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
E-mail:

Related Special Issue: The Special Issue Sensor Algorithms in the Journal Sensors

Submission

All papers should be submitted to algorithms@mdpi.org. To be published continuously until the deadline and papers will be listed together at the special issue website.

Submitted papers should not have been published nor be under consideration for publication elsewhere. All papers are refereed through a peer-review process. A guide for authors is available on the Instructions for Authors page. Algorithms is an international peer-reviewed quarterly journal published by Molecular Diversity Preservation International.

Open Access publication fees are 300 CHF per paper. English correction fees and/or formatting fees (250 CHF) will be added in certain cases (550 CHF per paper for those papers that require extensive additional formatting and/or English corrections.). For the first two issues to be published in 2008, the publishing fees will be waived for well-prepared manuscripts.

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Manuscript ID: algorithms-20080831-jia-cn
Title: Autonomous Vehicles Navigation with Visual Target Tracking: Technical Approaches
Authors: Zhen Jia, Arjuna Balasuriya and Subhash Challa
Abstract: This paper surveys the developments of the last 10 years in the area of vision based target tracking for autonomous vehicles navigation. First, the motivations and applications of using vision based target tracking for autonomous vehicles navigation are presented in the introduction section. It can be concluded that it is very necessary to develop robust visual target tracking based navigation algorithms for the broad applications of autonomous vehicles. Then this paper reviews the recent techniques in three different categories: vision based target tracking for the applications of land, underwater and aerial vehicles navigation. Next the increasing trends of using data fusion for visual target tracking based autonomous vehicles navigation are discussed. It can be seen that through data fusion the tracking performance is improved and becomes more robust. Based on the reviews, the remaining research challenges are summarized and future research directions are investigated.

Title: Retrieval algorithms for estimating soil moisture and vegetation biomass from satellite microwave images
Authors: S.Paloscia, P.Pampaloni, S.Pettinato, E.Santi
Abstract: to be added soon

Title: Energy-Efficient Adaptive Sensor Scheduling for Target Tracking in Wireless Sensor Networks.
Authors: Wendong Xiao, Lihua Xie, Sen Zhang, Frank L. Lewis
Affiliations: Institute for Infocomm Research, Singapore; Nanyang Technological University, Singapore; National University of Singapore; University of Texas at Arlington, USA
Abstract: to be added soon

Title: Deriving phytoplankton light absorption of the Arctic Ocean using ocean color: implications for phytoplanktonic response to ongoing global warming
Authors: Atsushi Matsuoka and Victoria J. Hill
Abstract: to be added soon

Title: Satellite remote sensing algorithms for cirrus cloud detection and retrieval
Author: Steve Ou
Abstract: to be added soon

Title: Algorithms of Active Suppresiion of Radiation and Scattering Acoustical Fields of some Physical Body in Liquid
Author: Vladimir Arabadzhi
Abstract: An algorithm of real time suppression of radiation and scattering fields of vibrating smooth closed surface of arbitrary shape body in a liquid is designed and investigated. The range of suppression frequencies permits both small and large wave dimensions of the surface protected. An active control system designed consists of: (a) a subsystem for fast forming of desired distribution of normal oscillatory velocities or displacements (on the basis of pulsed Huigence's sources) and (b) a subsystem for catching and targeting of incident waves on the basis of one level grid of the monopole microphones, embracing the surface protected. The efficiency and stability of control algorithm are considered. The algorithm forms the control signal during the time much smaller than the minimum time scale of the waves to be damped. The algorithm suggested includes logical and nonlinear operations, thus excluding reduction of the control system to some traditional combination of linear electric circuits with steady-state parameters constant in time. This algorithm converts some physical body in liquid into a transparent body relating to some predetermined class of incident waves. The active control system requires accurate information on its geometry, but need’t both a prior and current information on the vibroacoustical characteristics of the surface protected which present a vast data amount in practical cases.

Title: A survey on routing algorithms based on sensor position information in sensor networks
Authors: Jin Zhang, Si-wang Zhou, Ya-ping Lin, Guang Li
Abstract: to be added soon

Title: Semi-empirical algorithm for the retrieval of ecology-relevant water constituents in various aquatic environments
Author: Dmitry Pozdnyakov
Abstract: to be added soon

Title: A Survey on Star Identification Algorithms
Author: Benjamin B. Spratling and Daniele Mortari
Abstract: The author surveys algorithms used in star identification, commonly used in star trackers to determine the attitude of a spacecraft. Star Trackers are a staple of attitude determination systems for most types of satellites. The paper covers: (a) lost-in-space algorithms (when no a priori attitude information is available), (b) recursive algorithms (when some a priori attitude information is available), (c) and non-dimensional algorithms (when the star tracker calibration is not well-known). The performance of selected algorithms and supporting algorithms are compared.

