Browse Items (11810 total)
Sort by:
-
Method of enhancing quality of services in cloud computing environment using load balancer /
Patent Number: 202211006218, Applicant: Dr. Pratibha Giri. -
Method of enhancing quality of services in cloud computing environment using load balancer /
Patent Number: 202211006218, Applicant: Dr. Pratibha Giri. -
Method of computer added progressive die design with energy conversation /
Patent Number: 201941037095, Applicant: Dr. Debabrata Samanta.
The present invention is related to a method of computer added progressive die design with energy conservation. The computer implemented method is presented including the simulation of requirements of design with bending the blank sheet metal strip used as a simulation, boundary conditions and applying the constraint nodes motion on the object. -
Method of computer added progressive die design with energy conservation /
"Patent Number: 201941037095, Applicant: Debabrata Samanta.
The present invention is related to a method of computer added progressive die design with energy conservation. The computer implemented method is presented including the simulation of requirements of design with bending the blank sheet metal strip used as a simulation, boundary conditions and applying the constraint nodes motion on the object. An adaptive algorithm processed by the processor of the computer system which used for the energy-saving measurement and adjustment of the progressive die design." -
Method for synthesizing onion-like carbon nanostructures for high performance supercapacitor applications /
Patent Number: 202141000172, Applicant: A V Ramya.The present invention provides a facile, cost-effective, and scalable method for the preparation of onion-like carbon nanostructures from paraffin oil. The method includes a wick-and-paraffin oil flame pyrolysis process in a limited supply of oxygen, where the soot generated during combustion is collected and processed to obtain onion-like carbon nanostructures. The synthesized nanostructures exhibit nearly spherical morphology with particle size ranging from 30 to 50 nm and a BET specific surface area of 104 m2/g. v. -
Method for face-recognition on the basis of sketch using deep convolution neural network /
Patent Number: 201941045946, Applicant: Dr. Debabrata Samanta.
The present invention relates to method for face- recognition on the basis of sketch using deep convolution neural network. The objective of the present invention is to overcome the inadequacies of the prior art in techniques for face- recognition on the basis of sketches. -
Method for face-recognition on the basis of sketch using deep convolution neural network /
"Patent Number: 201941045946, Applicant: Dr. Debabrata Samanta.
The present invention relates to method for face- recognition on the basis of sketch using deep convolution neural network. The objective of the present invention is to overcome the inadequacies of the prior art in techniques for face- recognition on the basis of sketches." -
Metaverse marketing: a review and future research agenda
Purpose: The metaverse represents a rapidly evolving digital environment that blurs the lines between physical and virtual reality, and it offers unique opportunities and challenges for businesses and marketers. The purpose of this study is to provide a comprehensive review of metaverse marketing research. The present study reviews the literature on metaverse to identify theories, contexts, gaps and methodologies using TCCM framework (Theories, Contexts, Characteristics and Methodology) to set a future research agenda. Design/methodology/approach: A review was conducted of 179 English papers related to metaverse marketing from 2010 to 2023 from the Scopus and Web of Science core collection after applying relevant filters using the TCCM framework. Findings: The findings suggest that the studies have inadequately distinguished metaverse as something that only builds interactive experiences that combine the virtual environment and the real world, whereas the theoretical domain of metaverse is dominated by studies in various domains. The applicability of metaverse marketing research is pertinent in various domains of the management field. The study explores various facets of metaverse marketing to capture its dynamic nature. Research limitations/implications: By presenting a comprehensive review, themes and knowledge gaps of the research on metaverse marketing, this study will enhance research output and provide valuable tools for future research on metaverse. Practical implications: By analyzing metaverse in marketing, the companies will be able to use this concept effectively to formulate innovative marketing strategies and personalized consumer experiences and understand consumer behavior. Furthermore, research into metaverse marketing will be helpful in offering predictions about future trends in consumer behavior, technology adoption and virtual world development. Originality/value: This study provides a thorough analysis of the current state of research on metaverse in marketing and provides a road map for further research in this area. 2024, Emerald Publishing Limited. -
Metalsemiconductormetal visible photodetector based on Al-doped (Cd:Zn)S nano thin films by hydrothermal synthesis
High quality undoped and Al-doped nanocrystalline (Cd:Zn)S films [CZS and ACZS] were deposited on glass substrates by hydrothermal assisted chemical bath deposition. The Al concentration was varied from 0.5 mol.% to 2 mol.% in steps of 0.5 mol.% replacing cadmium while keeping other deposition parameters constant. XRD, SEM, and EDX were used to observe crystallinity, morphology and composition of the as prepared samples. X-ray diffraction revealed the hexagonal phase of CZS films with prominent orientation along the (002) plane. XPS analysis was used to confirm the doping concentration of Al in to CZS lattice. Repeatable photoresponse was recorded under 100 s cycle light-on and light-off conditions. 1 mol.% Al doped film being optimised as good photoconductor; a photodetector was fabricated with Ag/ACZS/Ag device structure. The ACZS photodetector exhibits similar time response, good photocurrent reproducibility and a sharp photoresponse at blue radiation with high photo-dark current ratio of 95. The device exhibits peak responsivity of 3.48 mA W?1 and detectivity of 1.26 1011 Jones at 470 nm. These properties suggest that the ACZS photodetector holds great potential for application in high-performance visible photodetectors, especially in the blue region. 2021 Elsevier GmbH -
