Project risk management in Iranian small construction firms

The objective of this study is to evaluate RM in small projects in Iran using identification of status, barriers, and the impact of RM on project performance. In this study, theoretical foundations and research literature were first developed through library, and then a questionnaire about these variables was designed and distributed among a number of experts in the active construction companies. Data were collected from 40 projects submitted by 25 experts from 5 executive companies. According to the studies, 10 barriers are identified as major obstacles to RM implementation in such projects, prioritized as follows: (1) lack of potential benefits, (2) not economical, (3) lack of time, (4) lack of budget, (5) lack of knowledge, (6) lack of government legislation, (7) lack of manpower, (8) low profit margin, (9) complexity of analytical tools, and (10) competition among SMCs. The findings of this research can provide an in-depth understanding of RM in small projects in Iran and make benefits of RM convincing to the participants of small projects.

Urban voids: identifying and optimizing urban voids potential as a revitalization source in enhancing developing countries’ city income

This study attempts to remedy the issue of urban voids, which are one of the possible choices for extra interactive spaces. As a city with a great civilization history, Egypt is also home to many urban voids, mainly buffer zones. This generates the research problem that urban voids result from managing isolated planning sites irrespective of the context and away from the community. Few studies tackled the impact of public spaces on city life; they were mainly theoretically oriented and focused on piazzas without highlighting other spaces or conducting empirical investigations. The study determines that voids could be a testing ground to establish a framework of how these spaces can be reused. Revitalizing urban voids goal is to reconnect these useless spaces with context, achieve users’ needs, integrate technologies with the space to revitalize the city, and increase its income through combining theoretical findings, empirical study, and questionnaires, which generate a framework that helps the planners and designers in developing urban voids and maximizing its efficiency. Currently, adaptive redesign is a hot topic to discuss, and this may be the moment to realize that following the updated design components, meeting community needs, and using technology will always reinvigorate the void.

On the modeling and simulation of coupled adsorption and thermosolutal convection in supercritical carbon dioxide

In this paper, we present a numerical study along with an exhaustive adsorption investigation in a binary dilute mixture model nearby the solvent’s critical point in a configuration relevant for soil remediation. By means of this model, mass and heat transfer efficiency were qualitatively and quantitatively discussed through this work. The convergence of the solution was evaluated on the values of the Nusselt and Sherwood numbers. The results reveal intense convection expanding into the cavity close to the critical point, thus enabling homogeneous adsorption of the solute. Moreover, the mass fraction perturbation isolines exhibit the existence, along the adsorbent plate, of a thin boundary layer which becomes thinner when approaching the critical point.

A high accuracy modeling scheme for dynamic systems: spacecraft reaction wheel model

Reaction wheels are crucial actuators in spacecraft attitude control subsystem (ACS). The precise modeling of reaction wheels is of fundamental need in spacecraft ACS for design, analysis, simulation, and fault diagnosis applications. The complex nature of the reaction wheel leads to modeling difficulties utilizing the conventional modeling schemes. Additionally, the absence of reaction wheel providers’ parameters is crucial for triggering a new modeling scheme. The Radial Basis Function Neural Network (RBFNN) has an efficient architecture, alluring generalization properties, invulnerability against noise, and amazing training capabilities. This research proposes a promising modeling scheme for the spacecraft reaction wheel utilizing RBFNN and an improved variant of the Quantum Behaved Particle Swarm Optimization (QPSO). The problem of enhancing the network parameters of the RBFNN at the training phase is formed as a nonlinear constrained optimization problem. Thus, it is proposed to efficiently resolve utilizing an enhanced version of QPSO with mutation strategy (EQPSO-2M). The proposed technique is compared with the conventional QPSO algorithm and different variants of PSO algorithms. Evaluation criteria rely upon convergence speed, mean best fitness value, stability, and the number of successful runs that has been utilized to assess the proposed approach. A non-parametric test is utilized to decide the critical contrast between the results of the proposed algorithm compared with different algorithms. The simulation results demonstrated that the training of the proposed RBFNN-based reaction wheel model with enhanced parameters by EQPSO-2M algorithm furnishes a superior prediction accuracy went with effective network architecture.

Enhancing corrosion resistance of RC pipes using geopolymer mixes when subjected to aggressive environment

The durability of reinforced concrete (RC) pipes depends upon the corrosion resistance of the reinforcing steel and the resistance of concrete mixes against an aggressive environment. This research paper aims to compare the performance of R.C. pipes made of ordinary Portland cement (OPC) concrete mixtures with others made of two different geopolymer concrete mixes based on different ratios of granulated blast furnace slag (GBFS), fly ash (FA), and pulverized red brick (RB) subjected to three different environments, ambient, tap water (TW), and an aggressive environment, and a solution of 10% magnesium sulfates + 5% chloride (MS-CL). An accelerated corrosion setup has been applied to accelerate the corrosion process in the tested samples. The evaluation of change of compressive strength of concrete and microstructure of different mixes was investigated too. Fourier transform infrared (FTIR) spectroscopy has been studied on all pipes. Geopolymer concrete mixes based on 90% GBFS and 10% RB show better results in all cases. Geopolymer concrete mixes based on 63% GBFS, 27% FA, and 10% RB increase the concrete compressive strength in the magnesium sulfate and chloride environment by 5% compared to tap water. It can be concluded that the geopolymer concrete mixes produced of 90% GBFS and 10% RB perform well under all environments, and its microstructure shows stable behavior in an aggressive environment.

