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Optimising Knee Replacement Surgery: Development and Assessment of a Parallel Kinematic Machine for Precise Positioning in Knee Arthroplasty 27th

Optimising Knee Replacement Surgery: Development and Assessm...

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27th International Conference on Climbing and Walking Robots and Mobile Machine Support Technologies (CLAWAR)

作者： Sohani, Behnaz Rahmani, Amir Mercer, Kieran Nelson-Smith, Owen Butcher, Charlotte Hazell, Scott Ren, Yaxin Aliyu, Aliyu Goher, Khaled Univ Lincoln Sch Engn Lincoln England Sultan Qaboos Univ Coll Engn Muscat Oman

ISBN: (纸本)9783031713002;9783031713019

This study delves into the development of a custom Parallel Kinematic Machine (PKM) tailored for Knee Arthroplasty Surgery (KAS) to enhance surgical precision and patient outcomes. Knee replacement surgery often leads to long-term pain due to suboptimal knee positioning during the procedure, posing a significant challenge. Previous research has hinted at the potential efficacy of PKMs, known for their versatility, stability, and precision, in facilitating superior knee positioning. The paper investigates the design intricacies of a PKM specifically for knee replacement surgery, spanning conceptualisation, prototyping, and rigorous testing stages. The primary objective is to engineer a PKM capable of positioning knees with unparalleled accuracy, addressing the critical need for precision in surgical interventions. By evaluating the PKM's performance within the context of knee arthroplasty surgery, this study aims to optimise knee positioning and potentially improve surgical outcomes for a broad patient spectrum. The performance of the model was verified through a simple simulation example, demonstrating its ability to track key structures' states and indicating the potential for precise positioning with suitable control algorithms. The next step involves designing control strategies based on this simulation model to meet specific control objectives.

关键词： Robotics for Healthcare Surgical Robotics Parallel Kinematic Machine Rehabilitation Knee Arthroplasty Surgery

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Benchmarking Metaheuristic-Integrated QAOA Against Quantum Annealing

Benchmarking Metaheuristic-Integrated QAOA Against Quantum A...

引用

Computing Conference

作者： Mazumder, Arul Rhik Sen, Anuvab Sen, Udayon Carnegie Mellon Univ Pittsburgh PA 15289 USA Indian Inst Engn Sci & Technol Sibpur 711103 India

ISBN: (纸本)9783031622717;9783031622694;9783031622687

The Quantum Approximate Optimization Algorithm (QAOA) is one of the most promising Noisy Intermediate Quantum (NISQ) Algorithms in solving combinatorial optimizations and displays potential over classical heuristic techniques. Unfortunately, QAOA's performance depends on the choice of parameters and standard optimizers often fail to identify key parameters due to the complexity and mystery of these optimization functions. In this paper, we benchmark QAOA circuits modified with metaheuristic optimizers against classical and quantum heuristics to identify QAOA parameters. The experimental results reveal insights into the strengths and limitations of both Quantum Annealing and metaheuristic-integrated QAOA across different problem domains. The findings suggest that the hybrid approach can leverage classical optimization strategies to enhance the solution quality and convergence speed of QAOA, particularly for problems with rugged landscapes and limited quantum resources. Furthermore, the study provides guidelines for selecting the most appropriate approach based on the specific characteristics of the optimization problem at hand.

关键词： Quadratic unconstrained binary optimization Quantum approximate optimization algorithm Quantum annealing Metaheuristics

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Management Control in the Industry 4.0 Era: Literature Review 4th

Management Control in the Industry 4.0 Era: Literature Revie...

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Najla, Sraidi Bouteina, El Gharbaoui Chafik, Bakour Sara, Griguer Abdelmalek Essaddi Univ ENCG Tangier Morocco Moulay Ismail Univ ENCG Meknes Morocco Int Univ Casablanca Bouskoura Morocco

ISBN: (纸本)9783031686740;9783031686757

This article explores the dynamics of the industrial environment in the era of Industry 4.0, characterized by a major technological transformation. In the face of increased competition, diverse market demands, and specific customer imperatives, the integration of management control and Industry 4.0 is emerging as a crucial evolution. The convergence of these two fields offers significant opportunities to improve operational efficiency, strengthen strategic decision-making and adapt to an increasingly complex industrial environment. Divided into three sections, the article explores the conceptual approach, the opportunities arising from this convergence, and concludes by reflecting on future implications for contemporary managerial and industrial practices. The focus is on how management control, as a traditional discipline, can evolve to meet the challenges of Industry 4.0, redefining how organizations plan, monitor and optimize their performance in a context of digital transformation.

关键词： Management control Industry 4.0 Digital transformation

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Application of Artificial Intelligence for Predicting of New Potential Inhibitors of Vitamin K Epoxide Reductase 2nd

Application of Artificial Intelligence for Predicting of New...

