469 research outputs found

    A Bibliometric Perspective Survey of Astronomical Object Tracking System

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    Advancement in the techniques in the field of Astronomical Object Tracking has been evolved over the years for more accurate results in prediction. Upgradation in Kepler’s algorithm aids in the detection of periodic transits of small planets. The tracking of the celestial bodies by NASA shows the trend followed over the years It has been noted that Machine Learning algorithms and the help of Artificial Intelligence have opted for several techniques allied with motion and positioning of the Celestial bodies and yields more accuracy and robustness. The paper discusses the survey and bibliometric analysis of Astronomical Object Tracking from the Scopus database in analyzing the research by area, influential authors, institutions, countries, and funding agency. The 93 research documents are extracted from the research started in this research area till 6th February 2021 from the database. Bibliometric analysis is the statistical analysis of the research published as articles, conference papers, and reviews, which helps in understanding the impact of publication in the research domain globally. The visualization analysis is done with open-source tools namely GPS Visualizer, Gephi, VOS viewer, and ScienceScape. The visualization aids in a quick and clear understanding of the different perspective as mentioned above in a particular research domain search

    Characterization and Visualization of Spatial Patterns of Urbanisation and Sprawl through Metrics and Modeling

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    Characterisation of spatial patterns of urban dynamics of Coimbatore, India is done using temporal remote sensing data of 1989 to 2013 with spatial metrics. Urban morphology at local levels is assessed through density gradients and zonal approach show of higher spatial heterogeneity during late1980’s and early 90’s. Urban expansion picked up at city outskirts and buffer region dominated with large number of urban fragments indicating the sprawl. Urban space has increased from 1.87% (1989) to 21.26 % (2013) with the decline of other land uses particularly vegetation. Higher heterogeneous land use classes during 90’s, give way for a homogeneous landscape (with simple shapes and less edges) indicating the domination of urban category in 2013. Complex landscape with high number of patches and edges in the buffer region indicate of fragmentation due to urban sprawl in the region. Visualisation of urban growth through Fuzzy-AHP-CA model shows that built up area would increase to 32.64% by 2025. The trend points to lack of appropriate regional planning leading to intensification of spatial discontinuity with the unsustainable urban growth

    Design capitalism: design, economics and innovation in the auto-industrial age

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    Automation is replacing white-collar office work and non-dexterous manual work, causing major structural change in the job market. As advanced economies shift from a post-industrial to an auto-industrial model, all kinds of routine work is being replaced by machines. Mid-range job opportunities are shrinking, and labor markets are polarizing. Demand for dexterous service work nevertheless remains strong, as does demand for abstract labor working with patterns rather than with rules or procedures. Design is a mid-tier occupation that is growing rather than declining. “Design” is also a metaphor for abstract labor of all kinds; it exemplifies work that is creative, innovative, problem-solving, and reliant on judgment rather than rules. Heightened demand for abstract labor reflects the evolving nature of capitalist economies. The contribution of invention, ingenuity and imagination to the creation of economic value continues to expand. The auto-industrial era is coeval with design capitalism; together they represent a key dimension of future economics

    Prediction of Initial and Striking Velocity of Primary Fragments from Cased Spherical Explosive inside Steel Cubical Structure

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    Usually, energy generated from an explosive’s detonation is transferred partly in the form of the blast impulse and some in the form of the kinetic energy of casing fragments. When detonation occurs in an explosive casing, it breaks the casing into fragments of different weights with varying velocities. The extent of destruction by these energized fragments depends upon the initial velocity they gain after an explosion. The momentum gained by the fragments decides the capability to perforate a barrier or propagate an explosion. A three-dimensional non-linear FEA method is used to model a box-shaped steel structure. This box-shaped structure is subjected to an internal cased explosion for estimating the initial and striking velocities of primary fragments. The effect of varying charge weight and the effect of the sacrificial wall on the initial and striking velocity of fragments via numerical simulations are also carried out. The initial and striking velocity values obtained through simulation are compared with the design guidelines of the code-based approach, and a good agreement is reported

    Design, Simulation, and Control of a Hexapod Robot in Simscape Multibody

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    In this chapter, we present the design, simulation, and control of a hexapod robot using tools available in MATLAB software. In addition, we design and implement a dynamic model (using the Simscape Multibody™ toolbox) as well as a three-dimensional model of the robot, using Virtual Reality Modeling Language (VRML), that help to visualize the robot’s walking sequence. This three-dimensional model is interconnected with the Simscape Multibody™ blocks using MATLAB’s virtual reality blocks. Apart from this, and following specific requirements, we design and implement a Proportional–Integral–Derivative controller in order to obtain a pre-established displacement for the robot that, thanks to the developed computer simulations, proved to be satisfactory. Special emphasis is put in obtaining a modular representation of the dynamic model of the studied robot because it will permit to design more sophisticated nonlinear controllers in future works, allowing a good dynamic behavior of the robot in front of environmental perturbations, an issue that will become evident through computer simulations of its displacement

