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In internal combustion engines, exhaust system plays a vital role in the improvement of the combustion efficiency. A good conditioned exhaust manifold increase the performance of the engine. The work is focused on reducing the backpressure in the exhaust manifold to increase the combustion efficiency using CFD. Flow through the exhaust manifold is analyzed using CFX with pressure and velocity parameters as boundary condition. The existing manifold is modified and the new design is analyzed. The results of new design are compared with the values of the existing model. Graphs are drawn for the new design and are compared with existing manifold. The decrease in back pressure is shown using contour and vector diagram. By comparing the existing and new design, the increase in efficiency is found.

This work can be used as a building block in other settings such as GPU, Map-Reduce, Spark or any other. Also, DDPML can be deployed on other distributed systems such as P2P networks, clusters, clouds computing or other technologies.

In the age of Big Data, all companies want to benefit from large amounts of data. These data can help them understand their internal and external environment and anticipate associated phenomena, as the data turn into knowledge that can be used for prediction later. Thus, this knowledge becomes a great asset in companies' hands. This is precisely the objective of data mining. But with the production of a large amount of data and knowledge at a faster pace, the authors are now talking about Big Data mining. For this reason, the authors’ proposed works mainly aim at solving the problem of volume, veracity, validity and velocity when classifying Big Data using distributed and parallel processing techniques. So, the problem that the authors are raising in this work is how the authors can make machine learning algorithms work in a distributed and parallel way at the same time without losing the accuracy of classification results. To solve this problem, the authors propose a system called Dynamic Distributed and Parallel Machine Learning (DDPML) algorithms. To build it, the authors divided their work into two parts. In the first, the authors propose a distributed architecture that is controlled by Map-Reduce algorithm which in turn depends on random sampling technique. So, the distributed architecture that the authors designed is specially directed to handle big data processing that operates in a coherent and efficient manner with the sampling strategy proposed in this work. This architecture also helps the authors to actually verify the classification results obtained using the representative learning base (RLB). In the second part, the authors have extracted the representative learning base by sampling at two levels using the stratified random sampling method. This sampling method is also applied to extract the shared learning base (SLB) and the partial learning base for the first level (PLBL1) and the partial learning base for the second level (PLBL2). The experimental results show the efficiency of our solution that the authors provided without significant loss of the classification results. Thus, in practical terms, the system DDPML is generally dedicated to big data mining processing, and works effectively in distributed systems with a simple structure, such as client-server networks.

The authors got very satisfactory classification results.

DDPML system is specially designed to smoothly handle big data mining classification.

The purpose of this paper is to focus on MHD unsteady flow of Carreau fluid over a variable thickness melting surface in the presence of chemical reaction and non-uniform heat sink/source.

The flow governing partial differential equations are transformed into ordinary ones with the help of similarity transformations. The set of ODEs are solved by a shooting technique together with the R.K.–Fehlberg method. Further, the graphs are depicted to scrutinize the velocity, concentration and temperature fields of the Carreau fluid flow. The numerical values of friction factor, heat and mass transfer rates are tabulated.

The results are presented for both Newtonian and non-Newtonian fluid flow cases. The authors conclude that the nature of three typical fields and the physical quantities are alike in both cases. An increase in melting parameter slows down the velocity field and enhances the temperature and concentration fields. But an opposite outcome is noticed with thermal relaxation parameter. Also the elevating values of thermal relaxation parameter/ wall thickness parameter/Prandtl number inflate the mass and heat transfer rates.

This is a new research article in the field of heat and mass transfer in fluid flows. Cattaneo–Christov heat flux model is used. The surface of the flow is assumed to be melting.

This study aims to discuss the results of fresh properties and compressive strength of self-compacting concrete using ingredients added red brick powder as a fine aggregate substitute. The results of the study were compared with the properties of fresh properties and compressive strength with ingredients added by rice husk ash, which is also a fine aggregate substitute. In addition, the initial compressive strength of each of these variations was also examined to accelerate the completion time of construction projects using self-compacting concrete.

This research was conducted in a laboratory by testing the characteristics of fresh and hardened properties of self-compacting concrete.

Fresh properties testing is carried out in the form of V-funnel, flow table, J-ring and L-box where all specimens produce quite varied flow rates. Compressive strength was estimated at ages 3, 7, 14 and 28 days with cylindrical specimens with a diameter of 150 mm and a height of 300 mm. The variation of fine aggregate substitutes used is 20, 40 and 60 per cent.

From the results of the compressive strength, it can be concluded that the added material is categorized as self-compacting concrete with high initial compressive strength, while at 28 days, the compressive strength test results are categorized as high-strength self-compacting concrete.

The steady two-dimensional laminar boundary layer flow, heat and mass transfer over a flat plate with convective surface heat flux was considered. The governing nonlinear partial differential equations were transformed into a system of nonlinear ordinary differential equations and then solved numerically by Runge–Kutta method with the most efficient shooting technique. Then, the effect of variable viscosity and variable thermal conductivity on the fluid flow with thermal radiation effects and viscous dissipation was studied. Velocity, temperature and concentration profiles respectively were plotted for various values of pertinent parameters. It was found that the momentum slip acts as a boost for enhancement of the velocity profile in the boundary layer region, whereas temperature and concentration profiles decelerate with the momentum slip.

Numerical Solution is applied to find the solution of the boundary value problem.

Velocity, heat transfer analysis is done with comparing earlier results for some standard cases.

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This paper aims to provide the security and privacy for Byzantine clients from different types of attacks.

In this paper, the authors use Federated Learning Algorithm Based On Matrix Mapping For Data Privacy over Edge Computing.

By using Softmax layer probability distribution for model byzantine tolerance can be increased from 40% to 45% in the blocking-convergence attack, and the edge backdoor attack can be stopped.

