In this paper, a novel method for slip detection using a capacitive sensor is proposed. We perform the Discrete Wavelet Transform (DWT) on the original signals of sensor. By comparing different wavelets, we find that the Haar wavelet is the most suitable to separate different frequency components. After performing the DWT by using the Haar wavelet, the separated high frequency components are pairwise due to properties of the Haar wavelet. Different from setting thresholds to detect object slip, our method detects slip by observing the variation trend of pairwise high frequency components. Meanwhile, we can distinguish signals of object loading and slip respectively. We carry out experiments on several objects with different surface properties and the results are consistent with our observations.
This paper investigates the problem of observer-based controller design for nonlinear networked control systems subject to imperfect communication links. The Takagi-Sugeno (T-S) model is utilized to approximate the nonlinear plant. Both the imperfect sensor-to-controller and controller-to-actuator links are considered, which are described via two independent Bernoulli stochastic processes. A dynamic compensation strategy is adopted in the controller-to-actuator link. The premise variables of the observer and the controller to be designed depend on the state variables estimated by the observer instead of those of the plant. Moreover, sufficient criteria are obtained to guarantee the resulting closed-loop system to be stochastically stable with H∞ performance. Finally, a numerical example is provided to illustrate the effectiveness of the methodology proposed in this paper.
In this paper, wireless statistic division multiplexing (WSDM) is proposed for wireless communication systems, which is a multiplexing scheme that transmits multiple signals simultaneously in the same frequency band over wireless channels. Therefore, the spectrum efficiency of WSDM is high compared to that of time division multiplexing (TDM), frequency division multiplexing (FDM), and code division multiplexing (CDM). WSDM signal is different from TDM, FDM and CDM signal, which is limited in time interval or frequency band or code. The multiple source signals transmitted in WSDM based wireless communication systems are only required to be statistical independent or statistical distinguished. Source signals are recovered at the multiple-antenna receiver by statistical independence or statistical distinction from the received signals. We show theoretically that the information content of all the signal inputs can be recovered by WSDM system. Computer simulation and realistic experimental results validate the performance of our new WSDM system.
In this paper, continuous-time Zhang dynamics (CTZD) models and discrete-time Zhang dynamics (DTZD) models are proposed to solve in real time for the time-varying pth root, from real domain to complex domain. In addition, the convergence properties of the proposed Zhang dynamics (ZD) models are discussed and proved. Furthermore, exploiting different parameters in the proposed ZD models is investigated in order to achieve superior convergence and better accuracy. Computer-simulation and experiment results further substantiate the efficacy of the proposed ZD models. Moreover, the superiority of DTZD models is verified by comparing with Newton-Raphson iteration (NRI).
With the development of network technology and information technology, the complexity of the information system, information security defense has become a hard nut to crack for modern society. The information security defense is a multidisciplinary field involving management, technology, operation and so on. Based on the military balance operation mechanism, this paper studies the information system security theories and problems from an overall, systemic and multi-dimensionally perspective; Around the information attack-defense nature, puts forward a new information security defense mechanism, gives and analyzes the information security confrontation and control model. This paper provides a new train of thought for information security research.
How to detect pedestrian quickly and accurately in complex traffic scenes is the key to pedestrian detection. In contrast to most standard approaches for pedestrian detection and tracking, the approach in this paper has better robust and accuracy. The core part of the approach is to extract local corner features of the objects using Moravec algorithm in video image and achieve tracking these corner features in different image sequence by block matching. Experiment results show the capacity of the approach to detection and tracking is effective in different complicated traffic scenes.
In this paper, a robust direct adaptive fuzzy control scheme is presented for a class of discrete-time nonlinear systems in the strict-feedback form. The fuzzy logic system (FLS) is used to approximate the unknown system function of the system, and backstepping design procedure is employed in adaptive controller and the adaptation laws design. Compared with the existing results, the proposed controller lighten the online computational burden. It is shown via Lyapunov theory that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of zero by choosing the design parameters ap- propriately. A simulation example is employed to illustrate the effectiveness of the proposed scheme.
