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2025 Design, Automation and Test in Europe Conference, DATE 2025

作者： Nikolaou, Panagiota Savva, Antonis Sorokos, Ioannis Aslansefat, Koorosh Missaoui, Sondess Naveed, Akram Mohammed Hillen, Daniel Lorenz, Marc Walker, Martin D. Papoutsakis, Manos Gerasimou, Simos Kolios, Panayiotis Papadopoulos, Yiannis Reich, Jan Ioannidis, Sotiris Michael, Maria K. University of Central Lancashire Cyprus Electrical and Computer Engineering Department University of Cyprus Cyprus Kios Research and Innovation Center of Excellence University of Cyprus Cyprus Computer Science Department University of Cyprus Cyprus Fraunhofer Iese Germany University of Hull United Kingdom University of York United Kingdom Institute of Computer Science Foundation for Research and Technology Greece

ISBN: (纸本)9783982674100

Unmanned Aerial Vehicles (UAVs) have become essential in search and rescue operations, especially in disaster management scenarios. Their effective navigation and the integration of a plethora of sensors assist in efficient person detection, making them an essential technological tool to first responders. Multi-UAV systems extend these benefits by using coordinated strategies to cover large areas efficiently, reducing overall mission response time and enhancing its success. Despite these advantages, challenges remain in ensuring the safety, security, and dependability of (mutli-)UAV missions. Issues such as navigation risks, potential cyber threats, and hardware-/software-related reliability issues can impact the mission results. Additionally, UAVs are highly constrained devices with limited battery capacity, requiring the use of lightweight technologies. In this paper, we present part of the results of the SESAME project, an EU multi-partner project that aims to develop safe and secure multi-robot Systems. In particular, we present some of the developed SESAME Executable Digital Dependability Identities (EDDI) technologies based on Markov models, statistical distance measures, and other advanced approaches for enhancing safety, security and dependability of the UAV platform and underlying models. These EDDI technologies are seamlessly integrated using the ConSerts framework in a multi-UAV platform and tested using search and rescue scenarios. The results demonstrate significant improvements in multi-UAV safety, with an availability rate of 91% and a search and rescue algorithmic accuracy of 99.8%. Additionally, the system achieves precise detection of spoofing attacks, using collaborative localization as a mitigation technique to guide the UAV to a safe landing, even in the absence of GPS signals © 2025 EDAA.

关键词： Drones

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Bend-induced Polarization-Dependent Loss in single mode fiber and its impact on Nonlinear Polarization Evolution 4

Bend-induced Polarization-Dependent Loss in single mode fibe...

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4th International Computational Imaging Conference, CITA 2024

作者： Song, Ruilong Jiang, Hongbo Lu, Heng Liu, Hang Set, Sze Yun Tang, Xiaoyun Jin, Lei Qingdao Innovation and Development Base Harbin Engineering University Shandong Qingdao266000 China Shandong Qingdao266520 China Research Center for Advanced Science and Technology The University of Tokyo Meguro-ku Tokyo153-8904 Japan College of Physics and Optoelectronic Engineering Harbin Engineering University Heilongjiang Harbin150001 China

ISBN: (纸本)9781510688834

This study investigates polarization-dependent loss (PDL) and bend loss characteristics in bent single-mode fiber (SMF) and demonstrates that specific fiber parameters beyond bending radius, particularly cladding and coating properties, can substantially alter loss characteristics. Experimental results reveal that changing the refractive index of the environment outside the coating layer significantly impacts bend loss oscillation due to the high refractive index contrast at the coating-air interface. Additionally, while polarization dependent loss exhibits oscillatory behavior similar to bend loss, it responds differently under certain parameter conditions, resulting in an out-of-phase relationship between bend loss and PDL. Simulations further suggest a method for enhancing polarization dependent loss while minimizing bend loss, enabling optimized polarizing elements in coiled SMF designs. These findings provide valuable insights for extending the all-fiber nonlinear polarization evolution (NPE) based mode-locking approach to a broader range of wavelengths, supporting advancements in ultrafast fiber laser applications. © 2025 SPIE.

关键词： Single mode fibers

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Mining Healthcare Data for Predictive Modeling and Prognosis of Alzheimer's Disease Progression with Artificial Intelligence 2

Mining Healthcare Data for Predictive Modeling and Prognosis...

