@article{Abuelhaija2020,
abstract = {This project presents a swarming and herding behaviour using simple robots. The main goal is to demonstrate the applicability of artificial intelligence (AI) in simple robotics that can then be scaled to industrial and consumer markets to further the ability of automation. AI can be achieved in many different ways; this paper explores the possible platforms on which to build a simple AI robots from consumer grade microcontrollers. Emphasis on simplicity is the main focus of this paper. Cheap and 8 bit microcontrollers were used as the brain of each robot in a decentralized swarm environment were each robot is autonomous but still a part of the whole. These simple robots don't communicate directly with each other. They will utilize simple IR sensors to sense each other and simple limit switches to sense other obstacles in their environment. Their main objective is to assemble at certain location after initial start from random locations, and after converging they would move as a single unit without collisions. Using readily available microcontrollers and simple circuit design, semi-consistent swarming behaviour was achieved. These robots don't follow a set path but will react dynamically to different scenarios, guided by their simple AI algorithm. {\textcopyright} 2020 Insitute of Advanced Engineeering and Science.},
annote = {Export Date: 23 March 2024; Cited By: 4},
author = {Abuelhaija, A and Jebrein, A and Baldawi, T},
doi = {10.11591/ijece.v10i2.pp2173-2181},
journal = {International Journal of Electrical and Computer Engineering},
keywords = {Artificial intelligence (AI),Infrared (IR) array,Swarm robotics,Whiskers circuit},
number = {2},
pages = {2173--2181},
title = {{Swarm robotics : Design and implementation}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85076461549&doi=10.11591%2Fijece.v10i2.pp2173-2181&partnerID=40&md5=259a68f732e967b87cea575202f6237d},
volume = {10},
year = {2020}
}
@article{Akhshirsh2021,
abstract = {This paper presents a robotic platform of a cost-effective GPS-aided autonomous guided vehicle (AGV) for global path planning. The platform is made of a mechanical radio controlled (RC) rover and an Arduino Uno microcontroller. An installed magnetic digital compass helps determine the right direction of the RC rover by con-tinuously synchronising the heading and bearing of the vehicle. To ensure effective monitoring of the vehicle's position as well as track the corresponding path, an LCD keypad shield was, further, used. The contribution of the work is that the designed GPS-aided AGV can successfully navigate its way towards a destination point in an obstacle-free outdoor environment by solely relying on its calculation of the shortest path and utilising the corresponding GPS data. This result is achieved with a minimum error possible that lies within a circle of one meter radius around the given destination, allowing the devised GPS-aided AGV to be used in a variety of applications such as landmine detection and removal. {\textcopyright} 2021, Institute of Advanced Engineering and Science. All rights reserved.},
annote = {Export Date: 03 April 2024; Cited By: 11; Correspondence Address: O.H. Hamid; University of Nottingham, United Kingdom; email: oh.hamid@gmail.com},
author = {Akhshirsh, G S and Al-Salihi, N K and Hamid, O H},
doi = {10.11591/eei.v10i2.2734},
journal = {Bulletin of Electrical Engineering and Informatics},
keywords = {Autonomous guided vehicles (AGVs),Deliberative and reactive robot architecture,GPS,Path planning},
number = {2},
pages = {650--657},
title = {{A cost-effective GPS-aided autonomous guided vehicle for global path planning}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103028754&doi=10.11591%2Feei.v10i2.2734&partnerID=40&md5=e0fb30d1ac49a77f37fbab99d4c42ad5},
volume = {10},
year = {2021}
}
@book{BohrAdam;Memarzadeh2020,
doi = {10.1016/C2018-0-04097-9},
editor = {{Bohr, Adam; Memarzadeh}, Kaveh},
isbn = {9780128184387},
publisher = {Elsevier},
title = {{Artificial Intelligence in Healthcare}},
year = {2020}
}
@book{boukherouaa2021powering,
author = {Boukherouaa, E B and Shabsigh, G and AlAjmi, K and Deodoro, J and Farias, A and Iskender, E S and Mirestean, A T and Ravikumar, R},
isbn = {9781589063952},
publisher = {International Monetary Fund},
series = {Departmental Papers},
title = {{Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance}},
year = {2021}
}
@article{Rashid2024,
author = {Rashid, Adib Bin and Kausik, MD Ashfakul Karim},
doi = {10.1016/j.hybadv.2024.100277},
issn = {2773207X},
journal = {Hybrid Advances},
month = {dec},
pages = {100277},
title = {{AI revolutionizing industries worldwide: A comprehensive overview of its diverse applications}},
volume = {7},
year = {2024}
}
@article{Mennella2024,
author = {Mennella, Ciro and Maniscalco, Umberto and {De Pietro}, Giuseppe and Esposito, Massimo},
doi = {10.1016/j.heliyon.2024.e26297},
issn = {24058440},
journal = {Heliyon},
month = {feb},
number = {4},
pages = {e26297},
title = {{Ethical and regulatory challenges of AI technologies in healthcare: A narrative review}},
volume = {10},
year = {2024}
}
@article{OlorunyomiStephenJoel2024,
abstract = {The integration of artificial intelligence (AI) technologies into supply chain management has emerged as a crucial avenue for enhancing efficiency, agility, and responsiveness in modern business operations. This comprehensive review synthesizes current practices and future potentials of leveraging AI for supply chain optimization. Beginning with an overview of traditional supply chain management challenges, the review elucidates how AI solutions address these complexities by enabling predictive analytics, real-time visibility, and intelligent decision-making. The review delves into the diverse applications of AI across different stages of the supply chain, including demand forecasting, inventory management, logistics optimization, and supplier relationship management. Examples of AI-driven technologies such as machine learning, natural language processing, and robotic process automation are analyzed for their role in revolutionizing supply chain operations. Furthermore, the review highlights the transformative impact of AI on supply chain resilience, emphasizing its ability to mitigate disruptions, adapt to dynamic market conditions, and optimize resource allocation. The review also addresses critical considerations such as data privacy, ethical implications, and organizational readiness for AI adoption within supply chain contexts. Lastly, the review discusses future research directions and potential advancements in AI-enabled supply chain management, envisioning intelligent autonomous supply chains characterized by self-learning systems, collaborative ecosystems, and enhanced sustainability practices. In conclusion, this review underscores the pivotal role of AI in driving continuous innovation and competitive advantage within supply chain networks, while also emphasizing the importance of strategic planning and responsible implementation to harness its full potential. Keywords: AI, Supply Chain, Optimization, Practices, Review.},
author = {{Olorunyomi Stephen Joel} and {Adedoyin Tolulope Oyewole} and {Olusegun Gbenga Odunaiya} and {Oluwatobi Timothy Soyombo}},
doi = {10.51594/ijmer.v6i3.882},
issn = {2664-3596},
journal = {International Journal of Management & Entrepreneurship Research},
month = {mar},
number = {3},
pages = {707--721},
title = {{LEVERAGING ARTIFICIAL INTELLIGENCE FOR ENHANCED SUPPLY CHAIN OPTIMIZATION: A COMPREHENSIVE REVIEW OF CURRENT PRACTICES AND FUTURE POTENTIALS}},
volume = {6},
year = {2024}
}
@book{satishkumar2024industry,
author = {Satishkumar, D and Sivaraja, M},
isbn = {9798369342770},
publisher = {IGI Global},
series = {Advances in Logistics, Operations, and Management Science},
title = {{Industry Applications of Thrust Manufacturing: Convergence with Real-Time Data and AI: Convergence with Real-Time Data and AI}},
year = {2024}
}
@book{citation-0,
author = {Hebooks},
publisher = {Hebooks},
title = {{AI-Powered Logistics: How Artificial Intelligence Will Revolutionize Transportation, shipping and logistics.}}
}
@article{Vinoi2025,
author = {Vinoi, Nivin and Shankar, Amit and Agarwal, Reeti and Alghafes, Rsha},
doi = {10.1016/j.jretconser.2024.104085},
issn = {09696989},
journal = {Journal of Retailing and Consumer Services},
month = {jan},
pages = {104085},
title = {{Revolutionizing retail: The transformative power of service robots on shopping dynamics}},
volume = {82},
year = {2025}
}
@article{DinkarJadhav2024TheIO,
author = {Jadhav, Rohan Dinkar and Banubakode, Abhijit},
journal = {International Journal For Multidisciplinary Research},
title = {{The Implications of Artificial Intelligence on the Employment Sector}},
url = {https://api.semanticscholar.org/CorpusID:270543196},
year = {2024}
}
@article{Guliyev2023,
author = {Guliyev, Hasraddin},
doi = {10.1016/j.resglo.2023.100140},
issn = {2590051X},
journal = {Research in Globalization},
month = {dec},
pages = {100140},
title = {{Artificial intelligence and unemployment in high-tech developed countries: New insights from dynamic panel data model}},
volume = {7},
year = {2023}
}
@article{2024RevolutionizingIT,
journal = {CONFERENCE PROCEEDING},
title = {{Revolutionizing Industries: The Impact of Artificial Intelligence Applications}},
url = {https://api.semanticscholar.org/CorpusID:270041312},
year = {2024}
}
@article{Wang2023,
abstract = {This article investigates the relationship between AI and the labor market, with a specific focus on job replacements and new opportunities. It examines the impact of AI on various sectors such as technology, law, medicine, finance, and creativity. AI has revolutionized work by automating repetitive tasks and, consequently, displacing certain job roles. However, it has also generated new avenues that demand a combination of technical expertise and human skills. To thrive in this evolving landscape, individuals and organizations must adapt to the changing nature of work and harness AI's potential for innovation and productivity. While embracing AI-driven advancements, it is crucial to uphold human values and ethics. The article emphasizes the need for a harmonious association between humans and AI in the labor market. By leveraging the unique strengths of both, individuals and organizations can drive efficiency, creativity, and productivity. This entails cultivating agility and adaptability to navigate the transformative impact of AI. Organizations must proactively integrate AI as a tool to enhance productivity and create new opportunities while ensuring that the human element remains integral to decision-making and problem-solving processes.},
