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Articles 8671 - 8700 of 195925
Full-Text Articles in Engineering
E-Taxi Technology: Assessing Operational Benefits And Sustainability In Modern Aviation, Arthur C. Dela Peña
E-Taxi Technology: Assessing Operational Benefits And Sustainability In Modern Aviation, Arthur C. Dela Peña
Journal of Aviation Technology and Engineering
This study evaluates the operational benefits and sustainability impacts of electrically driven landing gear systems (e-taxi technology) in the aviation industry, focusing on the Philippine context. The objective was to assess improvements in fuel savings, emissions reductions, and maintenance costs associated with e-taxi systems. Using a mixed-methods approach, data were collected through interviews with airline operators, and secondary data were collected from industry reports. Results showed that e-taxi systems reduced taxiing time by 15–22%, fuel consumption by 150–180 kg per flight, and engine wear by 10–14%. Carbon emissions were reduced by 472–566 kg per flight, while noise levels decreased by …
A Machine Learning-Driven Framework For Real Time Detection And Prevention Of Replica Node Attacks In Wireless Sensor Networks, Maram Pavani, Tanguturi Sharani, Amutha Jeevakumari S A
A Machine Learning-Driven Framework For Real Time Detection And Prevention Of Replica Node Attacks In Wireless Sensor Networks, Maram Pavani, Tanguturi Sharani, Amutha Jeevakumari S A
Northeast Journal of Complex Systems (NEJCS)
Mobile devices and wireless sensor networks (WSNs) are increasingly vulnerable to security threats such as unauthorized access and replica node attacks. Mobile devices face risks from replication and anomalous behavior, while attackers compromise WSNs by cloning legitimate nodes, thus threatening network integrity. Traditional security mechanisms often fall short in detecting such sophisticated threats, especially in resource-constrained environments. This research proposes a dual-component security system. A Machine Learning-Based Intrusion Detection System (IDS) for WSNs leverages Graph Neural Networks (GNNs) to detect replica nodes through structural network analysis and applies Federated Learning to preserve data privacy. The Sequential Probability Ratio Test (SPRT) …
The Spectral Response Of Time-Resolved Piv In A Turbulent Boundary Layer, Peter Manovski, Wagih Abu Rowin, Henry Ng, Paul Gulotta, Matteo Giacobello, Charitha De Silva, Nicholas Hutchins, Ivan Marusic
The Spectral Response Of Time-Resolved Piv In A Turbulent Boundary Layer, Peter Manovski, Wagih Abu Rowin, Henry Ng, Paul Gulotta, Matteo Giacobello, Charitha De Silva, Nicholas Hutchins, Ivan Marusic
Student Publications
This study presents the application of time-resolved particle image velocimetry (TR-PIV) to measure the mean and fluctuating velocity components in a turbulent boundary layer (TBL) over an axisymmetric body of revolution. A narrow wall-normal strip of the flow was captured using a synchronised high-speed laser and camera at a recording frequency of up to 80 kHz. The resulting streamwise and wall-normal velocity TR-PIV data were validated against hot-wire anemometry measurements and direct numerical simulations (DNS) of a flat plate under matched flow conditions. The mean flow results showed good agreement between all methods, while the expected attenuation due to the …
Shrinkage Study In Photopolymerisable Hybrid Sol-Gel Through Holographic Patterning, Jamshed Aftab, Izabela Naydenova, Tatsiana Mikulchyk
Shrinkage Study In Photopolymerisable Hybrid Sol-Gel Through Holographic Patterning, Jamshed Aftab, Izabela Naydenova, Tatsiana Mikulchyk
Articles
Photopolymerisation induced shrinkage of holographic materials is one of the main factors which needs to be considered for designing holographic optical elements (HOEs) with high accuracy in light redirection with maximum efficiency. This work studies the shrinkage in photopolymerisable hybrid sol-gel (PHSG) by examining the properties of volume transmission gratings recorded in PHSG layers. It explores both the dependence of shrinkage on the holographic grating parameters (thickness, spatial frequency, slant angle) and the effect of material aging. By using the fringe-plane rotation model, shrinkage is found to have the maximum value of 1.37 % at 765 lines/mm (19.36° slant angle) …