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Kaliappan, S. Ali, H. Mohammed Maranan, Ramya Sunil, G. Lovely Professional University Division of Research and Development Punjab Phagwara144411 India Srm Institute of Science and Technology Department Mechanical Engineering Ramapuram Campus Chennai89 India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai602105 India School of Computer Science and Artificial Intelligence Sr University Telangana Warangal506371 India

ISBN: (纸本)9798350370188

In this study, we propose a novel approach to predict and prognosticate Alzheimer's disease progression by leveraging cutting-edge artificial intelligence and data mining techniques. Our method integrates three powerful algorithms: Long Short-Term Memory Networks (LSTM), Random Forest, and Gradient Boosting Machines (GBM). LSTM excels in sequence analysis, effectively capturing temporal patterns in healthcare data crucial for disease progression prediction. Random Forest is utilized for feature importance analysis and classification, aiding in understanding the most influential aspects of healthcare data. GBM, known for ensemble learning, combines weak learners iteratively to create a robust predictive model, improving overall accuracy. By synergistically integrating these algorithms, our method optimizes predictive modeling and prognosis for Alzheimer's disease progression, ultimately enhancing patient care and management. © 2024 IEEE.

关键词： Long short-term memory

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A Comprehensive Review of Big Data Analysis Techniques in Health-Care 2nd

A Comprehensive Review of Big Data Analysis Techniques in He...

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Emergent Converging Technologies and Biomedical Systems Select Proceedings of the 2nd International Conference, ETBS 2022

作者： Tiwari, Sharad Kumar Kaur, Jaskirat Singla, Parveen Hrisheekesha, P.N. Electronics and Communication Engineering Department Vignan Foundation for Science Technology and Research Vadlamudi522213 India Chandigarh India Electronics and Communication Engineering Department Department of Research and Development Chandigarh Engineering College Landran Mohali140307 India Chandigarh Group of Colleges Mohali140307 India

ISBN: (纸本)9789819922703

With the development of the big data technologies in health-care, there is a big challenge to manage health care records such as meta-data, sensor data, imaging data and other health records. To handle, control and drive this big data, the traditional handing techniques, software and available hardware are not sufficient. Therefore, the current methodologies need to be augmented with advanced big data computation and system requirements. This huge data also provides opportunities for the health-care researchers to perform the data analysis on this available huge data. Hence, a modern solution is utmost required for diagnosis cost reduction and improving the healthcare facilities. In this research paper, a comprehensive review of big data techniques illustrated the different healthcare big data analysis algorithms, frameworks, tools, and techniques that are deployed on various platforms. Finally, convergence point of all the above-mentioned platforms in the form of Smart-health is established. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Information management

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Energy consumption modeling and prediction in the cloud data centers

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Journal of engineering science and Technology Review 2020年第3期13卷 224-234页

作者： Diouani, Sara Medromi, Hicham Research Foundation for Development and Innovation in Science and Engineering Casablanca Morocco Hassan II University of Casablanca Morocco

Energy efficiency has turned into an undeniably essential worry in data centers as a result of issues related to energy consumption, including capital costs, working costs, and natural effect. While energy wastage, because of imperfect utilization of facilities and IT hardware, has to a great extent been decreased using best-practice advances, tending to energy loss in IT equipment, still requires the plan and usage of energy-aware resource management frameworks. Various methods aimed to enhance the energy efficiency in data centers have been developed in the field related to the development of resource allocation. In fact, researchers and scientists utilize numerous ways to improve effectiveness for optimized power and performance: scaling virtual machine and server preparing abilities to minimize energy consumption, enhancing resource use through exploiting its heterogeneity and consolidating the workload. To accomplish these objectives, there is multiple proposes models, calculations, algorithms, techniques, and procedures that diminish energy use using virtual machine scaling, virtual machine sizing for CPU and memory, CPU frequency adjustment, and also equipment power control for resource allocation in the server-level. The proposed online performance and power models catch framework conduct while adjusting to changes in the fundamental infrastructure. In this context, we present different formulas for calculating energy consumption in cloud data centers and we propose a simplified and completed deduced formula for energy consumption estimation. © 2020 School of science, IHU. All rights reserved.

关键词： Energy utilization

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On the motion analysis of autonomous underwater vehicles under arbitrary waves 41

On the motion analysis of autonomous underwater vehicles und...

