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Artificial intelligence is Revolution or Devolution for Employability 3

Artificial Intelligence is Revolution or Devolution for Empl...

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3rd international conference on Innovative Mechanisms for Industry applications, ICIMIA 2023

作者： Devi, Pooja Kaur, Harmeet Kumar, Rakesh Aluvala, Srinivas Singh, Shrish Uttaranchal Institute of Management Uttaranchal University India SR University School of Computer Science & Artificial Intelligence Warangal India Amity University Noida India

ISBN: (纸本)9798350343632

Artificial intelligence and employability will go hand in hand in future if there is right implementation of artificial intelligence in industries. Software integrated with artificial intelligence has gained a lot of popularity over time and the high demand for artificial intelligence is increasing rapidly, and the shortage of AI can also be seen because of this. This study asses AI impact on employability in an organization. The race between human intelligence and artificial intelligence is still going on however, Artificial intelligence has managed to prove its benefits in many different working areas many stakeholders such as government, shareholders, and firms are able to see its worth. Artificial intelligence has proven to be impactful in generating, creating, and executing policies and plans for achieving organizational goals and economic stability. Employment management will be in high need when industries implement artificial intelligence. AI has seen great advancement during pandemic, when entire world was on complete lockdown many organizations started implementing various automation technologies to keep their business running. This research has been prepared with the use of secondary data. The overall research was done after going through many different research based on artificial intelligence, employability, their relations, and advancement and adoption of artificial intelligence. The Study explore future scope of AI in employability and its pros and cons. © 2023 IEEE.

关键词： Artificial intelligence Automation Employability technology

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Implementation of a Secured Document Classifier 3

Implementation of a Secured Document Classifier

引用

3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Koppurkar, Varsha R Ramisetty, Srividya Solapure, Vaishanavi Cmr Institute of Technology Deparment of Ise Bengaluru India

ISBN: (纸本)9781665462167

In the present smart digitization era, every document is prepared, presented and shared through electronic media effortlessly. Classifying these documents to everyone's advantage is gaining important insight. Adapting Machine Learning (ML) algorithms for classification, is an efficient and easiest way of classifying documents. It requires document to be presented in understandable form. Classifying documents available online using ML smart techniques aid everyone in effectively utilizing time and energy. The existing challenge in document classification is the security of the uploaded document. The paper focuses on types of features depending on which a document can be classified. The features may include information present in the document. Classifying and grouping document for various applications help in sorting and ordering data in required format. The Documents are also secured using Rivest Shamir Adleman (RSA) cipher and a case study depicting the same are considered here. © 2023 IEEE.

关键词： Cryptography

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Performance Analysis of Regression Models in Solar PV Forecasting 3

Performance Analysis of Regression Models in Solar PV Foreca...

引用

3rd international conference on Artificial intelligence and Signal Processing, AISP 2023

作者： Kaushik, A.R. Padmavathi, S. Gurucharan, K.S. Raja, S.Charles Thiagarajar College of Engineering Department of Information Technology Tamilnadu Madurai India Thiagarajar College of Engineering Department of Electrical & Electronics Engineering Tamilnadu Madurai India

ISBN: (纸本)9798350320749

Solar energy is increasingly becoming one of the promising sources of renewable energy for versatile purposes including residential and commercial applications. Forecasting of the power output of solar photovoltaic (PV) systems with high accuracy in the short term is of significant importance for production, delivery, and storage in the energy market. This work aims to produce reliable short-term forecasting using machine learning methods such as Linear Regression, Random Forest Regression, and Decision Tree Regression. Results show 99% percent accuracy for the proposed models. The work also detects faults and abnormalities occurring in Solar PV panels with the help of results thereby enhancing the production. © 2023 IEEE.

关键词： Forecasting

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Research on autonomous intelligent inspection technology of substation based on image recognition and computer vision 3

Research on autonomous intelligent inspection technology of ...

引用

3rd international conference on Electronics, Electrical and Information Engineering, ICEEIE 2023

作者： Fang, Mengran Li, Jingya Cai, Li Wang, Zheng State Grid Information and Communication Industry Group Co. Ltd. Beijing Branch Beijing China

ISBN: (纸本)9781510671423

Substation is the core hub of power grid transmission, which provides the necessary guarantee for the safe and stable operation of substation and even the whole power grid. There are many kinds of electrical equipment in substation, and the distribution is dense. Different equipment shows obvious differences in appearance and state. When inspecting these electrical equipment, we can not only use traditional manual inspection methods, but also rely on artificial intelligence technology and big data technology to build an intelligent inspection robot, and realize the recognition of image information through image recognition technology. In this article, the application of intelligent inspection robot in autonomous intelligent inspection of substation is studied, and the path planning model of inspection robot is constructed by combining image recognition and computer vision technology. The experimental results show that the path planning algorithm of inspection robot in this article has small error and excellent accuracy, which can reach more than 98% after many iterations. The algorithm realizes the stable, reliable and high-precision inspection operation of the substation inspection robot. © 2023 SPIE.

关键词： Computer vision

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MOPARAS: A Modular Parallel Spherical robot with Position-Adjustable Connectors 17th

MOPARAS: A Modular Parallel Spherical Robot with Position-Ad...