Metallic silver and copper oxide nanoparticles: Uses in food preservation and impacts on the environment
This review examines the applications of metallic silver and copper oxide nanoparticles in food preservation, emphasizing their potential to revolutionize food packaging and reduce environmental pollution through enhanced waste management strategies. Synthesis of these nanoparticles via green methods including bacteria-, fungi-, and plant-mediated approaches have been discussed. The antimicrobial properties and toxicity of silver and copper oxide nanoparticles have been evaluated highlighting their efficiency in inhibiting microbial growth and extending the shelf life of food products. Regulatory policies governing the use of these nanoparticles in food packaging have been analyzed along with the exploration of active packaging technologies that leverage their unique properties. By integrating advances in nanotechnology with better food formulations, this review underscores the transformative impact of silver and copper oxide nanoparticles on food safety and environmental sustainability, offering insights into the future directions for research and newer applications. 2024 -
Metal-Based Nanoparticles for Infectious Diseases and Therapeutics
Infectious diseases that are easily transmitted by microorganisms like bacteria, protozoa, fungus, etc. are a menace to humans. The greatest threat to human race is to mitigate the impact of these diseases. People with less immunity and children are prone to these diseases. Even healthy people get infected due to its easy transmission. Microorganisms causing these diseases are becoming more resistant to the drugs that are available in the market. So, there is a need to find new therapeutic which is facile, sensitive, and selective, is an important challenge for the medical field and this is where nanotechnology is having a greater chance. Nanoparticles especially metal-based nanoparticles have the ability to act against infectious and non-infectious diseases, this is because of their unique properties like small size, high surface area, etc. They do not have a specific binding site on the bacterial cell, which lead to the failure of bacterial resistant towards the nanoparticle mechanism. There are many nanoparticles which are efficient against particular diseases. In this review we are discussing about the advanced nanomaterials as therapeutics for infectious diseases. We have also discussed about antiviral activities which gives us a ray of hope for the solution of the SARS-COV-2. The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2022. -
Metal Organic Frameworks to Remove Arsenic Adsorption from Wastewater
Water is an integral part of life on earth. Rapid industrialization, urbanization, and population explosion have all contributed to the pollution of ground and surface water with, among other things, heavy metals. This has led to an acute shortage of clean drinking water. Arsenic is one of the most toxic heavy metals found in water, posing a serious threat to the environment, human beings, and aquatic life. Over the years, a considerable amount of research has been directed toward the elimination of arsenic from water via sustainable methodologies. Metal organic frameworks are a class of materials possessing exceptional features like chemical stability, high porosity, multiple functional groups, and large surface areas. These properties can be effectively channelized to make metal organic frameworks excellent adsorbents for the removal of arsenic from contaminated water and make it drinkable. We have reviewed herein, the problems of heavy metal contamination, specifically the different forms of arsenic that pollute water. The importance of metal organic frameworks and the progress made in the synthesis of materials having a metal oxide framework have been discussed. Significant properties like adsorption and mechanistic aspects of adsorption through metal organic frameworks have been described. Furthermore, the characterization of the electronic and geometric aspects of metal organic frameworks using density functional theory has been reviewed. Insight into proper scaling up and development of metal organic frameworks for practical applications have also been suggested. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Metal organic frameworks in biomedicine: Innovations in drug delivery
Metal-organic frameworks (MOFs) have emerged as a class of versatile materials, finding extensive applications in drug delivery because of their unique properties and flexible design. This comprehensive review aims to give a broad perspective on the recent advancements in the area of drug delivery applications using MOFs. The fundamental characteristics of MOFs, highlighting their exceptional porosity, high surface area, and tuneable framework structures, enable MOFs to serve as ideal drug carriers, allowing efficient drug loading and controlled release. The review delves into the various ligands and metal ions employed for drug encapsulation. These include physical encapsulation, covalent bonding, and host-guest interactions, each offering distinct advantages for diverse types of drugs and therapeutic applications. The importance of tailoring MOF properties to optimize drug loading capacity, stability, and release kinetics has been emphasized. Additionally, the explorations involve delving into the mechanisms of drug release from MOFs, with factors such as pH, temperature, and external stimuli that can be harnessed to trigger controlled drug release. The utilization of MOFs in combination therapies, such as co-delivery of multiple drugs or integrating imaging agents, has also been examined. Numerous examples of MOFs used for drug delivery, encompassing both in-vitro and in-vivo studies, covering a wide range of therapeutic areas, including cancer treatment, antimicrobial therapy, and targeted drug delivery, are included. Additionally, the review addresses the challenges and future perspectives in the development of MOFs for drug delivery. Strategies to improve MOF stability, biocompatibility, and scalability are discussed, along with the understanding of MOF-drug interaction and potential toxicity concerns. With their tuneable properties, high loading capacities, and controlled release capabilities, MOFs hold exceptional capabilities that promise to enhance the efficacy of therapeutic interventions. Continued research and development in this area can pave way for the translation of MOFs into clinical applications in the near future. 2024 The Author(s) -