author = {Wang, Jiashuo},
doi = {10.54254/2754-1169/46/20230309},
issn = {2754-1169},
journal = {Advances in Economics, Management and Political Sciences},
month = {dec},
number = {1},
pages = {10--15},
title = {{Navigating the AI Revolution: Job Replacements and New Opportunities in the Labor Market}},
volume = {46},
year = {2023}
}
@article{Toth2022,
abstract = {Business, management, and business ethics literature pay little attention to the topic of AI robots. The broad spectrum of potential ethical issues pertains to using driverless cars, AI robots in care homes, and in the military, such as Lethal Autonomous Weapon Systems. However, there is a scarcity of in-depth theoretical, methodological, or empirical studies that address these ethical issues, for instance, the impact of morality and where accountability resides in AI robots' use. To address this dearth, this study offers a conceptual framework that interpretively develops the ethical implications of AI robot applications, drawing on descriptive and normative ethical theory. The new framework elaborates on how the locus of morality (human to AI agency) and moral intensity combine within context-specific AI robot applications, and how this might influence accountability thinking. Our theorization indicates that in situations of escalating AI agency and situational moral intensity, accountability is widely dispersed between actors and institutions. ‘Accountability clusters' are outlined to illustrate interrelationships between the locus of morality, moral intensity, and accountability and how these invoke different categorical responses: (i) illegal, (ii) immoral, (iii) permissible, and (iv) supererogatory pertaining to using AI robots. These enable discussion of the ethical implications of using AI robots, and associated accountability challenges for a constellation of actors—from designer, individual/organizational users to the normative and regulative approaches of industrial/governmental bodies and intergovernmental regimes.},
author = {T{\'{o}}th, Zs{\'{o}}fia and Caruana, Robert and Gruber, Thorsten and Loebbecke, Claudia},
doi = {10.1007/s10551-022-05050-z},
issn = {1573-0697},
journal = {Journal of Business Ethics},
number = {4},
pages = {895--916},
title = {{The Dawn of the AI Robots: Towards a New Framework of AI Robot Accountability}},
url = {https://doi.org/10.1007/s10551-022-05050-z},
volume = {178},
year = {2022}
}
@article{Zirar2023,
author = {Zirar, Araz and Ali, Syed Imran and Islam, Nazrul},
doi = {10.1016/j.technovation.2023.102747},
issn = {01664972},
journal = {Technovation},
month = {jun},
pages = {102747},
title = {{Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda}},
volume = {124},
year = {2023}
}
@article{Donald2024AIAH,
author = {Donald, Obinna and Obaigbena, Alexander and Lottu, Oluwaseun Augustine and Ugwuanyi, Ejike David and Jacks, Boma Sonimitiem and Sodiya, Enoch Oluwademilade and Daraojimba, Obinna Donald},
journal = {GSC Advanced Research and Reviews},
title = {{AI and human-robot interaction: A review of recent advances and challenges}},
year = {2024}
}
@article{Venigandla2024HybridIS,
author = {Venigandla, Kamala and Vemuri, Navya and Vemuri, Naveen},
journal = {International Journal of Innovative Science and Research Technology (IJISRT)},
title = {{Hybrid Intelligence Systems Combining Human Expertise and AI/RPA for Complex Problem Solving}},
year = {2024}
}
@article{Elendu2023,
abstract = {Integrating Artificial Intelligence (AI) and robotics in healthcare heralds a new era of medical innovation, promising enhanced diagnostics, streamlined processes, and improved patient care. However, this technological revolution is accompanied by intricate ethical implications that demand meticulous consideration. This article navigates the complex ethical terrain surrounding AI and robotics in healthcare, delving into specific dimensions and providing strategies and best practices for ethical navigation. Privacy and data security are paramount concerns, necessitating robust encryption and anonymization techniques to safeguard patient data. Responsible data handling practices, including decentralized data sharing, are critical to preserve patient privacy. Algorithmic bias poses a significant challenge, demanding diverse datasets and ongoing monitoring to ensure fairness. Transparency and explainability in AI decision-making processes enhance trust and accountability. Clear responsibility frameworks are essential to address the accountability of manufacturers, healthcare institutions, and professionals. Ethical guidelines, regularly updated and accessible to all stakeholders, guide decision-making in this dynamic landscape. Moreover, the societal implications of AI and robotics extend to accessibility, equity, and societal trust. Strategies to bridge the digital divide and ensure equitable access must be prioritized. Global collaboration is pivotal in developing adaptable regulations and addressing legal challenges like liability and intellectual property. Ethics must remain at the forefront in the ever-evolving realm of healthcare technology. By embracing these strategies and best practices, healthcare systems and professionals can harness the potential of AI and robotics, ensuring responsible and ethical integration that benefits patients while upholding the highest ethical standards.},
author = {Elendu, Chukwuka and Amaechi, Dependable C. and Elendu, Tochi C. and Jingwa, Klein A. and Okoye, Osinachi K. and {John Okah}, Minichimso and Ladele, John A. and Farah, Abdirahman H. and Alimi, Hameed A.},
doi = {10.1097/MD.0000000000036671},
issn = {0025-7974},
journal = {Medicine},
month = {dec},
number = {50},
pages = {e36671},
title = {{Ethical implications of AI and robotics in healthcare: A review}},
volume = {102},
year = {2023}
}
@article{Pflanzer2023,
abstract = {Ethical considerations are the fabric of society, and they foster cooperation, help, and sacrifice for the greater good. Advances in AI create a greater need to examine ethical considerations involving the development and implementation of such systems. Integrating ethics into artificial intelligence-based programs is crucial for preventing negative outcomes, such as privacy breaches and biased decision making. Human–AI teaming (HAIT) presents additional challenges, as the ethical principles and moral theories that provide justification for them are not yet computable by machines. To that effect, models of human judgments and decision making, such as the agent-deed-consequence (ADC) model, will be crucial to inform the ethical guidance functions in AI team mates and to clarify how and why humans (dis)trust machines. The current paper will examine the ADC model as it is applied to the context of HAIT, and the challenges associated with the use of human-centric ethical considerations when applied to an AI context.},
author = {Pflanzer, Michael and Traylor, Zachary and Lyons, Joseph B. and Dubljevi{\'{c}}, Veljko and Nam, Chang S.},
doi = {10.1007/s43681-022-00214-z},
issn = {2730-5953},
journal = {AI and Ethics},
month = {aug},
number = {3},
pages = {917--935},
title = {{Ethics in human–AI teaming: principles and perspectives}},
volume = {3},
year = {2023}
}
@article{Gonzales2023,
abstract = {The application of artificial intelligence (AI) across firms and industries warrants a line of research focused on determining its overall effect on economic variables. As a general-purpose technology (GPT), for example, AI helps in the production, marketing, and customer acquisition of firms, increasing their productivity and consumer reach. Aside from these, other effects of AI include enhanced quality of services, improved work accuracy and efficiency, and increased customer satisfaction. Hence, this study aims to gauge the impact of AI on the economy, specifically on long-run economic growth. This study conjectures a positive relationship between AI and economic growth. To test this hypothesis, this study makes use of a panel dataset of countries from 1970 to 2019, and the number of AI patents as a measure of AI. A text search query is performed to distinguish AI patents from other types of innovations in a public database. Employing fixed effects and generalized method of moments (GMM) estimation, this paper finds a positive relationship between AI and economic growth, which is higher than the effect of the total population of patents on growth. Furthermore, other results indicate that AI's influence on growth is more robust among advanced economies, and more evident towards the latter periods of the dataset.},
author = {Gonzales, Julius Tan},
doi = {10.1186/s40008-023-00307-w},
issn = {2193-2409},
journal = {Journal of Economic Structures},
number = {1},
pages = {13},
title = {{Implications of AI innovation on economic growth: a panel data study}},
url = {https://doi.org/10.1186/s40008-023-00307-w},
volume = {12},
year = {2023}
}
@article{Soori2024,
author = {Soori, Mohsen and Jough, Fooad Karimi Ghaleh and Dastres, Roza and Arezoo, Behrooz},
doi = {10.1016/j.ject.2024.08.005},
issn = {29499488},
journal = {Journal of Economy and Technology},
month = {aug},
title = {{AI-Based Decision Support Systems in Industry 4.0, A Review}},
url = {https://linkinghub.elsevier.com/retrieve/pii/S2949948824000374},
year = {2024}
}
@book{lok2019artificial,
author = {Lok, J C},
isbn = {9781794091146},
publisher = {Amazon Digital Services LLC - KDP Print US},
title = {{Artificial Intelligence Brings Positive Or Negative Impaction to Influence Human Job Nature}},
url = {https://books.google.co.id/books?id=UbowwQEACAAJ},
year = {2019}
}
@article{Ajithkumar2023ImpactOA,
author = {Ajithkumar, Abhijith and David, Akhil and Jacob, Aryan and Alex, Alen and CMI, F R Akhil Thomas},
journal = {international journal of engineering technology and management sciences},
title = {{Impact of AI on Employment and Job Opportunities}},
url = {https://api.semanticscholar.org/CorpusID:261594339},
year = {2023}
}
@article{Shen2024,
