Journal of Science and Technique
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THE EFFECT OF ANNEALING REGIME ON THE PRECIPITATION OF FeCoNiAl0.75Nb0.25 HIGH ENTROPY ALLOY
Get PDFThis paper investigates the effect of the annealing regime on the precipitation of FeCoNiAl0.75Nb0.25 high entropy alloy. The as-cast microstructure consists of coarse dendritic phases that are replaced by equiaxed morphology, and the distribution of the interdendritic phase becomes regularly better with increasing time and annealing temperature up to 825ºC. The precipitated process begins at 700ºC for 8 hours, shortening to 4 hours when the annealing temperature increases. The size of this phase is only a few μm. The fraction of the precipitated phase increases and the size of the dendritic phase is reduced as the annealing temperature is up to 825ºC, while this size rises in the 925ºC/16 hours regime. The microstructure is coarse, and the precipitated phase gradually disappears when the annealing is at 1000ºC. The HV3 hardness of the alloy increases with annealing time when the temperature is lower than 825ºC and reaches the highest value of ~ 614 kg/mm2 at 600ºC/ 24 hours; this value begins to decrease for the 925ºC/16 hours regime. Meanwhile, the hardness gradually decreases with increasing annealing time at 1000ºC. It can be expected due to the rapid coarsening of the dendritic phase, the decrease in the proportion of the precipitated phase in the alloy, and the appearance of plastic flow phenomena at grain boundaries
RECONSTRUCTION OF THE SURFACE PROFILE OF OPTICAL-MECHANICAL STRUCTURE WITH WHITE LIGHT INTERFERENCE BY DEEP LEARNING U-NET MODEL
Get PDFThis research proposes a method to accurately determine the location of the interference signal peak in white light interferometry. This improves the accuracy and resolution of the measurement, enabling precise measurement and reconstruction of three-dimensional microstructures on optical surfaces. By using a deep learning algorithm with a U-net neural network architecture to generate a predicted signal that closely matches the reference signal, combined with Fast Fourier Transform to filter noise and fit the proposed function, the exact location of the envelope signal peak is determined, providing information about the height of the point. This method can achieve an accuracy of around 0.9 nanometers at a noise level of 50 dB, which is over 40% more accurate than the traditional Fourier transform method at various noise levels. The persistent issues of the traditional Fourier transform method, such as determining the location of the interference signal peak at a signal position and the accuracy being heavily influenced by noise and the fitting signal, are effectively addressed
AN IMPROVED POLARIZATION WEIGHTS CONSTRUCTION FOR POLAR CODES
Get PDFPolar codes proposed by Arikan based on channel polarization have been proven to achieve Symmetric Binary-Discrete Input Memoryless Channels capacity. 3GPP has also chosen the Polar codes as the error correction code in the fifth mobile communication system (5G New Radio - 5G NR) with a maximum codeword length of 1024 bits. The design of the code based on the reliability of the synthetic channels has been researched with many different methods to satisfy the requirements demanded in the application of 5G NR. The Polar codes design requirements are ease of implementation, low decoding complexity, and high performance in error correction. This paper has proposed a method of designing Polar codes by determining a synthetic channels reliability index sequence based on the Polarization Weights (PW) method called the Improved Polarization Weights (IPW) method. The simulation results show that the error correction performance of the code designed according to IPW is better than the code structure selected for 5G NR and designed according to the original PW method
DYNAMIC RESPONSE ANALYSIS OF h-FGS PLATES SUBJECTED TO CONSECUTIVE BLAST LOADING
Get PDFThe main aim of this work is to use a finite element method (FEM) based on Shi’s third-order shear deformation plate theory (TSDT) to study the dynamic response of sandwich plates subjected to consecutive blast loading. The sandwich plate has an auxetic honeycomb core and two different functionally graded materials (FGMs) skin layers (so-called h-FGS plates). The honeycomb core helps significantly reduce the weight of the sandwich structures as well as enhance vibration absorption. The governing equation is derived from Hamilton's principle. After verifying the present approach, the effect of input parameters on the dynamic response of h-FGS plates is carried out in detail. The obtained results are expected to be useful for calculating and designing h-FGS plates in practical engineering
APPLICATION OF LEAN CONSTRUCTION PRINCIPLES AND SIMULATION FOR PERFORMANCE IMPROVEMENT OF EARTHWORK ACTIVITIES IN CONSTRUCTION PROJECTS ON OFFSHORE ISLANDS
Get PDFThe main objective of this study is to apply Lean Construction principles combined with a discrete event simulation tool, namely EZStrobe, to improve the performance of earthworks in construction projects on offshore islands. Based on the observation of the real-world construction process and the collection of data on each activity, a simulation model of the digging and hauling operations of coral sand is established and validated. The analysis results of the real model indicate problems of resource shortage as well as congestion in the construction process that caused delays and poor productivity. Subsequently, the three Lean Construction principles are applied to the simulation model to enhance the construction process. The analysis results from the Lean model, when are compared with the real model, show that the waiting time of construction equipment is reduced by 70.2%, the cycle and total construction time are reduced by 34.2% and 33.9%, respectively. As a result, productivity is significantly enhanced with an increase of 51.3% and a savings of 16.8% in cost. Lean Construction principles, when combined with the simulation tool, have demonstrated their effectiveness in reducing waste and improving construction processes. This approach helps managers effectively manage their plans and make informed decisions to enhance construction productivity
