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The purpose of this research is to explore the extent to which internal corporate social responsibility activities affect employees’ normative organizational commitment during the COVID-19 crisis and to survey the role of the administrative level as a moderator between the two of them. A survey in the form of a self-completed questionnaire was conducted on a sample of employees in hospitality and tourism establishments in Hail city, Kingdom of Saudi Arabia. 213 employees voluntarily participated in the current study. Their responses were examined by using linear regression and exploratory factor analyses. The findings revealed that internal corporate social responsibility is a positive predictor of normative organizational commitment. The total effect of internal corporate social responsibility on normative organizational commitment could not be enhanced through the moderation of the administrative position. This study has important implications for both academics and professionals. Theoretical and managerial implications, contributions, limitations, and future study objectives were reviewed in light of the findings.

The search for a unification of the physical phenomena was the preoccupation of many physicists for long time. Starting from the seventeenth century with the unification of celestial mechanics and gravitation, then the unification of the electromagnetism in the nineteenth century. The early twentieth century brought about the unification of space and time and the unification of energy and mass while the advent of gauge theory enabled the unification of the weak interaction with the electromagnetism in the middle of the twentieth century. More recent theories are proposed as the answer to the unification question in physics include quantum gravity which unifies quantum mechanics and gravitation, and string theory. Unification effort should not only address the known fundamental forces but the space fabric interactions which till now remain unknown but their manifestations are described as the dark energy and dark matter. Here the concept of interacting space and time fields which constitute space time is discussed using classic method which has a certain advantage of bringing the physical meaning into visualization.

Autonomous Driving is one of the difficult problems faced the automotive applications. Nowadays, it is restricted due to the presence of some laws that prevent cars from being fully autonomous for the fear of accidents occurrence. Researchers try to improve the accuracy and safety of their models with the aim of having a strong push against these restricted Laws. Autonomous driving is a sought-after solution which isn’t easily solved by classical approaches. Deep Learning is considered as a strong Artificial Intelligence paradigm which can teach machines how to behave in difficult situations. It proved its success in many differ domains, but it still has sometime in the automotive applications. The presented work will use the end-to-end deep machine learning field in order to reach to our goal of having Full Autonomous Driving Vehicle that can behave correctly in different scenarios. CARLA simulator will be used to learn and test the deep neural networks. Results will show not only performance on CARLA’s simulator as an end-to-end solution for autonomous driving, but also how the same approach can be used on one of the most popular real datasets of automotive that includes camera images with the corresponding driver’s control action.

This essay explores the relationship between fantasy, fabulation, and the performative through the lens of exhibition design in general and, in particular, expo pavilions. While studying the case of the Austrian pavilion visited by the author during Expo Milan 2015, it further examines the repertoire of the performative as a spatial fabulation indicator. Furthermore, the essay proposes a dramaturgy of analytical tools that interpret the exhibition space as a metaphor of a fantasy-oriented spatial production, and as an illustration of a performative interior architecture opening newer perspectives through which we may study and analyse interiors.

With the aim of efficiently achieving complex trajectory tracking missions in the presence of model uncertainties and exogenous disturbances, this paper proposes a robust hybrid control for the orientation and position of flying robots by adopting insights from sliding mode, geometric tracking, and nonlinear feedback control strategies. Various retrofits are implemented to the composite control scheme in order to tackle the system uncertainties, eliminate the chattering effects, and enhance the trajectory tracking performance. The convergence and stability analysis demonstrated the asymptotic stability of the proposed control algorithm. To reveal the promising performance of the developed control schemes, a qualitative comparative analysis of different proposed control approaches is performed. The comparative analysis examines highly maneuverable trajectories for various tracking scenarios in the presence of uncertain disturbances. The simulation results demonstrated the versatility, robustness, and convergence of the developed control laws that allow autonomous flying robots to effectively perform agile maneuvers.

