• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.6 s.324
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• pp.9-15
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• 2004

In MIMO-OFDM systems, conventional channel estimation techniques using comb type training symbols give relatively large mean squared errors(MSEs) at the edge subcarriers. To reduce the MSEs at these subcarriers, a cyclic comb type training structure is proposed. In the proposed cyclic training structure, all types of training symbols are transmitted cyclically at each antenna. At the receiver, the channel frequency responses that are estimated using each training symbol are averaged with weights obtained from the corresponding MSEs. Computer simulations showed that the proposed cyclic training structure gives more SNR gain than the conventional training structure.

• Fisheries and Aquatic Sciences
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• v.18 no.2
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• pp.131-135
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• 2015

Two new bitter-tasting cyclic peptides comprising six amino acids, namely gamakamide C and D, were isolated from cultured oysters Crassostrea gigas. Dimethylaminoazobenzene sulfonyl-amino acid analysis detected Val and Leu in gamakamide C and Ile and Leu in gamakamide D. The molecular formula of gamakamide C was determined as $C_{43}H_{60}N_{7}O_8S$ by high-resolution fast atom bombardment mass spectroscopy (HR FAB-MS) ($[M+H]^+m/z822.4200{\Delta}-2.4mmu$), and that of gamakamide D was determined as $C_{43}H_{62}N_7O_8S$ by HR FAB-MS ($[M+H]^+m/z836.4379{\Delta}-2.0mmu$). Comparison of amino acid analyses and fragment ions by MS/MS among gamakamide C, D, and E (known), the structures of gamakamide C and D were confirmed $as-{\small{L}}-Val-{\small{L}}-Met(SO)-{\small{L}}-NMe-Phe-{\small{L}}-Leu-{\small{D}}-Lys-{\small{L}}-Phe-$ and $-{\small{L}}-Ile-{\small{L}}-Met(SO)-{\small{L}}-NMe-Phe-{\small{L}}-Leu-{\small{D}}-Lys-{\small{L}}-Phe-$, respectively.

• Steel and Composite Structures
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• v.37 no.5
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• pp.571-587
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• 2020

In this article the seismic demand and performance of two recent braced steel frames named steel moment frames with the elliptic bracing (ELBRFs) are assessed through a laboratory program and numerical analyses of FEM. Here, one of the specimens is without connecting bracket from the corner of the frame to the elliptic brace (ELBRF-E), while the other is with the connecting brackets (ELBRF-B). In both the elliptic braced moment resisting frames (ELBRFs), in addition to not having any opening space problem in the bracing systems when installed in the surrounding frames, they improve structure's behavior. The experimental test is run on ½ scale single-story single-bay ELBRF specimens under cyclic quasi-static loading and compared with X-bracing and SMRF systems in one story base model. This system is of appropriate stiffness and a high ductility, with an increased response modification factor. Moreover, its energy dissipation is high. In the ELBRF bracing systems, there exists a great interval between relative deformation at the yield point and maximum relative deformation after entering the plastic region. In other words, the distance from the first plastic hinge to the collapse of the structure is fairly large. The experimental outcomes here, are in good agreement with the theoretical predictions.

• Geomechanics and Engineering
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• v.37 no.1
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• pp.49-64
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• 2024

Rocks undergoing repeated loading and unloading over an extended period, such as due to earthquakes, human excavation, and blasting, may result in the gradual accumulation of stress and deformation within the rock mass, eventually reaching an unstable state. In this study, a CNN-CCM is proposed to address the mechanical behavior. The structure and hyperparameters of CNN-CCM include Conv2D layers × 5; Max pooling2D layers × 4; Dense layers × 4; learning rate=0.001; Epoch=50; Batch size=64; Dropout=0.5. Training and validation data for deep learning include 71 rock samples and 122,152 data points. The AI Rock Constitutive Model learned by CNN-CCM can predict strain values(ε₁) using Mass (M), Axial stress (σ₁), Density (ρ), Cyclic number (N), Confining pressure (σ₃), and Young's modulus (E). Five evaluation indicators R², MAPE, RMSE, MSE, and MAE yield respective values of 0.929, 16.44%, 0.954, 0.913, and 0.542, illustrating good predictive performance and generalization ability of model. Finally, interpreting the AI Rock Constitutive Model using the SHAP explaining method reveals that feature importance follows the order N > M > σ₁ > E > ρ > σ₃.Positive SHAP values indicate positive effects on predicting strain ε₁ for N, M, σ₁, and σ₃, while negative SHAP values have negative effects. For E, a positive value has a negative effect on predicting strain ε₁, consistent with the influence patterns of conventional physical rock constitutive equations. The present study offers a novel approach to the investigation of the mechanical constitutive model of rocks under cyclic loading and unloading conditions.

• Steel and Composite Structures
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• v.34 no.6
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• pp.891-907
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• 2020

Many studies reveal that during destructive earthquakes, most of the structures enter the inelastic phase. The amount of hysteretic energy in a structure is considered as an important criterion in structure design and an important indicator for the degree of its damage or vulnerability. The hysteretic energy value wasted after the structure yields is the most important component of the energy equation that affects the structures system damage thereof. Controlling this value of energy leads to controlling the structure behavior. Here, for the first time, the hysteretic behavior and energy dissipation capacity are assessed at presence of elliptical braced resisting frames (ELBRFs), through an experimental study and numerical analysis of FEM. The ELBRFs are of lateral load systems, when located in the middle bay of the frame and connected properly to the beams and columns, in addition to improving the structural behavior, do not have the problem of architectural space in the bracing systems. The energy dissipation capacity is assessed in four frames of small single-story single-bay ELBRFs at ½ scale with different accessories, and compared with SMRF and X-bracing systems. The frames are analyzed through a nonlinear FEM and a quasi-static cyclic loading. The performance features here consist of hysteresis behavior, plasticity factor, energy dissipation, resistance and stiffness variation, shear strength and Von-Mises stress distribution. The test results indicate that the good behavior of the elliptical bracing resisting frame improves strength, stiffness, ductility and dissipated energy capacity in a significant manner.