Applied Mechanics and Materials Vol. 145

Abstract: Extensible Authentication Protocol (EAP) is a universal authentication framework defined by RFC3748 and updated by RFC5247. It is not a specific authentication mechanism for exclusive system and then the widespread acceptance and implementation in wireless networks or other Point-to-Point (P2P) connections. A number of vendor specific EAP methods were proposed for special purpose such as EAP-MD5, EAP-TLS, EAP-TTLS, EAP-PEAP, LEAP, SPEKE, EAP-SIM, EAP-AKA, EAP-FAST, and so on. All of them have a common characteristic that the client submitted his Security Association (SA) to the neighbor Access Point (AP), then AP forward it to identify his validity by Authentication Authorization Accounting (AAA) server of both sides. Although these EAPs are design to meet the widespread authentication demands. But in fact they have the independent authentication procedure respectively. That is they are incompatible with each other. For mobile devices, in order to meet the needs of different connection it had to support many of the EAPs. This situation for the most mobile devices is a heavy load and result the inconvenient which move in the different service network. This paper devotes in solves this situation. For this goal, an extensible authentication protocol for mobile equipment to heterogeneous network (EAP-M2H) is provided in the paper. EAP-M2H development from the EAP-AKA and improve their applicability and compatibility in heterogeneous network.

Abstract: In this study, we present an image identification and measurement system for examining and testing the packaged semiconductor specifications. Most semiconductor processes rely on measurement gauges or inspectors to examine the finished product specifications visually. Measurement gauges are costly; inspectors have to be trained professionally and their performance depends on the maturity of their skills, which requires enormous costs, time, and efforts. Therefore, an automatic identification and measurement system will not only reduce costs, but minimize the complexity of measurement, thereby upgrading the effectiveness of manpower significantly. Experiments were conducted using 1657 BMP images with 640 * 480 pixels taken with a semiconductor machine. These images are snapshots randomly taken from of a variety of the 7.2 cm * 4.8 cm Substrate circuit boards each includes 180 pieces of 30 * 6 IC packaged products. Promising results were derived where 1492 out of 1657 product images were successfully detected and measured. In addition to the 90.04% success rate for inspection, the process time is reduced significantly to about 1/6 as compared to human professionals.

Abstract: Existing wireless control laser pointer with the function of paging PPT in projector can control the move of the mouse pointer. The original problem is that the traditional wireless mouse is unhandy with the mouse pointer moving in frames. To address the difficulty, this project through the camera getting images on the projection screen can first determine the edge of the screen, using frame difference algorithm to extract feature points of the laser light, then call the API of windows and finally move the cursor to the appropriate specified place. Four image processing modules are designed in order to accomplish the process. The result turns out that the mouse can move freely according to the laser spot. Experimental results show that light intensity of the external environment does not affect the control. Moreover, under the normal indoor environment, mouse delay and maximum use of the distance meet the practical requirements.

Abstract: Biometrics is the technology to identify a user by using the physiological or behavioral characteristics. Among the biometrics such as fingerprint, face, iris, and speaker recognition, finger-vein recognition has been widely used in various applications such as door access control, financial security, and user authentication of personal computer, due to its advantages such as small sized and low cost device, and difficulty of making fake vein image. Generally, a finger-vein system uses near-infrared (NIR) light illuminator and camera to acquire finger-vein images. However, it is difficult to obtain distinctive and clear finger-vein image due to skin scattering of illumination since the finger-vein exists inside of a finger. To solve these problems, we propose a new method of enhancing the quality of finger-vein image. This research is novel in the following three ways compared to previous works. First, the finger-vein lines of an input image are discriminated from the skin area by using local binarization, morphological operation, thinning and line tracing. Second, the direction of vein line is estimated based on the discriminated finger-vein line. And the thickness of finger-vein in an image is also estimated by considering both the discriminated finger-vein line and the corresponding position of finger-vein region in an original image. Third, the distinctiveness of finger-vein region in the original image is enhanced by applying an adaptive Gabor filter optimized to the measured direction and thickness of finger-vein area. Experimental results showed that the distinctiveness and consequent quality of finger-vein image are enhanced compared to that without the proposed method.

Abstract: Military SoS increasingly shows its relation of complex network. According to complex network theory, we construct a SoS network topology model for network warfare simulation. Analyzing statistical parameters of the model, it is concluded that the topology model has small-world, high-aggregation and scale-free properties. Based on this model we mainly simulate and analyze vulnerability of the network. And this provides basis for analysis of the robustness and vulnerability of real battle SoS network.

