Maximum Likelihood Approach for RFID Tag Set Cardinality Estimation with Detection Errors

Estimation schemes of Radio Frequency IDentification (RFID) tag set cardinality are studied in this paper using Maximum Likelihood (ML) approach. We consider the estimation problem under the model of multiple independent reader sessions with detection errors due to unreliable radio communication links and/or collisions. In every reader session, both the detection error probability and the total number of tags are estimated. In particular, after the $R$ -th reader session, the number of tags detected in $j$ ( $j=1,2,...,R$ ) reader sessions out of $R$ sessions is updated, which we call observed evidence. Then, in order to maximize the likelihood function of the number of tags and the detection error probability given the observed evidences, we propose three different estimation methods depending on how to treat the discrete nature of the tag set cardinality. The performance of the proposed methods is evaluated under different system parameters and compared with that of the conventional method via computer simulations assuming flat Rayleigh fading environments and framed-slotted ALOHA based protocol.     

Antifungal efficiency of corona pretreated polyester and polyamide fabrics loaded with Ag nanoparticles

This study discusses the possibility of using the corona (electric discharge at atmospheric pressure) treatment for fiber surface activation that can facilitate the loading of Ag nanoparticles (NPs) from colloids onto the polyester and polyamide fabrics and thus enhance their antifungal activity against Candida albicans. The laundering durability of achieved effects and the influence of dyeing of fabrics with disperse dyes on their antifungal efficiency were studied. The morphology of fibers loaded with Ag nanoparticles was characterized by SEM whereas X-ray photoelectron spectroscopy was used for the evaluation of surface chemical changes. Corona pretreated polyester and polyamide fabrics loaded with Ag nanoparticles showed better antifungal properties compared to untreated fabrics. The advantage of corona treated fabrics became even more prominent after washing test, particularly for polyester fabrics. Antifungal efficiency of polyester and polyamide fabrics loaded with Ag nanoparticles were almost unaffected by dyeing process.     

A 3D unsplit-advection volume tracking algorithm with planarity-preserving interface reconstruction

A new volume tracking method is introduced for tracking interfaces in three-dimensional (3D) geometries partitioned with orthogonal hexahedra. The method approximates interface geometries as piecewise planar, and advects volumes in a single unsplit step using fully multidimensional fluxes that have their definition based in backward-trajectory remapping. By using multidimensional unsplit advection, the expense of high-order interface reconstruction is incurred only once per timestep. Simple departures from strict backward-trajectory remapping remove any need for consideration of volume computations involving shapes consisting of non-planar ruled surfaces. Second-order accuracy of the method is demonstrated even for vigorous 3D deformations.     

A Class of Algorithms for Collision Resolution with Multiplicity Estimation

The wireless connectivity in pervasive computing has ephemeral character and can be used for creating ad hoc networks, sensor networks, connection with RFID (Radio Frequency Identification) tags etc. The communication tasks in such wireless networks often involve an inquiry over a shared channel, which can be invoked for: discovery of neighboring devices in ad hoc networks, counting the number of RFID tags that have a certain property, estimating the mean value contained in a group of sensors etc. Such an inquiry solicits replies from possibly large number of terminals n. This necessitates the usage of algorithms for resolving batch collisions (conflicts) with unknown conflict multiplicity n. In this paper we present a novel approach to the problem of collision resolution for batch conflicts. We show how the conventional tree algorithms for collision resolution can be used to obtain progressively accurate estimation of the multiplicity. We use the estimation to propose a more efficient binary tree algorithm, termed Estimating Binary Tree (EBT) algorithm. The EBT algorithm is suited for implementation when the conflicting nodes are passive, such as e.g. RFID tags. We extend the approach to design the Interval Estimation Conflict Resolution (IECR) algorithm. For n→∞ we prove that the efficiency achieved by IECR for batch arrivals is identical with the efficiency that Gallager’s FCFS algorithm achieves for Poisson packet arrivals. For finite n, the simulation results show that IECR is, to the best of our knowledge, the most efficient batch resolution algorithm reported to date.     

