Mukesh Agarwala, David Bourell, Joseph Beaman, Harris Marcus and Joel Barlow
Considers efforts to date to produce parts by direct selective laser sintering (SLS) of metals, including post processing to improve structural integrity and/or to induce a…
Abstract
Considers efforts to date to produce parts by direct selective laser sintering (SLS) of metals, including post processing to improve structural integrity and/or to induce a transformation. Provides a brief overview of the basic principles of SLS machine operation, and discusses materials issues affecting direct SLS of metals and the resultant properties and microstructures of the parts. Reviews results of past efforts on SLS of metal systems such as Cu‐Sn, Cu‐Solder (Pb‐Sn), Ni‐Sn, pre‐alloyed bronze (Cu‐Sn). Finally discusses more recent efforts on SLS of bronze‐nickel powder mixtures in greater detail.
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Mukesh Agarwala, David Bourell, Joseph Beaman, Harris Marcus and Joel Barlow
Gives a brief overview of post‐processing of selective laser sintered (SLS) metal parts to improve structural integrity and/or to induce a material transformation. Presents…
Abstract
Gives a brief overview of post‐processing of selective laser sintered (SLS) metal parts to improve structural integrity and/or to induce a material transformation. Presents results which show the effect of post‐processing liquid phase sintering temperature and time on material properties. Describes the hot isostatic pressing process, and discusses its application to SLS metal parts. Results gained from using this process show that it is suitable for achieving almost full‐density parts.
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Mukesh K. Agarwala, Vikram R. Jamalabad, Noshir A. Langrana, Ahmad Safari, Philip J. Whalen and Stephen C. Danforth
Commercial solid freeform fabrication (SFF) systems, which have been developed for fabrication of wax and polymer parts for form and fit and secondary applications, such as moulds…
Abstract
Commercial solid freeform fabrication (SFF) systems, which have been developed for fabrication of wax and polymer parts for form and fit and secondary applications, such as moulds for casting, etc., require further improvements for use in direct processing of structural ceramic and metal parts. Defects, both surface as well as internal, are undesirable in SFF processed ceramic and metal parts for structural and functional applications. Process improvements are needed before any SFF technique can successfully be commercialized for structural ceramic and metal processing. Describes process improvements made in new SFF techniques, called fused deposition of ceramics (FDC) and metals (FDMet), for fabrication of structural and functional ceramic and metal parts. They are based on an existing SFF technique, fused deposition modelling (FDM) and use commercial FDM systems. The current state of SFF technology and commercial FDM systems results in parts with several surface and internal defects which, if not eliminated, severely limit the structural properties of ceramic and metal parts thus produced. Describes systematically, in detail, the nature of these defects and their origins. Discusses several novel strategies for elimination of most of these defects. Shows how some of these strategies have successfully been implemented to result in ceramic parts with structural properties comparable to those obtained in conventionally processed ceramics.
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The importance of gender in inclusive economic growth has been a growing area of research. Finance is seen as an efficacious instrument for social inclusion, and sustainable women…
Abstract
Purpose
The importance of gender in inclusive economic growth has been a growing area of research. Finance is seen as an efficacious instrument for social inclusion, and sustainable women empowerment (SWE). The lack of credit access often constrains women to scale up. The objective of this study is to examine the attributes influencing the decision of women to access the credit at the bottom of the pyramid (BoP) and the impact of this credit access on social, psychological and economic dimensions of SWE at the BoP in rural India.
Design/methodology/approach
The threshold theory of decision-making in the form of logistic regression (LR) is applied here to analyze the influence of four determinants, namely individual household level (IHLA), social attributes (SA), economic attributes (EA) and ownership of documents (OD) on women’s credit access. Likewise, the same method is applied to study the relationship between credit access and three dimensions of SWE.
Findings
The results have revealed a statistically significant relationship between credit access and studied four attributes. Subsequently, a positive relationship has been observed between credit access and dimensions of SWE.
Originality/value
The present study broadly addresses the concern of accessing credit by women at BoP level, which helps the government and policymakers to promote enabling an environment for women entrepreneurship and comprehensive financial policies for the BoP.
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M.A. Jafari, W. Han, F. Mohammadi, A. Safari, S.C. Danforth and N. Langrana
In this article we present the system that we have developed at Rutgers University for the solid freeform fabrication of multiple ceramic actuators and sensors. With solid free…
Abstract
In this article we present the system that we have developed at Rutgers University for the solid freeform fabrication of multiple ceramic actuators and sensors. With solid free form fabrication, a part is built layer by layer, with each layer composed of roads of material forming the boundary and the interior of the layer. With our system, up to four different types of materials can be deposited in a given layer with any geometry. This system is intended for fabrication of functional parts; therefore the accuracy and precision of the fabrication process are of extreme importance.
