Brittleness analysis and important nodes discovery in large time-evolving complex networks

The brittleness analysis and important nodes detection have been a hot spot in the complex networks. How to get the overall feature of the whole network and how to find out some important nodes are requisites to solve these problems. In this paper, we adopt the trace of the adjacency matrix and the centrality of the complex networks to give a quantitative and qualitative analysis of networks being studied. Results show that the k-shell plays a more important role than the degree centrality and the betweenness in finding important nodes, and it can also be used to give direction on the immunization and maintenance of complex networks.     

Hybrid process of fabricating high-quality micro wine-glass fused silica resonators

A new hybrid method, which combines improved glass-blown technology with wet etching, is reported to fabricate micro wine-glass resonators with high-quality fused silica. The optimum placement is compared to achieve the resonators with good shell shape. The typical shell diameter is about 4mm and its thickness covers from dozens to hundreds of micrometers. The etching rates in corrosion solutions with different ratios and at different thicknesses of hemispherical shells are studied. We also conclude how to precisely control the thickness. The corrosion solutions with different ratios of HF solution to NH₄F solution make the spherical shells rougher in different degrees. The best roughness is 0.581 nm in the 1: 8 ratio corrosion solution while the original roughness is 0.537 nm. This fact shows that the resonator remains atomically smooth surface. Based on the glassblowing spherical fused silica structure, the thickness of the resonator is effectively controlled by buffered oxide etch (BOE) technology according to the measured etching rate. The measured resonant frequency of the hemispherical shell at ambient pressure and room temperature is 1.75 kHz of rocking mode which is close to the simulated frequency. Using such a low-cost hybrid approach, we can fabricate high-quality microscale resonators in batch.     

Automatic outer surface extraction of femoral head in CT images

Computer-aided hip surgery planning and implant design applications require accurate segmentation of femoral head and proximal acetabulum. An accurate outer surface extraction of femoral head using marching cubes algorithm remains challenging due to deformed shapes and extremely narrow inter-bone regions. In this paper, we present an automatic and fast approach for segmentation of femoral head and proximal acetabulum which leads to accurate and compact representation of femoral head using marching cubes algorithm. At first, valley-emphasized images are constructed from original images so that valleys stand out in high relief. Otsu’s multiple thresholding technique is applied to seperate the images into bone and non-bone classes. Region growing method and threedimensional (3D) morphological operations are performed to fill holes in the bone. In the reclassification process, the bone regions are further segmented, and the boundaries of the bone regions are further refined based on Bayes decision rule. Finally, marching cubes algorithm is applied to reconstruct a 3D model and extract the outer surface of femoral head and proximal acetabulum. Experimental results show that this method is an accurate segmentation technique for femoral head and proximal acetabulum and it can be applied as a tool in medical practice.     

Long-term tracking based on spatio-temporal context

Aiming at the problem that the fast tracking algorithm using spatio-temporal context (STC) will inevitably lead to drift and even lose the target in long-term tracking, a new algorithm based on spatio-temporal context that integrates long-term tracking with detecting is proposed in this paper. We track the target by the fast tracking algorithm, and the cascaded search strategy is introduced to the detecting part to relocate the target if the fast tracking fails. To a large extent, the proposed algorithm effectively improves the accuracy and stability of long-term tracking. Extensive experimental results on benchmark datasets show that the proposed algorithm can accurately track and relocate the target though the target is partially or completely occluded or reappears after being out of the scene.     

Poisson noise removal based on nonlocal total variation with Euler’s elastica pre-processing

An enhancement-based Poisson denoising method for photon-limited images is presented. The noisy image is firstly pre-processed for enhancing incomplete object information, and then it is denoised while preserving the restored structural details. A variational regularization model based on Euler’s elastica (EE) is proposed for image enhancement pre-processing. A nonlocal total variation (NLTV) regularization model is then employed in the second stage of image denoising. The above two optimization problems are solved by the alternating direction method of multipliers (ADMM). For Poissonian images with low image peak values, experiments demonstrate the validity and efficiency of the proposed method for both restoring geometric structure and removing noise.     

Target priority determination methods by interval-valued intuitionistic fuzzy sets with unknown attribute weights

The paper aims at the problem of multi-targets threat degree being hard to be evaluated accurately in complex air defense battlefield environments. Combined with multi-sensors information fusion and interval-valued intuitionistic fuzzy sets (IVIFS) theories, the target priority determination is studied. The score and accuracy functions of IVIFS are improved with thinking about the hesitating information in order to increase the rationality. Then, the influence factors of target priority and the nonlinear relationship between the influence factors and target priority are analyzed. Next, the algorithms for calculating the factor weights and sensor weights are given. Based on the theory of IVIFS and technique for order preference by similarity to an ideal solution (TOPSIS), two methods of target priority determination based on the IVIFS and TOPSIS are proposed. At last, an application example verifies the effectiveness and flexibility of the proposed algorithms.     

