was different depending on the environments where antioxidants were located. Although basic mechanisms of lipid oxidation and antioxidants were related each other, their contribution on the degree of oxidation was different. In thisreview, terminology on antioxidant properties were defined such as antioxidant activity and antioxidant capacities. In addition, antioxidant mechanisms including primary and secondary antioxidants or hydrogen donating or electron transferring antioxidants were introduced. Also, the impact of physical points of view and antioxidant polar paradox were introduced. Depending on the types of food matrice including bulk oil, oil-in-water emulsion (O/W), or solid state, antioxidant actions showed different degree and this point was explained in detail.

• Steel and Composite Structures
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• v.37 no.6
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• pp.741-759
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• 2020

Steel plate-concrete composite slabs provide attractive features, such as more effective loading transfer, and more cost-effective stay-in-place forms, thereby enabling engineers to design more high-performance light structures. Although significant studies in the literatures have been directed toward designing and implementing the steel plate-concrete composite beams, there are limited data available for understanding of the composite slabs. To fill this gap, nine the composite slabs with different variables in this study were tested to unveil the impacts of the critical factors on the ultimate strength behavior. The key information of the findings included sample failure modes, crack pattern, and ultimate strength behavior of the composite slabs under either four-point or three-point loading. Test results showed that the failure modes varied from delamination to shear failures under different design factors. Particularly, the shear stud spacing and thicknesses of the concrete slabs significantly affected their ultimate load-carrying capacities. Moreover, an analytical model of the composite slabs was derived for determining their ultimate load-carrying capacity and was well verified by the experimental data. Further extensive parametric study using the proposed analytical methods was conducted for a more comprehensive investigation of those critical factors in their performance. These findings are expected to help engineers to better understand the structural behavior of the steel plate-concrete composite slabs and to ensure reliability of design and performance throughout their service life.

• ETRI Journal
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• v.44 no.4
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• pp.672-685
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• 2022

This article proposes a subject-independent application of brain-computer interfacing (BCI). A 32-channel Electroencephalography (EEG) device is used to measure imagined speech (SI) of four words (sos, stop, medicine, washroom) and one phrase (come-here) across 13 subjects. A deep long short-term memory (LSTM) network has been adopted to recognize the above signals in seven EEG frequency bands individually in nine major regions of the brain. The results show a maximum accuracy of 73.56% and a network prediction time (NPT) of 0.14 s which are superior to other state-of-the-art techniques in the literature. Our analysis reveals that the alpha band can recognize SI better than other EEG frequencies. To reinforce our findings, the above work has been compared by models based on the gated recurrent unit (GRU), convolutional neural network (CNN), and six conventional classifiers. The results show that the LSTM model has 46.86% more average accuracy in the alpha band and 74.54% less average NPT than CNN. The maximum accuracy of GRU was 8.34% less than the LSTM network. Deep networks performed better than traditional classifiers.

• Advances in materials Research
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• v.12 no.1
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• pp.43-65
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• 2023

Free vibration analysis of power law and sigmoidal sandwich plates made up of functionally graded materials (FGMs) has been carried out using finite element based higher-order zigzag theory. The present model satisfies all-important conditions such as transverse shear stress-free conditions at the plate's top and bottom surface along with continuity condition for transverse stresses at the interface. A Nine-noded C0 finite element having eleven degrees of freedom per node is used during the study. The present model is free from the requirement of any penalty function or post-processing technique and hence is computationally efficient. The present model's effectiveness is demonstrated by comparing the present results with available results in the literature. Several new results have been proposed in the present work, which will serve as a benchmark for future works. It has been observed that the material variation law, power-law exponent, skew angle, and boundary condition of the plate widely determines the free vibration behavior of sandwich functionally graded (FG) plate.

• Current Optics and Photonics
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• v.7 no.3
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• pp.283-296
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• 2023

An intraoral spectral domain optical coherence tomography (SD-OCT) system has been developed, using a custom-built hand-held scanner and spectrometer. The hand-held OCT probe, based on a microelectromechanical systems scanner and a self-built miniaturized drive circuit, had a field of view sufficient for dental diagnosis. The spectrometer using a fabricated f-theta lens provided the image depth required for dental diagnosis. The axial and transverse resolutions of the OCT system in air were 7.5 ㎛ and 12 ㎛ respectively. The hand-held probe could scan an area of 10 × 10 mm², and the spectrometer could image along a depth of 2.5 mm. To verify the utility of the developed OCT system, OCT images of tooth hard and soft tissues were acquired, and a user-interface program for diagnosis was developed. Early caries and microcracks that were difficult to diagnose with existing methods could be found, and the state of restoration could be observed. Measuring the depth of the gingival sulcus, distinguishing subgingival calculus, and detecting an implant under the gingiva suggested the possibility of the SD-OCT system as a diagnostic for dental soft tissues. Through the presented OCT images, the capability of the developed SD-OCT system for dental diagnosis was demonstrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.2101-2123
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• 2023

Recent studies have shown that the neural network-based binary code similarity detection technology performs well in vulnerability mining, plagiarism detection, and malicious code analysis. However, existing cross-architecture methods still suffer from insufficient feature characterization and low discrimination accuracy. To address these issues, this paper proposes a cross-architecture binary function similarity detection method based on composite feature model (SDCFM). Firstly, the binary function is converted into vector representation according to the proposed composite feature model, which is composed of instruction statistical features, control flow graph structural features, and application program interface calling behavioral features. Then, the composite features are embedded by the proposed hierarchical embedding network based on a graph neural network. In which, the block-level features and the function-level features are processed separately and finally fused into the embedding. In addition, to make the trained model more accurate and stable, our method utilizes the embeddings of predecessor nodes to modify the node embedding in the iterative updating process of the graph neural network. To assess the effectiveness of composite feature model, we contrast SDCFM with the state of art method on benchmark datasets. The experimental results show that SDCFM has good performance both on the area under the curve in the binary function similarity detection task and the vulnerable candidate function ranking in vulnerability search task.