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Friction stir processing (FSP) as a solid-state process has the potential for the production of effective aluminum matrix composites (AMCs). In this investigation, various ceramic particles including B₄C, TiC, SiC, Al₂O₃ and WC were incorporated as the dispersed phase within AA6082 aluminum alloy by FSP. The wear rate of the composite is then investigated experimentally by making use of a design of experiments technique where wear rate is evaluated as the output parameter. The input parameters considered include tool rotational speed, traverse speed, groove width and ceramic particle type. An artificial neural network (ANN) simulation was then used to describe the wear rate of the surface composites. The weights of the network were adjusted to minimize the mean squared error using a feed forward back propagation technique. The effect of the individual input parameters on wear rate was then inferred from the ANN models. Trends are presented and related to the associated microstructures observed. The TiC infused AMC displayed the lowest wear rate whereas the Al₂O₃ infused AMC displayed the highest, within the scope of the current investigation. The paper aims to discuss these issues.

The paper used ANN for the research study.

The finding of this paper is that the wear rate of AA6063 aluminum surface composites is influenced remarkably by FSP parameters.

Original work of authors.

The SiC reinforced Al composite is perhaps the most successful class of metal matrix composites (MMCs) produced to date. They have found widespread application for aerospace, energy, and military purposes, as well as in other industries – for example, they have been used in electronic packaging, aerospace structures, aircraft and internal combustion engine components, and a variety of recreational products. In all these applications, welding plays a vital role. Little attention has been paid to SiC reinforced aluminium matrix composites joined by gas tungsten arc (GTA) welding. The purpose of this paper is to outline the manufacturing method for producing MMCs, GTA welding of MMCs and pitting corrosion analysis of welded MMCs.

This paper focuses upon production and welding of metal matrix composites. The welded composites have been treated at elevated and cryogenic temperatures for experimental studies. Pitting corrosion analysis of welded plates was carried out as per Box Benkehn Design.

From the results, it should be noted that maximum pitting resistance was observed with MMCs containing 10% SiC treated at cryogenic temperature. Corrosion resistance of welded composites treated at elevated temperature was found to be higher than that of as‐welded and at cryogenic temperature treated composites. The pitting potential increases with increase in % SiC to certain level and decreases with further increase in % SiC. Corrosion potential of composites treated at elevated temperature is high compared to other composites. Maximum pitting resistance is observed when the welding current was kept at 175 amps for 10% addition of SiC in LM25 matrix treated at cryogenic temperature.

The paper outlines the manufacturing method for producing MMCs, GTA welding of MMCs and pitting corrosion analysis of welded MMCs. The results obtained may be helpful for the automobile and aerospace industries.

Internet of Things (IoT) is an up-and-coming conception that intends to link multiple devices with each other. The aim of this study is to provide a significant analysis of Green IoT. The IoT devices sense, gather and send out significant data from their ambiance. This exchange of huge data among billions of devices demands enormous energy. Green IoT visualizes the concept of minimizing the energy consumption of IoT devices and keeping the environment safe.

This paper attempts to analyze diverse techniques associated with energy-efficient protocols in green IoT pertaining to machine-to-machine (M2M) communication. Here, it reviews 73 research papers and states a significant analysis. Initially, the analysis focuses on different contributions related to green energy constraints, especially energy efficiency, and different hierarchical routing protocols. Moreover, the contributions of different optimization algorithms in different state-of-the-art works are also observed and reviewed. Later the performance measures computed in entire contributions along with the energy constraints are also checked to validate the effectiveness of entire contributions. As the number of contributions to energy-efficient protocols in IoT is low, the research gap will focus on the development of intelligent energy-efficient protocols to build up green IoT.

The analysis was mainly focused on the green energy constraints and the different robust protocols and also gives information on a few powerful optimization algorithms. The parameters considered by the previous research works for improving the performance were also analyzed in this paper to get an idea for future works. Finally, the paper gives some brief description of the research gaps and challenges for future consideration that helps during the development of an energy-efficient green IoT pertaining to M2M communication.

To the best of the authors’ knowledge, this is the first work that reviews 65 research papers and states the significant analysis of green IoT.

This study aims to investigate the adaptation strategies they practice and the factors that influence their use of adaptation strategies.

The mixed-method sequential explanatory design was used to triangulate the data collected. Multistage sampling was used to select 400 sampled households for household surveys. Eight focus groups, each with eight to ten participants, and 24 key informants, were specifically chosen based on their farming experiences. Chi-square tests, one-way ANOVA and a binary logit model were used to analyze the data.

The majority of farmers used simple and low-cost adaptation strategies like changing planting dates, selling livestock and off-farm and nonfarm work. A minority of farmers used advanced adaptation strategies like crop diversification and water harvesting for irrigation. The result further revealed that: the age of the household head, educational status of household heads, farm size, livestock ownership, farming experiences, household income, access to credit and access to climate information significantly influenced the adoption of the adaptation strategies. Public policy should provide water harvesting and irrigation technology, climate-related information and the provision of microcredit facilities to enhance the farmers’ resilience to climate change risks.

Although several studies on climate change adaptation strategies are available, this paper is one of the few studies focusing on a particular agro-ecological zone, an essential precursor to dealing with current and projected climate change in the area. It provides helpful insights for developing successful adaptation policies that improve adaptive capacity and agricultural sustainability in southern Ethiopia’s lowlands.