abstract = {Sustainable Development Goal 8 proposes the promotion of full and productive employment for all. Intelligent production factors, such as robots, the Internet of Things, and extensive data analysis, are reshaping the dynamics of labour supply and demand. In China, which is a developing country with a large population and labour force, analysing the impact of artificial intelligence technology on the labour market is of particular importance. Based on panel data from 30 provinces in China from 2006 to 2020, a two-way fixed-effect model and the two-stage least squares method are used to analyse the impact of AI on employment and to assess its heterogeneity. The introduction and installation of artificial intelligence technology as represented by industrial robots in Chinese enterprises has increased the number of jobs. The results of some mechanism studies show that the increase of labour productivity, the deepening of capital and the refinement of the division of labour that has been introduced into industrial enterprises through the introduction of robotics have successfully mitigated the damaging impact of the adoption of robot technology on employment. Rather than the traditional perceptions of robotics crowding out labour jobs, the overall impact on the labour market has exerted a promotional effect. The positive effect of artificial intelligence on employment exhibits an inevitable heterogeneity, and it serves to relatively improves the job share of women and workers in labour-intensive industries. Mechanism research has shown that virtual agglomeration, which evolved from traditional industrial agglomeration in the era of the digital economy, is an important channel for increasing employment. The findings of this study contribute to the understanding of the impact of modern digital technologies on the well-being of people in developing countries. To give full play to the positive role of artificial intelligence technology in employment, we should improve the social security system, accelerate the process of developing high-end domestic robots and deepen the reform of the education and training system.},
author = {Shen, Yang and Zhang, Xiuwu},
doi = {10.1057/s41599-024-02647-9},
issn = {2662-9992},
journal = {Humanities and Social Sciences Communications},
number = {1},
pages = {122},
title = {{The impact of artificial intelligence on employment: the role of virtual agglomeration}},
volume = {11},
year = {2024}
}
@article{Guimaraes2022,
author = {Guimar{\~{a}}es, Lu{\'{i}}s and {Mazeda Gil}, Pedro},
doi = {10.1016/j.jedc.2022.104538},
issn = {01651889},
journal = {Journal of Economic Dynamics and Control},
month = {nov},
pages = {104538},
title = {{Looking ahead at the effects of automation in an economy with matching frictions}},
volume = {144},
year = {2022}
}
@article{Damioli2024,
author = {Damioli, Giacomo and {Van Roy}, Vincent and V{\'{e}}rtesy, D{\'{a}}niel and Vivarelli, Marco},
doi = {10.1016/j.techfore.2024.123249},
issn = {00401625},
journal = {Technological Forecasting and Social Change},
month = {apr},
pages = {123249},
title = {{Drivers of employment dynamics of AI innovators}},
volume = {201},
year = {2024}
}
@book{von2022robotics,
author = {von Braun, J and Archer, M S and Reichberg, G M and Sorondo, M S},
isbn = {9783030541750},
publisher = {Springer International Publishing},
title = {{Robotics, AI, and Humanity: Science, Ethics, and Policy}},
year = {2022}
}
@book{Corrales2018,
address = {Singapore},
doi = {10.1007/978-981-13-2874-9},
editor = {Corrales, Marcelo and Fenwick, Mark and Forg{\'{o}}, Nikolaus},
isbn = {978-981-13-2873-2},
publisher = {Springer Singapore},
series = {Perspectives in Law, Business and Innovation},
title = {{Robotics, AI and the Future of Law}},
year = {2018}
}
@article{Liu2024ServiceCA,
author = {Liu, Zhenzhen},
journal = {Academic Journal of Computing \& Information Science},
title = {{Service Computing and Artificial Intelligence: Technological Integration and Application Prospects}},
url = {https://api.semanticscholar.org/CorpusID:270272908},
year = {2024}
}
@book{de2017artificial,
author = {{De Spiegeleire}, S and Maas, M and Sweijs, T},
isbn = {9789492102546},
publisher = {The Hague Centre for Strategic Studies},
title = {{Artificial Intelligence and the Future of Defense: Strategic Implications For Small- and Medium-Sized Force Providers}},
url = {https://books.google.co.id/books?id=xZUnDwAAQBAJ},
year = {2017}
}
@article{Zhang2024TowardSA,
author = {Zhang, Jiyun and Hauch, Jens A and Brabec, Christoph Josef},
journal = {Accounts of Chemical Research},
pages = {1434--1445},
title = {{Toward Self-Driven Autonomous Material and Device Acceleration Platforms (AMADAP) for Emerging Photovoltaics Technologies}},
url = {https://api.semanticscholar.org/CorpusID:269329095},
volume = {57},
year = {2024}
}
@article{Wu2023,
abstract = {Following the development of big data, the use of microexpression technology has become increasingly popular. The application of microexpressions has expanded beyond medical treatment to include scientific case investigations. Because microexpressions are characterized by short duration and low intensity, training humans to recognize their yields poor performance results. Automatically recognizing microexpressions by using machine learning techniques can provide more effective results and save time and resources. In the real world, to avoid judicial punishment, people lie and conceal the truth for a variety of reasons. In this study, our primary objective was to develop a system for real-time microexpression recognition. We used FaceReader as the retrieval system and integrated the data with an application programming interface to provide recognition results as objective references in real-time. Using an experimental analysis, we also attempted to determine the optimal system configuration conditions. In conclusion, the use of artificial intelligence is expected to enhance the efficiency of investigations. {\textcopyright} 2023, Intelektual Pustaka Media Utama. All rights reserved.},
address = {Department Forensic Science Division, Investigation Bureau, Ministry of Justice, Taipei, Taiwan},
annote = {Export Date: 21 September 2024; Cited By: 1; Correspondence Address: Y.-C. Wu; Forensic Science Division, Investigation Bureau, Ministry of Justice, New Taipei City, No. 74, Zhonghua Rd., Xindian Dist, 231, Taiwan; email: shintenwu@gmail.com},
author = {Wu, Y.-C. and Liu, Y.-C. and Tsao, C and Huang, R.-Y.},
doi = {10.11591/ijra.v12i1.pp20-28},
issn = {20894856 (ISSN)},
journal = {IAES International Journal of Robotics and Automation},
keywords = {Artificial intelligence,Deception detection,Microexpression,Real-time recognition},
language = {English},
number = {1},
pages = {20--28},
publisher = {Intelektual Pustaka Media Utama},
title = {{Microexpression recognition robot}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85184162941&doi=10.11591%2Fijra.v12i1.pp20-28&partnerID=40&md5=91d799cae94a898aba6589be9d0617ce},
volume = {12},
year = {2023}
}
@article{Huong2024,
abstract = {The article shows how to build and identify intelligent automatic control problems for mobile robots in a flat surface environment at the workplace, with known and unknown obstacles. Research and develop programming and control methods as an operating system for mobile robots robot operating system (ROS). Update map data information, in the operating environment, robot position control process, obstacle overcoming process simultaneous positioning and mapping (SLAM). From there, we aim to calculate and determine the robot's motion trajectory to get a smart path. The positioning trajectory calculation system robots. The authors use actor-critic (AC) algorithm to research and develop control. Research results in simulations, in Gazebo environment and test runs on real mobile robots have shown high-quality practical performance of automatic navigation and control while using this algorithm. {\textcopyright} 2024, Institute of Advanced Engineering and Science. All rights reserved.},
address = {University of Economics, Technology for Industries, Hanoi, Viet Nam},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: P.T.T. Ha; University of Economics, Technology for Industries, Hanoi, Viet Nam; email: pttha@uneti.edu.vn},
author = {Huong, T T and Ha, P T T},
doi = {10.11591/eei.v13i5.7818},
issn = {20893191 (ISSN)},
journal = {Bulletin of Electrical Engineering and Informatics},
keywords = {Actor-critic algorithm,Artificial intelligence,Autonomous navigation,Intelligent control,Mobile robot},
language = {English},
number = {5},
pages = {3737--3745},
publisher = {Institute of Advanced Engineering and Science},
title = {{Controlling mobile robot in flat environment taking into account nonlinear factors applying artificial intelligence}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200713215&doi=10.11591%2Feei.v13i5.7818&partnerID=40&md5=dd6300cda4ee9c0c35c71c937c7b97d1},
volume = {13},
year = {2024}
}
@article{Abdul-Khalil2023,
abstract = {The advancement of autonomous mobile robots (AMR) is vastly being discovered and applied to several industries. AMR contributes to the development of artificial intelligence (AI), which focuses on the growth of human-interaction systems. However, it is safe to understand that mobile robots work closely in real-time and under changing surroundings. Similarly, some limitations may affect the efficiency of mobile robots. Thus, to improve the system's efficiency and accuracy, mobile robots should adopt the ability to detect incoming obstacles accurately. This paper presents the findings of a brief technology review aimed at identifying the current state of the art and future needs for AMR in object detection. This review paper is presented in the form of a narrative-literature review. Review articles were collected from 2015 until 2022 from journals or conference papers from well-known sources like IEEE Xplore, Science Direct, Scopus, and Web of Science (WOS). The analysis of the articles was discussed in four main topics, AI, object detection, AMR, and deep learning. {\textcopyright} 2023, Institute of Advanced Engineering and Science. All rights reserved.},
address = {School of Computing Sciences, College of Computing, Informatics and Media, Universiti Teknologi MARA, Selangor, Malaysia},
annote = {Export Date: 21 September 2024; Cited By: 3; Correspondence Address: S. Abdul-Rahman; Research Initiative Group of Intelligent Systems, College of Computing, Informatics and Media Universiti Teknologi MARA, Selangor, Malaysia; email: shuzlina@uitm.edu.my},
