An integrated retail space allocation and lot sizing models under vendor managed inventory and consignment stock arrangements

In this paper, we develop integrated retail shelf space allocation and inventory models for a single item with a stock dependent demand. The integrated models are developed for a supply chain operating under vendor-managed inventory (VMI) and consignment stock (CS) agreement. More precisely, the supplier is responsible for initiating orders on behalf of the retailer and decides about the size of each order, the quantity to be displayed on the shelves, and the reorder point. In addition, the supplier owns the stock at the retailer’s premises until it is sold. We develop mathematical models to assess the benefits accrued by both parties as a result of the adoption of VMI–CS partnership. Results from the numerical experimental study show that such partnership is more attractive to all supply chain members when the retailer provides a flexible display capacity. Moreover, the supplier can use his/her selling price and the maximum allocated shelf space as negotiation means to benefit from the partnership.     

On line and under veil: Technology-facilitated communication and Saudi female experience within academia

The Saudi female population, which is characterised as sheltered, hard-to-reach and conservative, is arousing good interest globally (and nationally). Therefore, a review of literature on emerging issues surrounding Saudi female experience is timely. This article, in the form of a literature review, provides a background to and justification for a forthcoming study, which will examine how technology-facilitated communication has shaped the social–cultural pattern of Saudi female experience within academia.     

Solubility of nitrogen in liquid nickel-based alloys

The solubility of nitrogen in liquid binary nickel-based alloys (Ni-Co, Ni-Fe, and Ni-Cr) and ternary Ni-Cr-Co alloys was measured by the Sieverts’ method between 1550 °C and 1750 °C. Solubility data and standard free energies and enthalpies of solution of nitrogen in the alloys are presented and interaction parameters are discussed. The validity of Sieverts’ law at 1600 °C and pressures up to 1 atm was also confirmed.     

Anchoring gold nanoparticles on graphene nanosheets functionalized with cationic polyelectrolyte: a novel catalyst for 4-nitrophenol reduction

In this paper, a stable aqueous dispersion of graphene nanosheets (GNs) has been prepared by chemical reduction of graphene oxide (GO) with hydrazine hydrate in the presence of poly [(2-ethyldimethylammonioethyl methacrylate ethyl sulfate)-co-(1-vinylpyrrolidone)] (PQ11). Taking advantages of the fact that PQ11 is a positively charged polymer exhibiting reducing ability, we further demonstrated the subsequent decoration of GN with gold nanoparticals (AuNPs) by in-situ chemical reduction of HAuCl4. It was found that such nanocomposites exhibit good catalytic activity toward 4-nitrophenol (4-NP) reduction and the GN supports also enhance the catalytic activity via a synergistic effect.     

Sailfish Optimizer with EfficientNet Model for Apple Leaf Disease Detection

Recent developments in digital cameras and electronic gadgets coupled with Machine Learning (ML) and Deep Learning (DL)-based automated apple leaf disease detection models are commonly employed as reasonable alternatives to traditional visual inspection models. In this background, the current paper devises an Effective Sailfish Optimizer with EfficientNet-based Apple Leaf disease detection (ESFO-EALD) model. The goal of the proposed ESFO-EALD technique is to identify the occurrence of plant leaf diseases automatically. In this scenario, Median Filtering (MF) approach is utilized to boost the quality of apple plant leaf images. Moreover, SFO with Kapur's entropy-based segmentation technique is also utilized for the identification of the affected plant region from test image. Furthermore, Adam optimizer with EfficientNet-based feature extraction and Spiking Neural Network (SNN)-based classification are employed to detect and classify the apple plant leaf images. A wide range of simulations was conducted to ensure the effective outcomes of ESFO-EALD technique on benchmark dataset. The results reported the supremacy of the proposed ESFO-EALD approach than the existing approaches.     