Advances In Bone And Orthopedics 2025 – 5th Edition, Jean-Philippe Berteau, Laurent Pujo-Menjouet, Hélène Follet, Aurélie Levillain
Advances In Bone And Orthopedics 2025 – 5th Edition, Jean-Philippe Berteau, Laurent Pujo-Menjouet, Hélène Follet, Aurélie Levillain
Publications and Research
This volume brings together selected works from the 2025 Bone and Orthopedics Interdisciplinary Symposium (BONITOS), underscoring our community’s ongoing commitment to advancing research in biomechanics, bone health, and orthopedic science. The symposium unites leading experts from around the world, fostering collaboration and the exchange of ideas across disciplines. Organized in partnership with the French-speaking Society of Biomechanics, the French National Institute of Health and Medical Research (INSERM), the University of Lyon, the College of Staten Island of the City University of New York (CUNY), and the American Association of Physical Therapists (APTA) – Brooklyn Staten Island Chapter, BONITOS 2025 represents …
Gbotuner: Autotuning Of Openmp Parallel Codes With Bayesian Optimization And Code Representation Transfer Learning, Kimsong Lor
Gbotuner: Autotuning Of Openmp Parallel Codes With Bayesian Optimization And Code Representation Transfer Learning, Kimsong Lor
Computer Science and Engineering Master's Theses
Empirical autotuning methods such as Bayesian optimization (BO) are a powerful approach that allows us to optimize tuning parameters of parallel codes as black-boxes. However, BO is an expensive approach because it relies on empirical samples from true evaluations for varying parameter configurations. In this thesis, we present GBOTuner, an autotuning framework for optimizing the performance of OpenMP parallel codes, where OpenMP is a widely used API that enables shared-memory parallelism in C, C++, and Fortran using simple compiler directives. GBOTuner improves sample efficiency of BO by combining code representation learning from a Graph Neural Network (GNN) into a BO …
Thermal Rheological Properties Of Heat-Moisture Modified And Its Application In Multigrain Cookies, Thi Huyen Trang, Li Xianghong, Miao Jinxu, Wang Faxiang, Liu Yongle, Li Shuang
Thermal Rheological Properties Of Heat-Moisture Modified And Its Application In Multigrain Cookies, Thi Huyen Trang, Li Xianghong, Miao Jinxu, Wang Faxiang, Liu Yongle, Li Shuang
Food and Machinery
[Objective] To develop low -burden,high -nutrient functional baked foods.[Methods] A single -factor experimental design is employed,with rapid visco analyzer,rheometer,and differential scanning calorimeter to analyze the physicochemical properties of heat -moisture modified wheat flour.The cookie formula is optimized based on sensory evaluation.[Results] Heat -moisture treatment significantly enhances the pasting stability and resistant starch content of wheat flour.The optimal auxiliary ingredient formula is 50 g of heat-moisture modified wheat flour,20 g of oat flour,10 g of mung bean flour,and 6 g of resistant dextrin powder.Compared with the control group,the cookies made from the experimental formula show a significantly lower digestibility,with a glycemic …
Multi-Field Quantum Conference Key Agreement Using An Integrated Photonic Green Machine, Benjamin J. Fisher
Multi-Field Quantum Conference Key Agreement Using An Integrated Photonic Green Machine, Benjamin J. Fisher
Theses and Dissertations
Quantum Conference Key Agreement (QCKA) enables a group of users to generate a shared secret key, which reduces the latency and equipment overhead of establishing multiple Quantum Key Distribution (QKD) links. Conventional QCKA protocols send a multi-photon entangled state from one user to others and a key is generated only when all photons are detected, which is inefficient at high loss and opens side-channels at the receiver side. Here, we overcome this barrier through a multi-field QCKA protocol enabled by designing, fabricating, and testing an integrated photonic Green Machine that implements an eight-mode Hadamard unitary transformation through a beam-splitter network. …