Application of digital image correlation method to in-situ dynamic strain measurement

Application of digital image correlation (DIC) method to determination of in-situ dynamic strain is presented in this study. Firstly, an integrative software is programmed based on the DIC algorithms and point-wise least-squares fitting technique. Then, simulated speckle images are generated to study the computational accuracy of this software. The experimental setup and procedures for measuring in-situ dynamic strain through both DIC and strain gauge are proposed. The DIC results are close to those measured by strain gauge. This fact reveals that DIC is a practical and effective tool for in-situ dynamic strain measurement. Finally, the full-field in-situ dynamic strain of another specimen is measured by DIC, and the overall distribution of the strain in the measurement area is clearly shown.     

Mathematical model validated by a crash test for studying the occupant’s kinematics and dynamics in a cars’ frontal collision

The aim of the paper was to determine the kinematic parameters that influence the occupant injury risk through a mathematical model. The developed model is a 2D model composed of 4 bodies (2 vehicles, thorax and head). The head and thorax are interconnected with a rotation joint and a torsion spring meant to stiffen the relative movement between the bodies. The thorax is connected with the vehicle body by a linear spring meant to simulate the seatbelt stiffness. The model was solved using Lagrange principle and the validation of the model was made through a crash test performed using the same initial conditions and comparing the obtained values of the displacement, velocity and acceleration parameters with the ones obtained with the mathematical model. The head and torso were chosen due to the fact that they are the common parts of the body that get injured, especially the head with the change of 80 % to cause fatal injury in car’s frontal collision. Once the model was validated, the stiffness of the seatbelt was modified in order to determine the behavior of the occupant in case of car frontal collisions. When the seatbelt stiffness was reduced, the occupant displacement and velocity increased, while by increasing the stiffness, these parameters decreased. The values of the developed model presented a high degree of similarity with the results obtained from the crash test with an error of 10 %. This model can be used by engineers to easily asses the occupant injury risk in case of vehicle frontal collisions.     

Application of the reverse 3D scanning method to evaluate the wear of forging tools divided on two selected areas

This study is focused on tools used in the industrial hot forging process of a front wheel forging (eventually–gear wheel) manufactured for the automotive industry. Four different variants were applied for the tools: 2 die inserts were coated with two different hybrid layers (GN + PVD type), i.e. AlCrTiN and AlCrTiSiN, one insert was only nitrided, and one was pad welded, to improve tool durability. The tool wear was analysed and represented by the material degradation on the working surface, based on the 3D scanning and the material growth of the periodically collected forgings. Additionally, the scanned tools were divided into two areas, in which it was found, based on the reliminary analysis, that various degradation mechanisms are predominant. Microstructural and hardness measurements of the analyzed tools were also performed. Based on the results, it was found that, in the central part of the die insert (area A), thermo-mechanical fatigue and wear occurred, while in the area of the bridge insert (area B), only abrasive wear could be observed. For these areas (A and B), the loss of material was determined separately. In area A for the inserts with hybrid layer GN+AlCrTiSiN and gas nitrided, an intensive increase of wear took place, which was not observed for the pad welded and GN+AlCrTiN layer insert, for which, together with the increase of the forging number, a proportional growth of the loss of material occurred. In area B the weakest results were obtained for the insert with GN+AlCrTiSiN layer, while wear of other die inserts grew similar and proportional.     

Lightweight mixture faults detection method for gasoline engine using on-line trend analysis

Mixture faults detection is meaningful for gasoline engines because proper mixture is the basic prerequisite for healthy running of a combustion engine. Among existing methods for faults detection, the data-driven trend analysis technique is widely used due to the simplicity and efficiency in time-domain. The CUSUM (Cumulative Sum Of Errors) algorithm is good at real-time trend extraction, but it’s easy to be costly on the fuel trim signal during the engine in normal working conditions, which will increase battery energy consumption because engine failure is rarely occurs. Hence, the conventional treatment methods of artifacts in the CUSUM algorithm are modified by means of decay function and detection time analysis. The thresholds are tuned according to the characteristics of artifacts instead of residual variability, which leads to better results of trend extraction and less computation. Then, the revised CUSUM algorithm is used for monitoring the mixture abnormal behaviors, and the mixture faults can be detected in real time through analyzing the variation features of fuel trim signal. The lightweight faults detector using the advanced CUSUM algorithm (FD-A-CUSUM) is evaluated on the experimental data collected from a Ford engine. The validation results show that while engine works under normal conditions, the computation of FD-A-CUSUM has decreased by 72.79 % in comparison with the detection method using the original CUSUM algorithm (FD-O-CUSUM), and the false alarm ratio of FD-A-CUSUM is 3.37 %. Futhermore, the detection results of FD-A-CUSUM for two leakage faults have achieved 91.18 % test accuracy.