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Articles 29551 - 29580 of 29612
Full-Text Articles in Entire DC Network
Decoupling Sustainability And Performance: How Government Infrastructure Projects In Australia Fare On Strategic Environmental Commitments, Richard Hughes, Kerry Brown
Decoupling Sustainability And Performance: How Government Infrastructure Projects In Australia Fare On Strategic Environmental Commitments, Richard Hughes, Kerry Brown
Research outputs 2022 to 2026
Australian government organisations are pivotal in helping to meet the United Nations sustainable development goals. Yet while these organisations promote sustainability in their strategic plans, they struggle to embed these same commitments into their own infrastructure and construction projects. This study examines this persistent disconnect using the lens of strategic decoupling, which explains how organisations symbolically align with external expectations while internal practices remain unchanged. Using a two-stage qualitative design, we conducted a positivist discourse analysis of strategic artefacts from six government organisations and a theoretically informed interpretivist analysis of 30 interviews with project professionals, framed by strong structuration theory. …
Influence Of Rice Hull Biochar And Cedar Bark Media On Strawberry Productivity And Carbon Sequestration Potential In Hydroponic Systems, Sakalya Rajapakse, Munehiro Tanaka
Influence Of Rice Hull Biochar And Cedar Bark Media On Strawberry Productivity And Carbon Sequestration Potential In Hydroponic Systems, Sakalya Rajapakse, Munehiro Tanaka
Research outputs 2022 to 2026
This study evaluated the influence of rice hull biochar (RHB) and cedar bark media (CBM) as sustainable substrates for hydroponic strawberry cultivation. The total yield from virgin CBM was 413 g/plant and that from virgin RHB was 354 g/plant. Used CBM increased the yield by 4 % (429 g/plant) while used RHB increased yield by 18 % (419 g/plant) compared to the virgin, with no significant substrate differences. Fruit yields and physical properties were strongly correlated, particularly with particle density (R2 = 0.573). After 7 years of cultivation, plant residues had accumulated in both substrates. Uncarbonized carbohydrates in RHB indicated …
Assessing The Application Of Optical-Photothermal Infrared Spectroscopy For Single-Grain Chemical Palynology, Laura Scoble, Hao Meng, Simon J. Ussher, Mark F. Fitzsimons, Lauren Ansell, Mustafa Kansiz, Billy Simmonds, Nick Stone, Ralph M. Fyfe
Assessing The Application Of Optical-Photothermal Infrared Spectroscopy For Single-Grain Chemical Palynology, Laura Scoble, Hao Meng, Simon J. Ussher, Mark F. Fitzsimons, Lauren Ansell, Mustafa Kansiz, Billy Simmonds, Nick Stone, Ralph M. Fyfe
School of Geography, Earth and Environmental Sciences
Single-grain pollen analysis is essential for advancing chemical palynology, which classifies morphologically similar taxa based on taxon-specific pollen and sporopollenin chemistry. Fourier-Transform Infrared (FT-IR) spectroscopy and microspectroscopy (μFT-IR) are widely used to differentiate morphologically similar grains but face limitations from Mie scattering and coarse spatial resolution. Here, we present the first application of Optical-PhotoThermal Infrared (O-PTIR) spectroscopy to chemically treated single pollen grains, using Molinia caerulea as a model taxon to fully test and evaluate the technical capabilities and limitations of this technique. O-PTIR achieves sub-micron “super-resolution” infrared spectroscopy through non-contact, non-destructive measurements by exploiting the photothermal effect. O-PTIR spectra …
Rock On Technology: Perspectives Of People With Neurological Conditions On Robot-Assisted Lower Limb And Gait Neurorehabilitation, Rachel G. Buckingham, Saran Chamberlain, Amanda Timler, Matthew K. Bagg, Nikki E. Bakhtazad, Taya Hamilton, Patricia Martinet, Bianca Haagman, Stuart I. Hodgetts, Barbara Singer, Ann Maree Vallence, Jodie Marquez, Eric Gaitho, Emma Gee, Jessica Nolan
Rock On Technology: Perspectives Of People With Neurological Conditions On Robot-Assisted Lower Limb And Gait Neurorehabilitation, Rachel G. Buckingham, Saran Chamberlain, Amanda Timler, Matthew K. Bagg, Nikki E. Bakhtazad, Taya Hamilton, Patricia Martinet, Bianca Haagman, Stuart I. Hodgetts, Barbara Singer, Ann Maree Vallence, Jodie Marquez, Eric Gaitho, Emma Gee, Jessica Nolan
