Earticle

A novel operator is presented which is suitable for object detection in images. The operator creates a so called area map of an image. Each element in this area map is calculated by evaluating an indicator function which computes the size of image areas according to predened and problem specic properties. In general, results are approximate, so further renement and verication is necessary for a reliable outcome of object detection. In this work the area map approach is categorized in relation to classical image processing algorithms and the dierence to other approaches is pointed out. Two specic area maps, the DecAMap (decrementing area map) and the IncAMap (incrementing area map) are used to illustrate the principle of operation on an example of indentation detection in Vickers hardness testing images.

In this work, we use the formulas of statistic techniques for developing an algorithm based on third order moments and autocorrelation function. This algorithm permits to identify non linear system coefficients for recovering the real information from input-output systems. Simulation examples and comparison with other method in the literature are provided to verify the performance of the developed algorithm. The obtained results demonstrate the efficiency and the accuracy of the developed algorithm for non linear system identification under various values of signal to noise ratio (SNR) and different sample sizes N. To corroborate the theoretical results for a real process, we applied the developed algorithm to search a model able to represent the internet traffic data.

Recent investigations illustrate that view-based methods, with pose normalization pre-processing get better performances in retrieving rigid models than other approaches and still the most popular and practical methods in the field of 3D shape retrieval [1, 2, 3, 4, 5]. In this paper we present an improvement of 3D shape retrieval methods based on bag-of features approach. These methods use this approach to integrate a set of features extracted from 2D views of the 3D objects using the SIFT (Scale Invariant Feature Transform [6]) algorithm into histograms using vector quantization which is based on a global visual codebook. In order to improve the retrieval performances, we propose to associate to each 3D object its local visual codebook instead of a unique global codebook. The experimental results obtained on the Princeton Shape Benchmark database [6], for the BF-SIFT method proposed by Ohbuchi, et al., [2] and CM-BOF proposed by Zhouhui, et al., [3], show that the proposed approach performs better than the original approach.

We treat in this paper the implementation of a graphic tool which allows to personalize smart card (JavaCard cards), which use the RSA (Rivest Shamir Adleman) algorithm and ECDSA (Elliptic Curve Digital Algorithm) for the authentication of the card by the personalization tools and by the authorization server of the card issuer and transforming them as bank cards and securing their use during the transactions of payment, credit, withdrawal, load of the electronic purse or the payment by PME (electronic purse). This personalization software secures the creation of a bank account by a strong authentication and realize the creation and the personalization of a bank card, the visualization of the data of the card, the consultation of the account, the putting an account or a card in opposition, the canceling of the last opposition of an account or a card, the blocking and the unblocking of a card, the blocking and the unblocking of an application as well as the consultation of the online and offline financial records and the commands sent to a card.

There are innumerable situations where the data observed from a non-stationary random field are collected with missing values. In this work a consistent estimate of the evolutionary spectral density is given where some observations are randomly missing

In the domain of Human-Computer Interaction (HCI), the main focus of the computer is to interpret the external stimuli provided by users. Moreover in the multi-person scenar- ios, it is important to localize and track the speaker. To solve this issue, we introduce here a framework by which multi-modal sensory data can be eciently and meaningfully com- bined in the application of speaker tracking. This framework fuses together four dierent observation types taken from multi-modal sensors. The advantages of this fusion are that weak sensory data from either modality can be reinforced, and the presence of noise can be reduced. We propose a method of combining these modalities by employing a particle lter. This method oers satised real-time performance. We demonstrate results of a speaker localization in two- and three-person scenarios.

The diversity, heterogeneity and innovation in network application domain prompted a new era of Internet. Many technologies such as ATM, Frame Relay, X.25, etc., were developed to provide alternative for communication in networked systems, but could not succeed to get evolved as one of the alternate / replacement technology for the Internet. The Internet adopted a method of patchwork approach to cope with the needs of evolution and revolution of technology growth with acceptable cost and speed. The Internet is not designed for any specific application purposes; rather it is for generic and evolves purposes. The Future Network is expected to hosts much more than today's applications in an efficient manner, but researcher predicted rigidity as one of the failure factors for Current Internet (CI). In this paper the authors’ emphasis on the development of the improved Future Network using with broker's communication which works based on SOA while accounting and addressing the issues of CI failure factors.

Clustering provides an effective method for improving the performance of wireless sensor networks (WSNs). In this paper, we study that different number of clusters leads to different network performance on the energy consumption, energy balancing and network lifetime. We propose an Energy-Efficient Multi-hop Hierarchical Routing Protocol (MHRP) for wireless sensor networks to enhance the network lifetime and avoid the formation of energy holes. MHRP is a hierarchical routing protocol which selects sensor nodes with criterion of residual energy level to act as cluster heads and establish intra-cluster multi-hop routing based on the tradeoff between the two criteria of residual energy level and distance. Simulation results show that our MHRP can largely reduce the total energy consumption and significantly prolong the network lifetime compared to other routing algorithm like LEACH.