Validation of MERIS LAI and FAPAR products for winter wheat-sown test fields in North-East Bulgaria

Progress in deriving land surface biophysical parameters in a spatially explicit manner using remotely sensed data has greatly enhanced our ability to model ecosystem processes and monitor crop development. A multitude of satellite sensors and algorithms have been used to generate ready-to-use maps of various biophysical parameters. Validation of these products for different vegetation types is needed to assess their reliability and consistency. While most of the current satellite biophysical products have spatial resolution of one kilometre, a recent effort utilizing data from the Medium Resolution Imaging Spectrometer (MERIS) provided leaf area index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), and other canopy parameters in a resolution as fine as 300 m over the European continent. This resolution would be more appropriate for application at the regional scale, particularly for crop monitoring. This higher-resolution MERIS product has been evaluated in a limited number of studies to date. This article aims to validate LAI and FAPAR from the MERIS 10-day composite BioPar BP-10 product over winter wheat fields in northeast Bulgaria. The ground measurements of LAI and FAPAR were up-scaled and 30 m resolution reference raster layers were created using empirical relationships with Landsat TM (RMSE = 0.06 and RMSE = 0.22 for FAPAR and LAI, respectively). MERIS FAPAR and LAI were found to have significant correlation with FAPAR and LAI from the reference raster layers (R² = 0.84 and R² = 0.78, respectively). When MERIS Green LAI was calculated (incorporating the fraction of vegetation and brown vegetation cover from the BioPar BP-10 product), better correspondence with LAI values from the reference raster layer was achieved, with RMSE and bias reduced by 30–35%. The results from this study confirm the findings of previous validations showing that MERIS Green LAI tends to overestimate LAI values lower than 1. As a conclusion of the study, the BioPar BP-10 product was found to provide reliable estimates of FAPAR and acceptably accurate estimates of LAI for winter wheat crops in North-East Bulgaria.     

Optimal closed-loop control of a hybrid step motor with chopper drive

Optimal closed-loop control of a hybrid step motor control with chopper drive is described. Expressions for the average torque and optimal control angle giving maximal average torque in the stationary state without phase current chopper control are presented. The effects of chopper current control on the torque and acceleration characteristics of a hybrid step motor are discussed. Expression have been developed for the control angle in the chopper current control mode, yielding greater torques and improved acceleration of hybrid step motors than for the optimal control angle without phase current control. The speed response of a hybrid step motor operated in a closed-loop system has been studied by computer simulation for different supply voltages and torque loads, using various control angle algorithms.     

Automated retrofit targeting of heat exchanger networks

The aim of this paper is to develop a novel heat exchanger network (HEN) retrofit method based on a new automated retrofit targeting (ART) algorithm. ART uses the heat surplus-deficit table (HSDT) in combination with the Bridge Retrofit concepts to generate retrofit bridges option, from which a retrofit design may be formulated. The HSDT is a tabular tool that shows potential for improved re-integration of heat source and sink streams within a HEN. Using the HSDT, retrofit bridges—a set of modifications that links a cooler to a heater to save energy—may be identified, quantified, and compared. The novel retrofit method including the ART algorithm has been successfully implemented in Microsoft ExcelTM to enable analysis of large-scale HENs. A refinery case study with 27 streams and 46 existing heat exchangers demonstrated the retrofit method’s potential. For the case study, the ART algorithm found 68903 feasible unique retrofit opportunities with a minimum 400 kW·unit^–1 threshold for heat recovery divided by the number of new units. The most promising retrofit project required 3 new heat exchanger units to achieve a heat savings of 4.24 MW with a favorable annualised profit and a reasonable payback period.

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Spatial targeting evaluation of energy and environmental performance of waste-to-energy processing

Waste-to-energy supply chains are important potential contributors to minimising the environmental impacts of municipal solid waste by reducing the amounts of waste sent to landfill, as well as the fossil fuel consumption and environmental footprints. Accounting for the spatial and transport properties of the waste-to-energy supply chains is crucial for understanding the problem and improving the supply chain designs. The most significant challenge is the distributed nature of the waste generation and the household energy demands. The current work proposes concepts and a procedure for targeting the size of the municipal solid waste collection zone as the first step in the waste-to-energy supply chains synthesis. The formulated concepts and the provided case study reveal trends of reducing the net greenhouse gas savings and energy recovery by increasing the collection zone size. Population density has a positive correlation with the greenhouse gas saving and energy recovery performance. For smaller zone size the energy recovery from waste approaches and in some cases may surpass the energy spent on waste transportation. The energy recovery and greenhouse gas savings remain significant even for collection zones as large as 200 km². The obtained trends are discussed and key directions for future work are proposed.

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