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The purpose of this paper is to propose and confer a strategic cost model as a concept for good decision making for highway asset treatment in the transport industry.

The paper is based on asset performance condition and treatment renewals using a five-point performance for developing prospective treatment strategies. The strategic cost model is presented in the similitude of picturesque and its outcomes via an exploratory data analysis.

The results articulate the best maintenance plan for the forthcoming and future years. The strategic cost model uses the combination of the current condition band, the sample area and likely treatment cost for proposing the optimal treatment solution based on consideration of desired treatment level.

The strategic cost model is suitable for outlining the asset performance condition, treatment renewals and analytical cost optimisation. The formulated analytical cost model and developed prospective strategies enable good decision making, long-term contract negotiations and whole life cost maintenance and management.

Embracing eminent performance condition from the research area of lifecycle planning and deterioration models of a physical asset, a prospective cost strategy for asset maintenance is proposed in the study. The resultant treatment strategies using the analytical approach portray the ability that enables the adaptation of expected outcomes.

Automated condition surveys have been recently introduced for condition assessment of highway infrastructures worldwide. Accurate predictions of the current state, median life (ML) and future state of highway infrastructures are crucial for developing appropriate inspection and maintenance strategies for newly created as well as existing aging highway infrastructures. The paper aims to discuss these issues.

This paper proposes Markov Chain based deterioration modelling using a linear transition probability (LTP) matrix method and a median life expectancy (MLE) algorithm. The proposed method is applied and evaluated using condition improvement between the two successive inspections from the Surface Condition Assessment of National Network of Roads survey of the UK Pavement Management System.

The proposed LTP matrix model utilises better insight than the generic or decoupling linear approach used in estimating transition probabilities formulated in the past. The simulated LTP predicted conditions are portrayed in a deterioration profile and a pairwise correlation. The MLs are computed statistically with a cumulative distribution function plot.

The paper concludes that MLE is ideal for projecting half asset life, and the LTP matrix approach presents a feasible approach for new maintenance regime when more certain deterioration data become available.

The purpose of this paper is to model the strain localization in J₂ materials with damage evolution using embedded strong discontinuity modes.

In this procedure, an heuristic bandwidth scale is adopted to model the damage evolution in the shear bands. The bifurcation triggering conditions and band growth directions are studied for these materials.

The resulting formulation does not require a specific mesh refinement to model a localization, provides mesh independent results also insensitive to element distortions and allows calibration of the model response using experimental data. The formulation capability is shown embedding the strong discontinuity modes into quadrilateral and higher order elements.

The work described in this paper extends the use of strong discontinuity modes to materials with damage evolution.

The purpose of this paper is to investigate the possibility to replace radio equipment compliance requirements based on equipment parameters with a set of simple metrics that accurately reflects spectrum utilization and spectrum-sharing efficiency.

The approach taken is to go back to the basic factors that determine radio system behavior in a shared spectrum environment: radio frequency power, duty cycle and frequency occupation. By normalizing these parameters, device specificity is avoided and a statistical perspective on spectrum utilization and sharing becomes possible.

The analysis shows that two technology-neutral metrics would be adequate to govern spectrum utilization and sharing: a spectrum utilization metric and a spectrum-sharing efficiency metric. These metrics form the core of regulatory requirements for shared frequency bands. Each shared frequency band could be assigned criteria based on these metrics that take into account the types of applications for which that band will be used.

This work is a first step that identifies the main factors that affect shared spectrum usage from a statistical point of view. More work is needed on the relationship between real-world interference and its abstraction in the spectrum-sharing rules.

The metrics proposed could be considered as the basis for a new approach to the regulation of the license-exempt spectrum, and, by extension, as the basis for generic compliance criteria. Their use would facilitate the compliance assessment of software-defined radio technology.

This work has no direct social implications.

This paper combines new work on spectrum utilization criteria with extensions of previous work on spectrum-sharing efficiency into a comprehensive proposal for a new approach to the regulation of the license-exempt spectrum.

Spectrum regulations have major impact on the development and deployment of innovative technologies. Current regulations for license-exempt radio spectrum generally are given in terms of technology-related criteria. This paper aims to propose a set of metrics that can be used to define technology-agnostic spectrum regulations which encourage rather than restrict technology innovation.

This paper builds on and expands two other papers on regulatory criteria for license-exempt spectrum which define metrics for spectrum loading and spectrum sharing efficiency. Here, we add metrics for Block Edge Masks and for medium access adaptivity. This gives a complete toolset for the management of radio spectrum.

Because of the diversity of use of license-exempt spectrum, performance criteria must be formulated in terms that abstract from the details of equipment properties. Instead, they must be formulated in terms of spectrum utilization dimensions: RF power, time and frequency occupation. The result is a concise set of metrics that can be applied to the regulation or management of shared spectrum.

The mathematics used in this paper deal with high-level parameters and may ignore factors that are important in certain cases and may require refinement.