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Mukesh Pal, Hemant Gupta and Yogesh C. Joshi
Women empowerment becomes an important policy discussion in development economics and modernization theory. The empowerment of women can lead to an increase in the quality…
Abstract
Purpose
Women empowerment becomes an important policy discussion in development economics and modernization theory. The empowerment of women can lead to an increase in the quality viz-a-viz the capacity of human resources accessible for economic development. The purpose of this study is to evidence the impact of social and economic dimensions on women empowerment through financial inclusion in rural India.
Design/methodology/approach
To reveal the research objective, the study has utilized a primary survey of women respondents from the Gujarat state of India by a simple random sampling method and applied a logistic regression approach to identify the relationship between the need of a bank account (determinant of financial inclusion) as a dependent variable and social and economic dimensions of women empowerment such as earning status, participation in financial decision-making, recipient of social welfare schemes and perception towards the safety of saving as independent variables.
Findings
The results of this study show that earning status, participation in financial decision-making at household level and recipient of social welfare schemes by women have a significant impact on women empowerment through financial inclusion; however, safety of their savings is observed as an insignificant variable, yet the odd value is very high (2.437) in the present study.
Originality/value
The present study is the first of its kind to examine the social and economic status of women and its impact on their requirement of a formal bank account for the overall empowerment of women in rural India.
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P. Sandhya, K. Shreyaas, R. Jayaraj and Ganesh Raja Rajeswari
One of the major challenges faced by the world at present is management and treatment of waste. Especially, waste such as polyethylene (plastics) is non-degradable and is causing…
Abstract
Purpose
One of the major challenges faced by the world at present is management and treatment of waste. Especially, waste such as polyethylene (plastics) is non-degradable and is causing great damage to our environment. Aquatic environment is one among them that is getting affected by these plastic wastes. Water pollution is a great issue faced in many countries and steps to reduce it are being taken on a wide scale. Unwanted aquatic plants grown in ponds and lakes create problems like totally covering up the surface of the lake that blocks the sunlight for aquatic species and also reducing their total storage. Identifying such unwanted plants and plastics is a very essential part in treating and management of waste. Detection and classification help us to achieve this. With the help of satellites, drone-shot images of many oceans are captured, and the amount of plastic content present is detected using artificial intelligence. In artificial intelligence, we have many algorithms and platforms that help us to achieve object detection. Tensorflow is one such framework that helps us to perform object detection with the help of pre-trained models present in it, and thus, it is used in this study. Object detection uses computer vision to detect objects from images. Convolutional neural networks are a subset of machine learning that is helpful in image processing – in other words, processing of pixel data. In this study, we used the ResNet-50 model involving transfer learning for classifying unwanted plants and plastics. Lakes and ponds are the major places among the other aquatic environments where these kinds of wastes are found, and therefore, this study concentrates on waste present in these aquatic bodies. The lakes and ponds present near residential areas act as a place for storing excess rainwater, which prevents flooding. Many cities, especially residential areas, face a lot of water stagnation problems during the rainy season. Ponds and lakes near these areas contain unwanted plants and plastics present, which makes it a problem to store the rainwater that comes during monsoon. Another problem is that they don’t provide sunlight to enter deep into water, making the aquatic species difficult to survive. Preserving and maintaining such lakes from getting filled with non-degradable plastics and unwanted plant growth becomes very important. Therefore, the lakes and ponds present in such residential areas would be useful to detect the unwanted waste.
Design/methodology/approach
In this study, the focus is on detection and classification of the plastics and unwanted plants. The dataset is very important for this study, which is an image dataset. There was not any readily available image data of unwanted plastics available online, and therefore, the images were captured from the lakes and ponds in Kanchipuram district. Images of duckweed, plastics, bulrush and leaves of sky lotus were taken. This dataset consisted a total of 200 images, with 50 images belonging to each category. Having this as the dataset, detection and classification were carried out.
Findings
The object detection took place for the plastic, duckweed, bulrush and leaves of sky lotus and the performance metrics such as precision and recall was evaluated to test the accuracy of the detections. Precision is used to calculate the number of correctly identified positive identifications. This is done by dividing the sum of true positives and false positives from the number of true positives. True positives are nothing but the number of correct predictions of positive identifications, and false positives are the number of false predictions of positive identifications. Similarly, recall is used to calculate the number of actual positives identified. We can calculate recall by dividing the sum of true positives and false negatives from the total number of true positives. Here false negatives are the number of false predictions of false identification. This performance metrics was evaluated for the trained model, and we obtained an average precision of 0.81 and an average recall of 0.86. The high precision and recall values of our model show that the model produces accurate results. Therefore, the model is producing good performance in detecting the unwanted plants and plastics from lakes and ponds. The evaluation results were visualized with the help of TensorBoard and are available in fig-4 and fig-5. The loss rate is visualized and is available in fig-6. We can see that the loss rate has reduced over the steps as we pass from 1,000 to 4000th step.
Originality/value
The work was originally carried out in the Kanchipuram district of Tamil Nadu.