Assessment of the Hubble parameter as an indicator of the expansion rate of the universe holds a central position in the field of astronomy. From its initial estimate of about 500 km⋅sec-1⋅parsc-1, this value had been steadily amended as the observational tools became more accurate and precise. Despite this, a gap remains between the value of observations relating to local and nonlocal estimations of the Hubble parameter that gave rise to what became known as the Hubble tension. This tension is addressed here while dealing with space fabric as a cosmological fluid that undergoes transition.

This paper proposes a robust control for wheeled inverted pendulum (WIP) taking into account the wheel position and pendulum angle in the presence of uncertain disturbances. The proposed control algorithm is a combination of time-varying sliding mode control (TVSMC), exponential reaching law (ERL), and nonlinear feedback control (NFC) to eliminate the chattering phenomenon and arrive at better stability and tracking performance. For consistency, the nonlinear dynamic model of WIP is derived using Lagrangian and Newtonian approaches. The convergence and stability of the proposed control scheme are proved using Lyapunov theorem. The study also presents a comparative analysis of linear and nonlinear control strategies based on investigation of time response, tracking error, and control energy. The WIP system has been subjected to various rigorous initial conditions and disturbances to characterize the stability and tracking performance of the implemented controllers. The simulation results demonstrate the promising performance of the proposed control scheme in eliminating the chattering phenomenon, suppressing the uncertain disturbances effect, and improving the stability and tracking performance.

The search for a unification of the physical phenomena was the preoccupation of many physicists forlong time. Starting from the seventeenth century with the unification of celestial mechanics and gravitation, then The unification of the electro magnetism in the nineteenth century. The early twentieth century brought about the unification of space and time and the unification ofenergy and mass while the advent of gauge theory enabled the unification of the weak interaction withthe electromagnetism in the middle of the twentieth century. More recent theories are proposed as the answer to the unification question in physics includequantum gravity which unifies quantum mechanics and gravitation, and stringtheory. Unification effort should not only address the known fundamental forces but the space fabric interactions which till now remain unknown but their manifestations are described as the dark energyand dark matter Here the concept of interacting space and time fields which constitute space time is discussedusing classic method which has a certain advantage of bringing the physical meaning intovisualization. &nbsp

This paper presents a new trajectory generation and optimization algorithm (TGOA) for an agile and aggressive flight of quadrotor UAVs. The optimizer considered the constraints associated with robot dynamics, actuator inputs, and flying environment to produce collision-free dynamically feasible trajectories. The algorithm is developed based on time-par-ametrized polynomials trajectories consist of a predefined sequence of waypoints indicating the robot's desired state over time. This work is an extension of existing studies that utilized the differential flatness property and polynomial-based trajectories. Doing so will lead to eliminating the need for iterative searching and computationally intensive sampling in the high dimensional state space of the quadrotor system dynamics. The main advantage of the proposed algorithm lies in its numerical stability for a large number of waypoints and high-order polynomials. The TGOA addressed the ill-conditioned problem of Quadratic Programming (QP) based methods, by reformulating the trajectory generation and optimization problem into unconstrained quadratic programming (UCP). To do so, the numerically stable null-space factorization method is used. The Proposed TGOA produces minimum derivatives trajectories along with minimum waypoints' arrival times. Several scenarios and comparisons have been conducted to reveal the numerical stability and computational advantages of the proposed TGOA. They also demonstrate the variety of aggressive trajectories that can be rapidly generated so that utilizing the full maneuvering capabilities of quadrotor robots.

Background To assess patients undergoing radical cystectomy using enhanced recovery protocol and standard protocol in terms of intraoperative and postoperative outcomes and complications. Results All operative and postoperative complications were recorded. In group B, time to normal bowel activity ranged from 1 to 4 days, and the mean was 1.8 days (± 1.02), while it ranged from 1 to 5 days, and the mean was 3.17 days (± 1.14) in group A which was statistically significant (p value p value = 0.033). Postoperative mortality was similar in both groups. Conclusion In patients undergoing radical cystectomy, enhanced recovery protocol is considered as a safe procedure and not associated with any increase in intraoperative and postoperative complications compared to standard protocol. The length of hospital stay and time to return to full diet are reduced.