Abstract: Early screening using appropriate biomarkers is helpful for the effective treatment of ovarian cancer. CA-125, the most widely used biomarker for the diagnosis of ovarian cancer, has high false positive and false negative rates. We introduce an approach for determining an appropriate combination of biomarkers known to be highly related to ovarian cancer among 21 predetermined biomarkers. Sera representing 27 cases and 31 controls from women undergoing surgery were examined using high-throughput, multiplexed bead-based immunoassays. Student’s t-test and a genetic algorithm (GA) were employed and compared for building the proper combination of two to four biomarkers. The combinations selected by both methods were compared with a 5-fold cross validation of the LDA classifier. The combination of four markers chosen by the GA had the best performance in regards to accuracy, with sensitivity and specificity of 81% and 100%, respectively.

Abstract: In this paper, a fuzzy neural network (FNN) compensator is proposed for the synchronous motion control of a gantry position stage. Firstly, the cascade control strategy is applied to reduce the single axis position tracking error. However, the synchronous error between dual servo systems is inevitable due to their inequality in characteristics and the environmental uncertainties. The FNN compensator and an online learning algorithm perform a fuzzy reasoning with two inputs of synchronous position and velocity errors between dual drive servo systems and generate the compensated force; the compensated force is fed back to the controller of each axis. The online learning algorithm adjusts the connected weighting of the neural network by using a supervised gradient descent methods, such that the define error function can be minimized. Finally, two kinds of position commands with high and low frequency are designed for the experiments, and the experimental results show that the proposed FNN compensator is feasible to improve the synchronous error of gantry stage.

Abstract: A three-dimensional finite element model of hydraulic excavator is proposed to simulate soil cutting. To consider nonlinear soil behaviors, we apply the theory of Arbitrary Lagrangian-Eulerian (ALE) and explicit dynamic method to analyze a large scale fluid-solid structure interaction problem. The elastic-plastic assumption theory is introduced to simulate soil material behavior during the process of soil cutting because the nonlinear elastic-plastic model has advantages of simultaneously accounting for dynamic effects of strain hardening, strain rate, automatic mesh contact with friction capability, soil mechanical behavior and soil-bucket interaction. Soil-bucket interaction is modeled as friction with adhesion depending upon different influencing factors. This paper also investigates the parameters that may cause computational instability in soil cutting analysis. The difficulties in the numerical simulation of soil cutting are overcome by adopting suitable parameters to meet the requirement of proper mesh separation criterion. The proposed modeling can also be used to predict soil stress distribution, soil deformation and Von Mises stress distribution of component in hydraulic excavator.

Abstract: Recent advances in coal mine safety training based on virtual reality in China are explored and reviewed according to the researches and papers in the last ten years, and the drawbacks in them are figured out, with some suggestions for further researches being given. A brief survey on the research contents is carried out with time as the clue in the first place, illustrating that more and more investigations and researches have been done over time. And then such issues as main research outlines, theories and algorithms, software and tools, and extent of achievement, are reviewed respectively. The drawbacks in these researches are that they are somewhat repetitive, too much contents and relatively superficial in one project, more geological modeling but less intelligent, lacking of high realistic and advanced system, and so on. We suggest that more attention should be paid to the following aspects: 1) More intelligent functions instead of just simple demonstrating and roaming; 2) studying and developing Coal Mine Safety Training Engine Based on Virtual Reality (CMSTEVR) by concentrating core strength, in order to reduce the large amount of elementary work such as geological modeling, etc; 3) Breaking through the real-time barrier of the accurate and complex calculations, and solving the integration and fusion issues between these kinds of calculations and VR software; 4) Developing Coal Mine Safety Training System by utilizing the most advanced and powerful Game Engine.

Abstract: Human eye state identification can be applied not only to monitoring of the drowsiness of a human car driver but also to medical treatment facilitating system for monitoring neonate or stuporous patient. Once the patient awake and open his eyes, human eye state identification system can notify nurses to take care of the patient. In this work, we propose an intelligent human eye state identification algorithm based on 2DPCA and skin color. Adaboost face detection function of OpenCV is first adopted to detect the human faces in color images acquired from camera. Then, we develop a more precise HSV skin color model and use it to eliminate the false alarms in the previous stage. Next, a heuristic segmentation method based on skin color and face geometry is proposed to segment the region of eyes, from which 2DPCA is then adopted to extract the features and identify the opening or closing state of eyes. We study three kinds of 2DPCA, i.e. 2DPCA, T-2DPCA and (2D)²PCA, and compare their performance. Experimental results reveal that our algorithm can achieve over 90% accuracy rate.