Research outputs 2022 to 2026
Purpose: Explore perspectives of people living with neurological conditions in Western Australia (WA) on robot-assisted lower limb neurorehabilitation (RALLR), and implementation requirements. Materials and methods: This co-designed, qualitative descriptive study included people living with neurological conditions. In-person semi-structured focus groups (FGs) were facilitated by a person with lived experience of stroke. FGs were recorded, data were transcribed, and thematically analysed using a reflexive approach. Results: Five FGs included 24 participants (54.2% women, median age 50 years). Of these, thirteen participants had RALLR experience. Primary neurological conditions represented among participants comprised spinal cord injury (n = 11), stroke (n = 3), …
Nutrient Legacy And Cycling In The Somerset Levels And Moors, Oscar Kemble, Paul Lunt
Nutrient Legacy And Cycling In The Somerset Levels And Moors, Oscar Kemble, Paul Lunt
School of Geography, Earth and Environmental Sciences
1. Executive summaryThe Somerset Levels and Moors (SLMs) are one of the UK’s most extensive and ecologically significant lowland wetland systems, supporting internationally important bird populations and nationally important assemblages of wetland plants and invertebrates. However, the ecological condition of the SLMs Ramsar and underpinning SSSIs has deteriorated in recent decades, driven primarily by phosphorus (P) enrichment. In 2021, Natural England downgraded the SLMs to “unfavourable declining”, citing persistent eutrophication, floating plant dominance, and loss of submerged macrophytes as key symptoms.This review synthesises current evidence and provides critical overviews for the following themes: (1) The Somerset Levels and Moors (SLMs) …
Algorithm Envelopment In Platform Markets, Liang Chen, Zhou Zhou, Lester Chan
Algorithm Envelopment In Platform Markets, Liang Chen, Zhou Zhou, Lester Chan
Research Collection Lee Kong Chian School Of Business
The theory of platform envelopment rests on network effects as the key mechanism for value creation, which nonetheless receives mixed support for its efficacy in determining competitive outcomes. We argue that the value of network effects depends on matching quality, which is a function of platform-specific algorithm technology and market-level data-driven learning. In formalizing these conceptualizations, we analyze a model that demonstrates how an entrant with a superior algorithm technology may outcompete an incumbent possessing a user base advantage, a strategy we call “algorithm envelopment.” By considering specific characteristics of data-driven learning, our analysis leads to propositions regarding the entry …
Influence Of Surface Features On Heat Transfer During Dropwise Condensation Over Superhydrophobic Surfaces In Shear Flow, Shaur Humayun, R. Daniel Maynes, Julie Crocket, Brian D. Iverson
Influence Of Surface Features On Heat Transfer During Dropwise Condensation Over Superhydrophobic Surfaces In Shear Flow, Shaur Humayun, R. Daniel Maynes, Julie Crocket, Brian D. Iverson
Faculty Publications
This study investigates heat transfer during dropwise condensation (DWC) on superhydrophobic (SH) surfaces in humid air shear flow, emphasizing the effect of increased drop mobility and the influence of surface micro/nanostructure on heat transfer rates. Experiments were conducted on smooth hydrophobic, microstructured SH, nanostructured carbon-infiltrated carbon nanotube (CICNT) surfaces, and two-tiered SH surfaces with both micro and nanostructures. Heat transfer rates were measured under humid air flow rates in the range of 2–4 CFM. Experimental results demonstrate that surfaces with nanostructure (including two-tiered structures) exhibit increased drop mobility and coalescence-induced drop jumping, enhancing drop removal rates and overall heat transfer …
Moringa Oleifera As An Immunomodulator, Noha Swilam, Khaled A. Nematallah, Omayma Eldahshan'
Moringa Oleifera As An Immunomodulator, Noha Swilam, Khaled A. Nematallah, Omayma Eldahshan'
Pharmacy
