Special Issue "Sensor Algorithms"

Guest Editor
Dr. Costas Busch
Department of Computer Science, Louisiana State University, 296 Coates Hall, Baton Rouge, LA 70803, USA
Website: http://www.csc.lsu.edu/~busch
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The Special Issue Sensor Algorithms in the Journal Algorithms

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Sensors is a highly rated journal with a 1.573 impact factor in 2007. Sensors is indexed and abstracted very quickly by Chemical Abstracts, Analytical Abstracts, Science Citation Index Expanded, Chemistry Citation Index, Scopus and Google Scholar.

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Sensor Algorithms

Title: Spatio-temporal Analysis of Human Grip-forces with Sensor-arrays
Authors: Dieter F. Kutz 1, Alexander Wölfel 1, Dagmar Timmann 2 and Florian P. Kolb 1
1 Department of Physiological Genomics, Institute of Physiology, University of Munich Pettenkoferstr. 12, 80336 Munich, Germany
2 Department of Neurology, University of Duisburg-Essen, Hufelandstr. 55, 45138 Essen, Germany
Abstract: Standardised resistor-based pressure sensor-arrays for industrial and medical applications have been available for some time. The aim of this study is to present an application for measuring human grip forces exerted on a cylindric object via a sensor-array. We use a special grip rod (diameter 20 mm) that subjects can move actively in the horizontal direction or apply reactive forces against opposing forces applied by a linear motor to the rod. The sensor-array film is attached to the rod by adhesive tape and covers at least 50 cm2 of the rod surface with a sensor density of 4 / cm2, with each sensor having a force resolution of 0.1 N. The scan of the sensors results in a corresponding frame containing all force values at a frame repetition rate of 150/s. Force values of all sensors are interpreted as pixel values of a greyscale image. Bending the film around the grip rod evokes pre-loads that are interpreted as noise. Based on remote sensed image analysis an algorithm was developed to distinguish significant force-representing pixels from those affected by the noise. To determine the position, the contact area and forces exerted by individual fingers touching the rod, corresponding neighbouring pixels are combined. The position of identified fingers is tracked in subsequent frames to construct spatio-temporal grip-force profiles of an individual finger. The algorithms allow measurement of the forces exerted by any number of fingers simultaneously without any constraints on finger position and, thus, are suitable for basic and clinical research in human physiology as well as for psychophysics studies.

Turgay Temel
Article: A Power-aware Distributed Routing and Tasking Algorithm for Optimized Coverage of De-centralized Sensor Networks
Abstract: Sensor networks (SNET) are considered to be a major research area to benefit from multi-agent supervising of shared information concerning particular tasks, including target tracking, environmental mapping etc. Due to limited resources available, such as power and bandwidth, routing each sensor toward a specific task is an outmost important. However, in case of de-centralized tasking, a query-server (QS) should be elected such that an individual sensor assigned by it needs to be tasked for an optimized network coverage with limited power budget. Depending on the domain which may be deterministic or stochastic, the election of a locally-centered QS will impose an ill-conditioned burden for conservative use of resources, which also determines the lifetime of overall network. The de-centralized network configuration necessiates efficient investigation on possible scenarios of election for a QS and covered sensors. This study investigates a new approach to determine candidate QSs toward optimized network lifetime and network coverage based on power-awareness capability with neigboring sensors. A routing and task-assignment algorithm is also proposed and relevant performance measures are given and compared to previous algorithms.

Liangpei Zhang, Xin Huang
The State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing; Wuhan University, P. R. China
Article: Advances in feature extraction, mapping and application algorithms for very high resolution (VHR) remote sensors
Abstract: In recent years, the image processing algorithms for very high resolution (VHR) imagery have received much attention since this new data can provide a large amount of detailed ground information. However, the availability of this type of data poses challenges to image information extraction, classification and applications. This paper reviews the feature extraction, classification and application algorithms for imagery from the VHR sensors. First, we introduce the widely used VHR sensors (e.g. SPOT-5, QuickBird, IKONOS). Then, we present an overview of the new advances in feature extraction, including extraction of shape and structural information, exploitation of texture measures, and analysis of object-based segmentation. Meanwhile, the classifiers used for VHR image classification are also discussed, such as the traditional Gaussian maximum likelihood (GML), neural networks (NN), support vector machines (SVM), and machine learning algorithms. After that, the applications of the VHR sensors are summarized, concerning the environment management, precision farming, military applications, hazards monitoring, etc.
Keywords: VHR sensors, feature extraction, classification, classifiers.