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2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI)

作者： Antonijevic, Marko R. Milenkovic, Dejan A. Avdovic, Edina H. Markovic, Zoran S. Univ Kragujevac Inst Informat Technol Kragujevac Jovana Cvijica bb Kragujevac 34000 Serbia State Univ Novi Pazar Dept Nat Sci & Math Vuka Karadzica bb Novi Pazar 36300 Serbia

ISBN: (纸本)9783031608391;9783031608407

Artificial intelligence (AI) integration in drug development has altered the pharmaceutical industry by delivering innovative and effective solutions to long-standing difficulties in this field. AI techniques and tools, such as machine learning and deep learning algorithms, can analyze enormous datasets and identify complex patterns, therefore speeding up the drug discovery process. The research presented in this paper introduces a systematic approach to the design of novel anticoagulative agents with significant therapeutic potential, driven by the utilization of AI in drug design and development. Coumarins are compounds isolated from plants, and they are responsible for a wide range of biological functions. The anticoagulant potential of coumarin derivatives is one of their most prominent pharmacological properties. Warfarin ( WFR), a common oral anticoagulant, belongs to the 4-hydroxycoumarin class. In one of our most recent studies, we performed pharmacological profiling and anticoagulant activity testing of a (E)-3-(1-((4-hydroxy-3-methoxyphenyl)amino)ethylidene)2,4-dioxochroman-7-yl acetate [15]. When compared to the WFR, it was discovered that the examined molecule has better anticoagulative capability, as well as a more desirable pharmacokinetic profile than WFR. Furthermore, preliminary laboratory tests revealed that (E)-3-(1-((4-hydroxy-3-methoxyphenyl)amino)ethylidene)chromane-2,4-dione (L) has similar pharmacokinetic properties with increased water solubility, making it an even better candidate for the development of potential anticoagulants. By utilization of the CReM web server, a series of 1000 derivatives of L were generated and narrowed down to 46 compounds through screening based on drug-likeness rules. Toxicity assessments further refined the selection to 16 non-toxic candidates, subsequently subjected to molecular docking simulations. Four compounds emerged from this subset, demonstrating excellent inhibition of VKOR, and VKORC1, compared to the

关键词： Learning algorithms

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Evolutionary Neuro-Fuzzy Network and Novel Hybrid Adaptive Crow Search-Modified Glowworm Swarm Optimization for Credit Card Fraud Detection 1

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Singh, Indu Malhotra, Hiten Shruti Jain, Sawan Jha, Siddharth Kumar Pal, Yash Kumar Delhi Technol Univ Dept Comp Sci & Engn Delhi India Delhi Technol Univ Dept Mech Engn Delhi India

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

The growing usage of credit cards for online transactions is accompanied by a rise in fraud instances, fostering the need to develop advanced and interpretable models for fraud detection. To address this problem, a novel methodology is proposed using an Evolutionary Neuro-Fuzzy Network (ENFN) for optimal feature selection followed by a novel Hybrid comprising of Adaptive Crow Search Algorithm and Modified Glowworm Swarm Optimization Algorithm (hACSA-mGSO), seamlessly integrated with SVM classifier for robust classification. The ENFN employs adaptive mutation and fuzzy logic activations to optimize feature selection. The proposed hybrid metaheuristic algorithm (hACSA-mGSO) harnesses the global search ability of CSA and the local optimization capability of GSO for enhanced convergence. Adaptability is incorporated into the CSA through dynamic parameter updates along with stochastic modifications and random spiral movement is introduced in GSO to promote diversity among glowworms, mitigating premature convergence and facilitating efficient search space exploration. Through experimental evaluations using the credit card fraud detection dataset from the ULB Machine Learning Group, the proposed approach showcases its prowess in achieving high accuracy and efficient performance, thereby providing an efficient solution to the intricate challenge of credit card fraud detection.

关键词： Credit Card Fraud Detection Neuro-Fuzzy Network Metaheuristic optimization Adaptive Crow Search Algorithm Modified Glowworm Swarm Optimization

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Learning Mechanical Impulse Response for Understanding Surface Characteristics 18th

Learning Mechanical Impulse Response for Understanding Surfa...

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Lee, Joohyun Ryu, Semin Kim, Seung-Chan Sungkyunkwan Univ Dept Sport Interact Sci Machine Learning Syst Lab Suwon South Korea Hallym Univ Intelligent Robot Lab Chunchon South Korea

This paper proposes an intelligent system that identifies the nature of a surface by knocking on it and interpreting the resultant vibrations to comprehend the complexity.

ISBN: (纸本)9783031449802;9783031449819

This paper proposes an intelligent system that identifies the nature of a surface by knocking on it and interpreting the resultant vibrations to comprehend the complexity.