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第41届中国控制会议

作者： Yibo Pang Zhan Wang Ye Wang College of Intelligent Systems Science and Technology Harbin Engineering University Engineering Research Center of Navigation Instruments Ministry of Education College of Shipbuilding Engineering Harbin Engineering University Qingdao Innovation and Development Center of Harbin Engineering University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,a linear AUV motion model of an autonomous underwater vehicle(AUV) is proposed based on a general nonlinear AUV model of *** this model,regular wave force conditions are established based on the Morison's formula with ocean wave *** the irregular waves with non-analytical flow field,the Monte Carlo method is proposed to compute wave force(moment).Based on the linear AUV motion model,the simulation models under linear(regular) and random(irregular) waves are developed,*** effectiveness of the proposed motion model is shown with numerical simulations.

关键词： Autonomous Underwater Vehicle Linear AUV Model Morison's Formula Monte Carlo Method

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Optimizing Resource Allocation in Healthcare Systems for Efficient Pandemic Management using Machine Learning and Artificial Neural Networks 2

Optimizing Resource Allocation in Healthcare Systems for Eff...

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2nd International Conference on Advancements in Smart, Secure and Intelligent Computing, ASSIC 2024

作者： Kaliappan, S. Maranan, Ramya Malladi, Avinash Yamsani, Nagendar Lovely Professional University Division of Research and Development Punjab Phagwara144411 India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai602105 India Mechatronics Engineering Hyderabad50 1203 India School of Computer Science & Artificial Intelligence Sr University Telangana Warangal506371 India

ISBN: (纸本)9798350370188

Pandemics pose significant challenges to healthcare systems, particularly in resource allocation and patient care. Traditional methods for resource allocation often face limitations in handling complex data, adapting to changing conditions, and providing real-time decision support. To address these challenges, we propose a novel method for optimizing resource allocation in healthcare systems using machine learning (ML) and artificial neural networks (ANN s). Traditional resource allocation methods, often based on historical data and manual decision-making, may not be adequate to handle the dynamic and complex nature of pandemics. These methods often fail to account for real-time changes in disease patterns, patient needs, and resource availability. The proposed method integrates predictive modeling, optimization algorithms, and real-time decision support to enhance resource utilization and improve patient outcomes during pandemics. © 2024 IEEE.

关键词： Neural networks

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research of Continuous Thermoplastic Coating Equipment Based on Virtual Simulation 8

Research of Continuous Thermoplastic Coating Equipment Based...

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8th International Workshop on Control engineering and Advanced Algorithms, IWCEAA 2024

作者： Hu, Lingyan Xue, Haixin Chenzhuang, Tianyi Cao, Meng Yuan, Chunping Hou, Huiming School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai China School of Information Engineering Nanchang University Nanchang Jiangxi Nanchang China China State Institute of Pharmaceutical Industry National Advanced Medical Engineering Research Center Shanghai China Shanghai Drug Evaluation and Verification Center Department Innovation and Regulatory Scientific Development Shanghai China Shanghai University of Engineering Science Shanghai Engineering Research Center of Pharmaceutical Intelligent Equipment Shanghai China

ISBN: (纸本)9798331528881

In order to realize the industrialization of the new thermoplastic coating method for osmotic pump tablets, it is necessary to develop new continuous coating equipment for thermoplastic coating. In order to accelerate the process of equipment development and reduce the research and development cost, this paper proposed a novel simulation method with VUP and PLC to test and validate the newly designed equipment in a virtual environment. After building a 3D model of the equipment in VUP and designing the PLC control algorithm in PLC, a communication connection is established between PLC and VUP, enabling the PLC at TIA Portal V16 to send control commands to control the mechanical system at VUP and receive feedback from the mechanical system at VUP. The novel simulation method can test and validate the system design, including the program and mechanical structure, in a virtual environment, and the potential problems can be identified in advance to avoid the high costs associated with fixing these problems at the physical prototyping stage. The simulation experiment and its actual experiment results show that the designed hardware and software can realize the continuous thermoplastic coating process. © 2024 IEEE.

关键词： Virtual environments

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Deep Learning-Based Mask Identification System Using ResNet Transfer Learning Architecture

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Computer Systems science & engineering 2024年第2期48卷 341-362页

