In the present study, high resolution remotely sensed data (<60-m resolution) has been used to locate and track changes in urban land cover in Cairo, Egypt. Landsat (TM) images for July months of the years 1985, 1990, 1995, and 2000 have been analyzed to identify the growth of urban region at Cairo. The population growth in Cairo City during the period 1985 to 2000 and its expected rates up to 2035 have been taken into consideration. The results of the study revealed that, a real extent of urban lands of Cairo City could be monitored accurately by using a high resolution Landsat satellite images. Among the main findings is the increase of urban area of Cairo from 267.38 Km2 to 548.13 Km2 through the period from 1985 to 2000 with percentage annual ratio estimates 7%. A significant correlation between the rate of increase of Cairo urbanized area, ΔUA, and the rate of population growth, ΔPA, has been found in the simple form, ΔUA = 40.85 – 100.6 ΔPA. Therefore, if the rates of population growth and human activities in Cairo City continued, the urban area will reach to be 1193.85 km2 by the year 2035. In addition to serious local climate changes will prevail.
Local scour around bridge piers and abutments, induced by hydraulic deficiencies, is the major cause of bridge failure. Most of the available empirical formulae have been developed based on experimental laboratory tests using uniform sand. However, the bed sediment in the field is to some extent graded. To develop a more reliable formula, well graded sand was used in the experimental flume of this study. In the present paper, the local scour depth around exposed single pile founded in sandy soil was studied experimentally in the laboratory to predict its maximum value. New scour depth prediction equations were developed and compared with some of the previous published equations, other researcher's data, and field data and they were found in very good agreement with them. For complete definition of the scour hole geometry, new equations were developed to estimate the scour hole width at different locations around the pile, thus helping in introducing protection measures for the scour hole. The developed equations are applicable for both clear-water and live-bed scour cases.
Two criteria of good vehicle suspension performance are typically their ability to provide good road-holding ability and increased passenger comfort. The main disturbance affecting these two criteria is terrain irregularities. Active suspension control systems reduce these undesirable effects by isolating car body motion from vibrations at the wheels. The paper describes an adaptive fuzzy control (AFC) schemes for the automobile active suspension system (ASS). The design objective is to provide smooth vertical motion so as to achieve the road-holding (with as small as possible tire deflection) and riding comfort over a wide range of road profiles. Effectiveness of the proposed control scheme is demonstrated via simulations. With respect to the optimal linear control (LQR), it is shown that superior results have been achieved by the AFC.
A method to evaluate the seismic collapse performance of frame structures through a probability-based assessment procedure is presented, considering uncertainties in both the ground motion hazard and inelastic structural response to extreme input ground motions. The procedure includes a new seismic-intensity scaling index that accounts for period softening and thereby reduces the large recordto-record variability typically observed in inelastic time-history analyses. Equations are developed to combine results from inelastic time history analyses and a sitespecific hazard curve to calculate the mean annual probability of a structure exceeding its collapse limit state.
This paper proposes a dynamic search based optimization algorithm for solving dual security constrained economic load dispatch problem in modern power systems. The proposed research paper presents a multi-objective Dynamic Random Neighborhood PSO “DRN-PSO”, which uses random neighborhood of every particle every time we need to know the experience we got in the swarm. This helps the diversity of the swarm to be preserved in order to discourage premature convergence. Moreover, the proposed algorithm uses dynamically adjusted Inertia weight to balance global exploration and local exploitation. Simulations were conducted on IEEE 30-bus test systems and compared to other optimization techniques that reported in the literature. The obtained results demonstrate the superiority of the proposed DRN-PSO compared to other optimization techniques that is reported in the literature. Additional economic benefits with secure settings are fulfilled, while preserving all system constraints within their permissible limits. The proposed algorithm improves the economic issue as well as enhancing the power system operation in the technical point of view with acceptable levels of emissions. So, it can be considered as a promising alternative algorithm for solving problems in practical large scale power systems.
