Analytical performance evaluation of association of active and passive tracks for airborne sensors

The performance of multilevel quadrature partial-response systems (QPRS) in the presence of an additive combination of Gaussian and impulsive noise is analytically evaluated by means of the Fourier-Bessel series expansion method. The model of the impulsive noise used, which closely models atmospheric and/or man-made electromagnetic interference, consists of a stream of Poisson impulses with areas distributed according to a power Rayleigh probability density function. Analytical performance evaluation results are presented for 9, 49, and 225 QPR systems. The results indicate severe system performance degradation, especially for highly bandwidth-efficient systems (e.g. 225 QPRS), mostly due to the long error bursts caused by the impulsive noise tails. However, a qualitative comparison between these results and the corresponding performance results of equivalent QAM schemes demonstrates that 49 QPRS could be a suitable choice for microwave radio or HDTV satellite links operating in pure impulsive noise environments.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Fields of distributed passive and multistatic active sonar sensors provide surveillance capabilities against quiet submarine threats in Anti-Submarine Warfare (ASW) scenarios. The joint cooperative use of passive and active sonar offers synergistic and complimentary acoustic performance as well as operational advantages. However, a significant challenge of heterogeneous, multi-sensor systems is the successful fusion of information from the various sensors to enable robust target detection, classification, localization, and tracking. This paper describes the formation of a passive acoustic track that may be used to cue an active multistatic acoustic tracking system. A cue from a passive acoustic track reduces the false track rate in the active tracker by focusing the search area and selectively initiating active tracks. The passive track is assumed to originate from a fixed passive acoustic horizontal line array (HLA) which is unable to determine target range or resolve the familiar left-right ambiguity. However, passive systems can predict Closest-Point-of-Approach (CPA) events. For each CPA event, a cue can be forwarded to the active system for multistatic active track initiation. This paper presents a minimal parametric representation for a passive acoustic track. It also describes an algorithm for obtaining initial estimates of parameters that can be used to initiate the passive track more effectively. A performance evaluation is given. This paper also describes the conversion of the passive track to pseudo-coordinates that are convenient for use with a multistatic tracking system. Lastly, a method for measuring passive track quality is described which determines if track quality is sufficient to justify cueing the active multistatic system.

High temperatures during a fire can lead to the evaporation of moisture and the degradation of hydration products within concrete, consequently compromising its mechanical properties. This paper thoroughly investigates the effect of fire-induced high temperatures on the residual load-bearing capacity of concrete structures, with a focus on prestressed concrete T-beams. By conducting constant temperature tests and residual load-bearing capacity tests, complemented by finite element modeling, this study examines the degradation of mechanical properties in prestressed concrete T-beams due to fire exposure and its impact on post-fire residual load-bearing capacity. Additionally, an equivalent concrete compressive strength method was employed to propose a calculation method for concrete material degradation under high temperatures and a corresponding concrete strength reduction factor. Simplified calculations were also performed for the high-temperature damage to reinforcement and prestressed tendons, leading to the derivation of a simplified formula for the residual load-bearing capacity of post-fire prestressed concrete T-beams. The results indicate that in prestressed concrete T-beams exposed to fire, an increase in holding time results in more severe damage modes, accelerated crack propagation, and wider crack widths during bending failure. Under the same load, a longer holding time corresponds to a more pronounced reduction in deflection. At holding times of 60 min, 120 min, and 180 min, the prestress losses were 48.17%, 85.16%, and 93.26%, respectively. The cracking load decreased by 15%, 27%, and 42%, while the residual load-bearing capacity decreased by 11%, 21%, and 28%. Comparison with experimental data demonstrates that both the finite element model and the simplified calculation formula exhibit high accuracy, offering a reliable reference for the performance evaluation of post-fire prestressed concrete T-beams.