The implications of the proposed metrics include an increase emphasis on the objectives of spectrum policy and on measures to assure efficient spectrum utilization both within frequency bands and between adjacent bands.

There are no social implications the authors are aware of.

The originality of this work lies in recognizing that the extreme variety of devices and mode of operation deployed in license-exempt spectrum calls for spectrum management criteria that are technology agnostic.

We study research designs where a binary treatment changes discontinuously at the border between administrative units such as states, counties, or municipalities, creating a treated and a control area. This type of geographically discontinuous treatment assignment can be analyzed in a standard regression discontinuity (RD) framework if the exact geographic location of each unit in the dataset is known. Such data, however, is often unavailable due to privacy considerations or measurement limitations. In the absence of geo-referenced individual-level data, two scenarios can arise depending on what kind of geographic information is available. If researchers have information about each observation’s location within aggregate but small geographic units, a modified RD framework can be applied, where the running variable is treated as discrete instead of continuous. If researchers lack this type of information and instead only have access to the location of units within coarse aggregate geographic units that are too large to be considered in an RD framework, the available coarse geographic information can be used to create a band or buffer around the border, only including in the analysis observations that fall within this band. We characterize each scenario, and also discuss several methodological challenges that are common to all research designs based on geographically discontinuous treatment assignments. We illustrate these issues with an original geographic application that studies the effect of introducing copayments for the use of the Children’s Health Insurance Program in the United States, focusing on the border between Illinois and Wisconsin.

The purpose of this paper is to study the fault diagnosis of internal combustion (IC) engine gearbox using vibration signals with signal processing and machine learning (ML) techniques.

Vibration signals from the gearbox are acquired for healthy and induced faulty conditions of the gear. In this study, 50% tooth fault and 100% tooth fault are chosen as gear faults in the driver gear. The acquired signals are processed and analyzed using signal processing and ML techniques.

The obtained results show that variation in the amplitude of the crankshaft rotational frequency (CRF) and gear mesh frequency (GMF) for different conditions of the gearbox with various load conditions. ML techniques were also employed in developing the fault diagnosis system using statistical features. J48 decision tree provides better classification accuracy about 85.1852% in identifying gearbox conditions.

The proposed approach can be used effectively for fault diagnosis of IC engine gearbox. Spectrum and continuous wavelet transform (CWT) provide better information about gear fault conditions using time–frequency characteristics.

In this paper, experiments are conducted on real-time running condition of IC engine gearbox while considering combustion. Eddy current dynamometer is attached to output shaft of the engine for applying load. Spectrum, cepstrum, short-time Fourier transform (STFT) and wavelet analysis are performed. Spectrum, cepstrum and CWT provide better information about gear fault conditions using time–frequency characteristics. ML techniques were used in analyzing classification accuracy of the experimental data to detect the gearbox conditions using various classifiers. Hence, these techniques can be used for detection of faults in the IC engine gearbox and other reciprocating/rotating machineries.

Challenges to a robust and accurate implementation of electric‐field‐enhanccd thermal‐generation mechanisms in a drift‐diffusion‐based semiconductor‐device simulation code are discussed and solutions proposed. The implementation of the physical models and associated numerical methods is applied to the simulation of leakage currents in trench‐DRAM cells.

The purpose of this paper is to develop the models of the dielectric permittivity dispersion of heterogeneous systems based on semiconductors to a level that would allow to apply effectively the method of broadband dielectric spectroscopy for the study of electronic processes in ceramic and composite materials.

The new approach for determining the complex dielectric permittivity of heterogeneous systems with semiconductor particles is used. It includes finding the analytical expression of the effective dielectric permittivity of the separate semiconductor particle of spherical shape. This approach takes into account the polarization of the free charge carriers in this particle, including capturing to localized electron states. This enabled the authors to use the known equations for complex dielectric permittivity of two-component matrix systems and statistical mixtures.

The presented dispersion equations establish the relationship between the parameters of the dielectric spectrum and electronic processes in the structures like semiconductor particles in a dielectric matrix in a wide frequency range. Conditions of manifestation and location of the different dispersion regions of the complex dielectric heterogeneous systems based on semiconductors in the frequency axis and their features are established. The most high-frequency dispersion region corresponds to the separation of free charge carriers at polarization. After this region in the direction of reducing of the frequency, the dispersion regions caused by recharge bulk and/or surface localized states follow. The most low-frequency dispersion region is caused by recharging electron traps in the boundary layer of the dielectric matrix.

Dielectric dispersion models are developed that are associated with: electronic processes of separation of free charge carriers in the semiconductor component, recapture of free charge carriers in the localized electronic states in bulk and on the surface of the semiconductor and also boundary layers of the dielectric at the polarization. The authors have analyzed to situations that correspond applicable and promising materials: varistor ceramics and composite structure with conductive and semiconductor fillers. The modelling results correspond to the existing level of understanding of the electron phenomena in matrix systems and statistical mixtures based on semiconductors. It allows to raise efficiency of research and control properties of heterogeneous materials by dielectric spectroscopy.