Despite 35 years of R&D on the problem of Optical character Recognition (OCR), the technology is not yet mature enough for the Arabic font-written script compared with Latin-based ones. There is still a wide room for enhancements as per: lowering the Word Error Rate “WER”, standing robust in face of moderate noise, and working on an omni-font open-vocabulary basis. Among the best trials done in this regard so far comes the HMM-based ones. Elaborating on this Automatic Speech Recognition “ASR”-inspired promising approach, our team has significantly refined basic processes and modules deployed in such architectures “e.g. lines & words decomposition, features extraction, models parameters selection, language modelling, .., etc.” to develop what is hoped to be a truly reliable “i.e. low WER, omni fontwritten, open-vocabulary, noise-robust, and responsive” Arabic OCR suitable for reallife IT applications. This paper extensively reviews the HMM-based approach for building Arabic font-written OCR’s in general, and our work in specific. It also reports about the experimental results obtained so far showing that our system outperforms its rivals reported in the published literature.
Although current design codes include detailed methodology for the design of beams, no provisions for the design of composite beams with web openings are incorporated. In this research, an elaborate finite element model for composite beams with web opening is developed. The model is verified by comparing its behavior with available experimental tests. The finite element model is used to conduct a parametric study to investigate the effect of opening location, depth, width, and vertical eccentricity on the behavior of the beam. The model is extended to take into consideration the material non-linearity, the shear connector non-linearity, and the geometric non-linearity. The extended model is used to determine the failure load for beams with different web opening geometry. Simplified approaches for modeling composite beams with web openings are presented and results are compared with available experimental tests and finite element model and limitations are investigated.
The shoreline changes in the vicinity of offshore breakwaters are significantly influenced by the geometric parameters of offshore breakwaters. The complexity of the behaviour of shoreline changes behind offshore breakwaters makes it difficult to predict analytically these changes. As a result, numerical models are frequently used. In this paper, Artificial Neural Networks (ANNs) are developed to predict the shoreline changes behind offshore breakwaters. The developed ANN models can accurately predict the salient size, XS , the sand deposited volume behind offshore breakwaters, VS , for a known set of geometric parameters of offshore breakwaters. Four geometric parameters are found to be important, they are: the breakwater length, LB, the offshore distance of the breakwater from the original shoreline, XB, the surf zone width, Xb and the gape spacing between adjacent breakwaters, GB, respectively. A comparison between ANNs and regression models for predicting the salient size and sand deposited volume is presented and the advantages of utilizing ANN methodology over regression techniques in model development are highlighted.
The basic idea behind fractional calculus is that it considers derivatives and integrals of non-integer orders giving extra degrees of freedom and tuning knobs for modeling complex and memory dependent systems with compact descriptions. This paper reviews fractional calculus history, theory, and its applications in electrical engineering. The basic definitions of fractional calculus are presented together with some examples. Integer order transfer function approximations and constant phase elements (CPEs) emulators are overviewed due to their importance in implementing fractional-order circuits and controllers. The stability theory of fractional-order linear systems is outlined and discussed. Four common electrical engineering applications are surveyed. Fractional-order oscillators allowcontrolling the phase difference, aswell as achieving high oscillation frequency independently. Fractional order electronic filters are used to provide non-integer order slopes eliminate the need to round up the filter order and achieve the exact required time and frequency domain specifications. Studying fractional-order bioimpedance models provides better fitting to the measured data from fruits and vegetables. Fractional order DC-DC converter models provide a better estimation of the power conversion efficiency by incorporating frequency-dependent losses.
In this study, a maintenance schedule optimization model is developed for multiunit, multi-state systems with multi-level of preventive maintenance actions. The decision variable in this model is the sequence of preventive maintenance actions which applied to the system in a finite time horizon. The total maintenance cost includes preventive maintenance, minimal repair, and downtime costs. Moreover, the developed model includes three types of constraints, which are system reliability, minimum interval between maintenance activities, and crew availability. The proposed model is solved using a specialized constrained genetic algorithm technique combined with simulation technique, and are programmed using MATLAB. The presented approach has the potential to solve realistic scale problems.
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