Metal and Ligand-Free Approach Towards the Efficient One-Pot Synthesis of Dipyridopyrimidinimine Derivatives
We report a facile, expeditious, user-friendly, and convenient metal-free synthesis employing base catalysis in a one-pot procedure to construct 11H-dipyrido[1,2-a : 3?,2?-d]pyrimidin-11-imine derivatives. This protocol involves a domino process leading to the formation of double C?N bonds utilising KOtBu as the base and DMAc as the superior solvent at 25 C for 2 h. The versatility of this methodology was demonstrated by its successful application to substrates with both electron-withdrawing and electron-donating functional groups, yielding novel functionalized stable 11H-dipyrido[1,2-a : 3?,2?-d]pyrimidin-11-imine derivatives in good to excellent yields. Additionally, we have discussed a plausible reaction pathway for the synthesis. 2024 Wiley-VCH GmbH. -
Metaheuristicsbased Task Offloading Framework in Fog Computing for Latency-sensitive Internet of Things Applications
The Internet of Things (IoT) applications have tremendously increased its popularity within a short span of time due to the wide range of services it offers. In the present scenario, IoT applications rely on cloud computing platforms for data storage and task offloading. Since the IoT applications are latency-sensitive, depending on a remote cloud datacenter further increases the delay and response time. Most of the IoT applications shift from cloud to fog computing for improved performance and to lower the latency. Fog enhances the Quality of service (QoS) of the connected applications by providing low latency. Different task offloading schemes in fog computing are proposed in literature to enhance the performance of IoT-fog-cloud integration. The proposed methodology focuses on constructing a metaheuristic based task offloading framework in the three-tiered IoT-fog-cloud network to enable efficient execution of latency-sensitive IoT applications. The proposed work utilizes two effective optimization algorithms such as Flamingo search algorithm (FSA) and Honey badger algorithm (HBA). Initially, the FSA algorithm is executed in an iterative manner where the objective function is optimized in every iteration. The best solutions are taken in this algorithm and fine tuning is performed using the HBA algorithm to refine the solution. The output obtained from the HBA algorithm is termed as the optimized outcome of the proposed framework. Finally, evaluations are carried out separately based on different scenarios to prove the performance efficacy of the proposed framework. The proposed framework obtains the task offloading time of 71s and also obtains less degree of imbalance and lesser latency when compared over existing techniques. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Metaheuristic Machine Learning Algorithms for Liver Disease Prediction
In machine learning, optimizing solutions is critical for improving performance. This study explores the use of metaheuristic algorithms to enhance key processes such as hyperparameter tuning, feature selection, and model optimization. Specifically, we integrate the Artificial Bee Colony (ABC) algorithm with Random Forest and Decision Tree models to improve the accuracy and efficiency of disease prediction. Machine learning has the potential to uncover complex patterns in medical data, offering transformative capabilities in disease diagnosis. However, selecting the optimal algorithm for model optimization presents a significant challenge. In this work, we employ Random Forest, Decision Tree models, and the ABC algorithmbased on the foraging behaviours of honeybeesto predict liver disease using a dataset from Indian medical records. Our experiments demonstrate that the Random Forest model achieves an accuracy of 85.12%, the Decision Tree model 76.89%, and the ABC algorithm 80.45%. These findings underscore the promise of metaheuristic approaches in machine learning, with the ABC algorithm proving to be a valuable tool in improving predictive accuracy. In conclusion, the integration of machine learning models with metaheuristic techniques, such as the ABC algorithm, represents a significant advancement in disease prediction, driving progress in data-driven healthcare. 2024, Iquz Galaxy Publisher. All rights reserved. -
Meta-analysis of EMF-induced pollution by COVID-19 in virtual teaching and learning with an artificial intelligence perspective
Concerns about the health effects of frequent exposure to electromagnetic fields (EMF) emitted from mobile towers and handsets have been raised because of the gradual increase in usage of cell phones and frequent setting up of mobile towers. The present study is targeted to detrimental effects of EMF radiation on various biological systems mainly due to online teaching and learning processes by suppressing the immune system. During the COVID-19 pandemic, the increased usage of internet due to online education and online office leads to more detrimental effects of EMF radiation. Further inculcation of soft computing techniques in EMF radiation has been presented. A literature review focusing on the usage of soft computing techniques in the domain of EMF radiation has been presented in the article. An online survey has been conducted targeting Indian academic stakeholders (specially teachers, students, and parents termed as population in the paper) for analyzing the awareness towards the biohazards of EMF exposure. 2022 IGI Global. All rights reserved. -
Messaging service for business and operations and inquiries /
Patent Number: 202111036684, Applicant: Dr. Akhilesh Tiwari.
The present inventions is about a method and system by which the entity can interact with each other in a manufacturing channel by using a messaging system (11). The said messaging system to perform status inquiry and functional processing steps with respect to data stored (1) at the resource management system of the other. That information is transmitted through a messaging system (11) to the other party such as the seller. -
Message from the General Chairs
[No abstract available]