作者： Arpit Jain Nageswara Rao Moparthi A.Swathi Yogesh Kumar Sharma Nitin Mittal Ahmed Alhussen Zamil S.Alzamil MohdAnul Haq Department of Computer Science and Engineering KoneruLakshmaiah Education FoundationVaddeswaram522302India Department of Computer Science and Engineering Sreyas Institute of Engineering and TechnologyHyderabad500068India University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Recently,the coronavirus disease 2019 has shown excellent attention in the global community regarding health and the *** Health Organization(WHO)and many others advised controlling Corona Virus Disease in *** limited treatment resources,medical resources,and unawareness of immunity is an essential horizon to *** all resources,wearing a mask is the primary non-pharmaceutical intervention to stop the spreading of the virus caused by Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2)*** countries made masks mandatory to prevent *** such enforcement,automatic and effective face detection systems are *** study presents a face mask identification approach for static photos and real-time movies that distinguishes between images with and without *** contribute to society,we worked on mask detection of an individual to adhere to the rule and provide awareness to the public or *** paper aims to get detection accuracy using transfer learning from Residual Neural Network 50(ResNet-50)architecture and works on detection *** experiment is tested with other popular pre-trained models such as Deep Convolutional Neural Networks(AlexNet),Residual Neural Networks(ResNet),and Visual Geometry Group Networks(VGG-Net)advanced *** proposed system generates an accuracy of 98.4%when modeled using Residual Neural Network 50(ResNet-50).Also,the precision and recall values are proved as better when compared to the existing *** outstanding work also can be used in video surveillance applications.

关键词： Transfer learning depth analysis convolutional neural networks(CNN) COVID-19

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Physicochemical properties of lard oil and rubber seed oil blends and their comprehensive characterization

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Chinese Journal of Chemical engineering 2024年第11期75卷 1-13页

作者： Amonrat Thangthong Wuttichai Roschat Phongsakorn Pholsupho Aekkaphon Thammayod Sunti Phewphong Tappagorn Leelatam Preecha Moonsin Boonyawan Yoosuk Pathompong Janetaisong Vinich Promarak Program of Environment Science Faculty of Science and TechnologySakon Nakhon Rajabhat UniversityMueang DistrictSakon Nakhon 47000Thailand Biomass Energy Research Laboratory Center of Excellence on Alternative EnergyResearch and Development InstitutionSakon Nakhon Rajabhat UniversityMueang DistrictSakon Nakhon 47000Thailand Program of Chemistry Faculty of Science and TechnologySakon Nakhon Rajabhat UniversityMueang DistrictSakon Nakhon 47000Thailand Innovation in Chemistry for Community Research Unit Faculty of Science and TechnologySakon Nakhon Rajabhat UniversityMueang DistrictSakon Nakhon 47000Thailand Appropriated Technology Center Faculty of Science and TechnologySakon Nakhon Rajabhat UniversityMueang DistrictSakon Nakhon 47000Thailand Program of Chemistry Faculty of ScienceUbon Ratchathani Rajabhat UniversityMueang DistrictUbon Ratchathani 34000Thailand National Energy Technology Center(ENTEC) 114 Thailand Science ParkPhahonyothin RoadKlong LuangPathumthani 12120Thailand Department of Material Science and Engineering School of Molecular Science&EngineeringVidyasirimedhi Institute of Science and TechnologyWangchanRayong 21210Thailand

This research investigates the potential of blending complementary lard oil with rubber seed oil as feedstock for biodiesel *** seed oil,obtained through hexane extraction using the Soxhlet method,contains the major fatty acids of oleic acid(C_(18:1)),palmitic acid(C_(16:0)),linoleic acid(C_(18:2)),and stearic acid(C_(18:0)),while rubber seed oil primarily consists of linoleic acid(C_(18:2)),oleic acid(C_(18:1)),linolenic acid(C_(18:3)),palmitic acid(C_(16:0)),and stearic acid(C_(18:0)).The least acid value of lard oil(0.55 mg KOH/g)can benefit of reducing soap formation of rubber seed oil during transesterification process in biodiesel production due to its substantial-high acid value(16.28 mg KOH/g).Blending at ratios below 80:20 volume ratio produced biodiesel exceeding 85%,utilizing CaO as a *** oil demonstrated a higher reaction rate constant(11.88×10^(-3)min^(-1))than rubber seed oil(2.11×10^(-3)min^(-1)),indicating a significant difference in *** acid value and free fatty acids in rubber seed oil correlated with lower reaction *** a mixture ratio below 80:20 volume ratio optimized reaction rates during biodiesel *** obtained from blends below 80:20 volume ratio met ASTM D6751 and EN 14214 standards,demonstrating suitability for bio-auto *** drawbacks of using rubber seed oil as a raw material for biodiesel production are overcome by blending with lard oil,giving rise to expanding renewable energy options for rural communities,community enterprises,and large-scale biodiesel production.

关键词： Biodiesel oil Rubber seed oil Lard oil High free fatty acid Physicochemical properties Liquid biofuels

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