Computational Fluid Dynamics And Fluid Structure Interaction Modeling In Healthy Vertebral Arteries: A Comparative Study, Bryce Clinkenbeard
Computational Fluid Dynamics And Fluid Structure Interaction Modeling In Healthy Vertebral Arteries: A Comparative Study, Bryce Clinkenbeard
Electronic Theses and Dissertations
Cerebral perfusion is critical for maintaining proper brain function, with each cerebrovascular artery playing an integral role in the overall cerebrovascular system. When these arteries become damaged or develop plaque, cardiovascular disease (CVDs) such as atherosclerosis can arise, leading to conditions like arterial stenosis. While CVDs are most prevalent in older individuals, they are also observed in young adults, particularly those engaged in high-endurance occupations such as military service. Diagnosis and prediction of CVDs often rely on imaging modalities supported by computational fluid dynamics (CFD) which account for low resolution in fluid flow. CFD models assume rigid arterial walls, which …
Supercritical Co2 Technology For Biomass Extraction: Review, Bahare Nozari, Ron Kander
Supercritical Co2 Technology For Biomass Extraction: Review, Bahare Nozari, Ron Kander
School of Design and Engineering Papers
Supercritical carbon dioxide extraction is increasingly recognized as a green and efficient alternative to conventional solvent-based techniques for valorizing plant biomass. This review provides a comprehensive overview of recent advances in a scCO2 extraction method, focusing on its advantages in isolating high-value compounds from agricultural feedstocks. The unique physicochemical properties of scCO2, combining gas-like diffusivity with liquid-like solvating power, enable selective extraction under mild and tunable conditions, which preserves the integrity of thermally sensitive molecules. In addition, scCO2 reduces energy consumption, eliminates toxic solvent residues, and offers greater extraction precision than traditional methods. These features have …
Development Of An Embedded Iot Board For Real-Time Floor Estimation Of Autonomous Robots, Carter J. Sorensen
Development Of An Embedded Iot Board For Real-Time Floor Estimation Of Autonomous Robots, Carter J. Sorensen
Electronic Theses and Dissertations
As service robots become more prevalent in multi-story environments such as hospitals, hotels, and laboratories, accurate floor-level detection is critical to ensuring operational reliability. Consider a robot tasked with delivering medical samples in a multi-story laboratory. Without accurate feedback, a robot exiting on the wrong floor could introduce delays, disrupt workflows, or compromise sample integrity. Internet of Things (IoT) technologies offer a way to address these risks by providing real-time error detection and corrective capability. However, current IoT-based floor estimation systems often require invasive modifications to building infrastructure—particularly elevator control panels. These approaches introduce challenges related to cost, liability, backward …
An Advanced Hexacopter For Autonomous Exploration Of Mars: Attitude Control And Navigation Strategies, Laura Sopegno
An Advanced Hexacopter For Autonomous Exploration Of Mars: Attitude Control And Navigation Strategies, Laura Sopegno
Electronic Theses and Dissertations
Mars exploration has recently witnessed major interest within the scientific community. Unmanned robotic platforms offer reliable solutions to acquire and collect data and information from the Red Planet. Particularly, rovers, landers, and orbiters have significantly shaped planetary exploration on the Moon and Mars, contributing significantly to past missions while also highlighting limitations in their capacity to cover diverse terrains over wide ranges. Given current advances in Unmanned Aircraft Systems (UASs), Unmanned Aerial Vehicles (UAVs) offer promising alternatives for future scientific missions.
