Accelerometers for bridge load testing

This paper describes a load-test procedure using accelerometer response and compares the results with that obtained using the traditionally used strain-gage data. The load rating provides an approximate load capacity of a bridge based on the available capacity of a critical girder for a predefined loading path. The results indicate that the accelerometer can conveniently extract information of bridges independent of their physical conditions. Application of accelerometers can remarkably enhance the response measurement of cracked concrete girders for bridge load rating. The proposed procedure can be useful in monitoring bridge performance over time and measuring the effectiveness of bridge retrofitting by comparing pre- and post-repair capacities.     

Multi-scale modeling of thermo-oxidation effects on the flexural behavior of cross-ply bismaleimide composites

Mechanics of Time-Dependent Materials - Mechanical properties of high-temperature polymer matrix composites deteriorate during their service. Oxidation plays a significant role in determining the...     

An intelligent system for gastrointestinal polyp detection in endoscopic video using fusion of bidimensional empirical mode decomposition and convolutional neural network features

This paper presents an intelligent system for gastrointestinal polyp detection in endoscopic video. Video endoscopy is a popular diagnostic modality in assessing the gastrointestinal polyps. But the accuracy of diagnosis mostly depends on doctors' experience that is crucial to detect polyps in many cases. Computer-aided polyp detection is promising to reduce the miss detection rate of polyp and thus improve the accuracy of diagnosis results. The proposed method illustrates an automatic system based on a new color feature extraction scheme as a support for gastrointestinal polyp detection. The scheme is the combination of color empirical mode decomposition features and convolutional neural network features extracted from video frames. The features are fed into a linear support vector machine to train the classifier. Experiments on standard public databases show that the proposed scheme outperforms the previous conventional methods, gaining accuracy of 99.53%, sensitivity of 99.91%, and specificity of 99.15%.     

Thermophilic aerobic wastewater treatment of waste metalworking fluids

An investigation into aerobic biological wastewater treatment was conducted over the temperature range 25–75°C in a semi‐batch bioreactor using waste metalworking fluids (MWFs) generated from Liverpool John Moores University's engineering workshop. The best treatment performance in terms of chemical oxygen demand (COD) removal occurred at 50°C (97.27%), with an operational time of 77.5 h. Cell viability was observed throughout the operation and it was found that higher temperature did not directly correlate to low viability. Effluent turbidity reduced considerably from 35 to 50°C and increased thereafter. Even when the system encountered alkaline shock, the overall performance was not affected, thus indicating how stable the system was. The results of this study indicate that an existing industrial‐activated sludge plant could be used to treat waste MWFs under thermophilic conditions. The COD reduction was significant but further investigation into biodegradation of recalcitrant compounds is needed to achieve optimum performance.     

A comparison study on node clustering techniques used in target tracking WSNs for efficient data aggregation

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregation process. In this paper, we have highlighted the gains of the existing schemes for node clustering‐based data aggregation along with a detailed discussion on their advantages and issues that may degrade the performance. Also, the boundary issues in each type of clustering technique have been analyzed. Simulation results reveal that the efficacy and validity of these clustering‐based data aggregation algorithms are limited to specific sensing situations only, while failing to exhibit adaptive behavior in various other environmental conditions. Copyright © 2016 John Wiley & Sons, Ltd.     

Improvement in DRX Power Saving for Non‐real‐time Traffic in LTE

A discontinuous reception (DRX) operation is included in the Long Term Evolution (LTE) system to achieve power saving and prolonged battery life of the user equipment. An improvement in DRX power saving usually leads to a potential increase in the packet delay. An optimum DRX configuration depends on the current traffic, which is not easy to estimate accurately, particularly for non‐real‐time applications. In this paper, we propose a novel way to vary the DRX cycle length, avoiding a continuous estimation of the data traffic when only non‐real‐time applications are running with no active real‐time applications. Because a small delay in non‐real‐time traffic does not essentially impact the user's experience adversely, we deliberately allow a limited amount of delay in our proposal to attain a significant improvement in power saving. Our proposal also improves the delay in service resumption after a long period of inactivity. We use a stochastic analysis assuming an M/G/1 queue to validate this improvement.     

Short-Term Urban Water Demand Prediction Considering Weather Factors

Accurate and reliable forecasting plays a key role in the planning and designing of municipal water supply infrastructures. Recent studies related to water demand prediction have shown that water demand is driven by weather variables, but the results do not clearly show to what extent. The principal aim of this research was to better understand the effects of weather variables on water demand. Additionally, it aimed to offer an appropriate and reliable technique to predict municipal water demand by using the Gravitational Search Algorithm (GSA) and Backtracking Search Algorithm (BSA) with Artificial Neural Network (ANN). Moreover, eight weather factors were adopted to evaluate their impact on the water demand. The principal findings of this research are that the hybrid GSA-ANN (Agent?=?40) model is superior in terms of fitness function (based on RMSE) for yearly and seasonal phases. In addition, it is evidently clear from the findings that the GSA-ANN model has the ability to simulate both seasonal and yearly patterns for daily data water consumption.     

Bio-inspired armor protective material systems for ballistic shock mitigation

Severe transient ballistic shocks from projectile impacts, mine blasts, or overhead artillery attacks can incapacitate an occupant at low frequencies, or sensitive equipment at high frequencies, if they are not properly attenuated by armor protective systems. Unique challenges exist in developing armor protective systems for mitigating both low and high frequency ballistic shocks due to the lack of robust design methodology, the severe dynamic loading conditions, and the uncertainties in predicting ballistic shock responses.Nature offers engineers a blueprint of highly effective, efficient, and adaptive material designs to protect certain regions from external threats. This paper presents the modeling, analysis, design, optimization, fabrication, and experimental validation of bone-inspired armor protective material systems for reducing projectile penetrations and alleviating ballistic shocks at both low and high frequencies. The optimized bone-inspired armor protective material system has a soft–stiff–soft–stiff material distribution pattern based on bone-foramen and osteonal-bone material systems. Analysis and experimental results demonstrated that the bone-inspired armor protective material systems have excellent capabilities for drastic ballistic shock mitigation, weight savings, and significant reductions in penetration and load transmission under ballistic loading conditions.     

A Method for Predicting Long-Term Municipal Water Demands Under Climate Change

Water Resources Management - The accurate forecast of water demand is challenging for water utilities, specifically when considering the implications of climate change. As such, this is the first...