By using Softmax layer probability distribution for model the results of the tests, the aggregation method can protect at least 30% of Byzantine clients.

The purpose of this research paper is to explore the possibility to enhance the power transfer from piezoelectric energy harvester (PEH) source to the load. As the proposed gyrator-induced voltage flip technique (GIVFT) does not require bulky components such as physical inductors, it is easily realizable in small integrated circuits (IC) package thereby offering performance benefits, reducing area overhead and providing cost benefits for constrained self-powered autonomous Internet-of-Things (IoT) applications.

This paper presents an inductorless interface circuit for PEH. The proposed technique is called GIVFT and is demonstrated using active elements. The authors use gyrator to induce voltage flip at the output side of PEH to enhance the charge extraction from PEH. The proposed technique uses the current-voltage (I-V) relationship of gyrator to get appropriate phasor response necessary to induce the voltage flip at the output of PEH to gain power transfer enhancement at the load.

The experimental results show the efficacy of the GIVFT realization for enhanced power extraction. The authors have compared their proposed design with popular earlier reported interface circuits. Experimentally measured performance improvement is 1.86×higher than the baseline comparison of full-wave bridge rectifier circuit. The authors demonstrated a voltage flip using GIVFT to gain power transfer improvement in piezoelectric energy harvesting.

To the best of the authors’ knowledge, pertaining to the field of PEH, this is the first reported GIVFT based on the I-V relationship of the gyrator. The proposed approach could be useful for constrained self-powered autonomous IoT applications, and it could be of importance in guiding the design of new interface circuits for PEH.

The purpose of this paper is to propose the use of graph theoretic structural modeling for assessing the possible reduction in complexity of the work flow procedures in an organization due to lean initiatives. A tool to assess the impact of lean initiative on complexity of the system at an early stage of decision making is proposed.

First, the permanent function-based graph theoretic structural model has been applied to understand the complex structure of a manufacturing system under consideration. The model helps by systematically breaking it into different sub-graphs that identify all the cycles of interactions among the subsystems in the organization in a systematic manner. The physical interpretation of the existing quantitative methods linked to graph theoretic methodology, namely two types of coefficients of dissimilarity, has been used to evolve the new measures of organizational complexity. The new methods have been deployed for studying the impact of different lean initiatives on complexity reduction in a case industrial organization.

The usefulness and the application of new proposed measures of complexity have been demonstrated with the help of three cases of lean initiatives in an industrial organization. The new measures of complexity have been proposed as a credible tool for studying the lean initiatives and their implications.

The paper may lead many researchers to use the proposed tool to model different cases of lean manufacturing and pave a new direction for future research in lean manufacturing.

The paper demonstrates the application of new tools through cases and the tool may be used by practitioners of lean philosophy or total quality management to model and investigate their decisions.

The proposed measures of complexity are absolutely new addition to the tool box of graph theoretic structural modeling and have a potential to be adopted by practical decision makers to steer their organizations though such decisions before the costly interruptions in manufacturing systems are tried on ground.

In the present scenario of global competition and economic recession, most of the organizations are facing tough challenge to survive in the market because of shortening product life cycle and reducing profit margin. Customers are seeking better design, production and delivery, which have made firms to concentrate on flexibility in supply chains. Therefore, the purpose of this study is to identify major factors and develop a suitable framework for flexibility in supply chains.

Based on literature review, about 14 factors have been identified. To develop relationship among these factors, a team of five experts from industry and academia was formed. Based on inputs from experts, different relationships are developed among factors to form structural self-interaction matrix (SSIM). Based on this matrix, a flexibility framework is developed by interpretive structural modelling approach.

Top management commitment, strategy development for flexible SC, application of advance technology and IT tools, information sharing in SC members, trust development among supply chain members have emerged as major driving factors. Logistics and warehouse management, suppliers flexibility, distribution flexibility and manufacturing flexibility have emerged as dependent factors.

Framework developed in this study is based on interpretive structural modelling. This framework can be further validated with some case analysis and empirical findings.

Findings of the study can be useful for industry professionals to develop strategies for flexible supply chains. It will help them in taking new initiatives for making supply chains more responsive and proactive for customers demand.

Predicting the critical velocity is crucial at the instability threshold for shell and tube heat exchangers in order to prevent tube failure due to vibrations. In this study, the vibration response of an aluminum tube bundle subjected to water cross flow was analyzed experimentally. Aluminum tubes are preferred over steel tubes because of aluminum tubes' excellent corrosion resistance, ease of manufacture, and high thermal efficiency.

The fluid elastic instability and vortex shedding mechanisms in a finned tube array of aluminum tubes with a base tube diameter of 19.05 mm and pitch of 34 mm were investigated. The current study considers parallel triangular finned tube arrays with fin heights of 3 mm and 6 mm with a uniform fin thickness and fin pitch. The plain tube array was tested to compare the finned tube array results. The tube vibration response was measured using an accelerometer mounted on the middle tube of the third row. In order to define the fluid elastic instability behavior of various tube arrays, the critical velocity at the instability threshold is measured. By finding the Strouhal number at the small peaks before instability, the vortex shedding behavior of the tube arrays is examined.

The results reveal that the critical velocity at instability for coarse finned tube arrays increases as the fin height increases. The effect of the tube material is evaluated by comparing the results with those previously reported for parallel triangular tube arrays made of steel. Finally, the occurrence of vortex shedding in a tube array is confirmed based on the Reynolds number and Strouhal number relationship. The instability constant K for the plain tube array of steel and aluminum material are 4.97 and 4.87, respectively.

This paper provides the research findings on the effect of fin height on coarse density finned tube array. This will add substantial knowledge to the literature in the field of fluid elastic instability and vortex shedding, which is needed for the safe functioning of shell and tube heat exchangers.