Background Glial Fibrillary Acidic Protein (GFAP) levels are shown to be an indicator of neurologic injury in conditions like Traumatic Brain Injury (TBI) and stroke and as a marker of disease progression in neuromuscular disorders such as multiple sclerosis. Plasma GFAP is also implicated in detecting AD pathology, correlating to the clinical stage of the disease. The performance characteristics of the plasma GFAP immunoassay currently being developed on Beckman Coulter Access 2 and DxI 9000 analyzers are described. Methods The prototype GFAP assay is a one-step sandwich assay utilizing an anti-GFAP mouse monoclonal (MAb) antibody/alkaline phosphatase conjugate and paramagnetic particles coated with a complementary anti-GFAP mouse MAb. Sample and reactants are incubated and washed, and then a chemiluminescent substrate is added. The light generated is directly proportional to the GFAP concentration in the sample. The assay time to the first result is ∼30 minutes. Analytical performance evaluation and method comparison across different platforms was performed. 43 EDTA plasma samples, consisting of 19 Alzheimer’s Disease (AD) patient samples and 24 age-matched healthy normal samples, were evaluated. Results The prototype GFAP assay has a targeted analytical measuring range of 1.0 pg/ml to approximately 700.0 pg/ml (up to 10,000 pg/ml). All normal samples were quantified with 90% measuring below 20.0 pg/ml and a low dose coefficient of variation &amp;lt;4.0%. A comparison of the prototype GFAP assay on DxI 9000 and Access 2 analyzers shows a Passing-Bablok slope of 0.94 (R=0.992) and an intercept of 0.37 pg/ml. Concordance analysis shows excellent agreement between the Access 2 and DxI 9000 assays. The dose ratio of the median of AD over the median of normal samples for Access 2 and DxI 9000 is 2.31 and 2.41, respectively, with AD patient median dose values of 14.3 pg/ml and 14.6 pg/mL, respectively, and normal sample median dose values of 6.2 pg/ml and 6.0 pg/mL, respectively. Conclusions The prototype GFAP assay provides fast, highly sensitive, and precise results in an automated immunoassay on the Beckman Coulter Access 2 and DxI 9000 platforms. The prototype plasma GFAP assay holds promise for diagnosing and monitoring various neurodegenerative diseases, including AD.

Low handover delay ensures seamless mobility of active communication flows across heterogeneous wireless networks. Handover delay resulting from host-based localized mobility management procedures remains high and unacceptable for real time applications. This paper, therefore, proposes an IEEE 802.21 assisted network-based localized mobility management framework to further reduce handover delay by optimizing the authentication delay. Through analytical evaluation and comparison of the handover delay performance for basic network-based and host-based localized schemes, we show that our proposed scheme performs better in terms of reducing handover delay.

The scaling trend of semiconductor devices has raised several issues such as energy consumption and heat dissipation, as well as the increasing probabilistic behavior of devices. Motivated by the necessity to consider probabilistic approaches to future designs, probabilistic CMOS (PCMOS) based computing has been proposed. PCMOS devices are inherently probabilistic devices that compute correctly with a probability <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</i> . This paper investigates the tradeoffs between the energy, speed (or performance), and probability of correctness ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</i> ) of PCMOS circuits. For given constraints on <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</i> , performance, and energy delay product (EDP), and using analytical models of energy, delay, and <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</i> , the optimum values of EDP and probability are found for PCMOS circuits. The analytical models are validated using circuit simulations for PCMOS circuits designed in a 0.13-mum process. The results show that, to minimize EDP, it is preferable to operate PCMOS circuits at lower supply voltages. On the other hand, to maximize <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</i> , the highest possible supply voltage under the given constraints is preferable. Our analysis makes it possible to achieve an optimal circuit design that satisfies the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</i> , performance, and EDP requirements for a given application. An analysis of the impact of variations in temperature, threshold voltage, and supply voltage on optimal EDP and probability values is also included.

