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Process development to synthesize plasma sprayable powders from nano alumina ceramic powders
Nano sized (?100 nm) alumina powders were converted into micron sized (30-75 mm) plasma sprayable powders by employing synthetic polymers to agglomerate them. The agglomeration process was carried out (a) in a spray dryer and (b) through systematic manual granulation procedure. The importance of process parameters that govern the plasma spray powder synthesis and thereby the characteristics were being suitable for being plasma spray coated have been brought out in this research paper. A comparative study has been made between the two synthesis methods by testing the powders synthesized under different processing conditions for their flowability characteristics. Micro-structural features related with the shape morphology and powder grain sizes were studied by Scanning Electron Microscope and the elemental composition characterization was carried out by Energy Dispersive Spectroscopy. The most suitable plasma sprayable powders were further coated onto metal substrates by using an Atmospheric Plasma Spray coating unit. The plasma sprayable powders were developed with a goal to explore their potential for their applications as wear resistant nano coatings. 2019 Elsevier Ltd. All rights reserved. -
Plasma sprayed nano refractory coatings
Nano powders may be reconstituted into micron sized plasma sprayable powders either by using a spray drier or a manual process by employing organic binders to agglomerate them. This paper deals with the synthesis of nano sized alumino-silicate plasma sprayable powders and plasma sprayed coatings prepared from them. Nano sized raw materials involving kyanite and andalusite refractory powders were converted into plasma sprayable powders by using polyvinyl alcohol (PVA) binders. The preparation methodology involved obtaining free flowing, micron sized agglomerated nano-alumino-silicates particles which could be plasma spray coated by using an Atmospheric Spray Coating Facility. About 220 microns thick nano-alumino silicate coatings were deposited on 75 microns thick commercial NiCrAlY bond coat on stainless steel substrates. The challenges involved in plasma spray coating the nano material with low density was in obtaining good deposition efficiency, retaining the nano micro structures and the structural phase composition of the coating. The coatings were evaluated for materials characteristics such as crystal structural phase via XRD, microstructure via SEM and chemical composition via EDS. The microstructure depicted fine grained nano-sized surface morphologies, kyanite and andalusite phase structure, with high potential for application as refractory coatings. Published under licence by IOP Publishing Ltd. -
Synthesis of Yttria-Stabilized Zirconia Nano Powders for Plasma Sprayed Nano Coatings
Plasma sprayed Yttria Stabilized Zirconia (YSZ) coatings, with few microns sized microstructure/grain morphology has been well researched, reported and established as an industrial Thermal Barrier Coatings (TBC) material/system. However, nano structured YSZ coatings possess improved characteristics when compared with their micron sized counterparts. However, due to their nano sizes, light weight, and low density, plasma spray coating process of nano powders suffers from flowability issues due to lack of nano powder inertia/momentum, leading to poor deposition/uneven coating thickness. In this research work, nano structured YSZ coatings were synthesized by using an Atmospheric Spray Coating (APS) facility. Nano powders of YSZ were used as the starting materials to prepare micron sized plasma sprayable powders. 80?m thick NiCrAlY bond coat (commercial) and 200?m thick YSZ top coat with nano microstructure (lab synthesized) were built on steel substrates. The starting nano crystalline (YSZ) powders, measuring 30-70 nanometers (nm) were synthesized in the laboratory via chemical method (sol-gel) by employing zirconium oxy chloride hexa-hydrate and yttrium nitrate as precursors, citric acid as chelating agent and ethylene glycol for the diversification reaction followed by calcination @ 1000C. They were then re-constituted into micron sized (53-106 ?m) plasma sprayable powders by agglomerating with polyvinyl alcohol (PVA) binders. The nano crystallite morphology of powders and coatings were analyzed by Scanning Electron Microscope (SEM), chemical composition by Energy Dispersive spectroscopy (EDS) and crystal structural phase by X-ray diffraction (XRD). The influence of calcination temperature of 1150C on nano crystallite morphology was also studied. 2019 Elsevier Ltd. -
Experimental Approach and CFD Analysis on Flow Devices
