Agro-Waste Generated Pd/CAP-Ash Catalyzed Ligand-Free Approach for Suzuki–Miyaura Coupling Reaction

Catalysis Letters - We converted agro-waste Custard Apple Peels (CAP) to ash via thermal treatment, on which Pd(OAc)2 was immobilized easily that produced a low-cost, highly efficient Pd/CAP-ash...     

Nature inspired supply chain solutions: definitions,analogies, and future research directions

ABSTRACT

Supply chains are becoming increasingly complex, and many companies and researchers are looking to nature for finding solutions. In this paper, we provide a narrative synthesis and systematic review to explore state-of-the-art, and identify key areas for exploration of nature inspired solutions in the supply chain area. We consider strategic, tactical, and operational decisions within supply chains and identify analogies between biological systems and supply chains to create a new research agenda. Our findings show that the majority of the research in nature inspired supply chains from the systemic perspective focuses on closed loop supply chains. In contrast, similar systemic solutions such as industrial symbiosis, circular economy, and industrial ecology have not been explored as frequently. Reducing production waste (industrial symbiosis) in addition to end-of-life product waste (closed loop supply chains), optimising raw material use and extending the life of used resources (circular economy), investigating the interactions between biosphere and technosphere (industrial ecology), and seeking solutions to industrial problems from nature (biomimicry) are all possible paths for reaching a zero-waste economy. These systemic solutions have a considerable impact on the supply chains at the strategic, tactical, and operational levels, which need to be explored to identify efficient and effective solutions.     

Microstructural and Tribological Behavior of Pulse Electroplated Nickel Barrier on Copper Conductors

The microstructural, mechanical, and tribological behaviors of electroplated Ni on Cu conducting substrates have been investigated in this study. The microstructural studies were performed by X-ray diffraction (XRD) analysis and scanning electron microscopy (SEM). The results showed that initially (111) with (220), (200) Ni texture components were predominant in the coating, and increasing the current density from 0.1 to 0.5 A/cm² led to the development of a strong (111) texture. The presence of ultrafine grains coupled with a (111) Ni texture improved the coating microhardness and wear properties significantly. It was shown that with an increase in current density, wear resistance of the coatings improved significantly and the electrical resistivity increased due to the highly populated grain boundaries.     

Assessment of critical buckling load of functionally graded plates using artificial neural network modeling

Neural Computing and Applications - Predicting the critical buckling loads of functionally graded material (FGM) plates using an analytical method requires solving complex equations with various...     

A privacy-preserving model based on differential approach for sensitive data in cloud environment

A large amount of data and applications need to be shared with various parties and stakeholders in the cloud environment for storage, computation, and data utilization. Since a third party operates the cloud platform, owners cannot fully trust this environment. However, it has become a challenge to ensure privacy preservation when sharing data effectively among different parties. This paper proposes a novel model that partitions data into sensitive and non-sensitive parts, injects the noise into sensitive data, and performs classification tasks using k-anonymization, differential privacy, and machine learning approaches. It allows multiple owners to share their data in the cloud environment for various purposes. The model specifies communication protocol among involved multiple untrusted parties to process owners’ data. The proposed model preserves actual data by providing a robust mechanism. The experiments are performed over Heart Disease, Arrhythmia, Hepatitis, Indian-liver-patient, and Framingham datasets for Support Vector Machine, K-Nearest Neighbor, Random Forest, Naive Bayes, and Artificial Neural Network classifiers to compute the efficiency in terms of accuracy, precision, recall, and F1-score of the proposed model. The achieved results provide high accuracy, precision, recall, and F1-score up to 93.75%, 94.11%, 100%, and 87.99% and improvement up to 16%, 29%, 12%, and 11%, respectively, compared to previous works.

     

Varna-based optimization:a novel method for capacitated controller placement problem in SDN

Recently,software defined networking(SDN)is a promising paradigm shift that decouples the control plane from the data plane.It can centrally monitor and control the network through softwarization,i.e.,controller.Multiple controllers are a necessity of current SDN based WAN.Placing multiple controllers in an optimum way is known as controller placement problem(CPP).Earlier,solutions of CPP only concentrated on propagation latency but overlooked the capacity of controllers and the dynamic load on switches,which is a significant factor in real networks.In this paper,we develop a novel optimization algorithm named varna-based optimization(VBO)and use it to solve CPP.To the best of our knowledge,this is the first attempt to minimize the total average latency of SDN along with the implementation of TLBO and Jaya algorithms to solve CPP for all twelve possible scenarios.Our experimental results show that TLBO outperforms PSO,and VBO outperforms TLBO and Jaya algorithms in all scenarios for all topologies.     

Effective solar power harnessing using a few novel solar tree designs and their performance assessment

Solar irradiance being considered as one of the most important alternative sources of energy can be harnessed in the form of electrical power using photovoltaic panels erected under the sun. Optimum conversion of power from solar panels can be obtained by using Maximum Power Point Tracking (MPPT), which involves continuously adjusting the angle of panels according to the change in the angle of falling irradiance. These trackers, however, use some amount of power for operation of MPPT equipment. Various techniques for arranging the solar panels in three dimensions have been suggested for optimizing the output power from them. The inspiration behind arranging the panels are often drawn from the natural trees where the branches and the leaves follow a particular pattern called phyllotaxy which is directly analogous to the Fibonacci number and Golden ratio. In this research work, the power output from two solar tree models based on 3/8 and 2/5 phyllotaxy pattern and solar conventional panel compared under similar irradiance conditions. There are so many phyllotaxy patterns like 1/3, 2/5, 3/8, etc. When the solar panels aligned in different phyllotaxies, then the orientation direction of solar panels are distinct. Each solar panel connected in solar trees is in a different direction, so that they received the maximum amount of sunlight throughout the day as compared to conventional panels which is oriented unidirectional.