Approximate analytical performance models for automatic assembly systems with statistical process control and automated inspection

The numerical model for the lateral impact of circular concrete-filled steel tubular (CFST) members after exposure to fire with and without carbon fiber reinforced polymer (CFRP) is established. The accuracy of the model is verified by different experiments. The whole impact process of reinforced post-fire members is analyzed. The impact force, mid-span deflection and sectional moment of the specimens are compared. In addition, the impact resistance and flexural capacity, plastic deformation and energy absorption capacity, as well as the distribution and development of the internal force are investigated. A simplified calculation formula for the maximum mid-span deflection of the specimens under impact load is proposed. The influence of CFRP reinforcement methods on the impact performance of the post-fire specimens is discussed. The results show that the plateau value of the impact force and the average sectional moment of post-fire specimens were increased by the CFRP reinforcement. However, the mid-span deflection and impact duration were significantly reduced. The impact resistance and flexural capacity of the specimens were significantly improved by the CFRP reinforcement. The impact resistance, flexural capacity and energy absorption capacity gradually decrease with the increase of the fire duration. In addition, the specimens experienced different degrees of plastic deformation at the span, and the energy was mainly absorbed by the formation of plastic hinges. The bending moment and shear force distributions of the specimens under lateral impact at the peak stage were different from those of the specimens under static load, but the distributions at the plateau stage were consistent with those of the specimens under static load. The simplified formula can well predict the maximum deflection of the specimens after lateral impact. The CFRP reinforcement methods have a noticeable influence on the impact resistance of post-fire members.

In several emerging and important applications, such as location-based services, sensor monitoring and biological databases, the values of the data items are inherently imprecise. A useful query class for these data is the Probabilistic Nearest-Neighbor Query (PNN), which yields the IDs of objects for being the closest neighbor of a query point, together with the objects’ probability values. Previous studies showed that this query takes a long time to evaluate. To address this problem, we propose the Constrained Nearest-Neighbor Query (C-PNN), which returns the IDs of objects whose probabilities are higher than some threshold, with a given error bound in the answers. We show that the C-PNN can be answered efficiently with verifiers. These are methods that derive the lower and upper bounds of answer probabilities, so that an object can be quickly decided on whether it should be included in the answer. We design five verifiers, which can be used on uncertain data with arbitrary probability density functions. We further develop a partial evaluation technique, so that a user can obtain some answers quickly, without waiting for the whole query evaluation process to be completed (which may incur a high response time). In addition, we examine the maintenance of a long-standing, or continuous C-PNN query. This query requires any update to be applied to the result immediately, in order to reflect the changes to the database values (e.g., due to the change of the location of a moving object). We design an incremental update method based on previous query answers, in order to reduce the amount of I/O and CPU cost in maintaining the correctness of the answers to such a query. Performance evaluation on realistic datasets show that our methods are capable of yielding timely and accurate results.

: In the Center for Opto-Electronic Systems Research at the University of Rochester, the primary goal of the faculty is to contribute fundamental scientific knowledge in the critical technology areas of lasers, modulation, optical system design, propagation and coherence, detection theory, signal and image processing, switching, neural networks, and displays. This research impacts on the following topics enumerated in the DoD critical technologies list: Photonics; Signal Processing; Passive Sensors; Software Producibility; and, to a lesser extent, Signature Control; Sensitive Radars; and Machine Intelligence or Robotics. Under the URI program, block funding will also permit us to educate a large number of superior doctoral scholars in a unique environment.

BThis study presents the development, performance evaluation, and environmental impact assessment of an opti-mized biogas-powered injera baking stove designed to enhance energy efficiency and reduce greenhouse gas emis-sions in rural Ethiopia. The system integrates a 45° conical burner, insulation, and optimized air-fuel mixing to achieve a thermal efficiency of 36%—more than double that of traditional three-stone biomass stoves. Experimental results show a 40% reduction in energy consumption per injera, with combustion characterized by stable blue flames and uniform heat distribution. Analytical and empirical evaluations indicate that widespread adoption of this stove by 5 million rural households could reduce national CO₂ emissions by 3.8 million tons annually and yield energy savings of 23,160 TJ (6.43 TWh). In parallel, injera quality—measured by porosity, texture, and flexibility—was consistently high and culturally ac-ceptable. The findings demonstrate that the biogas stove offers a sustainable, efficient, and appropriate alternative to wood fired mass stoves, with significant implications for clean energy transitions and climate change mitigation. Keywords: Biogas Stove ; Injera; thermal efficiency; CO2 emission reduction; Energy Saving