Clustering is an efficient technique that is widely adopted in wireless sensor networks. It divides network into clusters and let cluster heads be responsible for forwarding aggregated data to the sink. With energy efficiency in account, the conflict between an individual node and the entire network remains to be solved. In this paper, we propose a Density-based Energy-efficient Game-theoretic Routing Algorithm (DEGRA). As a clustering algorithm, DEGRA adopts game theory and set a utility function based on the nodes’ density, residual energy and average energy consumption of its neighboring nodes. Cluster heads are iteratively selected. We also design the intra-cluster and multi-hop inter-cluster routing algorithms. Simulation results show that cluster heads are evenly distributed and our proposed routing algorithm do consume much less energy than algorithms such as LEACH and DEER. The network lifetime is also largely prolonged.

In this work, effect of substrate properties on the performance of microstrip patch antenna is presented. Proposed geometry has been optimized to achieve a useful impedance bandwidth from 2.30 to 2.46 GHz at VSWR ≤ 2. Comparison has been done on the basis of physical dimensions, gain response and radiation properties.

Network based attacks have become a serious threat to the critical information infrastructure on which we depend .Identifying the source of the attackers behind the stepping stone(s), it is necessary to correlate the incoming and outgoing flows or connections of a stepping stone. To resist attempts at correlation, the attacker may encrypt or otherwise manipulate the connection traffic. Timing based correlation approaches have been shown to be quite effective in correlating encrypted connections. However, timing based correlation approaches are subject to timing perturbations that may be deliberately introduced by the attacker at stepping stones. In this paper we propose a novel watermark-based correlation scheme that is designed specifically to be robust against timing perturbations. Unlike most previous timing based correlation approaches, our watermark-based approach is “active” in that it embeds a unique watermark into the encrypted flows by slightly adjusting the timing of selected packets. The unique watermark that is embedded in the encrypted flow gives us a number of advantages over passive timing based correlation in resisting timing perturbations by the attacker.

In this paper we present a visible obstacle mobility model based on activity area (VOMBAA) for ad hoc network. Typical examples where the nodes of mobile ad hoc network are human-operated are natural or man-made disasters, military activities and so on. In these scenarios, people don’t move random and their sights are obstructed by obstacles. In the proposed mobility model, nodes are divided into several clusters. Each cluster has properties of activity area, speed, pause time and capacity. According to different clusters, the corresponding nodes’ activity areas are also different. There are no existed roads in this model, the nodes move around the obstacles in a natural and realistic way. When there are obstacles in the line that connected the node’s current position and the final destination point, the node will move to a current visible obstacle’s vertex to bypass the obstacle. The path that the node selected is the current shortest path from the source point to the destination point. Simulation results show that the proposed model has different impacts on network topology and routing performance.

In scenarios of real-time data collection in long-term deployed Wireless Sensor Networks (WSNs), low-latency data collection and long network lifetime become key issue. We propose a Long-Lifetime and Low-Latency Data Aggregation Scheduling algorithm (L4DAS) in wireless sensor networks. Firstly, we formally formulate the problem of long-lifetime and minimum-latency aggregation scheduling as a constrained optimization problem, and then propose an approximation algorithm for this problem by constructing a degree-bounded minimum height spanning tree as aggregation tree and designing a maximum interference priority scheduling scheme to schedule the transmission of nodes in aggregation tree. Finally, through the simulation and comparisons, we prove the effectiveness of the algorithm.

Secure user authentication without repeating registration is one of the important issues in multi-server networks that needs to be adequately addressed. Recently, two-factor (smart card and password) based remote user authentication protocols have been widely introduced due to their low constructional cost and convenient usability for the authentication purpose. In 2011, Chang and Cheng proposed a smart card and password based remote login mechanism for multi-server environments. However, in this paper, we found that Chang-Cheng's mechanism suffers from susceptibility to security attacks. As a result, we introduced an improved version of smart card based password authentication mechanism in multi-server networks. Compared with other related protocols, performance analysis shows that our proposed mechanism is still cost-efficient for the real application in multi-server environments.

Wireless mesh networks (WMNs) are wireless access networks based on IP technologies, which combine the advantages of WLANs and ad hoc networks and have thus become broadband access networks with high capacity, high speed and wide coverage. Due to the multi-hop characteristics of WMNs, security has become a critical issue in WMNs and a simple and effective distributed key management is essential for the development of secure WMNs. In this paper, we propose a distributed key management scheme in WMNs by combing several key technologies, such as ECC, (t, n) threshold cryptography, verifiable secret sharing, etc. Based on a zone-based hierarchical model, our proposed key management scheme is comprised of two parts: group key management in the backbone network and session key establishment in the zone networks. We also show the security and the effectiveness of the proposed scheme through analysis and simulations.