INVESTIGATION OF THE VERTICAL GROUND MOTION EFFECTS ON THE SEISMIC RESPONSES OF REINFORCED CONCRETE STRUCTURES
No full textThis article investigates the effects of vertical ground motion on the seismic responses of reinforced concrete (RC) structures. Conventional seismic design primarily focuses on horizontal ground motions, often neglecting the significant impacts of vertical accelerations. This study begins with a comprehensive analysis of the characteristics of vertical ground motion, thereby enhancing the understanding of these loads. A numerical analysis is performed on a typical multistorey RC building model to evaluate the impact of vertical ground motion on internal forces, specifically axial forces in column elements and bending moments in beam elements. The findings show that vertical ground motion can result in substantial increases in internal forces, which may necessitate revisions to current design practices. This study emphasizes the importance of considering vertical ground motion in the seismic-resistant design of RC structures to ensure safety and structural integrity
THE POST-QUANTUM AND PUBLIC-KEY BLOCK CIPHER ALGORITHMS BASED ON C.E. SHANNON’S THEORY OF PERFECT SECRECY
Get PDFThe article proposes a post-quantum and public-key block cipher algorithms constructed based on C.E. Shannon’s theory of perfect secrecy. The post-quantum block cipher algorithm proposed here can resist various types of attacks assisted by quantum computers. In addition to high security, this algorithm also has the ability to authenticate the origin and integrity of the encrypted messages. The public key block cipher algorithms here are developed from the proposed post-quantum block cipher algorithm combined with the Diffie - Hellman protocol, so this algorithm can be used similarly to pre-quantum block cipher algorithms (DES, AES,...) but the establishment of the shared secret key is completely based on the public key infrastructure (PKI)
A COMBINATION OF DEEP LEARNING AND DENSITY METHOD IN ANOMALOUS HUMAN TRAJECTORY DETECTION
Get PDFAbnormal human trajectories in working places are often associated with problems such as terrorism, violent attacks, and fire. Therefore, detecting anomalous human trajectories can improve safety and security in working areas. In this work, a novel framework of abnormal trajectory detection is proposed based on combining deep learning and density method. In particular, a Long Short-Term Memory-Autoencoder is first applied to learn informative representations of normal trajectories. Then, the density of trajectory representation in the latent space and reconstruction error of trajectory are used to detect anomalies. A novel metric is also proposed to determine the anomaly scores of trajectories. The proposed framework is evaluated using two real trajectory datasets: the MIT Badge and the sCREEN datasets. The experimental results show that our work effectively detects anomalies, achieving a f1-score of 81.08% on the MIT Badge dataset and 89.57% on the sCREEN dataset
MITIGATING POISONING ATTACKS TO FEDERATED LEARNING IN IoTs ANOMALY DETECTION WITH ATTENTION AGGREGATION
Get PDFFederated Learning (FL) is a privacy-preserving approach to train deep neural networks across decentralized devices without sharing raw data. Thus, FL has been popularly applied in domains like anomaly detection in Internet of Things (IoTs). However, IoT networks or devices have limited protection capabilities, resulting in the vulnerability of FL to data poisoning attacks. In order to address this challenge, we propose a new robust FL system designed to counter data poisoning attacks. Our approach, named as Federated Learning with Attention Aggregation (FedAA), leverages AutoEncoder (AE) models for local anomaly detection in IoT networks. In FedAA, the global model is aggregated from local models by using a novel aggregation method, named as Attention Aggregation (AA). This method is specifically designed to mitigate the impact of data poisoning attacks, which often lead to high values of the loss functions in the local models. More precisely, the local models with high loss values are assigned lower attention weights when contributing to the global model aggregation, and vice versa. As a result, the proposed AA method enhances the robustness of FedAA against data poisoning attacks. The extensive experiments are conducted on three datasets including N-BaIoT, NSL-KDD, and UNSW, of IoT anomaly detection. The results show that FedAA is more robust than other FL systems in mitigating data poisoning attacks
THE RELATIONSHIP BETWEEN THE MAXIMUM WALL THICKNESS THINNING AND THE RELATIVE HEIGHT OF THE PRODUCT DURING THE FREE DEFORMATION STAGE IN SHEET HYDROSTATIC FORMING OF STAINLESS STEEL SUS304
Get PDFThis article presents the establishment of the relationship between the maximum wall thinning and the relative height of the product during the free deformation stage in sheet hydrostatic forming of stainless steel SUS304. The numerical simulation and experiment are carried out using different input parameters for comparison and evaluation. The finite element method model with Dynaform was used to simulate the deformation process. The process and die parameters selected for the study include forming pressure (Pth), die radius (Rd), and blank holder pressure (Fh), while the responses are the maximum wall thinning ΔSmax (%) and the relative height of the product Hp (%). The relationship between ΔSmax and Hp also was built by changing the input parameters. This result allows us to determine the relative height of the deformed part with the corresponding maximum wall thinning. The research results provide useful technological recommendations for hydrostatic forming in the free deformation stage