Stochastic detection against deception attacks in CPS: Performance evaluation and game-theoretic analysis

Food security concerns are drawing more and more attention in Chinese society. As one of the most effective way for improving food quality and safety, how to promote logistics ability of the Cold-Chain enterprise has become an emergency issue. This paper aims to build a performance evaluation system for the cold-chain company based on the Chinese agri-food industry to analyze its strengths and weaknesses for improving its competitiveness. Improved Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation methods are blended to evaluate the performance of the target company in three steps. In the first step, rely on the AHP, with the literature review and the theory of the balanced score card method, the determination of evaluation criteria and the hierarchical structure of the evaluation index system are done. In the second step, the weights of each criterion are obtained through improved AHP and then an agri-food cold-chain logistics enterprises performance evaluation index system will be built. And, in the third step, the Fuzzy Comprehensive Evaluation method is used to evaluate the performance of the target company with the performance evaluation index system. Finally, a demonstration of the numerical example in Chinese agri-food industry is presented for better understanding. The proposed performance evaluation index system can assist managers to comprehensive comprehend the strengths and weaknesses of their agri-food cold-chain companies and could continuously improve the relevant cold-chain performance factors from the practice.

This paper presents a real-time remote water level monitoring system based on dense wavelength division multiplexing (DWDM)-passive optical fiber sensor (OFS) network for the application of the Internet of Things (IoT). This network employs a broadband light source based on amplified spontaneous emission (ASE) as a seed light. This ASE light is spectrum-sliced by an athermal type arrayed waveguide grating (200 GHz × 16 channel), then distributed towards multiple sensing units (SU). Here, 16 SUs are installed vertically at the specified height in the water pool according to the design specification (i.e., spatial resolution). Then, each SU reflects an optical spectrum having a different reflection coefficient depending on the surrounding medium (e.g., air or water). By measuring these reflected optical spectra with an optical spectrum analyzer, the water level can be easily recognized in real time. However, as the sensing distance increases, system performance is severely degraded due to the Rayleigh Back-Scattering of the ASE light. As a result, the remote sensing capability is limited at a short distance (i.e., &lt;10 km). To overcome this limitation, we propose a simple signal processing technique based on feature extraction of received optical spectra, which includes embedding a peak detection algorithm with a signal validation check. For the specific, the proposed signal processing performs the peak power detection, signal quality monitoring, and determination/display of the actual water level through three function modules, i.e., data save/load module, signal processing module, and Human–Machine Interface display module. In particular, the signal quality of the remote sensing network can be easily monitored through several factors, such as the number of spectral peaks, the wavelength spacing between neighboring peaks and the pattern of detected peak power. Moreover, by using this validation check algorithm, it is also possible to diagnose various error types (such as peak detection error, loss of data and so on) according to the pattern of measured optical spectra. As a result, the IoT sensor network can recognize 17 different level statuses for the water level measurement from a distance of about 25 km away without active devices such as optical amplifiers (i.e., passive remote sensing).

Single-carrier with frequency-domain equalization (SC-FDE) modulations are a natural choice for the uplink of massive multiple intput, multiple output (MIMO) systems, due to the low peak-to-average power ratio (PAPR) of their signals. However, equalization techniques should avoid matrix inversions. On the other hand, energy-efficient analog-to-digital converters (ADCs) should be used in each receive branch to reduce the power consumption and the implementation complexity, which might lead to strong nonlinear distortion effects. In this work, we present the analytical performance evaluation of nonlinear massive MIMO systems based on SC-FDE systems employing low-complexity, iterative FDE receivers1.