Moringa oleifera has gained increasing attention for its diverse pharmacological properties, including its potential to modulate immune responses. This chapter explores the immunomodulatory potential of M. oleifera, exploring both its phytochemical composition and experimental evidence from in vitro and in vivo studies. Key bioactive constituents, such as flavonoids (quercetin, kaempferol, apigenin), phenolic acids (chlorogenic, ferulic, caffeic), glucosinolates (glucomoringin) and their hydrolysis product, benzyl isothiocyanate, are identified as contributors to its immune-regulating properties. It has been demonstrated that these substances affect cytokine expression, suppress pro-inflammatory mediators, increase phagocytic activity and alter lymphocyte reactions. In order to support the plant's traditional use …
Multihoming And Single-Homing Complementors' Responses To Intensified Between-Platform Competition: Evidence From The Youtube–Twitch Rivalry, Niloofar Abolfathi
Multihoming And Single-Homing Complementors' Responses To Intensified Between-Platform Competition: Evidence From The Youtube–Twitch Rivalry, Niloofar Abolfathi
Research Collection Lee Kong Chian School Of Business
Research Summary: This paper examines how heterogeneous YouTube content creators-specifically, single-homing and multihoming channels-respond to a sudden increase in the exposure of the rival platform, Twitch. Contrary to expectations, I find that multihoming channels reduce their content creation efforts and underperform relative to single-homers. To make sense of these surprising results, I develop a formal model that characterizes the strategic behavior of different types of complementors operating across two platforms with varying levels of user exposure. The model offers a plausible explanation for the observed empirical patterns, suggesting that intensified competition between platforms, as a consequence of their changing exposure, …
Harmonic Mitigation And Reactive Power Support Using Dpfc And Upfc In Grid‑Connected Solar Pv Systems: A Comparative Performance Evaluation, Abhishek Vashistha, Dharmbir Prasad, Rudra Pratap Singh
Harmonic Mitigation And Reactive Power Support Using Dpfc And Upfc In Grid‑Connected Solar Pv Systems: A Comparative Performance Evaluation, Abhishek Vashistha, Dharmbir Prasad, Rudra Pratap Singh
Mansoura Engineering Journal
Harmonic distortion, reactive power imbalance, and voltage instability represent major challenges regarding the power quality of grid-connected solar photovoltaic (PV) systems. Various recently developed flexible AC transmission system (FACTS) devices such as the unified power flow controller (UPFC) and distributed power flow controller (DPFC), however, have made them possible solutions but still do not provide a quantitative comparison in similar dynamic conditions. In this paper, comparative performance analysis of UPFC and DPFC in 3 MW grid connected solar PV system using Matlab Simulink is presented. The two controllers are affected by same disturbances, namely irradiance step change at t = …
Performance Enhancement Of A Fully Integrated Solar Still Using Flat Plate Collector, Reflector, And Evaporative Cooling System, Joe Patrick Gnanaraj Sundararaj, Vanthana Jeyasingh
Performance Enhancement Of A Fully Integrated Solar Still Using Flat Plate Collector, Reflector, And Evaporative Cooling System, Joe Patrick Gnanaraj Sundararaj, Vanthana Jeyasingh
Mansoura Engineering Journal
Water scarcity has become a major global concern due to increasing population growth, industrialization, and depletion of freshwater resources. Solar desalination is considered an eco-friendly and sustainable solution, especially for rural and off-grid regions where conventional water treatment facilities are limited. However, conventional solar stills suffer from low productivity, which restricts their practical application. In this study, a fully integrated solar still system was designed and fabricated by incorporating a flat plate collector, front-wall reflector, and passive evaporative cooling arrangement. The system was experimentally tested under natural climatic conditions over seven consecutive days to evaluate temperature variation, distillate yield, and …
A Hybrid Geoid Model For The Perlis Region, Malaysia Based On Cadastral Reference Marks And A Geometric Approach, Muhammad Aiman Haiqal Abdul Malek, Muhammad Faiz Pa’Suya, Ramazan Alpay Abbak, Ami Hassan Md Din, Noorfatekah Talib
A Hybrid Geoid Model For The Perlis Region, Malaysia Based On Cadastral Reference Marks And A Geometric Approach, Muhammad Aiman Haiqal Abdul Malek, Muhammad Faiz Pa’Suya, Ramazan Alpay Abbak, Ami Hassan Md Din, Noorfatekah Talib
Mansoura Engineering Journal