    Disruptive Technologies in Smart Farming: An Expanded View with Sentiment Analysis

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    Smart Farming (SF) is an emerging technology in the current agricultural landscape. The aim of Smart Farming is to provide tools for various agricultural and farming operations to improve yield by reducing cost, waste, and required manpower. SF is a data-driven approach that can mitigate losses that occur due to extreme weather conditions and calamities. The influx of data from various sensors, and the introduction of information communication technologies (ICTs) in the field of farming has accelerated the implementation of disruptive technologies (DTs) such as machine learning and big data. Application of these predictive and innovative tools in agriculture is crucial for handling unprecedented conditions such as climate change and the increasing global population. In this study, we review the recent advancements in the field of Smart Farming, which include novel use cases and projects around the globe. An overview of the challenges associated with the adoption of such technologies in their respective regions is also provided. A brief analysis of the general sentiment towards Smart Farming technologies is also performed by manually annotating YouTube comments and making use of the pattern library. Preliminary findings of our study indicate that, though there are several barriers to the implementation of SF tools, further research and innovation can alleviate such risks and ensure sustainability of the food supply. The exploratory sentiment analysis also suggests that most digital users are not well-informed about such technologies

    An Algorithmic Framework for Multiobjective Optimization

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    Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization

    A Surface Plasmon Resonance Bio-Sensor based on Dual Core D-Shaped Photonic Crystal Fibre Embedded with Silver Nanowires for Multi-Sensing

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    K. Senthilnathan and K. Nakkeeran acknowledge the ASEM-DUO for support in the form of an International Joint Project Grant (2020 DUO-India-Scotland Professor Fellowship Award).Peer reviewedPostprin

    Analysis of a robot selection problem using two newly developed hybrid MCDM models of TOPSIS‐ARAS and COPRAS‐ARAS

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    Traditional Multi‐Criteria Decision Making (MCDM) methods have now become outdated; therefore, most researchers are focusing on more robust hybrid MCDM models that combine two or more MCDM techniques to address decision‐making problems. The authors attempted to create two novel hybrid MCDM systems in this paper by integrating Additive Ratio ASsessment (ARAS) with Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Complex PRoportional ASsessment (COPRAS). To demonstrate the ability and effectiveness of these two hybrid models i.e., TOPSIS‐ARAS and COPRAS‐ARAS were applied to solve a real‐time robot selection problem with 12 alternative robots and five selection criteria, while evaluating the parametric importance using the CRiteria Importance Through Inter criteria Correlation (CRITIC) objective weighting estimation tool. The rankings of the robot alternatives gained from these two hybrid models were also compared to the obtained results from eight other solo MCDM tools. Although the rankings by the applied methods slightly differ from each other, the final outcomes from all of the adopted techniques are consistent enough to suggest that robot 12 is the best choice followed by robot 11, and robot 4 is the worst one among these 12 alternatives. Spearman Correlation Coefficient (SCC) also reveals that the proposed rankings derived from various methods have a strong ranking relationship with one another. Finally, sensitivity analysis was performed to investigate th

    Sociocultural concepts of pandemic influenza and determinants of community vaccine acceptance in Pune, India

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    Vaccines are considered one of public health’s greatest achievements. Yet, public concerns and hesitancy towards acceptance of vaccines has been noted around the world for various vaccines. Limited vaccine uptake against influenza A (H1N1) was a problem during the 2009-2010 pandemic. Ensuring the ability to rapidly produce large quantities of an efficacious vaccine has been a focus of pandemic preparedness at the global and national levels. Notwithstanding the importance of these preparedness measures, its availability and clinical efficacy alone may not be sufficient for the vaccine to be effective at a community level. Culture has a powerful influence on the understanding of sickness and illness-related behaviour. The framework of cultural epidemiology used in this thesis integrates the local validity of anthropology and the explanatory power of epidemiology to clarify the cultural basis of vaccine hesitancy and acceptance. Despite cross-cultural differences and an acknowledged need for country-specific studies, relatively little research has focussed on pandemic influenza vaccine hesitancy in lower income settings. A mixed-methods research study was conducted in urban and rural Pune, a hotspot of the influenza pandemic in India. The aim was to study local sociocultural features of illness and determinants of pandemic influenza vaccine acceptance from a community perspective. This work is a contribution to global advances in the study of vaccine hesitancy and it underscores the value of sociocultural study and community preferences in planning effective vaccine action
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