Introduction and Objective: The incidence of erectile dysfunction (ED) after TURP for BPH is still debated. Current study aims at comparing the impact of monopolar and bipolar TURP on the sexual function of male patients with LUTS, using the IIEF EF-domain score (questions 1–5, 15) and to identify statistical risk factors associated with development of post-operative ED. Patients and methods: Between April 2014 and May 2015, 102 patients underwent TURP for symptomatic BPH. Sixty on underwent TURP by the monopolar technique and 41 by the bipolar technique. Patients were assessed on the day before the surgery by IIEF and followed up 3 and 6 months postoperatively, using the same scoring system. Results: On a 6 month follow up,13 patients (22.4%) in the monopolar group and 12 (30%) in the bipolar group, experienced clinical change in their EF score. Among risk factors studied, only diabetes, intraoperative capsular perforation and preoperative use of PDE5I had a statistically significant impact on the EF score.No statistically significant difference in IIEF score and EF domain score was observed between the patients who underwent TURP by the monopolar technique, compared to those patients in which the bipolar one was used; whether at three months (p value 0.33) or at six months (p value 0.397). Conclusion: No statistical difference could be detected between monopolar and bipolar TURP, regarding the risk of developing post-operative ED. However, a higher incidence of ED should be anticipated in patients with DM, intraoperative capsular perforation and preoperative use of PDE5I. Keywords: BPH, Prostate, TURP, Bipolar resection, Erectile dysfunction

The current literature on social responsibility in tourism is criticized for its bias in focusing on business ethics and responsibility while neglecting the tourist perspective. This paper aims to fill this gap by exploring the underlying factors of tourist social responsibility (TSR) in response to the COVID-19 pandemic, emphasizing the Saudi tourism market. Based on the common scale development procedures, including a thorough review of the literature, identifying TSR domains and items, purifying the measurement scale, and demonstrating its reliability, a five-dimensional 24-item scale is developed. The findings reveal that TSR can be measured based on five distinct factors: (1) “Responsibility for legal and social aspects”, (2) “Responsibility for COVID-19 health issues”, (3) “Responsibility for altruism and solidarity”, (4) “Responsibility for supporting socially responsible businesses”, and (5) “Responsibility for environmental impacts”. Moreover, the results confirm the significant relationship between TSR attitude and tourists’ intention to behave socially. These findings enable policymakers to understand the TSR notion and factors influencing tourists to be more socially responsible during and after the COVID-19 pandemic to realize a more resilient and sustainable tourism sector.

The Eocene sediments plays critical role in the evolution and development of the petroleum system in the Gulf of Suez region, where it is representing a self-source rock or self-reservoir or combination in some areas within the basin. Microfacies analysis and paleontological studies have not been conducted on these Eocene sediments in the area of the October oil field, which is mandatory for the formation characteristics assessment. Therefore, sidewall core and ditch-cuttings samples that was obtained from October Eocene carbonate sediments so far ascribed to the Thebes formation was studied in terms of sedimentology, paleontology and depositional environment. A total of 64 thin sections were analyzed petrographically, and three microfacies types recognized. Both Calcareous nanoplankton and Foraminifers were examined. The study of the Eocene carbonate facies in the October field revealed that the succession is composed of pelagic foraminiferal limestone of varied color, containing abundant planktonic foraminifers and minor traces of chert. Three microfacies are distinguished including wackestone of smaller planktonic foraminifera (50%), wackestone-packstone of planktonic foraminifera (40%) and packstone of planktonic foraminifera (10%). Nannoplankton and foraminifers indicate that the studied succession is of early Eocene to middle Eocene age. Microfacies and fossil assemblage of the studied section indicate a pelagic environment and deposition in deep basin at water depths of a few hundred meters. Finally, the current results were compared with data from previous publications on Eocene sediments in the region. It is revealed that the studied succession provides new data and contribution for the evolution of carbonate platform in the Ypresian-Lutetian age, and differs from the typical Thebes Formation and other Eocene Formations concerning facies, lithology, fossil content, age and depositional environment. Therefore, we suggest to abandon the term Thebes Formation for this Eocene carbonate succession in the October field, and a new lithostratigraphic unit, named Radwany Formation, is formally introduced.