Super 304HCu super austenitic stainless steel tubes containing 2.3 to 3 (Wt.%) of copper (Cu) is used in superheaters and reheater tubings of nuclear power plants. In general, austenitic stainless steels welded by conventional constant current gas tungsten arc welding (CC-GTAW) produce coarse columnar grains, alloy segregation and may result in inferior mechanical properties. Pulsed current gas tungsten arc welding (PC-GTAW) can control the solidification structure by altering the prevailing thermal gradients in the weld pool.

Super 304HCu tubes of Ø 57.1 mm and the wall thickness of 3.5 mm were autogenously welded using CC and PC-GTAW processes. Joints are characterized using optical microscopy, electron microscopy, energy dispersive spectroscopy and electron backscatter diffraction (EBSD) techniques. Hot tensile properties of the weld joints were evaluated and correlated with their microstructural features.

Current pulsing in GTAW has resulted in minimal eutectic film segregation, lower volume % of delta ferrite and appreciable improvement in tensile properties than CC-GTAW joints.

The EBSD boundary map and inverse pole orientation map of Super 304HCu weld joints evidence the grain refinement and much frequent high angle grain boundaries achieved using weld current pulsing.

The purpose of this study is to determine the enablers of the quality of work life (QWL) of employees working in the Garment industries.

The study was carried out in a fivefold step. In the first step, the enablers of QWL were identified through an exhaustive literature survey, in the second step identified vital few components through Pareto analysis. Then the third step was followed by exploratory factor analysis (EFA) to further, to identify the precise components and validate the same using confirmatory factor analysis in fourth step. The final step included interpretive structural modeling and Cross-Impact Matrix Multiplication Applied to Classification analysis to model the validated components and determine the interrelationships and linkages.

Predominant QWL enablers of employees working in the garment industries are training and development, satisfaction in job, compensation and rewards, relation and co-operation, grievance handling, work environment, job nature, job security and facilities.

In this study, the interpretive structural model is designed based on the opinion of the experts who are working in the garment industry considering the responses from employees in garment sectors. The framework can be extended further to the other sectors.

In future, the researchers in QWL may develop a model to quantify the level of employees’ QWL who are working in different sectors. Enablers of QWL are essential, and based on this further statistical analysis can be carried out. This study will provide limelight to the researchers in choosing the valid and reliable set of enablers for the empirical studies. Organizations can get benefit by implementing the outcome of this research for the enhancement of the QWL of employees.

The study was carried out in 133 garment industries where 851 workers constituted the final valid responses that were considered for analysis. The outcomes from the study help administrators, policy and decision-takers in taking decisions to enhance QWL.

The objective of this research is focused on the design of a new hybrid composite as well as to analyse the optimum turning conditions to minimise the surface roughness and work piece surface temperature, thereby increasing the productivity.

Mechanical properties such as hardness and tensile strength of Al-Si10Mg alloy reinforced with 3, 6 and 9 wt.% of alumina along with 3 wt.% of graphite prepared by stir casting method have been evaluated. The present study addresses the machinability parameter optimisation of Al alloy-9 per cent alumina-3 per centgraphite. Experiments were conducted based on the Taguchi parameter design by varying the feed (0.1, 0.15 and 0.2 mm/rev), cutting speed (200, 250 and 300 m/min) and depth of cut (0.5, 1.0 and 1.5 mm). The results were then analysed using analysis of variance (ANOVA).

Mechanical properties of the hybrid composite increases with reinforcement content. The surface roughness decreases with increasing cutting speed and conversely increases with increasing feed and depth of cut. The work piece surface temperature increases as cutting speed, feed and depth of cut increases. The ANOVA result reveals that feed plays a major role in minimising both surface roughness and surface temperature of work piece. The cutting speed and depth of cut follow feed in the order of importance, respectively.

The vibration of the machine tool is a factor which may contribute to poor quality characteristics. This factor has not taken been into account in this analysis since major vibrations in the machine are induced due to the machining process.

Design and development of new hybrid metal matrix composites (HMMCs) with a detailed analysis on machining conditions. The findings could help in the production of composite with a higher degree of surface finish. This will enable the adoption of HMMCs as industrial product for mass scale production.

Good quality characteristics were achieved using optimum machining conditions arrived using a statistical modelling.

This paper aims to discuss a comprehensive survey on fuzzy-based clustering techniques. The determination of an appropriate sensor node as a cluster head straightforwardly affects a network’s lifetime. Clustering often possesses some uncertainties in determining suitable sensor nodes as a cluster head. Owing to various variables, selection of a suitable node as a cluster head is a perplexing decision. Fuzzy logic is capable of handling uncertainties and improving decision-making processes even with insufficient information. Then, state-of-the-art research in the field of clustering techniques has been reviewed.

The literature is presented in a tabular form with merits and limitations of each technique. Furthermore, the various techniques are compared graphically and classified in a tabular form and the flowcharts of important algorithms are presented with pseudocodes.

This paper comprehends the importance and distinction of different fuzzy-based clustering methods which are further supportive in designing more efficient clustering protocols.

This paper fulfills the need of a review paper in the field of fuzzy-based clustering techniques because no other paper has reviewed all the fuzzy-based clustering techniques. Furthermore, none of them has presented literature in a tabular form or presented flowcharts with pseudocodes of important techniques.