引用

17th international conference on Intelligent robotics and applications

作者： Gu, Jie Lam, Tin Lun Tian, Chunxu Xia, Zhihao Zhang, Dan Fudan Univ Acad Engn & Technol Inst AI & Robot Shanghai 200433 Peoples R China Chinese Univ Hong Kong Sch Sci & Engn Shenzhen Peoples R China Shenzhen Inst Artificial Intelligence & Robot Soc Shenzhen Peoples R China Hong Kong Polytech Univ Dept Mech Engn Kowloon Hung Hom Hong Kong Peoples R China

ISBN: (纸本)9789819607976;9789819607983

This paper proposes a novel modular self-reconfigurable robot named MOPARAS (MOdular PARAllel Spherical robot), which can adjust connector positions to achieve docking in spherical continuous space. MOPARAS is mainly composed of six scissor linkage groups with four connectors arranged at their intersections, which form a parallel RCM mechanism. Compared to existing modular self-reconfigurable robots with fixed connectors, the pose of the four connectors of MOPARAS can be adjusted to attach to its peers, offering more flexible operational capabilities, especially for the aggregates. Additionally, the entire structure maintains rigidity and precision thanks to the parallel mechanism. Subsequently, the kinematics analysis and working space of the module are presented. The basic motion of the module is proposed and abstracted into the interrelationship of inscribed tetrahedrons. Based on this primitive motion, the module can achieve classic chain-like configurations such as manipulators, humanoid robots, and quadruped robots, among others, and can reconfigure between these configurations.

关键词： Modular Self-reconfigurable robots RCM Mechanism Parallel Mechanism

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Quantum Machine Learning Techniques based on Nurturing Agri-Ontology Framework in Agricultural Science 3

Quantum Machine Learning Techniques based on Nurturing Agri-...

引用

3rd international conference on Applied Artificial intelligence and Computing, ICAAIC 2024

作者： Deepa, R. Jayalakshmi, V. Thilakavathy, P. Bennet Prabhu, A. Surendran, R. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Chennai India Drbccc Hindu College Department of Computer Applications Chennai India Computer Science and Engineering Vels Institute of Science and Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Kone Elevator India Technology & Engineering Centre Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350375190

The absence of a consistent ontological framework often impedes efficient knowledge organization and sharing within the agricultural community, despite the quantity of data created in agricultural research. The lack of defined vocabulary and conceptual frameworks hinders data integration, agricultural research, and innovation by preventing interoperability between databases and systems. To address these issues, this research work proposes the Nurturing Agri-Ontology Framework (NAOF), which offers a systematic approach to creating and updating agricultural ontologies. Ontologies that faithfully portray agricultural ideas and connections can be more easily created with the help of NAOF, which combines ideas from knowledge management, agricultural science, and ontology engineering. NAOF aims to ensure that the ontologies produced reflect the wide range of viewpoints and terminology used in agricultural research by encouraging cooperation among stakeholders, ontology engineers, and domain specialists. In this study, the improvement of knowledge organization, sharing and integration in the agricultural area is shown with the application of NAOF. Using this research study, scientists can build ontologies that improve agricultural decision-making, data interoperability, and the discovery of new information. Using quantum machine learning techniques, a strong foundation of knowledge can be laid for several agricultural applications, such as precision agriculture, crop management, and the formulation of agricultural policies. Ontology coverage, interoperability, scalability, and usability are established evaluation parameters that are used to assess the efficacy of NAOF in this research work. The analysis shows that NAOF effectively solves the problems and creates a better agricultural knowledge ecosystem by thoroughly evaluating it using these standards. © 2024 IEEE.

关键词： Ontology

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HUGO, a Humanoid robot for Training Memory: A Pilot Study on Healthy Younger and Older Adults 3

HUGO, a Humanoid Robot for Training Memory: A Pilot Study on...

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3rd IEEE international conference on Metrology for eXtended Reality, Artificial intelligence and Neural Engineering, MetroXRAINE 2024

作者： Gigliotta, Onofrio Padulo, Caterina Chinzer, Erica Fairfield, Beth University of Naples Federico Ii Department of Humanistic Studies Naples Italy University of Macerata Macerata Italy

ISBN: (纸本)9798350378009

Low birth rates and higher life expectancy are shaping a society that is aging very quickly. Indeed, in 2023 the EU Statistical Office estimated that one-fifth of the EU population was aged 65 years old and over. More importantly, the number of older adults destined to live alone in the future has increased and society is facing a strong positive correlation between health costs and age. This aging population will need more medical and psychological support and will impact the healthcare system and healthcare costs by increasing the number of healthcare workers necessary in critical sectors. Moreover, successful aging, has led to yet another crucial issue to be faced by modern society. The need to identify a sufficient number of qualified individuals to support older adults' healthcare needs and successful aging. In recent years, there has been a significant growth in studies concerning the use of robots in social assistance contexts, a field of study known as Socially Assistive robotics (SAR), where the acronym SAR is used to refer to robots providing social assistance. One of the most frequently used robots in assistive settings is NAO. This small humanoid robot has great potential in social applications. The characteristics and capabilities of the NAO robot, such as motor skills, functionality, and affective abilities, have been studied in various contexts. The present pilot study evaluates the feasibility of the hUGO (Humanoid to GO) platform (developed by the first author of this contribution, based on the NAO robot), to replace the human trainer in the administration of a memory training protocol developed to actively sustain working memory in aging individuals. © 2024 IEEE.