It is argued that hexacopters, with their relatively compact design and redundancy, present a promising …
Reducing Attention Complexity In Graph Transformers Through Subgraph Partitioning, Ranjan Kumar Choubey
Reducing Attention Complexity In Graph Transformers Through Subgraph Partitioning, Ranjan Kumar Choubey
Master’s Dissertations
This dissertation addresses the challenge of scaling Graph Transformers by proposing a subgraph-based strategy to reduce attention complexity. The proposed framework preserves representational power while making attention computation tractable for largescale graphs. The method begins by partitioning the input graph into K subgraphs using the METIS algorithm. Each subgraph is encoded using a combination of local structural features from a Graph Convolutional Network (GCN) and global positional cues from Laplacian Positional Embeddings (LPEs). These embeddings are fused via a trainable projection function to form subgraph tokens. A supergraph is constructed to model interactions among subgraphs, allowing attention to be applied …
Sae Baja Drivetrain Capstone 2024-2025, Leslie Alvarez Cisneros
Sae Baja Drivetrain Capstone 2024-2025, Leslie Alvarez Cisneros
University Honors Theses
This thesis reviews the 2024-2025 Baja SAE Drivetrain capstone project. The Baja SAE competition mimics real world engineering problems where teams of students design and build off-road vehicles that can handle tough, rough terrain. The objective of this capstone was to design a functional and reliable drivetrain system for the vehicle, within the constraints of a limited budget and the SAE competition guidelines. As part of a 12-member capstone team divided into three subgroups: frame, suspension, and drivetrain. As part of a four person drivetrain team, we picked up where the 2023-2024 team left off by relying on their past …
Optimized Wireless Power Transmission For Low-Cost, Energy-Efficient Internet Of Things Devices In Residential Environments, Daniel Brook Hatch
Optimized Wireless Power Transmission For Low-Cost, Energy-Efficient Internet Of Things Devices In Residential Environments, Daniel Brook Hatch
Theses and Dissertations
Wireless power transmission (WPT) offers a promising solution for powering devices in locations where traditional electrical outlets are inaccessible, such as ceilings or outdoor environments. By utilizing electromagnetic waves, such as light, WPT enables power delivery without the need for physical connections. With line-of-sight (LoS) as its primary limitation, this technology offers significant flexibility and potential for a wide range of applications, making it a compelling focus for research and innovation. Despite the advancements in WPT technologies, their practical application for powering Internet of Things (IoT) devices in real-world scenarios remains underexplored. Many IoT devices are installed in locations where …
Online Hyperparameter Tuning For Llm Optimization, Ethan Lin, Nathan Yu, Jeromy Chang
Online Hyperparameter Tuning For Llm Optimization, Ethan Lin, Nathan Yu, Jeromy Chang
Computer Science and Engineering Senior Theses
Large Language Models (LLMs) are becoming increasingly popular in modern society. However, despite their popularity, the deployment of LLMs in real-world scenarios is extremely challenging due to substantial computational costs and memory constraints. Edge devices, like smartphones and IoT devices, lack resources needed to run these models locally, instead offloading computations for cloud computing. Cloud computing requires users to send their data over the internet leading to numerous privacy and security concerns. In some domains, such as health and finances, sending such sensitive information is not an option. Existing solutions to compress or increase inference speed include Small Language Models …