author = {Abdul-Khalil, S and Abdul-Rahman, S and Mutalib, S and Kamarudin, S I and Kamaruddin, S S},
doi = {10.11591/ijai.v12.i3.pp1033-1043},
issn = {20894872 (ISSN)},
journal = {IAES International Journal of Artificial Intelligence},
keywords = {Artificial intelligence,Autonomous mobile robot,Deep learning,Object detection},
language = {English},
number = {3},
pages = {1033--1043},
publisher = {Institute of Advanced Engineering and Science},
title = {{A review on object detection for autonomous mobile robot}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85152909460&doi=10.11591%2Fijai.v12.i3.pp1033-1043&partnerID=40&md5=61c6009c173708d2ad3df5c1f7230f92},
volume = {12},
year = {2023}
}
@article{Hamed2022,
abstract = {The cooperation and coordination in multi-robot systems is a popular topic in the field of robotics and artificial intelligence, thanks to its important role in solving problems that are better solved by several robots compared to a single robot. Cooperative hunting is one of the important problems that exist in many areas such as military and industry, requiring cooperation between robots in order to accomplish the hunting process effectively. This paper proposed a cooperative hunting strategy for a multi-robot system based on wolf swarm algorithm (WSA) and artificial potential field (APF) in order to hunt by several robots a dynamic target whose behavior is unexpected. The formation of the robots within the multi-robot system contains three types of roles: the leader, the follower, and the antagonist. Each role is characterized by a different cognitive behavior. The robots arrive at the hunting point accurately and rapidly while avoiding static and dynamic obstacles through the artificial potential field algorithm to hunt the moving target. Simulation results are given in this paper to demonstrate the validity and the effectiveness of the proposed strategy. {\textcopyright} 2022 Institute of Advanced Engineering and Science. All rights reserved.},
address = {Complex Cyber Physical Systems Laboratory, National Higher School of Arts and Crafts (ENSAM), University of Hassan II, Casablanca, Morocco},
annote = {Export Date: 21 September 2024; Cited By: 12; Correspondence Address: O. Hamed; Complex Cyber Physical Systems Laboratory, National Higher School of Arts and Crafts (ENSAM), University of Hassan II, Casablanca, Morocco; email: oussamahamed11@gmail.com},
author = {Hamed, O and Hamlich, M and Ennaji, M},
doi = {10.11591/ijeecs.v25.i1.pp159-171},
issn = {25024752 (ISSN)},
journal = {Indonesian Journal of Electrical Engineering and Computer Science},
keywords = {Cooperative systems Mobile robots Multi‐robot systems Optimization Path planning},
language = {English},
number = {1},
pages = {159--171},
publisher = {Institute of Advanced Engineering and Science},
title = {{Hunting strategy for multi-robot based on wolf swarm algorithm and artificial potential field}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122018266&doi=10.11591%2Fijeecs.v25.i1.pp159-171&partnerID=40&md5=6ea32fcb4da82d258ffb515f3a1adc5d},
volume = {25},
year = {2022}
}
@article{Owoeye2024,
abstract = {Quadruped home surveillance robots represent a promising advancement in home security and automation. This innovative robotic system is equipped with four-legged locomotion, allowing it to traverse various terrains within a household environment. The robot's primary function is surveillance, and it is equipped with high-definition cameras, motion sensors, and object recognition software. These sensors enable the robot to detect intruders, track their movements, and capture real-time video footage for remote monitoring. The quadruped robot's compact and agile design allows it to navigate through narrow spaces and overcome obstacles, ensuring it can patrol every corner of a home effectively. Its autonomous operation is made possible through advanced artificial intelligence algorithms, ensuring that it can detect anomalies and respond to security threats promptly. Furthermore, integrating the robot with smart home systems enables seamless communication with other connected devices and allows homeowners to control and monitor it remotely. {\textcopyright} 2024, Intelektual Pustaka Media Utama. All rights reserved.},
address = {Department of Mechatronics Engineering, Federal University of Agriculture, Abeokuta, Nigeria},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: S.O. Owoeye; Department of Mechatronics Engineering, Federal University of Agriculture, Abeokuta, Nigeria; email: owoeyeso@funaab.edu.ng},
author = {Owoeye, S O and Durodola, F and Adeniyi, P O and Abdullahi, I T and Hector, A B},
doi = {10.11591/ijra.v13i2.pp233-246},
issn = {20894856 (ISSN)},
journal = {IAES International Journal of Robotics and Automation},
keywords = {Automation,ESP32,Home security,Quadruped,Surveillance},
language = {English},
number = {2},
pages = {233--246},
publisher = {Intelektual Pustaka Media Utama},
title = {{Design and development of a quadruped home surveillance robot}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202945117&doi=10.11591%2Fijra.v13i2.pp233-246&partnerID=40&md5=2fed7f8c138c09b5f1ca9ce32228bb70},
volume = {13},
year = {2024}
}
@article{Sanabria2023,
abstract = {Given the recent events worldwide due to viral diseases that affect human health, automatic monitoring systems are one of the strong points of research that has gained strength, where the detection of biohazardous waste of a sanitary nature is highlighted related to viral diseases stands out. It is essential in this field to generate developments aimed at saving lives, where robotic systems can operate as assistants in various fields. In this work an artificial intelligence algorithm based on two stages is presented, one is the recognition of paper debris using a ResNet-50, chosen for its object localization capacity, and the other is a fuzzy inference system for the generation of alarm states due to biological risk by such debris, where fuzzy logic helps to establish a model for a non-predictive system as the one exposed. A biohazard detection algorithm for paper waste is described, oriented to operate on an assistive robot in a residential environment. The training parameters of the network, which achieve 100% accuracy with confidence levels between 82% for very small waste and 100% in direct view, are presented. Timing cycles are established for validation of the exposure time of the waste, where through the fuzzy system, risk alarms are generated, which allows establishing a system with an average reliability of 98%. {\textcopyright} 2023 Institute of Advanced Engineering and Science. All rights reserved.},
address = {Department of Mechatronic Engineering, Faculty of Engineering, Universidad Militar Nueva Granada, Bogota, Colombia},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: R. Jimenez-Moreno; Mechatronics Engineering, Faculty of Engineering, Universidad Militar Nueva, Bogot{\'{a}}, Granada Carrera 11 #, D.C., 101-80, Colombia; email: robinson.jimenez@unimilitar.edu.co},
author = {Sanabria, J S and Jimenez-Moreno, R and Baquero, J E M},
doi = {10.11591/ijece.v13i1.pp249-257},
issn = {20888708 (ISSN)},
journal = {International Journal of Electrical and Computer Engineering},
keywords = {Biological risk,Convolutional network,Deep learning,Fuzzy system,Paper detection,ResNet50},
language = {English},
number = {1},
pages = {249--257},
publisher = {Institute of Advanced Engineering and Science},
title = {{Paper biological risk detection through deep learning and fuzzy system}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143851913&doi=10.11591%2Fijece.v13i1.pp249-257&partnerID=40&md5=d71a9ec7c7510e90533c903105eabf0b},
volume = {13},
year = {2023}
}
@article{Kadafi2024,
abstract = {Artificial intelligence (AI), consisting of models and algorithms capable of concluding data to produce future predictions, has revolutionary potential in various aspects of human life. One application is an Alzheimer's disease (AD) prediction chat robot (chatbot). Only now has a method provided very accurate findings and recommendations regarding the early detection of AD using magnetic resonance imaging (MRI). Therefore, this research aims to measure AD prediction performance in four stage classes, namely very mild demented, mild demented, moderate demented, and non-demented, using brain MRI images trained in the convolutional neural network (CNN)support vector machine (SVM) model. The research involved nine combination schemes of dataset proportions and preprocessing in the CNN-SVM model. Evaluation shows that scheme 1 produces the highest accuracy, precision, recall, and F1-score, namely 98%, 99%, 98%, and 98%. The chatbot, trained using CNN, achieved 99.34% accuracy in question responses, and was then combined with AD prediction models for improved accuracy. The test results show that the chatbot functionality runs well for each transition, with a functionality score reaching 99.64 points out of 100.00. This success shows excellent potential for early detection of AD. This research brings new hope in preventing AD through AI, with potential positive impacts on human health and quality of life. {\textcopyright} 2024 Institute of Advanced Engineering and Science. All rights reserved.},
address = {Department of Engineering, Faculty of Advanced and Multidisciplinary Technology, Airlangga University, Surabaya, Indonesia},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: S.D. Astuti; Department of Physics, Faculty of Science and Technology, Airlangga University Surabaya, Indonesia; email: suryanidyah@fst.unair.ac.id},
author = {Kadafi, M S and Yaqubi, A K and Astuti, S D},
doi = {10.11591/ijeecs.v36.i1.pp64-73},
issn = {25024752 (ISSN)},
journal = {Indonesian Journal of Electrical Engineering and Computer Science},
keywords = {Alzheimer disease,Chat robot,Convolutional neural network,Magnetic resonance imaging,Support vector machine},
language = {English},
number = {1},
pages = {64--73},
publisher = {Institute of Advanced Engineering and Science},
title = {{Alzheimer's prediction via CNN-SVM on chatbot platform with MRI}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200208231&doi=10.11591%2Fijeecs.v36.i1.pp64-73&partnerID=40&md5=96c37b8b132b7f90331fb17eda6a14cc},
volume = {36},
year = {2024}
}
@article{Yahya2024,