Chunyu Ai, N. Xiong, A. Vasilakos, Yingshu Li
Article: Data Estimation in Sensor Networks Using Physical and Statistical Methodologies
Abstract: Wireless Sensor Networks (WSNs) are employed in many applications in order to collect data. One key challenge is to minimize energy consumption to prolong network lifetime. A scheme of making some nodes asleep and estimating their values according to the other active nodes’ readings has been proved energy-efficient. For the purpose of improving the precision of estimation, we propose two powerful estimation models, Data Estimation using Physical Model (DEPM) and Data Estimation using Statistical Model (DESM). DEPM estimates the values of sleeping nodes by the physical characteristics of sensed attributes, while DESM estimates the values through the spatial and temporal correlations of the nodes. Experimental results on real sensor networks show that the proposed techniques provide accurate estimations and conserve energy efficiently.

Jiang Dong , Jianhua Wang, Jingying Fu
Review: Advances in multiple resource data fusion: algorithm and application.
Abstract: With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have been available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. The paper presented an overview of advances in multi-sensor image fusion in recent years and focused on its main application fields in remote sensing, such as feature extraction, classification, change detection, etc. Methods for fusion evaluation were also described and discussed.

Shaohui Chen
Article: Scaling-up Transformation of Multisensor Images with Multiple Resolutions.
Abstract: Intensity hue saturation (IHS) and empirical mode decomposition (EMD) are two highly efficient image processing methods. In this paper, a combination of the IHS transform and the EMD is proposed as a general scaling-up transformation method for fusing high resolution panchromatic image (HRPI) with low resolution multispectral images (LRMIs). The principle consists of transforming the LRMIs into the IHS components.The low-resolution intensity component (LRIC) is fused with the HRPI in the EMD domain through a suitable model. Then, the high-resolution intensity component (HRIC) produced is substituted to the LRIC. High resolution multispectral images (HRMIs) are obtained through the inverse EMD and IHS transforms. Quickbird images are used to illustrate the superiority of this approach over the IHS and dyadic wavelet transform(DWT) based methods in terms of preservation of spectral properties visually and quantitatively.

Silvia Ferrari et al.
Article: Robust Deployment of Ocean Sensor Networks for Cooperative Target Tracking
Abstract: will be added soon

M. Baietto, A. D. Wilson, and D. Bassi
Review tentative title: Applications and advances in electronic-nose technologies
Abstract: will be added soon

Title: Designing, Control and in-situ Visualization of Gas Nitriding Process
Authors: Jerzy Ratajski¹, Roman Olik¹, Tomasz Suszko¹, Jerzy Dobrodziej², Jerzy Michalski^3
1Institute of Mechatronics, Nanotechnology and Vacuum Technique, Koszalin University of Technology
²Institute for Sustainable Technology, Radom
³Institute of Precision Mechanics, Warsaw
Abstract: The article presents a complex system of the designing, in-situ visualization and control of the commonly used process of surface treatment, the gas nitriding process. In the conception of computer designing, artificial intelligence methods were used taking into consideration difficulties in an analytical or numerical solution of complex thermodynamic problems concerning phase transformations among others. As a result, possibilities were obtained of the poly-optimization and poly-parametric simulations of the course of the process combined with a visualization of the changes of the values of parameters in the function of time, as well as possibilities of prediction of the properties of nitrided layers. For in-situ visualization of the growth of the nitrided layer, computer procedures were developed which make use of the results of the correlations of direct and differential voltage and time runs of the process result sensor (magnetic sensor), with the proper layer growth stage. Computer procedures make it possible to combine, in the duration of the process, registered voltage and time runs with the theoretical and experimental model of the process.