This paper deals with the study of experimental approach and investigation by using computational fluid dynamics (CFD) on various flow devices. An orifice meter, venturimeter and a nozzle meter are the most common type of measuring devices used for rate of flow by creating the differences in velocity and pressure. Pressure drop is an important parameter occurring in these flow devices, which is due to restricted passage of flow, properties, diameter ratio, etc. The focus here is to calculate the coefficient of discharge and other flow parameters to analyze theoretically with the application of Bernoullis equation. The main objective of this paper is to analyze the variations across the sections of orifice meter, venturimeter and nozzle meter. Comparison of results by both experimental and computational methods was clearly understood, and also, the flow level was calibrated by calculating the coefficient of discharge in both the methods. 2021, Springer Nature Singapore Pte Ltd. -
A Survey on Solution of Imbalanced Data Classification Problem Using SMOTE and Extreme Learning Machine
Imbalanced data are a common classification problem. Since it occurs in most real fields, this trend is increasingly important. It is of particular concern for highly imbalanced datasets (when the class ratio is high). Different techniques have been developed to deal with supervised learning sets. SMOTE is a well-known method for over-sampling that discusses imbalances at the level of the data. In the area, unequal data are widely distributed, and ensemble learning algorithms are a more efficient classifier in classifying imbalances. SMOTE synthetically contrasts two closely connected vectors. The learning algorithm itself, however, is not designed for imbalanced results. The simple ensemble idea, as well as the SMOTE algorithm, works with imbalanced data. There are detailed studies about imbalanced data problems and resolving this problem through several approaches. There are various approaches to overcome this problem, but we mainly focused on SMOTE and extreme learning machine algorithms. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Approach Towards Web for Exploring the Suitable Job for Individuals
In light of future work challenges, true human resource management (HRM) must be rebuilt. This involves over time human resource development; it must also contain the concept of sustainability to move from consuming to generating human resources. The labor market is constantly changing, with nontraditional jobs becoming increasingly important, especially in light of the current COVID-19 legislation. A useful teaching strategy in a variety of academic fields, including career development, is experiential learning. Important elements for establishing experiential learning programs at the institutional level are also covered by researchers. Our framework may assist businesses in identifying the type of experiential learning that best fits their objectives and setting for professional training. It can also help ensure that the training is successfully designed and delivered. 2024 IEEE. -
Importance Of Artificial Intelligence in Improving Human Resource Management For Companies To Find Suitable Candidature
The efficient use of pertinent human resources both inside and outside the company via management structures guided by economic and humanistic principles is known as human resource management. It is a catch-all word for a set of actions that guarantee the accomplishment of group objectives and the optimization of member growth. Employers need the correct recruitment tools to fill available positions since traditional recruiting approaches are not up to par in the global talent battle. First, as the digital tool redesigns business, we look at how talent acquisition has evolved from digital 1.0 to 3.0 (AI-enabled). Artificial intelligence technology has made recruiting more efficient and made recruiters' daily tasks easier. Additionally, the analysis in the paper shows that artificial intelligence (AI) is crucial to every step of the hiring process, including promotion, application, screening, evaluation, and coordination. This study demonstrates how organizations are realizing the value of talent management in gaining a competitive edge as the need for higher-level talent grows. Even though some HR managers are using AI for talent acquisition, our research shows that there is still an opportunity for development. 2024 IEEE. -
On Improving Quality of Experience of 4G Mobile Networks A Slack Based Approach
This paper analyses Indias four top 4G Mobile network Providers with respect to five key user experience metrics Video, Games, Voice app, Download speed and Upload speed. Results using Data Envelopment Analysis show Airtel and Vodafone-Idea performing with maximum relative efficiency with respect to these metrics, while BSNL and Jio closely follow them. Further analysis using the Slack Based Measure shows where and by how much BSNL and Jio need to improve to perform at par with Airtel and Vodafone-Idea. On certain variables, for instance Voice app, BSNL and Jio perform well, with no need for improvement. On the contrary, for Upload and Download speed experiences, both BSNL and Jio lag. For Video and Games, there is still scope for improvement, although both these players are reasonable in their performance. Thus, this analysis provides an accurate and optimal benchmark for each variable whose user experience has been evaluated. 2021, Springer Nature Switzerland AG. -