Objective: We compared the results of holmium laser and pneumatic intracorporeal lithotripsy for large ureteric calculi in terms of efficacy, safety and complications. Methods: The study was conducted between April 2009 and October 2010. 80 patients divided into two equally matched groups were included in a prospective randomized trial including patients with a ureteric stone size of 0.5–2 cm. A holmium laser with a 550-µm fiber was employed in the laser lithotripsy (LL) group. The Swiss Lithoclast was used in the pneumatic lithotripsy (PL) group. Results: Mean stone size was comparable in both groups, namely 13.1 mm in the PL group and 12.9 mm in the LL group. The early stone-free rate was equal in both groups, while the delayed stone-free rate was 95% in LL and 85% in PL. Stone migration occurred in 12 PL cases and in 5 LL cases. Ureteric perforation occurred in 3 LL cases and in 2 PL cases. Ureteric stricture occurred in 1 case following LL. Conclusion: Both PL and LL are effective and safe modalities in treating large ureteric stones with minor insignificant differences. A pneumatic system may be more efficient with regard to the cost-benefit ratio, which was not studied in the present work; further studies should address this issue.

This paper presents an algorithm to develop a mission-based optimal task space control for a Stewart manipulator. The proposed algorithm consists of two optimization phases. The first phase seeks an optimal polynomial approximate model for the forward kinematics of a Stewart manipulator using a predicted square error cost function. The second phase optimally tunes the controller gains in order to meet special mission requirements. Genetic algorithms are used in both phases as the optimization method. A stall recovery maneuver, one of the most dangerous flight conditions, is selected as the test case. The proposed mission-based optimal task space control shows the capability to reduce the error in training the pilot for stall recovery maneuver.

The terms ‘Performative’ and ‘Performance’ are more and more emerging in the spatial design discourses, from exhibition, to interior, arriving to urban design. These notions are not clearly defined yet. They are characterized by a semantic width and multiple applicative possibilities. Between the different interpretations and uses of ‘performance’ and ‘performative’ in architectural discourses, this paper will focus on two main dimensions of a particular importance: The first refers to the concepts of the scenic, the narrative, and the theatrical qualities in architecture. The second relates to the ‘event-character’ of spatial interventions, and the relation between event, and soft intervention, which tackles the concept of the ‘transformative power of the performative’, which indicates to the capacity of architecture to activate spaces and processes.

PurposeThe purpose of this paper is to show the merit of using mission information in tuning the controller gains for Stewart manipulator instead of the generic inputs previously developed in literature.Design/methodology/approachThe paper introduces two optimization techniques based on mission information. The first technique, a partial‐information technique, uses gain scheduling that applies different controllers for different mission tracks. The second technique, a full‐information technique uses a single robust controller by considering the full mission data. For demonstrating these techniques' feasibility, a nonlinear numerical simulation for a Stewart manipulator was built and tested using a generic mission. This mission consists of two piecewise trajectories (tracks). The proposed techniques were compared with one of the previous optimization techniques in literature, no‐information technique, in which a step response is used to search for optimal controller gains without any information about the mission. Genetic algorithms were used to search for the optimal controller gain in each case with different cost functions.FindingsBased on the numerical simulations, the proposed mission‐based optimization techniques have superior performances compared with no‐information technique.Research limitations/implicationsThe proposed techniques were applied in a joint space or for a decentralized control. The work can be extended to be applied in a task space or for a centralized control.Originality/valueThe paper proposes two novel optimization techniques: partial‐ and full‐information techniques for tuning the controller gains of a Stewart manipulator, where mission information was imbedded into the cost function. These two techniques are generally applicable for other nonlinear systems such as aircraft stability and control augmentation systems.