Title: Wavelet Entropy for Millimeter Wave Conducted Speech Enhancement
Author: Sheng Li, Jianqi Wang, Tian Liu, and Xijing Jing
Abstract: By means of millimeter wave radar, a new non-air conducted speech detecting method is developed in our laboratory. Since the special attribute of the millimeter wave, this method may extend the traditional speech detecting method to a large extent. However, the additive combined noises which are composed of radar harmonic noise, electrocircuit noise, and ambient noise corrupted the radar speech greatly. This study, therefore, proposed an improved spectrum subtract algorithm, which is based on adaptive detecting voiced and unvoiced section by using wavelet entropy analysis. The results from both simulation and evaluations are also compared to the traditional spectral subtraction algorithm, suggest that this method achieves a better reduction of the whole-frequency noise, as well as musical noise, and yields good speech quality.

Title: Variations on the Kalman filter for aircraft engine health monitoring
Authors: Olivier Léonard and Sébastien Borguet
Affiliation: University of Liège, Belgium
Abstract: The concept of condition-based maintenance is widely recognised in the aircraft engine community as a means to improve engine safety and operability as well as to reduce its life cycle costs. In this perspective, generating a reliable information about the health condition of the engine is a requisite. Module performance analysis aims at assessing the changes in the performance of the engine components, described by so-called health parameters, on the basis of measurements collected along the gas path of the engine. Among numerous possibilities, the evaluation of the health parameters can be cast as a parameter estimation problem. The celebrated Kalman filter has enjoyed a reasonable success in estimating the health parameters. This algorithm can be seen as a minimum mean-squared-error (variance) estimator within a recursive framework. With respect to the specificity of engine performance monitoring, the Kalman filter possesses a number of appealing features. Indeed, it takes into account the noisy nature of the data, it allows a prior knowledge to be set on the parameters, it is recursive and it has a moderate computational burden. Modifications of the generic algorithm can however be considered in order to further enhance its capability to track accurately the health condition of an engine. Three directions investigated by the authors are reported in the subsequent paragraphs. The first area for possible enhancement is the robustness of the Kalman filter with respect to sensor faults. In the derivation of the Kalman filter, the measurement noise is modelled as a zero-mean, white, gaussian random variable. Obviously, this assumption is not verified when instrumentation faults occur. As a result, the identified health parameters tend to diverge from their actual values which strongly deteriorates the relevance of the diagnosis. Robustness against outliers can efficiently be blended in the algorithm by replacing the Gaussian distribution for the measurement noise by the Huber distribution, leading to a Quadratic Programming problem for which efficient solvers are available. The second area for improvement is linked to the temporal evolution of the engine health. The Kalman filter has proven its capability to track gradual deterioration with a good accuracy, but its response to an abrupt fault is a long delay in recognising the fault, and/or a spread of the estimated fault on several components whereas it generally impacts only a reduced number of them. The main reason of this deficiency lies in the transition model of the parameters that is blended in the Kalman filter and assumes a smooth evolution of the engine condition. The tracking of abrupt faults is enhanced by combining the Kalman filter and a secondary system that monitors the residuals in order to detect and estimate the abrupt fault event.
The third area for innovation is related to the nature of the data. Most of the applications reported so far make use of measurements collected during steady-state operation of the engine. However, processing measurements obtained during transient operation of the engine has been shown to significantly improve the diagnosis procedure. The level of information about the condition of the engine is indeed much richer during a transient sequence due to the large number of operating points traversed. During a transient analysis, two tasks must be performed simultaneously : the estimation of the state variables associated to the dynamic behaviour of the engine and the identification of the health parameters. This is carried out by running two Kalman filters in parallel, each dedicated to one of both tasks.
The present paper reviews the aforementioned modifications to the Kalman filter at the theoretical level and illustrates the expected improvements through a number of scenarios simulated with a generic commercial turbofan model.

Title: Kernel Extrapolation Methods for Probabilistic Gas Distribution Modelling
Author: Achim Lilienthal
Affiliation: Örebro University, Department of Technology, AASS Learning Systems Lab, 70182 Örebro, Sweden
Abstract: Gas distribution modelling is the task of deriving a truthful representation of the observed gas distribution from a set of spatially and temporally distributed measurements. It is a very challenging task mainly because in many realistic scenarios gas is dispersed by turbulent advection. Instead of trying to solve the fluid dynamics equations, we propose to create a probabilistic model of the observed gas distribution, treating gas sensor measurements as random variables. To create a probabilistic gas distribution model, we propose and discuss Kernel extrapolation algorithms, which model the observed variance in addition to the distribution mean. We derive the algorithm and present a method for learning the hyper-parameters. Based on real world data collected with a mobile robot that was periodically stopped at pre-defined points to carry out the measurements, we demonstrate the consistency of maps obtained from stationary and mobile sensors and present a quantitative comparison with alternative approaches.