Piloted Autonomous Crisis Reconnaissance Robot 2.0 (Pacrr 2.0), Awawu Alimi, Urmika Ghosh, Marissa Kuo, Jonathan Santosa, Ethan Wyrick
Piloted Autonomous Crisis Reconnaissance Robot 2.0 (Pacrr 2.0), Awawu Alimi, Urmika Ghosh, Marissa Kuo, Jonathan Santosa, Ethan Wyrick
Electrical and Computer Engineering Senior Theses
PACRR 2.0 (Piloted Autonomous Crisis Reconnaissance Robot, version 2) builds upon the original low-cost, autonomous-capable quadruped platform by enhancing both mobility and environmental perception for first-responder applications such as search and rescue, gas leak detection, and mapping of confined or hazardous areas. In PACRR 2.0, we integrate an RGB-D camera with analytic inverse kinematics and frame-based motion planning to achieve precise foot placement and stable quasi-static gaits even on sloped or uneven terrain. An NVIDIA Jetson processor runs high-level control and mapping alongside a Raspberry Pi 4 to manage motor control. Through simulation, we demonstrate robust 3D map generation and …
Predictive Analysis Of Crash Severity And Modeling Of 85th Percentile Speed For Rural Highways Of Arkansas Using Artificial Intelligence (Ai), Sagun Basel
Student Theses and Dissertations
Crash severity is a significant aspect of transport safety as its contributing factors assist engineers and designers in designing safer roads. The focus of this project is to predict crash severity, analyze crash parameters, and modeling of the 85th percentile speed (V85) selected rural roads (i.e., Interstate-555, East Johnson Avenue Highway, and Red Wolf Blvd) in Arkansas, using Artificial Neural Network (ANN) models. MATLAB® was used to predict the V85 and compare it with the actual V85 collected from field instrumentation. Besides the speed data, weather (e.g., rainfall), road geometry, light conditions, and traffic volume were used as input in …
A Modular Simulation Environment And B-Spline Trajectory Generation Methods For Multi-Agent Uav Systems, Landon D. Shumway
A Modular Simulation Environment And B-Spline Trajectory Generation Methods For Multi-Agent Uav Systems, Landon D. Shumway
Theses and Dissertations
Multi-agent UAV systems present a complex challenge requiring solutions to numerous subproblems. This research addresses two key issues: simulation testing and path planning. A modular simulation environment is developed, enabling users to run diverse mission scenarios with heterogeneous UAV teams and to implement custom dynamic models and guidance laws. Additionally, two novel B-spline trajectory generation methods are proposed. The first generates time-synchronized B-spline paths for UAVs with arbitrary initial and final states in 2D space, accommodating scenarios where agents must follow predetermined speed profiles. The second guidance method converts spline paths between MINVO, Bézier, and non-uniform B-spline representations, leveraging the …
The Dpe Shortage And How To Fix It, Paul Dye
The Dpe Shortage And How To Fix It, Paul Dye
Honors Theses
The following content delves into the current issues surrounding the FAA’s designated pilot examiner (DPE) system, which, while functional, is increasingly strained by growing demand and outdated policies. Through firsthand experience, survey data, and analysis of current practices, the paper emphasizes some of the most pressing problems, including scheduling inefficiencies, inconsistent examiner expectations, manual eligibility checks despite the widespread use of digital logbooks, and a lack of meaningful oversight or feedback mechanisms for both DPEs and CFIs.
