• +919888650222
  • This email address is being protected from spambots. You need JavaScript enabled to view it.

International Conference on Financing and Accounting for Economic Strategies (IC-FAES)

Image

Articles

The Impact of Artificial Intelligence on Management Productivity and Efficiency

Dr.shaifali garg, Dr Bhadrappa Haralayya, Mohammad ali AL Qudah, Lakshmana Phaneendra Maguluri, András SZEBERÉNYI, Aws Zuhair Sameen

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

The paper seeks to investigate, while acknowledging its limits, how artificial intelligence (AI) affects employee commitment and productivity at work. The study combines a qualitative research approach with a simple random sample technique. Online surveys are created using Google Forms and are used to gather data. Sixty percent of the one hundred participants are female, forty percent are male, and ninety-nine percent of responses are between the ages of twenty and forty. The findings demonstrate that AI can positively affect employee engagement and productivity. The use of computers to simulate intelligent behavior with little to no human intervention is known as artificial intelligence (AI). Artificial intelligence (AI) is revolutionising management practices and has a big impact on output and efficiency across a range of industries. This abstract explores the ways in which artificial intelligence (AI) has impacted management, emphasizing the ways in which AI has automated data processing, decision-making, and repetitive tasks. AI technologies, such as machine learning and predictive analytics, let managers make well-informed decisions based on huge datasets, which improves strategic planning and resource allocation. Additionally, AI-driven solutions make teamwork, communication, and project management easier, which encourages an organisational structure that is more adaptive and agile. Keywords: Artificial Intelligence, Management, Productivity, Efficiency, Ai Technologies, Ai-Driven,

Medical Dataset Classification Using Ensemble Feature Selection And Back Propagation Neural Network Algorithm

Dr.T. Christopher, N. Kumar

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

Due to the ongoing creation of digital data, the amount of medical data has significantly expanded in recent years. the many types of medical information, including reports, text, numbers, monitoring, and laboratory results. Because of a problem with a single optimisation technique in the current system, classification accuracy is not considerably guaranteed. Another significant issue is error rates, which prevents early illness prediction from being carried out effectively. This research work uses EFS (Ensemble Feature Selection) with BPNN (Back Propagation Neural Networks) to handle the afore mentioned issues. The input data is pre-processed using KMC (K-Means Clustering) algorithm, mainly for handling missing values and subsequently, EFS method is used to choose the features since it produces the best fitness values using an objective function. To solve the FS problem, EFS relies on integrating many FS rather than just one FS. Combining the results of multiple single FS approaches, such as EEHO (Entropy Elephant Herding Optimisation) and AFOA (Adaptive Firefly Optimisation Algorithm), is one alternative for the EFS method. And EBFO (Entropy Butterfly Optimization Algorithm) acquire improved outcomes rather than utilizing a single FS methodology. Finally, the medical dataset classification is performed using BPNN algorithm. With the help of the BPNN algorithm, a multilayer FFNN (feed forward neural networks) is trained. The class labels in tuples are predicted using weights that are learnt iteratively. The experimental findingsof the proposed EFS-BPNN algorithm demonstrates better values for accuracy, sensitivity, specificity, and execution time when compared with existing methods. Key words: Medical dataset classification, EFS, Entropy Elephant Herding Optimization (EEHO), Adaptive Firefly Optimization Algorithm (AFOA) and Entropy Butterfly Optimization Algorithm (EBFO) and Back Propagation Neural Network (BPNN)

Advancing Sustainable Energy with Water-Responsive Materials

Yaewon ParkaandXi Chen

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This study explores the burgeoning field of water-responsive materials and their pivotal role in sustainable energy applications. Water-responsive materials exhibit dynamic properties in respodevices, these materials offer versatile solutions for renewable energy generation and storage. Through a comprehensive review of recent advancements, this abstract highlights the key principles and applications driving the development of water-responsive materials in the pursuit of sustainable energy. By harnessing the power of water-responsive materials, researchers aim to revolutionize energy systems while mitigating environmental impact. This abstract underscores the significance of this emerging field in advancing the global transition towards cleaner and more sustainable energy sources.

Advancing Renewable Energy: A Review of Organic/Inorganic Solar Cell Performance for Sustainable Photovoltaic Technologies

J. Ajayan, D. Nirma,l P. Mohankumar , M. Saravanan M. Jagadesh, L. Arivazhagan

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This paper presents a comprehensive review of the performance of organic/inorganic solar cells, aiming to contribute to future renewable and sustainable energy technologies. The growing interer cells, which combine the advantages of both organic and inorganic materials, this review sheds light on their potential to revolutionize renewable energy generation. Key factors such as efficiency, stability, and scalability are analyzed, providing insights into the challenges and opportunities for advancing sustainable photovoltaic technologies. This review serves as a valuable resource for researchers, policymakers, and industry stakeholders seeking to accelerate the adoption of renewable energy solutions.

Unlocking Sustainable Energy Solutions with Phase Change Material-Integrated Latent Heat Storage Systems

Waseem Aftab, Ali Usman, Jinming Shi, Kunjie Yuan, Mulin QinaandRuqiang Zou

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This paper investigates the potential of phase change material-integrated latent heat storage systems as a sustainable solution for energy storage. By harnessing the latent heat properties of PCM-based latent heat storage, including material selection, system design, and performance evaluation. Furthermore, it examines the integration of these systems into renewable energy technologies such as solar thermal systems and waste heat recovery, highlighting their role in enhancing overall system efficiency and sustainability. Through a comprehensive analysis of recent advancements and challenges, this paper provides insights into the opportunities and future directions for leveraging PCM-integrated latent heat storage systems in sustainable energy solutions.

