Building change detection after earthquake using multi-criteria decision analysis based on extracted information from high spatial resolution satellite images

Change detection of ground surface objects can provide essential and precious information for experts in the fields of Geomatics, emergency management, urban management, agriculture, and forestry. Space-borne remote-sensing images are one of the main sources for change detection. Various change detection methods have been proposed on remote-sensing applications. However, often, no single efficient method can be selected for a case study because the existing methods sometimes have good performance and sometimes perform poorly. Therefore, it is necessary to propose an integrated change detection method according to some change detection methods. Multi-criteria decision analysis is a powerful framework that can integrate several criteria that may be in contrast to each other. In this study, a multi-criteria decision analysis framework was used to integrate the spectral, textural, and transformed features for detecting building changes with the help of high spatial resolution satellite images. First, the spectral, textural, and transformed features were extracted from the pre- and post-event satellite images. Second, the spectral, textural, and transformed factor maps were produced by entering the related features to three separate Adaptive Network-Based Fuzzy Inference Systems (ANFIS). Third, the ANFIS model was used again to integrate the mentioned factor maps for producing the preliminary building change map. And finally, a comprehensive sensitivity analysis was carried out to determine the proper parameters of the ANFIS models leading to accurate change detection results. The proposed method was tested on the earthquake data set of Bam City in Iran. The achieved results indicated an overall accuracy of 89.62% for identifying the changed and unchanged building regions. Moreover, the obtained results proved the efficiency and accuracy of the proposed method with respect to other implemented methods regarding the Bam earthquake. Furthermore, the aggregation of the spectral, transformed, and textural features resulted in improving the change detection accuracy by about 5–15%, compared with the accuracy of every one of them for the mentioned purpose.     

Aggregation and clogging phenomena of rigid microparticles in microfluidics

We developed a numerical tool to investigate the phenomena of aggregation and clogging of rigid microparticles suspended in a Newtonian fluid transported through a straight microchannel. In a first step, we implement a time-dependent one-way coupling Discrete Element Method (DEM) technique to simulate the movement and effect of adhesion on rigid microparticles in two- and three-dimensional computational domains. The Johnson–Kendall–Roberts (JKR) theory of adhesion is applied to investigate the contact mechanics of particle–particle and particle–wall interactions. Using the one-way coupled solver, the agglomeration, aggregation and deposition behavior of the microparticles is studied by varying the Reynolds number and the particle adhesion. In a second step, we apply a two-way coupling CFD–DEM approach, which solves the equation of motion for each particle, and transfers the force field corresponding to particle–fluid interactions to the CFD toolbox OpenFOAM. Results for the one-way (DEM) and two-way (CFD–DEM) coupling techniques are compared in terms of aggregate size, aggregate percentages, spatial and temporal evaluation of aggregates in 2D and 3D. We conclude that two-way coupling is the more realistic approach, which can accurately capture the particle–fluid dynamics in microfluidic applications.     

Parallel‐series connected rectenna array using frequency selective surface (FSS) for power harvesting applications at 5.8 GHz

This article presents a frequency selective surface (FSS) and rectenna array in parallel‐series connection to harvest power of wireless power systems. To improve the basic antenna parameters, a frequency selective surface was mounted on the reverse side of the substrate. According to the results, the proposed method showed significant improvement in comparison to other methods in both single and rectenna array. Moreover, the conversion efficiency of the presented technique was increased to 76%. The output voltage of 4.5 and 9 V and the current of 60 and 120 mA were resulted for 5 and 10 rectenna units, respectively. The proposed arrays can be expanded to large scale integrated array without any significant degradation in conversion efficiency.     

Fuzzy logic controller and cascade inverter for direct torque control of IM

In this paper, a five-level cascaded H-bridge multilevel inverters topology is applied on induction motor control known as direct torque control (DTC) strategy. More inverter states can be generated by a five-level inverter which improves voltage selection capability. This paper also introduces two different control methods to select the appropriate output voltage vector for reducing the torque and flux error to zero. The first is based on the conventional DTC scheme using a pair of hysteresis comparators and look up table to select the output voltage vector for controlling the torque and flux. The second is based on a new fuzzy logic controller using Sugeno as the inference method to select the output voltage vector by replacing the hysteresis comparators and lookup table in the conventional DTC, to which the results show more reduction in torque ripple and feasibility of smooth stator current. By using Matlab/Simulink, it is verified that using five-level inverter in DTC drive can reduce the torque ripple in comparison with conventional DTC, and further torque ripple reduction is obtained by applying fuzzy logic controller. The simulation results have also verified that using a fuzzy controller instead of a hysteresis controller has resulted in reduction in the flux ripples significantly as well as reduces the total harmonic distortion of the stator current to below 4 %.     