5G Planning and QoE Management Using Mathematical Benchmarking Techniques for Europe and Middle Eastern Countries
This paper analyses performance of Europe and Middle Eastern (EMEA) countries over 5G networks across eight key QoE metrics using robust and sophisticated mathematical techniques. The current position of the countries is realized along with feasible benchmarks/targets for metrics that need improvement. The benchmark countries and stretch goals are also presented. 2022 IEEE. -
Towards a Smarter Connected Society by Enhancing Internet Service Providers' QoS metrics using Data Envelopment Analysis
This paper analyses wireline broadband Quality of Service (QoS) metrics of India's small and medium Internet Service Providers (ISPs). Key Performance Indicators (KPIs) used in this analysis are - Fault repair (>90% in 1 working day and >=99% in 3 working days), Response time to customer for voice-to-voice operator assistance (in 60 sec. >60% and in 90 sec. >90%), Broadband connection speed from ISP to node (Download speed) and Service availability/uptime. Benchmarks are arrived at, using the Slack Based Measure (SBM) in Data Envelopment Analysis (DEA). Twenty Decision Making Units (DMUs - ISPs) were used in the analysis with eight of them needing to improve their QoS on some of the mentioned parameters. Relative benchmark providers for all providers needing improvement with their weightage are found and optimal targets by each QoS metric is mathematically arrived at. The Electrochemical Society -
Clustering-based Optimal Resource Allocation Strategy in Title Insurance Underwriting
Production of insurance policies in all types of Insurance requires a thorough examination of the entity against which the Insurance is to be issued. In health insurance, it is the past medical data of the individuals. Vehicle insurance needs the examination of the vehicle and the owner's data. Likewise, in Title Insurance, it is the historical data of the property which needs scrutiny before the policy issuance. Underwriters perform the job of examining the property records. The scrutiny of the property records requires a high degree of the domain and legal expertise, and title insurance underwriters are often associated with legal professions. They do the final round of validation of the examination process. There are examination teams that take care of the initial set of regular examination tasks associated with each title insurance order. Some human experts assign the orders to the team associates. Not all the orders are of the same complexity in terms of examination. The allocation of the tasks happens based on the gut feeling of the supervisor, considering their experience with the team members. Our research creates clusters of the orders based on specific parameters associated with the orders. It builds a cost model of the past associates working on orders belonging to different clusters. Based on this cost matrix, we have built an optimal task allocation model that assigns the orders to the associates with the promise of optimal cost using a Linear programming solution used frequently in operations research. 2022 IEEE. -
Real-Time Application of Document Classification Based on Machine Learning
This research has been performed, keeping a real-time application of document (multi-page, varying length, scanned image-based) classification in mind. History of property title is captured in various documents, recorded against the said property in all the countries across the world. Information of the property, starting from ownership to the conveyance, mortgage, refinance etc. are buried under these documents. This is by far a human driven process to manage these digitized documents. Categorization of the documents is the primary step to automate the management of these documents and intelligent retrieval of information without or minimal human intervention. In this research, we have examined a popular, supervised machine learning technique called, SVM (support vector machine) with a heterogeneous data set of six categories of documents related to property. The model obtained an accuracy of 88.06% in classifying over 988 test documents. 2020, Springer Nature Switzerland AG. -
Review of open space rules and regulations and identification of specificities for plot-level open spaces to facilitate sustainable development: An Indian case