A major focus is the outdated scheduling process, which remains largely decentralized and prone to double-booking, cancellations, and long wait times, especially for …
Tunable Methacrylated Decellularized Heart Matrix: A Versatile Scaffold For Cardiac Tissue Engineering, Valinteshley Pierre, Douglas H. Wu, Chao Liu, Elif Ertugral, Chandrasekhar R. Kothapalli, Samuel E. Senyo
Tunable Methacrylated Decellularized Heart Matrix: A Versatile Scaffold For Cardiac Tissue Engineering, Valinteshley Pierre, Douglas H. Wu, Chao Liu, Elif Ertugral, Chandrasekhar R. Kothapalli, Samuel E. Senyo
Chemical & Biomedical Engineering Faculty Publications
Therapeutic tissue regeneration remains a significant unmet need in heart failure and cardiovascular disease treatment, which are among the leading causes of death globally. Decellularized heart matrix (DHM) offer promising advantages for tissue engineering, including low immunogenicity and seamless integration into biological processes, facilitating biocompatibility. However, DHM is challenged by weak mechanical properties that limit its utility to biomedical applications like tissue engineering. To address this limitation, we functionalized DHM with methacryloyl functional groups (DHMMA) that support UV-induced crosslinking to enhance mechanical properties. By modulating the degree of methacryloyl substitution, a broad range of stiffness was achieved while maintaining cell …
Remote Sensing Of Seismic Signals Via Enhanced Moiré-Based Apparatus Integrated With Active Convolved Illumination, Adrian A. Moazzam, Anindya Ghoshroy, Durdu Güney, Roohollah Askari
Remote Sensing Of Seismic Signals Via Enhanced Moiré-Based Apparatus Integrated With Active Convolved Illumination, Adrian A. Moazzam, Anindya Ghoshroy, Durdu Güney, Roohollah Askari
Michigan Tech Publications
The remote sensing of seismic waves in challenging and hazardous environments, such as active volcanic regions, remains a critical yet unresolved challenge. Conventional methods, including laser Doppler interferometry, InSAR, and stereo vision, are often hindered by atmospheric turbulence or necessitate access to observation sites, significantly limiting their applicability. To overcome these constraints, this study introduces a Moiré-based apparatus augmented with active convolved illumination (ACI). The system leverages the displacement-magnifying properties of Moiré patterns to achieve high precision in detecting subtle ground movements. Additionally, ACI effectively mitigates atmospheric fluctuations, reducing the distortion and alteration of measurement signals caused by these fluctuations. …
Evolutionary Influences On Oceanic Islands Parasites: Phylogeography, Genetic Structure, And The “Island Rule” Of Common Ground Doves (Columbina Passerina) And Their Lice, Paige Jordan Brewer
Evolutionary Influences On Oceanic Islands Parasites: Phylogeography, Genetic Structure, And The “Island Rule” Of Common Ground Doves (Columbina Passerina) And Their Lice, Paige Jordan Brewer
Student Theses and Dissertations
Organisms on oceanic island archipelagos often exhibit strong genetic signatures and adaptations. Here, we focus on Common Ground Doves (Columbina passerina) and their parasitic lice, Physconelloides body lice and Columbicola wing lice, across the Caribbean islands to examine phylogeography, population genetics, and the “Island rule”. We used genome-wide sequences and found C. passerina doves and their lice exhibited unique dispersal patterns and phylogenetic relationships; however, similar population structure. We also found distinct patterns of genetic diversity between Physconelloides and Columbicola, likely caused by variations in their dispersal abilities. Additionally, we measured C. passerina specimens and their lice to compare island …
Sees Presentation: Small Satellites Power Systems, Robert J. Twiggs
Sees Presentation: Small Satellites Power Systems, Robert J. Twiggs
Robert "Bob" Twiggs STEM Education Collection
A PowerPoint Presentation created by Professor Bob Twiggs titled "SEES Presentation: Small Satellites Power Systems" from June 12, 2025.
How Education Sats Started, Robert J. Twiggs
How Education Sats Started, Robert J. Twiggs
Robert "Bob" Twiggs STEM Education Collection
A PowerPoint Presentation created by Professor Bob Twiggs titled "How Education Sats Started" from June 12, 2025.
Space Program, Robert J. Twiggs
Space Program, Robert J. Twiggs
Robert "Bob" Twiggs STEM Education Collection
A PowerPoint Presentation created by Professor Bob Twiggs titled "Space Program" from June 12, 2025.