abstract = {The integration of artificial intelligence (AI)-based robot therapy (AIBRT) has become prominent in addressing the needs of children with disabilities, including autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), learning disabilities, and speech delays. However, questions arise regarding the effectiveness of different AI techniques in enhancing therapy for children with specific needs. This review explores current literature on AIBRT for children with disabilities, aiming to understand the efficacy and potential of various AI techniques in improving their therapy. This paper presents a comprehensive search of research articles published from 2019 to September 2023. 39 articles focusing on AI-based robot platforms, the employed treatment or therapy methods, assessment procedures during therapy, and the variables or parameters used to measure intervention effectiveness have been discussed in detail. These AI-based robot platforms have been utilized to engage individuals diagnosed with ASD, offering therapeutic interventions and assessments. In conclusion, the integration of AI and robotics in therapy shows promise for enhancing the development and quality of life for children with disabilities. The findings of this review have implications for therapists, practitioners, and researchers interested in incorporating AI applications into therapy practices. This integration can lead to improved therapy outcomes, optimized children's development, and enhanced quality of life. {\textcopyright} 2024 Institute of Advanced Engineering and Science. All rights reserved.},
address = {School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, Shah Alam, Malaysia},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: R. Jailani; School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA Shah Alam, Selangor, Malaysia; email: rozita@ieee.org},
author = {Yahya, R and Jailani, R and Hanapiah, F A and Zakaria, N K},
doi = {10.11591/ijeecs.v33.i3.pp1855-1865},
issn = {25024752 (ISSN)},
journal = {Indonesian Journal of Electrical Engineering and Computer Science},
keywords = {Artificial intelligence,Children with disablities,Precision health,Robot therapy},
language = {English},
number = {3},
pages = {1855--1865},
publisher = {Institute of Advanced Engineering and Science},
title = {{A scoping review of artificial intelligence-based robot therapy for children with disabilities}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185572862&doi=10.11591%2Fijeecs.v33.i3.pp1855-1865&partnerID=40&md5=0d670083f1a735051cdf8daad172fc56},
volume = {33},
year = {2024}
}
@article{Nguyen2023,
abstract = {The goal of this study is to investigate the potential effects that artificial intelligence (AI) could have on education. The narrative and framework for investigating AI that emerged from the preliminary research served as the basis for the study's emphasis, which was narrowed down to the use of AI and its effects on administration, instruction, and student learning. According to the findings, artificial intelligence has seen widespread adoption and use in education, particularly by educational institutions and in various contexts and applications. The development of AI began with computers and technologies related to computers; it then progressed to web-based and online intelligent education systems; and finally, it applied embedded computer systems in conjunction with other technologies, humanoid robots, and web-based chatbots to execute instructor tasks and functions either independently or in partnership with instructors. By utilizing these platforms, educators have been able to accomplish a variety of administrative tasks. In addition, because the systems rely on machine learning and flexibility, the curriculum and content have been modified to match the needs of students. This has led to improved learning outcomes in the form of higher uptake and retention rates. {\textcopyright} 2023, Institute of Advanced Engineering and Science. All rights reserved.},
address = {Faculty of International Training, Thai Nguyen University of Technology, Thai Nguyen City, Viet Nam},
annote = {Export Date: 21 September 2024; Cited By: 3; Correspondence Address: H.T. Tran; Center of Electrical Engineering, Duy Tan University, Danang, 550000, Viet Nam; email: tranthuanhoang@duytan.edu.vn},
author = {Nguyen, T T K and Nguyen, M T and Tran, H T},
doi = {10.11591/ijere.v12i4.26623},
issn = {22528822 (ISSN)},
journal = {International Journal of Evaluation and Research in Education},
keywords = {Artificial intelligence,Data mining,Deep learning,Education,Educational management,Learning analytics,Machine learning},
language = {English},
number = {4},
pages = {2387--2400},
publisher = {Institute of Advanced Engineering and Science},
title = {{Artificial intelligent based teaching and learning approaches: A comprehensive review}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174944516&doi=10.11591%2Fijere.v12i4.26623&partnerID=40&md5=2a87780da21c83164b6750c23128706a},
volume = {12},
year = {2023}
}
@article{FredyH.Martinez2020,
abstract = {This paper proposes a strategy for the coordination of a swarm of robots in an unknown environment. The basic idea is to achieve the autonomous movement of the group from an initial region to a target region avoiding obstacles. We use a behavior model similar to bacterial Quorum Sensing (QS) as a technique for the coordination of robots. This behavior has been described as a key element in the interaction between bacteria, and we use it as a basic tool for local interaction, both between the robot and between the robot and the environment. The movement of the swarm of robots, or multi-agent robotic system, is shown as an emerging behavior resulting from the interaction of agents (in the context of artificial intelligence) from basic rules of behavior. The proposed strategy was successfully evaluated by simulation on a set of robots. {\textcopyright} 2020, Institute of Advanced Engineering and Science. All rights reserved.},
address = {Universidad Distrital Francisco Jos{\'{e}} de Caldas, Facultad Tecnol{\'{o}}gica, Colombia},
annote = {Export Date: 21 September 2024; Cited By: 5; Correspondence Address: S. Fredy H. Mart{\'{i}}nez; Universidad Distrital Francisco Jos{\'{e}} de Caldas, Facultad Tecnol{\'{o}}gica, Bogot{\'{a}}, Carrera 7 #40-53, D.C., Colombia; email: fhmartinezs@udistrital.edu.co},
author = {{Fredy H. Mart{\'{i}}nez}, S and {Fernando Mart{\'{i}}nez}, S and {Holman Montiel}, A},
doi = {10.11591/eei.v9i1.1538},
issn = {20893191 (ISSN)},
journal = {Bulletin of Electrical Engineering and Informatics},
keywords = {Bacteria,Path planning,Quorum sensing,Robots,Swarm},
language = {English},
number = {1},
pages = {67--74},
publisher = {Institute of Advanced Engineering and Science},
title = {{Bacterial quorum sensing applied to the coordination of autonomous robot swarms}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083263377&doi=10.11591%2Feei.v9i1.1538&partnerID=40&md5=8ccd98f7c6d17205c4a0ace60bad56f5},
volume = {9},
year = {2020}
}
@article{Al-Ansi2024,
abstract = {The next generation of wireless networks, 6G is being designed with data-intensive applications. One of the key technologies that will enable 6G is blockchain technology. The emergence of blockchain technology and 6G networks has revolutionized service migration. Service migration in 6G networks is a complex process that requires the integration of new technologies, such as artificial intelligence (AI), edge computing, and network slicing. Motivated by these facts, this comprehensive review includes an overview of blockchain and service migration integration in 6G. First, state of art, development frame work and related works were introduced. Then, we used content analysis by WordStat software and bibliographic analysis by VOSviewer to analysis the current status of service migration and blockchain integration in 6G networks. Next, patterns and characteristics, benefits and challenges and potential cases were reviewed. Then, we proposed an architectural blockchain-based model including decentralized architecture, edge computing, network slicing, software-defined networking, and 5G-6G interworking in 6G. Finally, we described potential application service migration-based in 6G networks including digital twin (DT), holograms, robot avatar, high density internet of things (IoT), AR and VR in 6G and collected open research and future directions of service migration and blockchain. {\textcopyright} 2024 Institute of Advanced Engineering and Science. All rights reserved.},
address = {Department of Telecommunication Networks and Data Transmission, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, Saint Petersburg, Russian Federation},
annote = {Export Date: 21 September 2024; Cited By: 1; Correspondence Address: A.M. Al-Ansi; Department of Management, College of Commerce and Business Administration, Dhofar University, Salalah, Oman; email: aalansi@du.edu.om},
author = {Al-Ansi, A and Al-Ansi, A M and Muthanna, A and Koucheryavy, A},
doi = {10.11591/ijeecs.v34.i3.pp1654-1664},
issn = {25024752 (ISSN)},
journal = {Indonesian Journal of Electrical Engineering and Computer Science},
keywords = {6G communication network,Artificial intelligence,Blockchain,Comprehensive review,Service migration},
language = {English},
number = {3},
pages = {1654--1664},
publisher = {Institute of Advanced Engineering and Science},
title = {{Blockchain technology integration in service migration to 6G communication networks: a comprehensive review}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85191024311&doi=10.11591%2Fijeecs.v34.i3.pp1654-1664&partnerID=40&md5=72c684ed850702df992f7490c8e76391},
volume = {34},
year = {2024}
}
@article{Sutikno2023,
abstract = {Robotics has experienced significant growth and development over the past few decades, with the first industrial robots introduced in the 1950s. As technology advances, robotics has become more intelligent, smart, and flexible, with the introduction of artificial intelligence (AI) and machine learning (ML). Robots are now being integrated into various fields, including healthcare, agriculture, transportation, and space exploration. Robots are set to revolutionize our daily lives, transforming interactions and work processes as technology advances. Emerging trends in robotics, such as AI and ML, soft robotics, and swarm robotics, can transform industries and improve efficiency. The future of robotics and automation promises safer workplaces, improved healthcare, and enhanced environmental sustainability. Society must adapt to this changing landscape, requiring continuous learning and upskilling to remain relevant in the workforce. {\textcopyright} 2023, Intelektual Pustaka Media Utama. All rights reserved.},