Development of impact attenuator analysis tools in crash scenario using Euler method and finite element analysis

The problem considered in this work is the development of simulation method for simulating car crash which utilizes simple car—impact attenuator model developed in MATLAB. Usually, car crash simulation is done using full finite element simulation which could take hours or days depending on the model size. The purpose of proposed method is to achieve quick results on the car crash simulation. Past works which utilizes simple car—impact attenuator model to simulate car crash use continuous time model and the impact attenuator parameter is obtained from the experimental results. Different from the related works, this work uses discrete time model, and the impact attenuator parameter is obtained from finite element simulation. Therefore, the proposed simulation method is not only achieving quick simulation results but also minimizing the cost and time in obtaining the impact attenuator parameter. The proposed method is suitable for parametric study of impact attenuator.

Effect of service differentiation on QoS in IEEE 802.11e enhanced distributed channel access: a simulation approach

The enhanced distributed channel access (EDCA) protocol is a supplement to IEEE 802.11 medium access control (MAC), ratified by IEEE 802.11e task group to support quality of service (QoS) requirements of both data and real-time applications. Previous research show that it supports priority scheme for multimedia traffic but strict QoS is not guaranteed. This can be attributed to inappropriate tuning of the medium access parameters. Thus, an in-depth analysis of the EDCA protocol and ways of tuning medium access parameters to improve QoS requirements for multimedia traffic is presented in this work. An EDCA model was developed and simulated using MATLAB to assess the effect of differentiating contention window (CW) and arbitration inter-frame space (AIFS) of different traffic on QoS parameters. The optimal performance, delay, and maximum sustainable throughput for each traffic type were computed under saturation load. Insight shows that traffic with higher priority values acquired most of the available channels and starved traffic with lower priority values. The AIFS has more influence on the QoS of EDCA protocol. It was also observed that small CW values generate higher packet drops and collision rate probability. Thus, EDCA protocol provides mechanism for service differentiation which strongly depends on channel access parameters: CW sizes and AIFS.

Activating biophilic design patterns as a sustainable landscape approach

Biophilic design elements are found around us in many landscape elements while we do not perceive them as biophilic design patterns. By developing our understanding of biophilic design as a phenomenon, we could discover simple ways to utilize landscape elements and transform them into a good biophilic design that might have positive impacts on a user’s health and well-being. Activating existing biophilic elements as an approach to a sustainable landscape has not been studied yet. Therefore, we rather analyse some international case studies in order to understand how biophilic design patterns can be implemented and see their different forms. Later, we will also go through an Egyptian biophilic design pattern case study and implement it to reach a sustainable landscape model. To summarize, the purpose of this study is to present a new sustainable landscape approach by activating biophilic design patterns in order to increase landscape efficiency.

Effect of short glass fiber on shear capacity for shallow wide reinforced concrete beams

Shallow wide reinforced concrete beams are used in modern buildings especially in residential building structures. According to current Egyptian Code Practice 203-2018; the characteristic of a shallow wide concrete beam is that the cross-section width (b) over the effective depth (d) ratio is greater than two and the beam depth is less than 250 mm. Without any shear reinforcing contribution, the applied shear stresses in shallow wide beams must be less than the concrete shear strength. And only concrete provides shear strength. An experimental program was conducted to investigate the contribution of short glass fiber polymer reinforcement to shear strength in shallow wide beams under shear stress. The short glass fiber polymer reinforcement ratio was the main parameter in this study. And also, the contribution of web shear stirrups reinforces against shear stresses. The experimental program consisted of five simply supported reinforced shallow wide concrete beams. Test results show that the use of short glass fiber reinforced polymer has a great effect on shear strength capacity, mode of failure, and ductility of shallow wide concrete beams.

A survey on GAN acceleration using memory compression techniques

Since its invention, generative adversarial networks (GANs) have shown outstanding results in many applications. GANs are powerful, yet resource-hungry deep learning models. The main difference between GANs and ordinary deep learning models is the nature of their output and training instability. For example, GANs output can be a whole image versus other models detecting objects or classifying images. Thus, the architecture and numeric precision of the network affect the quality and speed of the solution. Hence, accelerating GANs is pivotal. Data transfer is considered the main source of energy consumption, that is why memory compression is a very efficient technique to accelerate and optimize GANs. Two main types of memory compression exist: lossless and lossy ones. Lossless compression techniques are general among all models; thus, we will focus in this paper on lossy techniques. Lossy compression techniques are further classified into (a) pruning, (b) knowledge distillation, (c) low-rank factorization, (d) lowering numeric precision, and (e) encoding. In this paper, we survey lossy compression techniques for CNN-based GANs. Our findings showed the superiority of knowledge distillation over pruning alone and the gaps in the research field that needs to be explored like encoding and different combination of compression techniques.