A hybrid heuristic optimization technique based on genetic algorithms and particle swarm optimization has been developed and tested for trajectory optimization problems with multi-constraints and a multi-objective cost function. The technique is used to calculate control settings for two types for ascending trajectories (constant dynamic pressure and minimum-fuel-minimum-heat) for a two-dimensional model of an aerospace plane. A thorough statistical analysis is done on the hybrid technique to make comparisons with both basic genetic algorithms and particle swarm optimization techniques with respect to convergence and execution time. Genetic algorithm optimization showed better execution time performance while particle swarm optimization showed better convergence performance. The hybrid optimization technique, benefiting from both techniques, showed superior robust performance compromising convergence trends and execution time.

In this paper, a new method for the numerical calculation of optimal, or nearly optimal, solutions to trajectory problems is presented. This method, which is applicable to a large category of problems, is based on a modified genetic algorithm that is an optimum-seeking method that attempts to apply the rules of biological evolution, mutation, and selection to technical optimization problems. The modification is achieved by repeatedly applying a global optimization genetic algorithm method while incrementing the number of design variables (i.e., increasing the size of the chromosomes). The trajectory data used for the optimization process are produced via simulation of the equations of motion using numerical integration techniques. The trajectory optimization technique is tested on a supersonic missile moving in the vertical plane but it is equally applicable to three-dimensional trajectories with minimum formulation time and effort, and ideally suited for parallel computing. The results show the successful application of the incremented genetic algorithm to trajectory problems and its superiority over the fixed chromosome-size genetic algorithm technique.

Several obstacles limiting the use of contemporary control design techniques in production vehicles are noted. These obstacles restrict one from obtaining insight into the control law augmentation of the vehicle. For example, with the linear quadratic (LQ) state feedback method, detail effects from cost function weight adjustment are not easily understood. Further, the role of each feedback loop is not readily apparent. Fundamental to overcoming this problem is factoring of the LQ characteristic polynomial. Useful analytical expressions, and ultimately the relationships they represent, are sought between basic design parameters of the system and the closed-loop eigenvalues. An approximate analytical factoring technique, previously developed for open-loop applications, is considered as a tool for this closed-loop problem. The e rst two terms of a Taylor series are used to capture the polynomial coefe cient dependencies on the polynomial factors. By analytically inverting the e rst-order sensitivity matrix, corrections to preliminary approximate factors are generated. Expressions for the closed-loop factors are in terms of basic parameters such as stability and control derivatives, structural vibration damping ratio and natural frequency, and cost function weights, allowing key relationships to beuncovered between the design knobs and important closed-loop features.

The beginning of modern engineering education in Egypt dates back to 1816 when the famous ruler “Wali”; Mohammed Ali Pasha established “Madrasat El-Mohandeskhana” (which means the School of Engineering). This start was 92 years before the establishment of Cairo University which became a reality on December 21st, 1908. In 1935, it was renamed as the “Faculty of Engineering”. The Faculty of Engineering has kept this name ever since. Aerospace engineering department was established in 1953 under the name of “Aeronautics Engineering” and it played an important role for promoting the economic and strategic growth in Egypt since its inception. This paper aims to reflect past, present and future research and development in Aerospace Engineering department at Cairo University. It will shed some light on the department capabilities and accomplishments and future hopes and vision.