Over the past several years, The Mel-Frequency Cepstral Coefficients (MFCCs) and Gaussian mixture models (GMMs) using the well-known EM algorithm have become the state-of-the-art approach in text-independent speaker recognition applications. However, in recent few years, Self-Organizing Mixture Models which combines the strengths of Self-Organizing Maps and Mixture Models have been proposed in the literature and yielded better results than the classical GMM training in many applications. In this paper, firstly, the implementation and the comparison of the most popular MFCCs variants are done in order to find the best implementation for our speaker identification system. Then, The Self-Organizing Mixture Models are introduced for speaker modeling in text-independent speaker identification. The performance of the Self-Organizing Mixture Models is assessed and compared with the classical Gaussian mixture models using the EM algorithm.
In recent years, adaptive learning systems rely increasingly on concept maps to customize the educational logic developed in their courses. Most approaches do not take into account the possibility of combining the concept maps predefined by experts of field and those developed automatically using the Fuzzy Sets Theory. In this article, we present a hybrid approach using on the one hand the feedback from experts of domain to select, prioritize relevant concepts and create prerequisite relationships to get the initial concept map, on the other hand we use the fuzzy logic to measure relevance degree of all relationships existing in this concept map, these links are considered as fuzzy relationships. With this approach we got two types of prerequisite relationships between concepts, the first type can be classified as relationships correctly established by the expert. These relationships must be kept in the final concept map. The second type can be considered as relationships incorrectly established by the expert, because the concepts involved in these relationships are independent, in this case these relations must be deleted or substituted with the inverse of the original relations, or because the items used in evaluations of these concepts are inappropriate and must be reviewed.
The verification process in industrial context of embedded software in smart card is considered difficult, extremely time-consuming, and costly, with very few tools and techniques available to aid in the verification process. The work proposed in this paper consist to define the main architecture of testing java card application and a specific test model which consists of reducing a given java-card application to one method which have one input and one output data which correspond with the real communication between the card and the off-card applications. The paper details the first step of testing constraint specifications which consist of modeling and generating control flow graph in inter and intra procedural level from the byte code of java-card applications.
Today the world is moving towards wireless system. Wireless networks are gaining popularity to its peak today, as the users want wireless connectivity irrespective of their geographic position. Vehicular ad-hoc networks (VANETs) are considered to be the special application of infrastructure-less wireless Mobile ad-hoc network (MANET). In these networks, vehicles are used as nodes. In this paper, we examine and analyze the performance of Ad-hoc On-Demand (AODV), Dynamic Source Routing (DSR) and Destination-Sequenced Distance Vector (DSDV) routing in terms of Packet Delivery Ratio, Average End to End Delay, Latency and Throughput. The objective of this study is to find the best routing protocol over all circumstances. Based on our validated results, AODV performs the best among all evaluated protocols.
The clamp-on transit-time ultrasonic flow meters are widely applied for the advantage of noninvasive measurement and convenient deployment. Its key point lies on measuring of the time difference between the upstream and downstream. While high quality of the transducer transmitting/receiving ultrasonic signals is the premise of measuring time difference accurately. This paper studies on the main factors contributing to the uncertainty of the transducer's output signal and focuses on the transducer's frequency, incident angle and the separate distance. The selection principle of transducer's frequency is presented by the analysis of the ultrasonic attention characteristics in the liquid. The incident angle range and precise installation distance of the transducers are calculated and analyzed by Snell's law. Experiments are also carried out with the 1MHz transducers clamped on the aluminium pipe of 20mm outer diameter. The results show that the accurate calculation separate distance 18.16mm is effective to guarantee the output of high quality ultrasonic wave. If the axial installation error reaches more than 3mm, the one beam of ultrasonic signal cannot be guaranteed.
The optimized link state routing (OLSR) protocol is widely used in wireless ad hoc networks. With OLSR, only one routing path from source to destination is established at a time. However, links of wireless networks are very unreliable, and network topologies might vary rapidly. These features may cause frequent data retransmissions or the route rebuilding. Hence, improving the network throughput becomes a big challenge. This paper designs a new high-throughput routing protocol (HTRP) for wireless sensor networks, which combines the OLSR protocol with opportunistic routing and network coding. Opportunistic routing is able to leverage the wireless channel's characteristic of broadcasting and opportunistically deliver data through multiple routing paths. And OLSR can provide the information about network topologies and other parameters that opportunistic routing needs but cannot gain by itself. We evaluate the performance through both simulation and empirical experiments. The throughput of the HTRP is more than 10× and 2× of the OLSR protocol respectively in simulation and experiments.