Optimizing The Use Of Sustainable Additives In Subgrade Soil Stabilization, Orchi Mallick
Optimizing The Use Of Sustainable Additives In Subgrade Soil Stabilization, Orchi Mallick
Student Theses and Dissertations
Subgrade soil critically impacts pavement lifespan, where poor conditions lead to premature failure. This study evaluates soil stabilization of AASTHO classified, A-4 and A-6 soil, using sustainable additives: Rice Husk Ash (RHA), Reclaimed Fly Ash (RFA), and a traditional stabilizer Hydrated Lime (HL). Laboratory tests (Atterberg Limits, Modified Proctor, California Bearing Ratio (CBR), and Free Swell) were conducted on untreated and treated soils with RHA (3%, 6%, and 9% by weight), HL (1%, 3%, and 5% by weight), RFA (4%, 6%, and 8% by weight), and combinations of HL + RHA. Results showed all stabilizers improved strength and reduced swell. …
Intelligent Intrusion Detection In Clustered Wireless Sensor Networks: A Dynamic Clustering And Machine Learning-Based Approach, Abdullah R. Abdulwahhab, Mohd Fadzli Mohd Salleh, Muhammad Firdaus Akb, Mohammed Najm Abdullah
Intelligent Intrusion Detection In Clustered Wireless Sensor Networks: A Dynamic Clustering And Machine Learning-Based Approach, Abdullah R. Abdulwahhab, Mohd Fadzli Mohd Salleh, Muhammad Firdaus Akb, Mohammed Najm Abdullah
Iraqi Journal for Computer Science and Mathematics
Traditional Intrusion Detection Systems (IDS) designed for more conventional network infrastructures are often ill-equipped to handle the unique challenges WSNs pose, leading to significant gaps in security and resilience. This paper introduces an Intelligent Intrusion Detection System (IIDS) explicitly tailored for clustered WSNs to address these critical challenges. The proposed IIDS integrates dynamic clustering with advanced machine learning algorithms to create a robust and adaptive security solution capable of real-time threat detection and mitigation. The dynamic clustering mechanism is designed to continuously monitor and respond to changes in sensor node network topology and energy levels, ensuring that energy consumption is …
Non-Overlapping Patch-Based Pre-Trained Cnn For Breast Cancer Classification, Lamyaa Sabeeh Ashour, Ahmed Abed Mohammed, Mustafa M. Abd Zaid, Putra Sumari, Ahmed Kateb Jumaah Al-Nussairi, Sura Abdulateef Al-Shammari, Sarah Thabit Abdulmunem
Non-Overlapping Patch-Based Pre-Trained Cnn For Breast Cancer Classification, Lamyaa Sabeeh Ashour, Ahmed Abed Mohammed, Mustafa M. Abd Zaid, Putra Sumari, Ahmed Kateb Jumaah Al-Nussairi, Sura Abdulateef Al-Shammari, Sarah Thabit Abdulmunem
Iraqi Journal for Computer Science and Mathematics
Breast cancer (BC) significantly impacts women's mortality rates and requires early detection to improve survival chances and enable appropriate treatment. Thus, a computer-aided system with high performance can speed up this process. A convolutional neural network (CNN) is considered sensitive to insufficient, noisy data. It cannot achieve high performance, however, restricted access to high-quality medical data, stemming from stringent confidentiality and privacy issues, is a considerable obstacle to the successful training of deep learning models. The current study aims to develop a remarkable, influential model for BC classification whilst considering modern pre-trained models ResNet50, AlexNet, InceptionV3 and VGG16 for extracting …
Retracted: Navigating The Complexities And Artificial Intelligence Of Internet Of Things Security Claims, Tamara Saad Mohamed, Saad Mohammed Khalifah
Retracted: Navigating The Complexities And Artificial Intelligence Of Internet Of Things Security Claims, Tamara Saad Mohamed, Saad Mohammed Khalifah
Iraqi Journal for Computer Science and Mathematics
The term ``Internet of Things'' (IoT) describes a system that allows everyday objects to communicate with one another and with controlled systems, servers, and other linked devices through a variety of connectivity constructions by means of embedded software, sensor technology, electronics, and connections. Data from the Internet of Things (IoT) will be sent to the servers over the internet from a variety of sensors, nods, and collectors. Governments, medical facilities, consumers, and corporations all make use of IoT devices. approximately, More than 65 billion Internet of Things devices are expected to be in operation by 2024. The proliferation of IoT …