Title: An investigation of DMSP Special Sensor Microwave Imager (SSM/I) nonlinearity
Authors: Banghua Yan and Fuzhong Weng
Abstract: will be added soon

Title: Sensor Algorithms for Damage Detection with Active Sensing Technology
Author: Lingyu (Lucy) Yu and Victor Giurgiutiu
Abstract: will be added soon

Title: Closed Loop Insulin Delivery Systems: a Review
Author: Joseph El Youssef, Jessica Castle and W. Kenneth Ward
Abstract: With the discovery of insulin came a deeper understanding of therapeutic options for one of the most devastating chronic diseases of the modern era, diabetes mellitus. The use of insulin in the treatment of diabetes, especially in those with severe insulin deficiency (type 1 diabetes), by the use of multiple injections or continuous subcutaneous infusion, has been largely successful, but the risk for short term and long term complications remains substantial. Insulin treatment decisions are based on the patient’s knowledge of the intermittent blood glucose values, meal size, and exercise plans, and as such are open loop methods that require input of a human. The idea of closed loop control of diabetes treatment is quite different: automated control of a device that delivers insulin (and possibly glucagon or other medications). Closed loop insulin control for type 1 diabetes is not new but is far from optimized. The goal of such a system is to avoid short-term complications (hypoglycemia) and long-term complications (disease of the eyes, kidneys, nerves and cardiovascular system) by mimicking the normal insulin secretion pattern of the pancreatic beta cell.
A control system for automated diabetes treatment consists of three major components, (1) a glucose sensing device that serves as the afferent loop of the system; (2) an automated control unit that uses algorithms which acquires sensor input and generates treatment outputs; and (3) a drug delivery device (primarily for delivery of insulin), which serves as the system’s efferent loop.
There are several major issues that highlight the difficulty of interacting with the complex unknowns of the biological world. For example, development of accurate continuous glucose monitors is crucial; the state of the art in 2008 is that such devices sometimes experience drift and are intended only to supplement information received from standard intermittent blood glucose data. In addition, it is important to acknowledge that an “automated” closed loop pancreas cannot approach the complexity of the normal human endocrine pancreas, which takes continuous data from substrates, hormones, paracrine compounds and neural inputs, and in response, secretes four hormones. Another major issue is the substantial absorption/action delay of insulin given by the subcutaneous route. Because of this delay, some researchers have recently given a portion of the meal-related insulin in an open loop manner before the meal and found this hybrid approach to be superior to closed loop control.
Proportional-Integral-Derivative (PID) systems adapted from the industrial sector utilize control algorithms that alter output based on proportional (difference between actual and target levels), derivative (rate of change) and integral (time-related summative) errors in glucose. These algorithms, and adaptations, have proven to be largely effective. Related algorithms include a “fading memory” system that combines the proportional-derivative components of a classic PID system with time-relating decay of input signals that allow greater emphasis on more recent glucose values, a characteristic noted in mammalian beta-cells.
Model Predictive Control (MPC) systems create mathematical models based on observations of biological behavior patterns using system identification and have now been tested in humans. The application of further mathematical models, such as fuzzy control and artificial neural networks, are also promising, but are largely clinically untested.
In summary, the prospects for closed loop control of glycemia in persons with diabetes have improved considerably. Major limitations include the delayed absorption/action of subcutaneous insulin and the imperfect accuracy of currently-available continuous glucose sensors.

Title: Mathematical ProgrammingTechniques in Sensor Applications
Authors: Vladimir Boginski; Panos Pardalos
Abstract: coming soon

Title: Methodology, Algorithms, and Emerging Tool for Automated Design of
Intelligent Integrated Multisensor Systems
Authors: Kuncup Iswandy and Andreas König
Abstract: The emerging of novel sensing elements, computing nodes, wireless communication and integration technology provides unprecedented possibilities for intelligent systems design and application. Each new application system must be designed from scratch employing sophisticated methods from conventional signal processing to computational intelligence. Currently, a significant part of this overall algorithmic chain still has to be assembled manually in a time and labor consuming process by experienced designers. In this research work, the challenge is picked up and a methodology and algorithms for automated design of intelligent integrated and resource-aware multisensor systems is introduced, employing multi-objective evolutionary computation. A benchmark gas sensor data of gas recognition example is investigated in our experiments. The experimental results prove the effectiveness of our proposed methodology and tool, where competitive results in terms of classification accuracy and flexibility can be achieved.