The failure rate analysis of brake assemblies of a commercial airplane, i.e., Boeing 737, is analyzed using the artificial neural network and Weibull regression models. One-layered feed-forward back-propagation algorithm for artificial neural network whereas three parameters model for Weibull are used for the analysis. Three years of data are used for model building and validation. The results show that the failure rate predicted by neural network is closer in agreement with the actual data than the failure rate predicted by the Weibull model. Results also indicate that neural network can be effectively integrated into an aviation maintenance facility computerized material requirement planning system to forecast the number of brake assemblies needed for a given planning horizon.

In this paper, we propose a design methodology for the tracking of spacecraft attitude. The plant (spacecraft model) is a second order nonlinear multi-input-multi-output system. We stabilize the plant using state feedback. The stability of the closed-loop is assured using a Lyapunov function. Then the step response of the closed-loop system is used to design PID controller using standard classical techniques. Then adaptive feed-forward learning based adaptive filter is used for accomplishment of the tracking objective. The stabilizing controller is independent of the plant parameters. Further, we do not require plant parameters for the tracking. The parameters of adaptive inverse are directly estimated online. The over-all closed-loop gives robust performance as the controller design depends on the output of the plant and not on the parameters of the plant. Computer simulation results are given to illustrate the effectiveness of the proposed controller.

This paper presents a simple methodology for improving the estimation of a satellite orbit. It combines a low cost propagator and azimuth and elevation optical measurements, collected by a low-cost commercial camera, to correct orbit initial conditions. The corrected satellite Initial condition is fed to the propagator to allow accurate orbit propagation for longer period of time. The correction process aims at minimizing the deviation between optical measurements and numerical orbit calculations. A Genetic Algorithm procedure is used for the minimization process. The International space station (ISS) is used as a case study for the proposed methodology. The results show that it is possible to improve satellite orbit Estimation using measurements acquired from low cost cameras under certain conditions. The conditions and limitations for the methodology will be also discussed in this work.

*† Aerospace -plane ascent -trajectory optimization is a difficu lt problem due to the complexity of optimization cost surfaces and the need for human expertise during all steps of the optimization process in order to achieve good results. In this paper, a heuristic technique based on a genetic algorithm is used. The t echnique is applied to calculate minimum -fuel -minimum -heat ascent control settings for an energy state model of an aerospace plane.

In this paper, the formulation and the solution procedure of a minimum time dispatch problem (MTDP) is given. The problem can be summarized as finding the minimum time and path to transfer time sensitive materials from a dispatch center to certain targets or vice versa. It is a famous problem with many civil and military applications. A heuristic approach using two stages formulation is given here. The first stage is an iterative k-mean algorithm to cluster targets to lie within specific distance and the next stage is traveling salesman problem, solved with Genetic Algorithms (GA), to find the minimum path. The details of the problem and the solution procedure are given with simple test cases.

Feedforward neural networks can be used for nonlinear dynamic modeling. Although the basic principle of employing such networks is straightforward, the problem of selecting the training data set and the network topology is not a trivial task. This paper examines the use of genetic algorithm optimization techniques to optimize the neural network. The paper presents the results of studies on the effect of number of neurons and input combination method on the performance of neural networks and the application of this study to improve leak monitoring in pipelines. The neural networks examined in this study do not use the sensor reading directly as in conventional neural networks but combine it using polynomial type laws to produce hybrid inputs. The optimization technique tries to find the best polynomial laws (input combination) to reduce network size, head variation effect, and optimize network performance. The resulting networks show superior performance and use fewer numbers of neurons.Copyright © 2004 by ASME

This paper presents the dynamics and control of a small-scale quad-rotor using custom-built frame, off-the-shelf avionics, motors and batteries. The modeling part incorporates the airframe and motors dynamics as well as aerodynamic and gyroscopic effects. The modeling process includes analytical equations and experimental identification of different parameters which is difficult to be estimated analytically. The control part incorporates different classical schemes such as PID, PD, and derivative only feedback. A simulator of the complete system was built using Matlab and Simulink. The control code was written in C and was implemented in a PIC microcontroller. A prototype was built and tested with the selected controller to show good stabilization and good matching with the simulator.