Suppression of the α → β-nickel hydroxide transformation in concentrated alkali: Role of dissolved cations

The presence of dissolved cations such as Al and Zn in alkaline electrolyte (6 M KOH) suppresses the -nickel hydroxide transformation. The uptake of Al (10 mol%) and Zn (30 mol%) exhibited by the active material likely stabilizes the -phase. Dissolved Al is deleterious to the performance of the nickel hydroxide electrode, whereas, dissolved Zn enhances the specific discharge capacity of nickel hydroxide by approximately 25% showing that the mode of metal uptake is different in the two cases.     

Equivalence of classicality and separability based on P phase–space representation of symmetric multiqubit states

Classical and quantum world views differ in peculiar ways. Understanding decisive quantum features—for which no classical explanation exist—and their interrelations is of foundational interest. Moreover, recognizing non-classical features carries practical significance in information processing tasks as it offers insights as to why quantum protocols work better than their classical counterparts. We focus here on two celebrated notions of non-classicality viz., negativity of P phase–space representation and entanglement in symmetric multiqubit systems. We prove that they imply each other.     

Improvisation of Node Mobility Using Cluster Routing-based Group Adaptive in MANET

In today's Internet routing infrastructure, designers have addressed scaling concerns in routing constrained multiobjective optimization problems examining latency and mobility concerns as a secondary constrain. In tactical Mobile Ad-hoc Network (MANET), hubs can function based on the work plan in various social affairs and the internally connected hubs are almost having the related moving standards where the topology between one and the other are tightly coupled in steady support by considering the touchstone of hubs such as a self-sorted out, self-mending and self-administration. Clustering in the routing process is one of the key aspects to increase MANET performance by coordinating the pathways using multiple criteria and analytics. We present a Group Adaptive Hybrid Routing Algorithm (GAHRA) for gathering portability, which pursues table-driven directing methodology in stable accumulations and on-request steering strategy for versatile situations. Based on this aspect, the research demonstrates an adjustable framework for commuting between the table-driven approach and the on-request approach, with the objectives of enhancing the output of MANET routing computation in each hub. Simulation analysis and replication results reveal that the proposed method is promising than a single well-known existing routing approach and is well-suited for sensitive MANET applications.     

Cost Effective Optimal Task Scheduling Model in Hybrid Cloud Environment

In today’s world, Cloud Computing (CC) enables the users to access computing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located in remote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and task scheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud is employed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the current research work develops a Cost-Effective Optimal Task Scheduling Model (CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) model is used in the proposed work for hybrid clouds. Moreover, the algorithm works on the basis of multi-intentional task completion process with optimal resource allocation. The model was successfully simulated to validate its effectiveness based on factors such as processing time, make span and efficient utilization of virtual machines. The results infer that the proposed model outperformed the existing works and can be relied in future for real-time applications.     

Field equations for incompressible non-viscous fluids using artificial intelligence

In this article, we introduce new field equations for incompressible non-viscous fluids, which can be treated similarly to Maxwell’s electromagnetic equations based on artificial intelligence algorithms. Lagrangian and Hamiltonian formulations are used to arrive at field equations that are solved using convolutional neural networks. Four linear differential equations, which describe the two fields, namely, the dynamic pressure and the vortex fields, are derived, and these can be used in place of Euler’s equation. The only assumption while deriving this equation is that the dynamic pressure and vortex fields obey the superposition principle. The important finding to be noted is that Euler’s fluid equations can be converted into field equations analogous to Maxwell’s electromagnetic equations. We solve the flow problem for laminar flow past a cylinder, sphere, and cone in two dimensions similar to the conduction in a uniform electric field and arrive at closed-form expressions. These closed-form expressions, which are obtained for the potentials of fluid flow, are similar to the streamline potential functions in the case of fluid dynamics.

     

A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem

A new data-driven reference vector-guided evolutionary algorithm has been successfully implemented to construct surrogate models for various objectives pertinent to an industrial blast furnace. A total of eight objectives have been modeled using the operational data of the furnace using 12 process variables identified through a principal component analysis and optimized simultaneously. The capability of this algorithm to handle a large number of objectives, which has been lacking earlier, results in a more efficient setting of the operational parameters of the furnace, leading to a precisely optimized hot metal production process.     

Mixed-Mode Stress Intensity Factor Determination of Riveted Lap Joints Used in Aircraft Fuselage Structures

Journal of Failure Analysis and Prevention - In the present work, mixed-mode stress intensity factor (SIF) of multiple cracks in a riveted lap joint has been determined, with and without the...     

Application of fuzzy quality function deployment for sustainable design of consumer electronics products: a case study

With a steep increase in the demand for consumer electronics products, the contemporary manufacturers are committed toward sustainable development of such products. There exists a scope for developing a methodology for enabling sustainable development of consumer electronics products. In this context, fuzzy quality function deployment (QFD) approach has been presented in this article in order to prioritize relevant customer requirements, sustainability parameters and sustainability initiatives. Key influential parameters for sustainable development of consumer electronics products have been identified from the literature. In the first phase of fuzzy QFD, parameters influencing sustainable development have been prioritized in accordance with customer requirements. In the second phase, environmental design initiatives have been prioritized based on critical sustainability parameters. From phase I of fuzzy QFD, ‘reduction in environmental release’ has been found as the most significant sustainability parameter with a crisp value of 22.83, and from phase II, environmental impact assessment is proved to be the significant design method with a crisp value of 20.40. The methodology would provide a comprehensive understanding to practitioners on the interrelationships among customer requirements, sustainability parameters and environmentally benign initiatives for development of consumer electronic products. The generic model developed can be applied to most of the consumer electronics product     

Concurrent consideration of evacuation safety and productivity in manufacturing facility planning using multi-paradigm simulations

Manufacturing facilities are expected to maintain a high level of production and at the same time, employ strict safety standards to ensure the safe evacuation of the people in the event of emergencies (fire is considered in this paper). These two goals are often conflicting. This paper presents a methodology to evaluate evacuation safety versus productivity concurrently for various, widely known manufacturing layouts. While the safety performance indicators such as evacuation times are inferred from the crowd (agent based) simulation, the productivity performance indicators (e.g. throughput) are analyzed using the discrete event simulation. To this end, this research focuses on creating innovative techniques for developing accurate crowd simulations, where Belief-Desire-Intention (BDI) agent framework is employed to build each person’s individual actions and the interactions between them. The data model and rule based action algorithms for each agent are reverse-engineered from the human-in-the-loop experiments in the immersive virtual reality environments. Finally, experiments are conducted using the constructed simulations to compare safety and productivity for different layouts. To demonstrate the proposed methodology, an automotive power-train (engine and transmission) manufacturing plant was used. Initial results look quite promising.     

B2B e-commerce supply chain integration and performance: A contingency fit perspective on the role of environment

Drawing upon contingency theory “fit” research in the IT and supply chain management literature, we applied the “fit” concept to the relationship between B2B e-commerce supply chain integration and performance. The results demonstrated that the effect of B2B supply chain integration on financial, market, and operational performance decreased as product turbulence and demand unpredictability jointly increased. Managerial implications include the conditions under which IT investments yield performance improvement and the need for firms to actively manage demand uncertainty.