Rapid urbanization and an increase in the alteration of natural resources have led to climate crises, driving the need to promote sustainable development. Urban open space management plays a vital role in such scenarios. Research on urban open spaces has been mainly conducted at regional, municipal, and neighborhood scales. Rarely has the focus been on the plot-level potentials and management of open spaces. Therefore, the study looks into the Indian development control rules and regulations and identifies that although these stipulate the percentage of open space for development on each plot, specificities for open spaces are unclear. Further, the study analyses quantitative and qualitative aspects of open spaces for selected group housing schemes in Pune city. The inquiry shows that per capita open space in Pune is comparatively lower than national standards. The quantitative aspects include FSI, building ground coverage, built-up area, number of floors, and number of dwelling units, and each relates to open spaces in one way or another. The qualitative interpretations disclose that a plot-level open space can significantly impact the regional-level open space network. Hence, the research advocates a bottom-up approach wherein plot-level open space can become the focus in formulating new norms and policies for sustainable development. Published under licence by IOP Publishing Ltd. -
Dynamic response of parabolic reflector antenna subjected to shock load and base excitation considering soil-structure interaction
Parabolic reflector antenna structures are subjected to dynamic loads along with normal loads. Determining the dynamic response of the antenna structure subjected to short-duration loads such as earthquake loads and shock loads considering soil-structure interaction is very important to ensure the safety and functionality of the antenna system resting on soft soil. A 7.2m diameter parabolic reflector antenna with a 90-degree elevation orientation is considered for the study. A triangular pulse of shock load is applied to the antenna at different locations and responses are estimated to understand the coupling effect of soil and structure on frequencies, damping, and response. Transient response analysis is carried out. Earthquake analysis is also carried out as per IS 1893 part 4:2016 considering Zone V site location. The foundation soil below the antenna is considered homogeneous with shear wave velocity (Vs) of 100m/sec. A direct method of analysis considering soil-structure interaction as per ASCE 4-16 is performed. FEM software MSC NASTRAN is used for analysis. The absorbing boundary conditions are used to reflect radiation damping. The depth-wise stress variation in foundation soil is evaluated. The results of free vibration analysis, transient response analysis with fixed base and SSI are compared. 2022 the Author(s). -
Structural analysis of log periodic and monopole antennas considering cyclonic, interference effects
The Broadband High Frequency (HF) Transmit and Receive Antenna System are used as Surface Waveover the Horizon Radars (SWOTHR) for surveillance application. HF Transmit & Receive antenna systemconsists of transmit antenna and receive antenna array operating in HF band 2 to 30?MHz, which have tobe installed near sea shore. The antennas are of Monopole and Log periodic Dipole wire mesh antenna (LPDA). The height of Monopole and LPDA depends on wavelength ? of antenna. For HF band, the height range of receive is from 5 to 25m and transmit is from 10m to 100m. In this study, 10m high monopole for receive and 55m high 60m long Log periodic antenna for transmit are considered. Structural analysis and design of these antennas is critical due to installation at sea coasts. Based on the application, receive antennas are designed as array type consisting of 64 numbers monopoles as 32 doublet's and transmit antennas are 2 numbers of LPDA. If the same height structures installed side by side as an array, wind interference is caused by the obstruction caused by a structure in the path of wind. The antennas are installing on sea coast subjected to cyclonic storms. Dynamic effect of cyclonic and interference of wind is studied. Wind loads are calculated as per IS: 875 part 3:2015. Antennas are analyzed using FEM software STAAD Pro Advanced Connect Edition. Both antennas are analyzedfor self-weight, wind loads considering cyclonic and interference factors. Natural frequency of structure is determined using modal analysis to examine the problems of wind induced oscillations and dynamic effects of wind. 2023 Author(s). -
PCRS: Personalized Course Recommender System Based on Hybrid Approach
The traditional system of selecting courses to carry out research work is time consuming, risky and a tedious task, that not only badly affect the performance but the learning experience of a researcher as well. Therefore, choosing appropriate courses in seminal years could help to do research in a better way. This Study presents a recommender system that will suggest and guide a learner in selecting the courses as per their requirement. The Hybrid methodology has been used along with ontology to retrieve useful information and make accurate recommendations. Such an approach may be helpful to learners to increase their performance and improve their satisfaction level as well. The proposed recommender systems would perform better by mitigating the weakness of basic individual recommender systems. 2018 The Authors. Published by Elsevier B.V. -