‘Breaking’ news: uncovering sense-breaking patterns in social media crisis communication during the 2017 Manchester bombing

ABSTRACT

Individuals, (media-) organisations, and crisis responders who are involved in ad hoc crisis communication steadily deploy social media to contribute to collective sense-making as an endeavour to create meaning in highly uncertain situations. Exerting sense-giving in order to shape others’ conceptions is causally preceded by an initial breakup of existing understanding. This study aims to explore patterns of sense-breaking in social media crisis communication and its impact on collective sense-making and sense-giving. To this end, we conducted a case study of the Manchester bombing in 2017, including a social network analysis of 708,147 Twitter postings and a content analysis of 2006 original tweets. We found individual role types to be initiators of sense-breaking in early crisis stages when uncertainty is at its height. Exerting successive sense-giving becomes more challenging if the collective sense-making has progressed along with the sequence of events. This understanding aims to encourage emergency management organisations to move their sense-giving actions closer to the point in time when sense-breaking occurs.     

Development of ensemble machine learning approaches for designing fiber-reinforced polymer composite strain prediction model

Engineering with Computers - Over the past few decades, it has been observed a remarkable progression in the development of computer aid models in the field of civil engineering. Machine learning...     

Will smartwatches last? factors contributing to intention to keep using smart wearable technology

This study aims to deepen our understanding of the underlying factors affecting the intention to continue using increasingly popular wearable technology. A new theoretical model is developed and validated to extend traditional technology acceptance theories by identifying several value drivers of the continuous intention and actual usage of wearable devices. Hypotheses were tested using partial least squares path modeling on data collected from 383 actual smartwatch users. The results provide wearable device manufacturers with practical guidance for optimizing competition strategies. They also offer policy-making insights for practitioners to promote better wearable devices on the market, especially during the early stages of adoption.     

Establishment of a calibration curve for an isocentric cobalt unit using Monte Carlo simulation

Measurement of dose distribution in patients during radiotherapy is impossible. The Monte Carlo simulation is an alternative method for dose calculations. In routine radiotherapy, the source-to-surface distance(SSD)method is not practical for an isocentric unit because it requires numerous values of tissue–air ratios and inverse square law. Therefore, this method is time consuming. In this paper, the curves of relative depth doses were obtained for three different SSDs using the MCNP4C Monte Carlo simulation and approximated with a single curve called calibration curve. This curve was compared to the curve obtained by published data, differing in approximately 5% in the worst case. It was also observed that the obtained results were more accurate for distances between-5 and 10 cm from source-to-axis distance.     

FIVE-SPOT INJECTION/PRODUCTION WELL LOCATION DESIGN BASED ON FRACTURE GEOMETRICAL CHARACTERISTICS IN HEAVY OIL FRACTURED RESERVOIRS DURING MISCIBLE DISPLACEMENT: AN EXPERIMENTAL APPROACH

Mapping fracture characteristics by using seismic acquisition and processing is important not only to identify sweet spots, but also to optimize production, especially for unconventional heavy oil reservoirs. In this experimental work we used five-spot micromodels initially saturated with heavy oil to find the optimum well locations during first-contact miscible displacement. The experiments were performed at a fixed injection rate on fractured micromodels with various patterns. The optimum location for injection/production wells was found in the pattern where fractures make an angle of 45° with the mean flow direction. Moreover, oil recovery was increased with the density, length, level of scattering, and discontinuity of fractures. The analysis of the experimentally measured recovery curve revealed that there are three distinct stages for each displacement. The efficiency of the first stage was found to be dominated by dispersion and diffusion. However, the recovery of the second stage was significantly affected by the fracture orientation. The displacement efficiency of the third stage was controlled by solvent dispersion, which is at maximum for the pattern with higher density, length, scattering, and discontinuity of fractures. Saturation monitoring showed that the fracture geometrical characteristics strongly affected the splitting, spreading, and shielding of the produced fingers and solvent front shape and consequently affected the recovery factor. As a result, five-spot micromodels can be used to investigate the optimum location of injection/production wells during miscible displacements in fractured heavy oil reservoirs.