18413233
Range-Free Localization Using Expected Hop Progress in Wireless Sensor Networks
Localization algorithm continues to be an important and challenging topic in today's wireless sensor networks (WSNs). In this paper, a novel range-free localization algorithm using expected hop progress (LAEP) to predict the location of any sensor in a WSN is proposed. This algorithm is based on an accurate analysis of hop progress in a WSN with randomly deployed sensors and arbitrary node density. By deriving the expected hop progress from a network model for WSNs in terms of network parameters, the distance between any pair of sensors can be accurately computed. Since the distance estimation is a key issue in localization systems for WSNs, the proposed range-free LAEP achieves better performance and less communication overhead as compared to some existent schemes like DV-Hop and RAW. In addition, we study the effect of anchor placement on the algorithm performance by deriving the corresponding mean position error range. Extensive simulations are performed and the results are observed to be in good agreement with the theoretical analysis.
38892570
Nonuniform Deployment Prolongs Lifetime of Wireless Sensor Networks
A sweater having windbreaking characteristics especially usable by active sportsmen such as golfers who must concentrate on their golf swing, is disclosed. The sweater is a relatively thin pullover type which has an outer layer and a layer adjacent the wearer's body of flexible, quiet, warm and soft material with a very thin windproofing layer sandwiched between the outer layer and body layer. Said windproofing layer is divided into five sections or parts: a torso and two lower arm sections which are loosely attached to the inner-facing surface of the outer layer and two upper arm sections loosely attached to the outer facing surface of the body layer in a manner that the windproofing layer does not make any noise, can be very thin because it is protected by the inner and outer layer, and does not restrict the freedom of movement of the wearer.
6062507
On Data Fusion and Lifetime Constraints in Wireless Sensor Networks
The problems of energy efficient sensor network configuration and local fusion of sensed data have been addressed separately in the previous works. In this paper, we propose to analyze the sensing accuracy with the consideration of the node distribution and fusion overhead in terms of the energy consumption. By extending existing sensing model in the literature, we quantify how the sensing ranges and node densities of sensor nodes impact the sensing accuracy, and how it affects the fusion overhead and the sensing lifetime of the network. We identify the tradeoff between sensing accuracy and energy consumption in an analytical framework. It can be used to choose optimal parameters of sensor networks to meet the specified sensing or lifetime requirements.
9019882
Intrusion Detection in Homogeneous and Heterogeneous Wireless Sensor Networks
Intrusion detection in Wireless Sensor Network (WSN) is of practical interest in many applications such as detecting an intruder in a battlefield. The intrusion detection is defined as a mechanism for a WSN to detect the existence of inappropriate, incorrect, or anomalous moving attackers. For this purpose, it is a fundamental issue to characterize the WSN parameters such as node density and sensing range in terms of a desirable detection probability. In this paper, we consider this issue according to two WSN models: homogeneous and heterogeneous WSN. Furthermore, we derive the detection probability by considering two sensing models: single-sensing detection and multiple-sensing detection. In addition, we discuss the network connectivity and broadcast reachability, which are necessary conditions to ensure the corresponding detection probability in a WSN. Our simulation results validate the analytical values for both homogeneous and heterogeneous WSNs.
19569321
An Efficient Data Exchange Protocol Using Improved Star Trees in Wireless Sensor Networks
In wireless sensor networks, it is necessary and important to send information to all nodes. In some situation, every node has its own data to send to all the other nodes. The communication patterns are all-to-all broadcasting, which is called data exchange problem. In this paper, we present an efficient data exchange protocol using improved star trees. We divide the sensor area into four equal grids and each sensor node associates itself with a virtual grid based on its location information. These grids can be divided again if necessary. In each grid, we calculate the position of root node with location information of sensor nodes. Then, an efficient data exchange Star-Tree was constructed and used to achieve the exchange behavior in the grid. The fused data of each grid was sent to the center node. Simulations show that our protocol can prolong the lifetime about 69% to the multiple-chain protocols, and the delay can be reduced at least 35%.
6926567
Semi-Latent Dirichlet Allocation: A Hierarchical Model for Human Action Recognition
We propose a new method for human action recognition from video sequences using latent topic models. Video sequences are represented by a novel "bag-of-words" representation, where each frame corresponds to a "word". The major difference between our model and previous latent topic models for recognition problems in computer vision is that, our model is trained in a "semi-supervised" way. Our model has several advantages over other similar models. First of all, the training is much easier due to the decoupling of the model parameters. Secondly, it naturally solves the problem of how to choose the appropriate number of latent topics. Thirdly, it achieves much better performance by utilizing the information provided by the class labels in the training set. We present action classification and irregularity detection results, and show improvement over previous methods.
9587091
Topology control for delay-constraint data collection in wireless sensor networks
Data collection is one of the most important operations in wireless sensor networks. Many practical applications require the real-time data transmission, such as monitoring, tracking, etc. In this paper, we import and define the topology control problem for delay-constraint data collection (TDDC), and then formalize this problem into an integer programming problem. As NP-Hardness of this problem, we present a load-aware power-increased topology control algorithm (namely LPTC) to heuristically solve the problem. The theoretical analysis shows that this algorithm can reach O(1)-approximation ratio for the linear networks. And we also analyze the impact of the delay-constraint on the worst-case for the planar networks. Moreover, this paper designs two localized algorithms, called as SDEL and DDEL, based on the area division for TDDC problem. The experimental results show that LPTC algorithm can save at least 17% power consumptions compared with HBH algorithm in many situations.
5756583
Face Relighting from a Single Image under Arbitrary Unknown Lighting Conditions
In this paper, we present a new method to modify the appearance of a face image by manipulating the illumination condition, when the face geometry and albedo information is unknown. This problem is particularly difficult when there is only a single image of the subject available. Recent research demonstrates that the set of images of a convex Lambertian object obtained under a wide variety of lighting conditions can be approximated accurately by a low-dimensional linear subspace using a spherical harmonic representation. Moreover, morphable models are statistical ensembles of facial properties such as shape and texture. In this paper, we integrate spherical harmonics into the morphable model framework by proposing a 3D spherical harmonic basis morphable model (SHBMM). The proposed method can represent a face under arbitrary unknown lighting and pose simply by three low-dimensional vectors, i.e., shape parameters, spherical harmonic basis parameters, and illumination coefficients, which are called the SHBMM parameters. However, when the image was taken under an extreme lighting condition, the approximation error can be large, thus making it difficult to recover albedo information. In order to address this problem, we propose a subregion-based framework that uses a Markov random field to model the statistical distribution and spatial coherence of face texture, which makes our approach not only robust to extreme lighting conditions, but also insensitive to partial occlusions. The performance of our framework is demonstrated through various experimental results, including the improved rates for face recognition under extreme lighting conditions.
6194383
Deep Web Navigation by Example
An arc furnace for quickly and continuously melting directly reduced iron ore so as to make steel, wherein the furnace wall above the hearth line and the furnace roof have partly spherical inner surfaces, the spherical surface defining these inner surfaces having the center located adjacent to the point equidistantly spaced apart from the lower ends of electrodes, and the electrodes are inclined at an angle to the vertical so that the distance between the lower ends thereof may be reduced to a minimum.