Improved diabetes disease prediction IWFO model using machine learning algorithms
Diabetic disease is the mostly affected and massive disease on a global level. Diagnosing the diabetic earlier will help the medicalist to give the improved and latest clinical treatment. The healthcare specialist unit uses many machine learning techniques, methodologies and tools for decision making in diabetic field. The machine learning techniques are utilized for the prediction of the diabetic diseases in the initial level. To eliminate such issues, optimized detection techniques are proposed. First of all, the training samples are increased using the sliding window protocol. Further, class imbalanced training data classes are balanced and resolved using the adaptive and gradient booster technique. Further, the diabetic feature selection process is improved by the Intensity Weighted Firefly Optimization firefly techniques (IWFO), in which irrelevant features are reduced based on the correlation between the features that deducts the unwanted features involved in the diabetic disease process. Then the feature transformation problem is faced by the PCA technique, which manages the several types of features. Finally, the improved and optimal hybrid random forest is applied into the normal and diabetes classes respectively. The proposed system predicts the diabetic disease efficiently and maximizes its precision of the prediction system. The present paper is compared with different classifiers to determine the efficiency of the work. Overall, the initiated system improved the present studies accuracy level. 2024 Author(s). -
Word-of-Mouth Promotion: How to Attract Consistent Consumers as a Promoter for the B2C Model
The primary goal of this research article is to discover the consumers' behaviour while spending time on the e-commerce platform and to use the consumers who have positive Word-of-Mouth on the products to motivate them as promoters through positive Word of Mouth behaviour. The behavioural factors considered in this study are Relationship value, Trust value, Satisfaction level and Word of Mouth. The trial model includes the consumers who use an e-commerce platform for their online shopping in India. A proper questionnaire with four components was created and used to collect the sample data. Totally 300 responses have been received and analysed with the help of structured equation model and SPSS and AMOS software. The findings suggest that the 'Word of Mouth' technique can be used as a tool to increase the number of consumers in an online platform, particularly e-commerce. We investigated how Relationship Value and Trust Value can be used as key factors to motivate consumers' positive WoM behaviour. This research would be more beneficial to the B2C model. The research has done only for Indian e-commerce portals for survey. There is a scope to do research for the global level e-commerce market. Future study focuses on dynamic attributes for relationship values. This research work will help the researchers who is working on B2C model and consumer behavioural models. This model would be used for any online transactions-based services. As best of the knowledge of the authors' this study is the novel idea to understand the consumers' behaviour for purchasing items through the positive WoM. This work can be adopted for any e-commerce platform. 2024 IEEE. -
A Brief Review of Intelligent Rule Extraction Techniques
Rule extraction is a process of extracting rules which helps in building domain knowledge. Rules plays an important role in reconciling financial transactions. This paper presents a brief study of intelligent methods for rule extraction. The paper touches upon heuristic, regression, fuzzy-based, evolutionary, and dynamic adaptive techniques for rule extraction. This paper also presents the state-of-the-art techniques used in dealing with numerical and linguistic data for rule extraction. The objective of the paper is to provide directional guidance to researchers working on rule extraction. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Portfolio Optimization Using Quantum-Inspired Modified Genetic Algorithm
Optimization of portfolios has an additional level of complexity and has been an area of interest for both financial leaders and artificial intelligence experts. In this article, a quantum-inspired version of an improved genetic algorithm is proposed for the task of portfolio optimization. An effort is made to implement two different genetic versions along with their extension in the quantum-inspired space. Improvements to the popular crossover techniques, viz. (i) arithmetic and (ii) heuristic crossover are proposed to reduce computational time. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.