This study aimed to propose, a different architecture of a collision detection neural network (DCNN). The ability to detect and avoid collision is very important for mobile intelligent machines. However many artificial vision systems are not yet able to quickly and cheaply extract the wealth information. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons linear and threshold logic, which simplified the actual implementation of all the networks proposed. This article represents a comprehensive algorithm that determine through the AMAXNET network a measure (a mini-maximum point) in a fixed time, which allows us to detect the presence of a potential collision.
Predicting user preferences and providing personalized services based on his past preferences present an important issue in the field of pervasive computing. However, studies considering users' preferences are relatively insufficient in this domain. The aim of this paper is to propose an approach to provide personalized services to users, using context history and machine learning techniques. In this approach, we integrate, to pervasive recommender systems, the ability of predicting user preferences on new context situations even in unforeseen contexts that have not been considered when building the knowledge base of the system. And this, in order to serve the user in a proactive and uninterrupted way in various contexts that may arise in the future.
In this paper, we present a hardware design which can support the inverse transform size from 32×32 in high efficiency video coding (HEVC) and is implemented by a using single 1-D IDCT core with a memory to low cost architecture. The proposed 1-D IDCT core employs two calculating paths to achieve a high throughput rate and is implemented by a 1-D inverse transform which can calculate 1st-D and 2nd-Ddata simultaneously in two parallel paths. The proposed 2-D transform core can implement a throughput rate of 332-Mpels/s with 129k gate area.
In this paper, we briefly analyzed the advantages of passive distance measurement based on Wireless Fidelity (WiFi). Based on the analysis of the principle of traditional interferometer direction finding, we derived the equations which are suitable for indoor distance measurement. Through theoretical analysis and simulation, we prove the correctness of the equations. Finally, we analyze and conclude the conditions of using the method, the scope of distance measurement, and the main influencing parameters of system accuracy.
Mobile positioning by cellular networks has received growing attention and several researches are carried out to enhance positioning algorithms and techniques that will be able to give better performance at multiple environments (outdoors/indoors). In this paper, we are interested in UTDOA (uplink time difference of arrival) approach to determine the location of a Mobile Station within an acceptable accuracy and respect of emergency cases in both areas (Indoor/Outdoor). The enhancement of this method is performed with adaptive filtering, with MATLAB software, using two different algorithm to show the advantages of the chosen one, and its efficiency in emergency calls even with legacy phones.
Understanding human mobility dynamics is of an essential importance to today mobile applications, including context-aware advertising and city wide sensing applications. Recently, Location-based social networks (LBSNs) have attracted important researchers' efforts, to investigate spatial, temporal and social aspects of user patterns. LBSNs allow users to "check-in" at geographical locations and share this information with friends. In this paper, analysis of check-ins data provided by Foursquare, the online location-based social network, allows us to construct a set of features that capture: spatial, temporal and similarity characteristics of user mobility. We apply this knowledge to location prediction problem, and combine these features in supervised learning for future location prediction. We find that the supervised classifier based on the combination of multiple features offers reasonable accuracy.
To separating the overlapping communication signals in time and frequency domain, wireless communication system constantly put forward higher demands for the performance of separation algorithm (convergence rate, separation precision) in order to achieve better separating effect. Current algorithm cannot satisfy these new demands. Recently Ebrahimzadeh proposed to use bees colony algorithm to separate signals for better performance of convergence rate and separate precision. This paper studies the bees colony algorithm deeply, and in view of the problems that the algorithm mainly depends on the method of 'casting net' and lack clear direction in the process of optimization, which generally leads to large computational load and some blindness, this paper proposes a modified bees colony algorithm with the 'directional indication' called Gradient-BCA (GBCA). GBCA takes the 'directional indication' based on gradient into the process of seeking optimization. Simulations suggest that GBCA has the better performance of convergence rate and separation precision than BCA and classic algorithm based on gradient. GBCA is more practical in separating the overlapping communication signals in time and frequency domain in wireless communication for the demand of the better performance of convergence rate and separation precision.
