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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...

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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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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AI-Powered Multi View Face Video Super-Resolution Techniques for Real-Time Video Processing 2

AI-Powered Multi View Face Video Super-Resolution Techniques...

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2nd IEEE International Conference on Integrated Intelligence and Communication Systems, ICIICS 2024

作者： Manjunatha, D.V. Maindola, Meenakshi Jose, Reny Kaliappan, S. Patel, Mitul Maranan, Ramya Department of Electronics & Communication Engineering Alvas Institute of Engineering & Technology Moodabidri India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Idukki India Division of Research and Development Lovely Professional University Phagwara India Faculty of Engineering and Technology Parul institute of Engineering and Technology Parul University Vadodara India Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai India

ISBN: (纸本)9798331504960

In order to improve the visual quality of low-resolution video frames, this study introduces a new superresolution method for real-time video processing that is powered by artificial intelligence. With little computational overhead, the suggested approach uses a hybrid deep learning model to reconstruct high-resolution frames. This model mixes Convolutional Neural Networks (CNNs) with Generative Adversarial Networks (GANs). The suggested method outperforms state-of-the-art methods by 12.3% in PSNR and 8.7% in SSIM, according to experimental results on benchmark video datasets. The PSNR is 34.56 dB and the SSIM is 0.94. Also, running on a GTX 1080Ti GPU, the system shows an average processing speed of 30 fps, which is great for real-time apps. The suggested strategy is effective in eliminating artifacts, improving visual clarity, and retaining fine details in various real-time video processing contexts, according to both quantitative and qualitative results. © 2024 IEEE.

关键词： Convolutional neural networks

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engineering Educators' Adoption and implementation of Project-Based Learning: Experiences from a South Indian University 13

Engineering Educators' Adoption and implementation of Projec...

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13th IEEE International Conference on Teaching, Assessment and Learning for engineering, TALE 2024

作者： Dijo, Anjal P Anantha, Krishnan K. P. Subheesh, N.P. John, Aby Anzar, S.M. Sachidananthan, Sajin Federal Institute of Science and Technology Department of Computer Science and Engineering India College of Engineering Department of Computer Science and Engineering Kerala India Srm University - Ap Teaching Learning Centre Andhra Pradesh 522502 India Rudn University Faculty of Philology Moscow Russia Tkm College of Engineering Department of Electronics and Communication Engineering Kollam India Curriculum Research and Development U-DNA Educational Foundation Andhra Pradesh Anantapur India

ISBN: (纸本)9798350376234

This research investigates the attitudes and perceptions of engineering educators in Kerala, India, towards the implementation of Project-Based Learning (PjBL) within the framework of APJ Abdul Kalam Technological University (APJAKTU), Kerala. Despite the growing emphasis on experiential learning, only limited research studies focus on understanding the attitudes and perceptions of engineering faculty members towards PjBL. Against this backdrop, the present study aims to critically examine the readiness of engineering educators in adopting and identifying PjBL strategies for its effective integration into engineering curricula. The paper explores various dimensions of engineering educators' engagement with PjBL, including faculty interest levels, satisfaction of implementation, perceived effectiveness, and career implications. The data were collected from engineering faculty members by distributing a comprehensive questionnaire titled Project-Based Learning in engineering Education in Kerala (PLEEK), uniquely designed by the researchers. The research findings reveal that over 90% of the surveyed faculty members have shown keen interest in implementing PjBL, while the remaining respondents exhibited a neutral stance. This underscores a noteworthy receptivity to PjBL among engineering educators in Kerala. Suggestions from participants indicate that, if implemented correctly, PjBL would be highly effective, although time constraints pose a significant challenge. The results obtained are pivotal as they provide an explicit idea of the current status of the engineering education settings and the discrepancies between traditional theoretical instruction and project-based learning. © 2024 IEEE.

关键词： engineering education

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Multi-stage anisotropic etching of two-dimensional heterostructures

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Nano research 2022年第6期15卷 4909-4915页

作者： Lin Li Jichen Dong Dechao Geng Menghan Li Wei Fu Feng Ding Wenping Hu Hui Ying Yang Institute of Molecular Plus Tianjin UniversityTianjin 300072China Centre for Multidimensional Carbon Materials Institute for Basic ScienceUlsan 44919Republic of Korea Pillar of Engineering Product Development Singapore University of Technology and DesignSingapore 487372Singapore Tianjin Key Laboratory of Molecular Optoelectronic Sciences Department of ChemistrySchool of ScienceTianjin University and Collaborative Innovation Center of Chemical Science and EngineeringTianjin 300072China Institute of Materials Research and Engineering(IMRE) Agency for ScienceTechnologyand Research(A*STAR)Singapore 138634Singapore

Regarding the reverse process of materials growth,etching has been widely concerned to indirectly probe the growth kinetics,offering an avenue in governing the growth of two-dimensional(2D)*** this work,interface-driven anisotropic etching mode is demonstrated for the first time to be generally applied to 2D *** is shown that the typical in-plane graphene and hexagonal boron nitride(h-BN)heterostructures follow a multi-stage etching behavior initiated first along the interfacial region between the two materials and then along edges of neighboring h-BN flakes and finally along central edges of *** accurately tuning etching conditions in the chemical vapor deposition process,series of etched 2D heterostructure patterns are controllably ***,scaled formation of graphene and h-BN heterostructures arrays has been realized with full assist of as-proposed etching mechanism,offering a direct top-down method to make 2D orientated heterostructures with order and *** of interface-driven multi-staged anisotropic etching mode will shed light on understanding growth mechanism and further expanding wide applications of 2D heterostructures.

关键词： anisotropic etching two-dimensional materials heterostructures graphene h-BN

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Optimization of main process control parameters of PHA bio-polymer in material extrusion additive manufacturing: experimental design and predictive models

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The International Journal of Advanced Manufacturing Technology 2025年 1-17页

作者： Vidakis, Nectarios Petousis, Markos Mountakis, Nikolaos Spyridaki, Maria Gkagkanatsiou, Katerina Stratakis, Emmanuel Department of Mechanical Engineering Hellenic Mediterranean University Heraklion Greece Foundation for Research and Technology-Hellas (FO.R.T.H) Heraklion Crete Greece Innovation and Development Center Harbin Engineering University Qingdao China

The sustainability of additive manufacturing (AM) has attracted attention nowadays, with different aspects needed to be considered. A key effort in this direction is the replacement of fossil fuel–originating polymers with biologically derived polymers. To achieve this, biologically derived polymers should exhibit a performance similar to that of commonly used polymers. Bacterially produced pure polyhydroxyalkanoate (PHA) was recently proposed by filament vendors for material extrusion (MEX) AM. Despite extensive research on the utilization of PHA in polymeric blends, the literature on the printability metrics of pure PHA is limited. At the same time, it has a high potential as an alternative to common petrochemical polymers. In this study, the impact of the main generic settings on the mechanical response of pure bio-sourced PHA in MEX AM was investigated. Four critical 3D printing parameters (print speed, layer height, nozzle temperature, and strand width) were evaluated using a robust design to optimize the tensile and impact metrics. Regression modeling was performed, and predictive equations were compiled and verified using validation testing. The quality of the samples was evaluated using electron microscopy. The analysis proved the importance of layer thickness in the tensile score, whereas nozzle temperature was found to be the most influential setting for impact loading. An increase of approximately 20% can be achieved by selecting appropriate 3D printing settings in the tensile test, whereas the impact strength can be radically improved by up to 550%.

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