关键词： Anthropomorphic robots

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The Impact of Blockchain and AI in the Healthcare 3

The Impact of Blockchain and AI in the Healthcare

引用

3rd IEEE international conference on Electrical Power and Energy Systems, ICEPES 2024

作者： Thatikonda, Ramya Kempanna, M. Tatikonda, Reshmi Bhuvanesh, A. University of the Cumberlands PhD in Information Technology Williamsburg United States Bangalore Institute of Technology Department of Artificial Intelligence and Machine Learning Karnataka Bengaluru India University of the Central Missouri Masters in Computer Information Systems Warrensburg United States PSN College of Engineering and Technology Department of Electrical and Electronics Engineering Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350390728

Integrating blockchain and artificial intelligence (AI) in healthcare presents a transformative opportunity. Therefore, this can revolutionize patient care by improving data management and medical research. Decentralization and invulnerability granted by blockchain technology foster improved data consistency and interoperability. AI enhances blockchain by streamlining data examination, automatic tasks, and decision-making processes, resulting in more precise medical diagnoses and tailored therapy programs. The intersection of blockchain and AI is explored, along with their potential benefits and practical applications in healthcare. The document examines the hurdles encountered when integrating innovations, including scalability, interoperability, and regulatory adherence issues. Additionally, the study investigates moral questions surrounding data ownership and patient consent, thereby protecting confidentiality and trust. The synergy between blockchain, AI, and healthcare will lead to transformative advancements. It pledges to fortify data safety and expedite information sharing. Consequently, this will result in an improved, price-effective, and patient-focused healthcare environment. Recommendations were made for additional research and practical implementation in healthcare technology. The study should concentrate on creating scalable and compatible blockchain systems. A vital factor for extensive use is tackling regulatory and moral issues. Hybrid blockchain designs and federated learning strategies will bolster information privacy and utility. © 2024 IEEE.

关键词： Data consistency

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A Low-Profile UCA Antenna to Generate Conical beam based on OAM Technique for Vehicular applications 3

A Low-Profile UCA Antenna to Generate Conical beam based on ...

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3rd international conference on Artificial intelligence and Signal Processing, AISP 2023

作者： Sudheep, Veeravalli Srinivas, Maddu Kumar, Gurrala Kranthi Rao, Madasu Venkateswara Yuvaraj, S. Kartikeyan, M.V. National Institute of Technology Andhra Pradesh Dept. Electronics & Communication Engg. Tadepalligudem India Indian Institute of Information Technology Design and Manufacturing Kancheepuram Chennai India Indian Institute of Technology Roorkee Dept. Electronics & Communication Engg. Uttarakhand India

ISBN: (纸本)9798350320749

In this paper, a single-layer uniform circular array (UCA) antenna is designed to generate the conical beam (CB) using the orbital angular momentum (OAM) technique for vehicular applications. Unlike traditional techniques, the proposed UCA takes advantage of inherent OAM beam property to generate a CB. The proposed UCA is a single layered structure with a simple feed network. The UCA consists of 2×2 circularly polarized (CP) square patch elements, which are geometrically rotated to generate a CB with OAM mode l=-1 at 5.8 GHz. The CP square patches are geometrically rotated to achieve the required phase excitation. The simulation results indicate a cone-shaped radiation pattern in the elevation plane. A good isolation is achieved between co and cross polarization. A peak gain of 10 dB is observed at the operating frequency of 5.8 GHz. © 2023 IEEE.

关键词： Directional patterns (antenna)

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Comprehensive design of a distributed intelligent unmanned shipborne radar system 3

Comprehensive design of a distributed intelligent unmanned s...

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3rd international conference on Algorithms, Microchips, and Network applications, AMNA 2024

作者： Xue, Tong Liu, Xiaotong Zhang, Xiongfei Zuo, Hangzhou 20th Research Institute of China Electronics Technology Group Xi'an710000 China

ISBN: (纸本)9781510680098

Starting from practical needs, this article combines network technology, control technology, and radar technology based on the latest developments in communication technology. A distributed remote control shipborne radar system has been designed, focusing on solving the problem of unmanned shipborne radar and achieving unmanned and intelligent remote control of shipborne radar. The system is divided into three parts: the shore remote control center, the shipborne radar end, and the wireless network. The operator obtains real-time information such as radar intelligence, radar working status, and surrounding situation from the human-machine interface of the shore remote control center, and controls the shipborne radar equipment through the wireless network to achieve intelligent remote control of the shipborne radar. It meets the needs of unmanned and intelligent shipborne radar, improves the reliability and safety of shipborne radar, and provides reference and inspiration for the intelligent unmanned application of shipborne radar in the future. © 2024 SPIE.

关键词： Remote control

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