Education•Kapurthala Town, India•
About: Punjab Technical University is a education organization based out in Kapurthala Town, India. It is known for research contribution in the topics: Wireless sensor network & Network packet. The organization has 1154 authors who have published 2401 publications receiving 21622 citations.
Topics: Wireless sensor network, Network packet, Feature extraction, Routing protocol, Efficient energy use
Papers published on a yearly basis
••01 Feb 2019
TL;DR: A new nature-inspired algorithm, namely butterfly optimization algorithm (BOA) that mimics food search and mating behavior of butterflies, to solve global optimization problems and results indicate that the proposed BOA is more efficient than other metaheuristic algorithms.
Abstract: Real-world problems are complex as they are multidimensional and multimodal in nature that encourages computer scientists to develop better and efficient problem-solving methods. Nature-inspired metaheuristics have shown better performances than that of traditional approaches. Till date, researchers have presented and experimented with various nature-inspired metaheuristic algorithms to handle various search problems. This paper introduces a new nature-inspired algorithm, namely butterfly optimization algorithm (BOA) that mimics food search and mating behavior of butterflies, to solve global optimization problems. The framework is mainly based on the foraging strategy of butterflies, which utilize their sense of smell to determine the location of nectar or mating partner. In this paper, the proposed algorithm is tested and validated on a set of 30 benchmark test functions and its performance is compared with other metaheuristic algorithms. BOA is also employed to solve three classical engineering problems (spring design, welded beam design, and gear train design). Results indicate that the proposed BOA is more efficient than other metaheuristic algorithms.
TL;DR: A comprehensive survey of the major applications of deep learning covering variety of areas is presented, study of the techniques and architectures used and further the contribution of that respective application in the real world are presented.
Abstract: Nowadays, deep learning is a current and a stimulating field of machine learning. Deep learning is the most effective, supervised, time and cost efficient machine learning approach. Deep learning is not a restricted learning approach, but it abides various procedures and topographies which can be applied to an immense speculum of complicated problems. The technique learns the illustrative and differential features in a very stratified way. Deep learning methods have made a significant breakthrough with appreciable performance in a wide variety of applications with useful security tools. It is considered to be the best choice for discovering complex architecture in high-dimensional data by employing back propagation algorithm. As deep learning has made significant advancements and tremendous performance in numerous applications, the widely used domains of deep learning are business, science and government which further includes adaptive testing, biological image classification, computer vision, cancer detection, natural language processing, object detection, face recognition, handwriting recognition, speech recognition, stock market analysis, smart city and many more. This paper focuses on the concepts of deep learning, its basic and advanced architectures, techniques, motivational aspects, characteristics and the limitations. The paper also presents the major differences between the deep learning, classical machine learning and conventional learning approaches and the major challenges ahead. The main intention of this paper is to explore and present chronologically, a comprehensive survey of the major applications of deep learning covering variety of areas, study of the techniques and architectures used and further the contribution of that respective application in the real world. Finally, the paper ends with the conclusion and future aspects.
TL;DR: Ten major technologies of Industry 4.0 can fulfil the requirements of customised face masks, gloves, and collect information for healthcare systems for proper controlling and treating of COVID-19 patients.
Abstract: Background and aims COVID 19 (Coronavirus) pandemic has created surge demand for essential healthcare equipment, medicines along with the requirement for advance information technologies applications. Industry 4.0 is known as the fourth industrial revolution, which has the potential to fulfil customised requirement during COVID-19 crisis. This revolution has started with the applications of advance manufacturing and digital information technologies. Methods A detailed review of the literature is done on the technologies of Industry 4.0 and their applications in the COVID-19 pandemic, using appropriate search words on the databases of PubMed, SCOPUS, Google Scholar and Research Gate. Results We found several useful technologies of Industry 4.0 which help for proper control and management of COVID-19 pandemic and these have been discussed in this paper. The available technologies of Industry 4.0 could also help the detection and diagnosis of COVID-19 and other related problems and symptoms. Conclusions Industry 4.0 can fulfil the requirements of customised face masks, gloves, and collect information for healthcare systems for proper controlling and treating of COVID-19 patients. We have discussed ten major technologies of Industry 4.0 which help to solve the problems of this virus. It is useful to provide day to day update of an infected patient, area-wise, age-wise and state-wise with proper surveillance systems. We also believe that the proper implementation of these technologies would help to enhance education and communication regarding public health. These Industry 4.0 technologies could provide a lot of innovative ideas and solution for fighting local and global medical emergencies.
TL;DR: A review of available and in-development diagnostic tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) including nanomaterial-based tools is presented in this paper.
Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread to nearly every corner of the globe, causing societal instability. The resultant coronavirus disease 2019 (COVID-19) leads to fever, sore throat, cough, chest and muscle pain, dyspnoea, confusion, anosmia, ageusia and headache. These can progress to life-threatening respiratory insufficiency, also affecting the heart, kidney, liver and nervous systems. The diagnosis of SARS-CoV-2 infection is often confused with that of influenza and seasonal upper respiratory tract viral infections. Due to available treatment strategies and required containments, rapid diagnosis is mandated. This Review brings clarity to the rapidly growing body of available and in-development diagnostic tests, including nanomaterial-based tools. It serves as a resource guide for scientists, physicians, students and the public at large.
TL;DR: In this article, the authors present an up-to-date review of progress and benefits of different routes for fabrication and machining of composites and conclude that polycrystalline tools and diamond-coated tools are best suitable for various conventional machining operations.
Abstract: Intrinsically smart, metal matrix composites (MMCs) are lightweight and high-performance materials having ever expanding industrial applications. The structural and the functional properties of these materials can be altered as per the industrial demands. The process technologies indulged in fabrication and machining of these materials attract the researchers and industrial community. Hybrid electric discharge machining is a promising and the most reliable nonconventional machining process for MMCs. It exhibits higher competence for machining complex shapes with greater accuracy. This paper presents an up-to-date review of progress and benefits of different routes for fabrication and machining of composites. It reports certain practical analysis and research findings including various issues on fabrication and machining of MMCs. It is concluded that polycrystalline tools and diamond-coated tools are best suitable for various conventional machining operations. High speed, small depth of cut and low feed ra...
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|Howard E. Gendelman||101||567||39460|
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|Balbir Singh Kaith||39||215||6330|
|Juan R. Torregrosa||29||236||3565|
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