address = {Master Program of Electrical Engineering, Faculty of Industrial Technology, Universitas Ahmad Dahlan, Yogyakarta, Indonesia},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: T. Sutikno; Faculty of Industrial Technology, Universitas Ahmad Dahlan, Yogyakarta, Ahmad Yani Street (South of Ring Road), Tamanan, 55166, Indonesia; email: tole@te.uad.ac.id},
author = {Sutikno, T},
doi = {10.11591/ijra.v12i4.pp405-411},
issn = {20894856 (ISSN)},
journal = {IAES International Journal of Robotics and Automation},
keywords = {Artificial intelligence,Automation,Environmental sustainability,Industrial robots,Machine learning,Robotics},
language = {English},
number = {4},
pages = {405--411},
publisher = {Intelektual Pustaka Media Utama},
title = {{An overview of emerging trends in robotics and automation}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189021288&doi=10.11591%2Fijra.v12i4.pp405-411&partnerID=40&md5=5137c8d0bf3063eae0e05b48022ffd4a},
volume = {12},
year = {2023}
}
@article{Beggar2023,
abstract = {Expert systems have been widely used in medicine to diagnose different diseases. However, these rule-based systems only explain why and how their outcomes are reached. The rules leading to those outcomes are also expressed in a machine language and confronted with the familiar problems of coverage and specificity. This fact prevents procuring expert systems with fully human-understandable explanations. Furthermore, early diagnosis involves a high degree of uncertainty and vagueness which constitutes another challenge to overcome in this study. This paper aims to design and develop a fuzzy explainable expert system for coronavirus disease-2019 (COVID-19) diagnosis that could be incorporated into medical robots. The proposed medical robotic application deduces the likelihood level of contracting COVID-19 from the entered symptoms, the personal information, and the patient's activities. The proposal integrates fuzzy logic to deal with uncertainty and vagueness in diagnosis. Besides, it adopts a hybrid explainable artificial intelligence (XAI) technique to provide different explanation forms. In particular, the textual explanations are generated as rules expressed in a natural language while avoiding coverage and specificity problems. Therefore, the proposal could help overwhelmed hospitals during the epidemic propagation and avoid contamination using a solution with a high level of explicability. {\textcopyright} 2023 Institute of Advanced Engineering and Science. All rights reserved.},
address = {Laboratory of Intelligence Machine, Faculty of Sciences, Techniques of Mohammedia, Hassan II University of Casablanca, Casablanca, Morocco},
annote = {Export Date: 21 September 2024; Cited By: 2; Correspondence Address: O.E. Beggar; Laboratory of Intelligence Machine, Faculty of Sciences, Techniques of Mohammedia, Hassan II University of Casablanca, Casablanca, Morocco; email: omar.elbeggar@fstm.ac.ma},
author = {Beggar, O E and Ramdani, M and Kissi, M},
doi = {10.11591/ijece.v13i6.pp6940-6951},
issn = {20888708 (ISSN)},
journal = {International Journal of Electrical and Computer Engineering},
keywords = {Coronavirus disease-2019,Diagnostic robot,Expert system,Explainable artificial,Fuzzy logic,intelligence},
language = {English},
number = {6},
pages = {6940--6951},
publisher = {Institute of Advanced Engineering and Science},
title = {{Design and development of a fuzzy explainable expert system for a diagnostic robot of COVID-19}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172186315&doi=10.11591%2Fijece.v13i6.pp6940-6951&partnerID=40&md5=2de142e6b6bf5033faf65e098a7f3ce7},
volume = {13},
year = {2023}
}
@article{Jebadurai2024,
abstract = {As decades go by, technology advances and everything around us becomes smarter, such as televisions, mobile phones, robots, and so on. Artificial intelligence (AI) is applied in these technologies where AI assists the computer in making judgments like humans, and this intelligence is artificially fed to the model. The self-driving technique is a developing technology. Autonomous driving has been a broad and fast-expanding technology over the last decade. This model is carried out using the tiny you only look once (YOLO) algorithm. YOLO is mainly used for object detection classification. Tiny YOLO model is explored for the traffic signal detection. ROBI FLOW dataset is used for object detection which contains 2000+ image data to train the tiny YOLO model for traffic signal detection in real time. This model gives an improved accuracy and lightweight implementation compared to other models. Tiny YOLO is fast and accurate model for real-time traffic signal detection. {\textcopyright} 2024, Intelektual Pustaka Media Utama. All rights reserved.},
address = {Division of Computer Science and Engineering, Karunya Institute of Technology and Science, Coimbatore, India},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: E. Veemaraj; Division of Data Science and Cyber Security, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India; email: ebenezerv@karunya.edu},
author = {Jebadurai, I J and Paulraj, G J L and Veemaraj, E and Sharance, R P and Keren, R and Karan, K},
doi = {10.11591/ijict.v13i2.pp285-296},
issn = {22528776 (ISSN)},
journal = {International Journal of Informatics and Communication Technology},
keywords = {Artificial intelligence,Autonomus vehicle,Deep learning,Object detection,Tiny YOLO},
language = {English},
number = {2},
pages = {285--296},
publisher = {Intelektual Pustaka Media Utama},
title = {{Efficient traffic signal detection with tiny YOLOv4: enhancing road safety through computer vision}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85202948299&doi=10.11591%2Fijict.v13i2.pp285-296&partnerID=40&md5=cc9ad265fa8f27fe23fb9b422e300773},
volume = {13},
year = {2024}
}
@article{Loukili2024,
abstract = {In order to enhance marketing efforts and improve the performance of marketing campaigns, the effectiveness of language generation models needs to be evaluated. This study examines the performance of large language models (LLMs), namely GPT-3.5, PaLM 2, and bidirectional encoder representations from transformers (BERT), in generating email subjects for advertising campaigns. By comparing their results, the authors evaluate the efficacy of these models in enhancing marketing efforts. The objective is to explore how LLMs contribute to creating compelling email subject lines and improving opening rates and campaign performance, which gives us an insight into the impact of these models in digital marketing. In this paper, the authors first go over the different types of language models and the differences between them, before giving an overview of the most popular ones that will be used in the study, such as GPT-3.5, PaLM 2, and BERT. This study assesses the relevance, engagement, and uniqueness of GPT-3.5, PaLM 2, and BERT by training and fine-tuning them on marketing texts. The findings provide insights into the major positive impact of artificial intelligence (AI) on digital marketing, enabling informed decision-making for AI-driven email marketing strategies. {\textcopyright} 2024 Institute of Advanced Engineering and Science. All rights reserved.},
address = {Data and Intelligent Systems Team FSTT, Abdelmalek Essaadi University, Tetouan, Morocco},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: S. Loukili; Data and Intelligent Systems Team FSTT, Abdelmalek Essaadi University, Tetouan, Morocco; email: soumaya.loukili1@etu.uae.ac.ma},
author = {Loukili, S and Fennan, A and Elaachak, L},
doi = {10.11591/ijece.v14i4.pp4655-4663},
issn = {20888708 (ISSN)},
journal = {International Journal of Electrical and Computer Engineering},
keywords = {Artificial intelligence,Deep learning,Digital marketing,GPT,Large language models},
language = {English},
number = {4},
pages = {4655--4663},
publisher = {Institute of Advanced Engineering and Science},
title = {{Email subjects generation with large language models: GPT-3.5, PaLM 2, and BERT}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195209396&doi=10.11591%2Fijece.v14i4.pp4655-4663&partnerID=40&md5=060c5467481cf69b19bb877762c35611},
volume = {14},
year = {2024}
}
@article{Roxas2024,
abstract = {This paper conducted a systematic review of Scopus-indexed publications on large language models (LLMs) and natural language processing (NLP) extracted in October 2023 to address the dearth of literature on their opportunities and challenges. Through bibliometric analysis, from the 1,600 relevant documents, the study explored research productivity, revealing both opportunities and challenges spanning research and real-world applications in education, medicine, and health care, citations, and keyword co-occurrence networks. Results highlighted distribution patterns and dominant players like Google LLC and Stanford University. Opportunities such as technological development in generative artificial intelligence (AI), were contrasted with challenges such as biases and ethical concerns. The intellectual structure analysis revealed prominent application areas in health and education and also emphasized issues such as AI divide and human-AI partnership. Improvement on the technology performance of LLM and NLP remains to be a challenge. Recommendations include further exploration of open research problems and bibliometric studies using other research databases given the research bias towards Scopus-indexed English publications. {\textcopyright} 2024 Institute of Advanced Engineering and Science. All rights reserved.},
address = {Institute of Computer Science, College of Arts and Sciences, University of the Philippines Los Ba{\~{n}}os, Los Ba{\~{n}}os, Philippines},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: R.E.O. Roxas; Institute of Computer Science, College of Arts and Sciences, University of the Philippines Los Ba{\~{n}}os College, Laguna, Philippines; email: roroxas2@up.edu.ph},
author = {Roxas, R E O and Recario, R N C},
doi = {10.11591/ijeecs.v36.i1.pp252-263},
issn = {25024752 (ISSN)},
journal = {Indonesian Journal of Electrical Engineering and Computer Science},