Implications of Onshore Development on Global Software Engineering

Recently software industry has paid significant attention to customizing software products across distributed boundaries. Communicating the requirements of multiple clients across distributed borders is a crucial challenge for the software customization process. Local decision-making and local development at the client site are considered methods for reducing difficulties in communicating the requirements of multiple clients across distributed boundaries. This paper introduces a new model called the onshore development model (ODM) for accomplishing the customization requests in the distributed development process of software. This model presents a scenario for enhancing the onsite development of specific requirements to reduce delays and misunderstandings between the clients and the team involved. This model depends on moving the development process to the client’s location. Three empirical studies were conducted to evaluate the proposed model to measure its productivity, time performance, and cost reduction. The proposed model has been compared with two other models: the basic model (BM), which allocates the decision-making process and the development process for teams at the vendor’s location, and the local decision-making model (LDec), which assigns the decision-making process for team at the client’s location. The results of the empirical studies showed significant outperforming of the proposed model over the basic model and local decision-making model in productivity, time performance, and cost reduction. The productivity of the proposed model improved by 39% and 10% more than the basic model and the local decision-making model, respectively. In addition, the time performance of the proposed model became faster by 49% and 20.8% than the basic model and the local decision-making model, respectively. Also, it reduced the total cost of the development process by 31% in terms of the salaries of all persons involved in requirements collecting, decision-making, and development.     

Forecasting E-Commerce Adoption Based on Bidirectional Recurrent Neural Networks

E-commerce refers to a system that allows individuals to purchase and sell things online. The primary goal of e-commerce is to offer customers the convenience of not going to a physical store to make a purchase. They will purchase the item online and have it delivered to their home within a few days. The goal of this research was to develop machine learning algorithms that might predict e-commerce platform sales. A case study has been designed in this paper based on a proposed continuous Stochastic Fractal Search (SFS) based on a Guided Whale Optimization Algorithm (WOA) to optimize the parameter weights of the Bidirectional Recurrent Neural Networks (BRNN). Furthermore, a time series dataset is tested in the experiments of e-commerce demand forecasting. Finally, the results were compared to many versions of the state-of-the-art optimization techniques such as the Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Genetic Algorithm (GA). A statistical analysis has proven that the proposed algorithm can work significantly better by statistical analysis test at the P-value less than 0.05 with a one-way analysis of variance (ANOVA) test applied to confirm the performance of the proposed ensemble model. The proposed Algorithm achieved a root mean square error of RMSE (0.0000359), Mean (0.00003593) and Standard Deviation (0.000002162).     

Experimental Study of Heat Transfer Enhancement in Solar Tower Receiver Using Internal Fins

The receiver is an important element in solar energy plants. The principal receiver’s tubes in power plants are devised to work under extremely severe conditions, including excessive heat fluxes. Half of the tube’s circumference is heated whilst the other half is insulated. This study aims to improve the heat transfer process and reinforce the tubes’ structure by designing a new receiver; by including longitudinal fins of triangular, circular and square shapes. The research is conducted experimentally using Reynolds numbers ranging from 28,000 to 78,000. Triangular fins have demonstrated the best improvement for heat transfer. For Reynolds number value near 43,000 Nusselt number (Nu) is higher by 3.5% and 7.5%, sequentially, compared to circular and square tube fins, but varies up to 6.5% near Re = 61000. The lowest friction factor is seen in a triangular fin receiver; where it deviates from circular fins by 4.6%, and square fin tubes by 3.2%. Adding fins makes the temperature decrease gradually, and in the case of no fins, the temperature gradient between the hot tube and water drops sharply in the planed tube by 7%.     

Effect of Ammonium Hydrogen Carbonate and Sodium Bromide on the Flammability of Hardboard

The fire retardancy properties of hardboard treated with ammonium hydrogen carbonate (AHC) and sodium bromide were investigated by measuring their ignition time and flame temperature. An increase in ignition time and lowered flame temperature were observed with increased flame retardant (FR) concentration. AHC was found to be less effective as a fire retardant for this material. © 1996 by John Wiley & Sons, Ltd.     

Reactive phase separation: Prediction of an occlusion morphology

Reaction-induced phase separation occurring by spinodal decomposition is simulated in this paper. A technique developed earlier [Alfarraj A, Nauman EB. Spinodal decomposition in ternary systems with significantly different component diffusivities. Macromolecular Theory and Simulations, 2007;16:627-31.] that allows component diffusivities to be dramatically different has been extended to reactive conditions. The example system is the formation of impact polystyrene. The final morphology is a continuous polystyrene phase and a discrete rubber phase where the rubber particles contain polystyrene occlusions. The morphology is modeled for an agitated batch reactor. Simulations of a quiescent batch polymerization also give a discrete rubber phase. This is contrary to reports in the early patent literature, the difference being attributed to cross-linking of the rubber that is not considered in the current model.