Tailored Energy Engineering Curricula for Sustainable Development: Addressing Underserved Areas

Ulpiano Ruiz-Rivas, Jorge Martinez-Crespo, Maria Venegas, Monica Chinchilla-Sanchez

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This study proposes a framework for developing energy engineering curricula tailored to promote sustainable development, particularly focusing on underserved areas. In light of global challeng

Accelerating Sustainable Energy Storage Material Discovery through Quantum Chemistry-Informed Active Learning

Hieu A. Doan , Garvit Agarwal, Hai Qian, Michael J. Counihan, Joaquín Rodríguez-López, Jeffrey S. Moore, and Rajeev S. Assary

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This paper introduces a novel approach to expedite the design and discovery of sustainable energy storage materials by leveraging quantum chemistry-informed active learning.g demand for renewable energy storage solutions, there is a critical need for efficient methods to identify and optimize materials with desirable properties. The proposed approach integrates quantum chemistry calculations with active learning techniques to guide the exploration of material space systematically. By iteratively selecting informative candidate materials for experimental validation, this framework minimizes the computational and experimental resources required for material discovery. The paper discusses the theoretical foundations of quantum chemistry-informed active learning and its application in accelerating the development of energy storage materials with enhanced performance and sustainability. Through case studies and performance evaluations, the effectiveness and potential of this approach are demonstrated, offering a promising avenue for addressing the challenges in sustainable energy storage materials research.

Exploring Redox-Active Organic Compounds for Sustainable Future Energy Storage Systems

Sechan Lee, Jihyun Hong, Kisuk Kang

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This paper investigates the potential of redox-active organic compounds as promising candidates for sustainable energy storage systems of the future. With the increasing demand for renewable energy sources, efficient and cost-effective energy storage solutions are imperative for grid stability and widespread adoption of renewable technologies. Redox-active organic compounds offer several advantages, including high abundance, tunable redox properties, and environmental compatibility. This review examines recent advancements in the design, synthesis, and characterization of redox-active organic molecules for energy storage applications, highlighting their potential for electrochemical energy storage devices such as redox flow batteries and organic electrodes in lithium-ion batteries. Furthermore, the paper discusses challenges and opportunities in integrating redox-active organic compounds into practical energy storage systems, paving the way for sustainable and scalable energy storage solutions.

Unlocking Sustainable Energy: Harnessing Terrestrial Radiative Cooling from the Cold Universe

XIAOBO YIN, RONGGUI YANG, GANG TAN, AND SHANHUI FAN

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This paper delves into the innovative concept of terrestrial radiative cooling as a renewable and sustainable energy source, capitalizing on the frigid expanse of the universe. Traditional energy generation methods contribute to environmental degradation and climate change, necessitating the exploration of alternative, eco-friendly solutions. Terrestrial radiative cooling exploits the natural process of thermal radiation to dissipate heat from Earth's surface into outer space, leveraging the vast reservoir of coldness beyond our planet. The study discusses the fundamental principles of radiative cooling and reviews recent advancements in materials and technologies. Moreover, it explores potential applications in passive cooling for buildings, thermal management in electronics, and agricultural refrigeration. By tapping into the boundless coldness of the universe, terrestrial radiative cooling presents a promising avenue for sustainable energy generation and environmental preservation.

Scoping Renewable Energy: A Review on Sustainability and Environmental Impact

Svitlana Kolosok ,Yuriy Bilan ,Tetiana Vasylieva ,Adam Wojciechowskiand Michał Morawski

Year: 2021| Conference Paper | Publisher: Scitech Conference Xplorer

Abstract:

This study delves into the concept of terrestrial radiative cooling as a renewable and sustainable energy source, capitalizing on the vast coldness of the universe. Amidst escalating concerns over climate change and environmental degradation, the quest for eco-friendly energy solutions has become paramount. Terrestrial radiative cooling presents a promising avenue, leveraging natural thermal radiation to dissipate heat from the Earth's surface into outer space. This paper examines the fundamental principles of radiative cooling and surveys recent advancements in materials and technologies. Moreover, it explores potential applications such as passive building cooling, electronic device thermal management, and agricultural refrigeration. By tapping into the limitless cold reservoir of the universe, terrestrial radiative cooling offers a compelling pathway toward sustainable energy generation and environmental preservation.


International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

International Conference on Sustainable Energy and Materials Engineering (ICSEME)

International Conference on Biomedical Robotics and Computational Imaging (ICBRCI)

International Conference on Smart Cities and Civil Infrastructure (ICSCCI)

International Conference on Aerospace Technologies and Data Science (ICATDS)

International Conference on Renewable Resources and Chemical Engineering (ICRRCE)

International Conference on Cyber-Physical Systems and Electrical Engineering (ICCPSE)

International Conference on Robotics in Manufacturing and Environmental Engineering (ICRMEE)

International Conference on Advanced Materials and Mechanical Engineering (ICAMME)

International Conference on Nanotechnology for Electrical Systems (ICNES)

International Conference on Geotechnical Innovations and Computer-Aided Design (ICGICAD)

International Conference on Water Resources and Environmental Engineering (ICWREE)

International Conference on Intelligent Transportation Systems and Structural Engineering (ICITSE)

Flex

+91 9888374777
icmsetm@scitechconference.org