keywords = {Artificial intelligence,Bibliometrics,Large language models,Natural language processing,Opportunities,challenges},
language = {English},
number = {1},
pages = {252--263},
publisher = {Institute of Advanced Engineering and Science},
title = {{Scientific landscape on opportunities and challenges of large language models and natural language processing}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85199862427&doi=10.11591%2Fijeecs.v36.i1.pp252-263&partnerID=40&md5=9c55255f4c543ba86693dbdad0d26467},
volume = {36},
year = {2024}
}
@article{Riftiarrasyid2024,
abstract = {Increasing need for food resources, State of Indonesia to strive to maximize the output of food production. Not only in agriculture but also aquaculture results are also trying to be improved. This is also supported by the increase of Indonesia's national fish consumption rate from 50.69 Kg per capita in 2018 to 55.37 Kg per capita in 2021. Recent aquaculture research only explored topics about monitoring the cultivation environment. But there have been no studies exploring how bad the impact of weather on the process of farming. Hence, this study aims to measure the influence of weather on freshwater aquaculture pond water quality and analyze its impact on fish growth namely Oreochromis Sp., using pH sensors and dissolved oxygen (DO). Then a weather simulation was carried out based on Indonesia's tropical climate, which majorly consists of sunny and rainy weather. The experimental results indicate the instability of the pH value during the rainy period. DO values tend to decrease at the end of periods of sunny weather. Moreover, fish growth analysis showed that there was a decrease in food conversion ratio (FCR) by 0.956, specific growth rate (SGR) by 2.13% and survival rate (SR) by 5.715% during rainy weather. {\textcopyright} 2024 Institute of Advanced Engineering and Science. All rights reserved.},
address = {Department of Computer Science, BINUS Graduate Program, Bina Nusantara University, Jakarta, Indonesia},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: M.F. Riftiarrasyid; Department of Computer Science, BINUS Graduate Program, Bina Nusantara University, Jakarta, Indonesia; email: mohammad.riftiarrasyid@binus.ac.id},
author = {Riftiarrasyid, M F and Soewito, B},
doi = {10.11591/ijeecs.v35.i3.pp1426-1436},
issn = {25024752 (ISSN)},
journal = {Indonesian Journal of Electrical Engineering and Computer Science},
keywords = {Aquaculture,Fish growth,Internet of things,Nile tilapia,Water quality parameter,Weather},
language = {English},
number = {3},
pages = {1426--1436},
publisher = {Institute of Advanced Engineering and Science},
title = {{Monitoring water quality parameters impacted by Indonesia's weather using internet of things}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197921885&doi=10.11591%2Fijeecs.v35.i3.pp1426-1436&partnerID=40&md5=d8d2eb7cb1ac2581969b9db0aafc9e0b},
volume = {35},
year = {2024}
}
@article{Bouhlali2024,
abstract = {The field of chatbots has witnessed a remarkable evolution in recent years, marked by a transition from simplistic rule-based structures to sophisticated systems employing advanced natural language processing (NLP) techniques. While most languages benefit from NLP support, the majority of chatbot research and development has been conducted in English, leaving a notable scarcity of comparable works in Arabic. This scarcity is attributed to the myriad challenges posed by the linguistically intricate nature of Arabic, encompassing orthographic variations and diverse dialects. This study systematically reviews articles that represent implementations of Arabic chatbots, revealing a discernible shift from rule-based frameworks to the predominant adoption of machine learning (ML) and deep learning (DL) methods. The results highlight the dynamic trajectory of chatbot technology, with a notable emphasis on the pivotal role of DL, as evidenced by a significant peak in 2023. Looking forward, the study anticipates a more sophisticated future for chatbot development, driven by ongoing advancements in artificial intelligence (AI) and NLP, offering valuable insights into the current state of Arabic chatbot research and laying the foundation for continued exploration in this evolving and dynamic field. {\textcopyright} 2024 Institute of Advanced Engineering and Science. All rights reserved.},
address = {Laboratory of Information Security Intelligent Systems and application (ISISA), Faculty of Sciences, Abdelmalek Essaadi University, Tetouan, Morocco},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: A. Bouhlali; Laboratoy of Information Security Intelligent Systems and application (ISISA), Faculty of Sciences, Abdelmalek Essaadi University, Tetouan, 93030, Morocco; email: abdelmounaim.bouhlali@etu.uae.ac.ma},
author = {Bouhlali, A and Elmansouri, A and {El Mhouti}, A and Fahim, M and Boudaa, T},
doi = {10.11591/ijeecs.v35.i3.pp1751-1764},
issn = {25024752 (ISSN)},
journal = {Indonesian Journal of Electrical Engineering and Computer Science},
keywords = {AIML,Arabic NLP,Arabic chatbot,Deep learning,Pattern matching,Question answering systems},
language = {English},
number = {3},
pages = {1751--1764},
publisher = {Institute of Advanced Engineering and Science},
title = {{Reviewing approaches employed in Arabic chatbots}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197849548&doi=10.11591%2Fijeecs.v35.i3.pp1751-1764&partnerID=40&md5=9bad82202a24650da58e58ce4958cf1e},
volume = {35},
year = {2024}
}
@article{Abdo2023,
abstract = {Over the past decade, chatbots have experienced a significant increase in popularity, especially since the outbreak of COVID-19. In the United Arab Emirates, most businesses have accelerated their digital transformation and are relying on chatbots as a primary way to interact with customers. However, many of these chatbots lack a voice input option for customers. This study investigates the benefits and challenges of incorporating artificial intelligence (AI) voice-enabled chatbots into United Arab Emirates (UAE) businesses and how this impacts customer experience. Qualitative research techniques were used to gather information, and the results demonstrate that implementing AI chatbots with voice input and sentiment analysis features can enhance the customer experience by making it more efficient and convenient. Additionally, the study found that AI chatbots can ultimately save businesses time and money, and while they may reduce the need for human agents, they will not replace them entirely. Finally, an implementation framework and suggestions are provided for businesses that are interested in adopting AI voice-enabled chatbots for customer interactions. {\textcopyright} 2023, Institute of Advanced Engineering and Science. All rights reserved.},
address = {Faculty of Engineering and Information Sciences, University of Wollongong in Dubai, Dubai, United Arab Emirates},
annote = {Export Date: 21 September 2024; Cited By: 4; Correspondence Address: A. Abdo; Faculty of Engineering and Information Sciences, University of Wollongong in Dubai, Dubai, United Arab Emirates; email: asaadabdo1@gmail.com},
author = {Abdo, A and Yusof, S M},
doi = {10.11591/ijai.v12.i4.pp1920-1927},
issn = {20894872 (ISSN)},
journal = {IAES International Journal of Artificial Intelligence},
keywords = {Artificial intelligence,Chatbots,Cognitive services,Customer experience,Customer interaction,Sentiment analysis,Voice chatbots},
language = {English},
number = {4},
pages = {1920--1927},
publisher = {Institute of Advanced Engineering and Science},
title = {{Exploring the impacts of using the artificial intelligence voice-enabled chatbots on customers interactions in the United Arab Emirates}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85167625603&doi=10.11591%2Fijai.v12.i4.pp1920-1927&partnerID=40&md5=4040e9eda0f9d1eab85fb33c8cfb3289},
volume = {12},
year = {2023}
}
@article{Ha2023,
abstract = {The automation of organic compound synthesis is pivotal for expediting the development of such compounds. In addition, enhancing development efficiency can be achieved by incorporating autonomous functions alongside automation. To achieve this, we developed an autonomous synthesis robot that harnesses the power of artificial intelligence (AI) and robotic technology to establish optimal synthetic recipes. Given a target molecule, our AI initially plans synthetic pathways and defines reaction conditions. It then iteratively refines these plans using feedback from the experimental robot, gradually optimizing the recipe. The system performance was validated by successfully determining synthetic recipes for three organic compounds, yielding that conversion rates that outperform existing references. Notably, this autonomous system is designed around batch reactors, making it accessible and valuable to chemists in standard laboratory settings, thereby streamlining research endeavors. Copyright {\textcopyright} 2023 The Authors, some rights reserved.},
address = {Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., 130 Samsung-ro, Yeongtong-gu, Gyeonggi-do, Suwon-si, 16678, South Korea},
annote = {Export Date: 21 September 2024; Cited By: 11; Correspondence Address: Y.-S. Choi; Samsung Advanced Institute of Technology, Samsung Electronics Co. Ltd., Suwon-si, 130 Samsung-ro, Yeongtong-gu, Gyeonggi-do, 16678, South Korea; email: ysuk.choi@samsung.com},
author = {Ha, T and Lee, D and Kwon, Y and Park, M S and Lee, S and Jang, J and Choi, B and Jeon, H and Kim, J and Choi, H and Seo, H.-T. and Choi, W and Hong, W and Park, Y J and Jang, J and Cho, J and Kim, B and Kwon, H and Kim, G and Oh, W S and Kim, J W and Choi, J and Min, M and Jeon, A and Jung, Y and Kim, E and Lee, H and Choi, Y.-S.},
doi = {10.1126/sciadv.adj0461},
issn = {23752548 (ISSN)},
journal = {Science Advances},
keywords = {Artificial intelligence technologies,Autonomous functions,Batch reactors,Compound synthesis,Intelligent robots,Molecules,Organic compounds,Organic molecules,Power,Reaction conditions,Robotic technologies,Synthesis (chemical),Synthetic pathways,Systems performance,Target molecule},
language = {English},
number = {44},
publisher = {American Association for the Advancement of Science},
title = {{AI-driven robotic chemist for autonomous synthesis of organic molecules}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85175770271&doi=10.1126%2Fsciadv.adj0461&partnerID=40&md5=f9e7c7e1bcc875254519cefb1b6925c8},