关键词： Machine learning Vibration Vibrational communication

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Generation Y Health Care Professionals and Their Acceptance of Chatbots 1

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11st World Conference on Information systems and Technologies (WorldCIST)

作者： Zwicky, Anja Stallone, Valerio Haarmann, Jens Zurich Univ Appl Sci Winterthur Switzerland

ISBN: (数字)9783031456428

ISBN: (纸本)9783031456411;9783031456428

Medical chatbots are already used regularly by patients and health care professionals (HCPs). By the end of 2020, the majority of practicing HCPs were born between 1980 to 1994. In other words, most HCPs currently belong to Generation Y, who are generally assumed to be more open towards new digital technologies. The aim of this study was to evaluate HCP acceptance and influencing factors on the latter of a chatbot-based information platform as a proxy for information that HCPs usually provide to patients. This research of 99 HCP showed that system relevance and the innovative elements of the chatbot itself were essential factors in perceiving the chatbot as useful. The innovative elements also had a positive effect on perceived ease of use. Our study provides insights into user acceptance of chatbots supporting the work of HCPs and is a starting point for further discussions and generational change in the labor market for HCPs.

关键词： health care health care professionals telemedicine chatbots conversational agents technology acceptance model

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Machine Learning Approaches to Support Medical Imaging Diagnosis of Pancreatic Cancer - A Scoping Review 12th

Machine Learning Approaches to Support Medical Imaging Diagn...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Tavares, Florbela Rosa, Gilberto Henriques, Ines Rocha, Nelson Pacheco Univ Aveiro Dept Med Sci Aveiro Portugal Univ Aveiro Dept Med Sci IEETA Aveiro Portugal

ISBN: (纸本)9783031602177;9783031602184

The early diagnosis of pancreatic cancer through medical imaging modalities could be an important breakthrough in the increasing of the survival rate. The purpose of this scoping review was to systematize the application of machine learning models to assist the medical imaging diagnosis of pancreatic cancer. An electronic search was conducted on PubMed, Scopus, Web of Science and Association for Computing Machinery, and 20 studies were included in this review after the selection process. Eleven different machine models were identified in the included studies, and, among these, convolutional neural network (CNN) the most referred (i.e., six studies). In general, the included studies present high values in terms of accuracy, sensitivity, and specificity of the machine learning algorithms. However, the included studies only considered retrospective data. This means that randomized clinical trials are required to translate machine learning implementations to clinical practice.

关键词： Pancreatic Cancer Machine Learning Diagnosis Medical Imaging Scoping Review

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LUBB: Augmented Reality (AR) Application for Learning Transmission Control Protocol/Internet Protocol (TCP/IP) Model

LUBB: Augmented Reality (AR) Application for Learning Transm...

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Intelligent systems Conference

作者： Alsahli, Raghad Sili Alobud, Rana Fahad Alsuhaibani, Lamya Abdulaziz Alabdulhafith, Maali Alfarraj, Munirah Fahad Princess Nourah Bint Abdul Rahman Univ Coll Comp & Informat Sci Riyadh Saudi Arabia

ISBN: (纸本)9783031664274;9783031664281

Transmission Control Protocol/Internet Protocol (TCP/IP) is a fundamental concept in computer science and networking, consisting of five layers from the physical to the application layer. Being able to build a comprehensive understanding of the entire model is challenging because each layer has its own set of protocols and concepts. TCP/IP model works behind the scenes, making it difficult to see and directly experience it. In currently fast-evolving world, limiting education to traditional methods results in a lack of perception and interest in the student. Results showed that 70% of the top-20 ranked universities in 2018 had at least one AR learning object created, making AR technology more widely employed as an educational tool. Given the previously mentioned argument, in this project, we introduced immersive techniques that can help students understand the TCP/IP model and become fully immersed in its concepts, which areAR and gamification. AR is a technology that integrates computer-generated information with real-world components. It will help to simplify the learning process of the TCP/IP model by displaying its layers in a three-dimensional form enabling them to see how data packets transfer through each layer. Gamification is a technique where challenges and scores turn learning into an exciting adventure. By combining AR and gamification, we are launching an immersive learning environment to improve learning effectiveness and grab students' attention which boosts engagement and immerses them in educational activities.

关键词： Transmission Control Protocol/Internet Protocol (TCP/IP) model Augmented reality (AR) Gamification Immersive learning networks

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Smart Workplace Past Covid-19: Perceived Challenges and Potential Smart Solutions for University Work Environment

Smart Workplace Past Covid-19: Perceived Challenges and Pote...

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Computing Conference

作者： Tahir, Rabail Krogstie, John Norwegian Univ Sci & Technol Trondheim Norway

ISBN: (纸本)9783031622793;9783031622779;9783031622762

The COVID-19 has reshaped work environment by introducing a lot of challenges and transitions in the way we work. However, there are still inadequate studies exploring the changes and challenges in the post-pandemic work environment. This study explores the changing dimensions of university work environment on post-pandemic return to campus to identify the key challenges and present implications for smart workplace solutions. A focus group was conducted with university staff and students after return to campus focusing on workplace experience past Covid-19. The findings revealed that the main workplace challenges consisted of three categories: 1) Technological challenges, 2) workspace challenges and 3) non-technical challenges. These results present users' perception and experience with the workplace in post pandemic era. Moreover, implications are presented for smart workplace solutions to overcome the identified challenges in the post-pandemic work environment and design better workplaces from three perspectives.

关键词： Workplace challenges Smart workplace solutions University Post-pandemic work environment

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