volume = {9},
year = {2023}
}
@article{Wang2024,
abstract = {Last-mile delivery has gained much popularity in recent years, it accounts for about half of the whole logistics cost. Unlike container transportation, companies must hire significant number of employees to deliver packages to the customers. Therefore, many companies are studying automated methods such as robotic delivery to complete the delivery work to reduce the cost. It is undeniable that the security issue is a huge challenge in such a system. In this article, we propose an AI-driven robotic delivery system, which consists of two modules. A multilevel cooperative user authentication module for delivering parcel using both PIN code and biometrics verification, i.e., voiceprint and face verification. Another noncooperative user identification module using face verification which detects and verifies the identification of the customer. In this way, the robot can find the correct customer and complete the delivery task automatically. Finally, we implement the proposed system on a Turtlebot3 robot and analyze the performance of the proposed schema. Experimental results show that our proposed system has a high accuracy and can complete the delivery task securely.  {\textcopyright} 1988-2012 IEEE.},
address = {University of Sheffield, Department of Computer Science, Sheffield, S10 2TN, United Kingdom},
annote = {Export Date: 21 September 2024; Cited By: 6; Correspondence Address: P. Gope; University of Sheffield, Department of Computer Science, Sheffield, S10 2TN, United Kingdom; email: p.gope@ieee.org; CODEN: IEEMA},
author = {Wang, W and Gope, P and Cheng, Y},
doi = {10.1109/TEM.2022.3142282},
issn = {00189391 (ISSN)},
journal = {IEEE Transactions on Engineering Management},
keywords = {AI,Audio classification,Authentication,Cooperative user authentication,Cooperative users,Costs,Delivery systems,Face,Face Verification,Face recognition,Intelligent robots,Multi-level authentications,Noncooperative user authentication,Password,Robotic delivery system,Sales,Speaker verification,Spectrograms,Speech recognition,Task analysis,User authentication,audio classification,cooperative user authentication,face verification,multilevel authentication,noncooperative user authentication,robotic delivery system,speaker verification},
language = {English},
pages = {12658--12673},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
title = {{An AI-Driven Secure and Intelligent Robotic Delivery System}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126335832&doi=10.1109%2FTEM.2022.3142282&partnerID=40&md5=8cab844d1700732da1f664549199ac3e},
volume = {71},
year = {2024}
}
@article{Zeineldin2023,
abstract = {Recent advances in artificial intelligence have enabled promising applications in neurosurgery that can enhance patient outcomes and minimize risks. This paper presents a novel system that utilizes AI to aid neurosurgeons in precisely identifying and localizing brain tumors. The system was trained on a dataset of brain MRI scans and utilized deep learning algorithms for segmentation and classification. Evaluation of the system on a separate set of brain MRI scans demonstrated an average Dice similarity coefficient of 0.87. The system was also evaluated through a user experience test involving the Department of Neurosurgery at the University Hospital Ulm, with results showing significant improvements in accuracy, efficiency, and reduced cognitive load and stress levels. Additionally, the system has demonstrated adaptability to various surgical scenarios and provides personalized guidance to users. These findings indicate the potential for AI to enhance the quality of neurosurgical interventions and improve patient outcomes. Future work will explore integrating this system with robotic surgical tools for minimally invasive surgeries.  {\textcopyright} 2023 the author(s), published by De Gruyter, Berlin/Boston.},
address = {Research Group Computer Assisted Medicine, Reutlingen University, Reutlingen, Germany},
annote = {Export Date: 21 September 2024; Cited By: 2; Correspondence Address: R.A. Zeineldin; Research Group Computer Assisted Medicine, Reutlingen University, Reutlingen, Germany; email: ramy.zeineldin@reutlingen-university.de},
author = {Zeineldin, R A and Junger, D and Mathis-Ullrich, F and Burgert, O},
doi = {10.1515/auto-2023-0061},
issn = {01782312 (ISSN)},
journal = {At-Automatisierungstechnik},
keywords = {AI,minimal invasive robotics,neurosurgery,segmentation,user experience},
language = {English},
number = {7},
pages = {537--546},
publisher = {De Gruyter Oldenbourg},
title = {{Entwicklung eines KI-gesteuerten Systems f{\"{u}}r die Neurochirurgie mit einer Usability-Studie: Ein Schritt in Richtung minimal-invasive Robotik}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85166131192&doi=10.1515%2Fauto-2023-0061&partnerID=40&md5=9b0281f02441c3831e97d15a0668f3ce},
volume = {71},
year = {2023}
}
@article{Berdell2024,
abstract = {The paper introduces the ‘Smart Handle', a compact, lightweight, fully solid-state control device based on machine learning (ML) models, enabling intuitive manipulation across all three degrees-of-freedom (DOF) of translation and orientation. This handle-type control device utilizes low-cost, easily accessible sensors and materials. It addresses the need for natural control mechanisms in upper-extremity exoskeletons used in rehabilitation and occupational settings, offering position and orientation trajectories crucial for kinematic models. Additionally, individuals with motor difficulties using mobility chairs could benefit from its ability to learn and interpret diverse inputs as control commands. Through empirical study, it was demonstrated that the device adeptly learns and outputs continuous translation and rotation information from training sets focused on single DOF motions. Personalized calibration enables consistent movement classification with over 95% accuracy. Successful proof-of-concept experiments were conducted in exoskeleton and wheeled robot control applications, showcasing the Smart Handle's adaptability and reliability in diverse settings. This research underscores the device's potential across multiple domains, providing a foundation for enhanced intuitive control mechanisms in various technological applications. {\textcopyright} 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.},
address = {Electrical Engineering Department, Northern Illinois University, DeKalb, IL, United States},
annote = {Export Date: 21 September 2024; Cited By: 0; Correspondence Address: H. Ferdowsi; Electrical Engineering Department, Northern Illinois University, DeKalb, United States; email: hferdowsi@niu.edu},
author = {Berdell, J and Kudernatsch, S and Ferdowsi, H},
doi = {10.1080/21642583.2024.2331061},
issn = {21642583 (ISSN)},
journal = {Systems Science and Control Engineering},
keywords = {Control device,Control mechanism,Degrees of freedom (mechanics),Exoskeleton (Robotics),Kinematics,Learn+,Machine learning,Machine learning models,Machine-learning,On-machines,Robotic exoskeletons,Solid state devices,Solid-state devices,State-control,Upper-extremity,control,machine learning},
language = {English},
number = {1},
publisher = {Taylor and Francis Ltd.},
title = {{AI-Driven solid-state device to enable natural control of upper-extremity robotic exoskeletons}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189468004&doi=10.1080%2F21642583.2024.2331061&partnerID=40&md5=3a6b6db2357c482defa0490a507941b4},
volume = {12},
year = {2024}
}
@article{Dhabliya2023,
abstract = {It is very important for today's safety that a Domain-based Message Authentication, Reporting, and Conformance (DMARC) system is set up correctly. This outline sums up the main points of a thorough study that looked at many aspects of DMARC application. The goal was to find a good mix between strong email security and the smooth flow of official communications. The review looks at important factors like email delivery rates, spam protection, false positives, DMARC policy enforcement, alignment success, and issue reaction times. It does this through categorized tables. Collectively, these measures show how complicated DMARC execution is, stressing the need for a complete method. In addition to looking at how well the technology works technically, the study also looks at how well it works for people by looking at things like user education, knowledge, and the cost of implementation. All of these things work together in a complex way to make the system last and be successful overall. The strategic benefits of a well-run DMARC project are shown by the wider effects it has on brand image, return on investment, and customer trust. The results affect more than just safety; they also affect the company's reputation and ability to survive in a tough business world. In conclusion, the evaluation tables are useful tools that help businesses improve and tweak their email security plans. A good DMARC strategy not only protects against online dangers but also builds a culture of knowledge, trust, and organizational excellence. This sets the organization up for long-term success in a digital world that is always changing. {\textcopyright} JES 2023 on-line : journal.esrgroups.org},
address = {Department of Information Technology, Vishwakarma Institute of Information Technology, Maharashtra, Pune, India},
annote = {Export Date: 21 September 2024; Cited By: 0},
author = {Dhabliya, D and Ghule, G and Khubalkar, D and Moje, R K and Kshirsagar, P S and Bendale, S P},
doi = {10.52783/jes.654},
issn = {11125209 (ISSN)},
journal = {Journal of Electrical Systems},
keywords = {Bot,Botnet,Business Process,Cyber security,Cybersecurity,E-mails security,Electronic mail,Message authentication,Process automation,Process control,RPA,Reaction rates,Robotic Process Automation,Robotic process automation,Robotics,Rule-based process,Software robot,automation,bots,business processes,data entry,efficiency,rules-based processes,software robots},
language = {English},
number = {3},
pages = {96--105},
publisher = {Engineering and Scientific Research Groups},
title = {{Robotic Process Automation in Cyber Security Operations: Optimizing Workflows with AI-Driven Automation}},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185200412&doi=10.52783%2Fjes.654&partnerID=40&md5=a429b04d60de3b264623aba0d91c43ad},
volume = {19},
year = {2023}
}