This study presents the development of a high-resolution local geoid model for the Perlis region, Malaysia, using a geometric approach that integrates GNSS-levelling benchmarks with Cadastral Reference Mark (CRM) data. A total of 38 GNSS-levelling benchmarks were used as reference points, while 3,725 CRMs were incorporated to significantly enhance spatial coverage for geoid modelling. Orthometric heights at the CRM points were first determined by transferring heights from the reference benchmarks using gravimetric geoid information. Subsequently, geometric geoid heights were computed from the differences between ellipsoidal and orthometric heights. Five interpolation techniques were evaluated to generate the geometric geoid surface, namely …
An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare
An Iterative & Analytical Hybrid Deep Learning Framework For Enhanced Brain Tumor Detection And Segmentation In Mri Video Scans, Swati V. Sakhare
Mansoura Engineering Journal
The critical need for accurate and robust brain tumor detection in MRI video scans is for early diagnosis and treatment planning operations. However, the existing methods suffer from several limitations, such as not being able to capture spatio-temporal features, handling class imbalances, and generalizing across datasets with diverse characteristics. To address these challenges, I propose a hybrid deep learning framework that integrates multiple advanced techniques to enhance the detection and segmentation of brain tumors. My approach starts by using the 3D CNN-LSTM (ResNet3D-LSTM) to extract spatio-temporal feature, which utilizes ResNet3D for spatial detail extraction and LSTM for temporal coherence across …
Comparative Finite Element Method-Based Optimisation Of Coir Fibre Laminates: Aluminium Skins Versus Carbon Cloth Skins, Muhamed Swaleh Ahmed, Bernard Wamuti Ikua, Abel Nyakundi Mayaka
Comparative Finite Element Method-Based Optimisation Of Coir Fibre Laminates: Aluminium Skins Versus Carbon Cloth Skins, Muhamed Swaleh Ahmed, Bernard Wamuti Ikua, Abel Nyakundi Mayaka
Mansoura Engineering Journal
Natural fibre composites offer a sustainable alternative to conventional composite materials. Their mechanical efficiency is influenced by laminate structure and skin material selection. This study presents a comparative finite element analysis and optimisation of coir fibre-reinforced laminates employing either aluminium skins or carbon cloth skins. COMSOL Multiphysics was used to determine their mechanical response. Optimisation was performed using the BOBYQA algorithm to enhance load sharing between the coir core and skin materials. Results indicated that aluminium-skinned laminates achieve superior compressive and flexural performance, achieving a peak compressive strength of 210 MPa and sustaining a flexural load of 0.65 kN at …
A Machine Learning–Based Framework For Traffic Classification And Threshold-Based Load Management In 5g Network Slicing, Safi Ibrahim, Younis S. Younis, Kamal S. Hamza, Mohamed M. Ashour
A Machine Learning–Based Framework For Traffic Classification And Threshold-Based Load Management In 5g Network Slicing, Safi Ibrahim, Younis S. Younis, Kamal S. Hamza, Mohamed M. Ashour
Mansoura Engineering Journal
This study proposes a machine learning–based framework that applies machine learning techniques to improve the efficiency of 5G network slicing through automated traffic classification and threshold-based load management . The proposed model optimizes resource allocation among the three standardized 5G slice types: enhanced Mobile Broadband (eMBB), ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC). Two supervised learning algorithms—K-Nearest Neighbors (KNN) and Support Vector Machine (SVM)—are trained using Quality of Service (QoS) parameters such as packet delay, loss rate, and Quality Class Identifier (QCI). Experimental evaluations were conducted on two large-scale datasets containing over 400,000 traffic instances, demonstrating that the …
Optimizing The Lightweight Steel Fibre Reinforced Bacterial Concrete With Nano-Silica And Coconut Shell Aggregates Using Taguchi Method, Damodaran Pooja, Mayilsamy Yuvaperiyasamy
Optimizing The Lightweight Steel Fibre Reinforced Bacterial Concrete With Nano-Silica And Coconut Shell Aggregates Using Taguchi Method, Damodaran Pooja, Mayilsamy Yuvaperiyasamy
Mansoura Engineering Journal
Concrete is essential for construction due to its high strength and durability. It supports most modern infrastructure globally. Cement production is a major source of CO₂ emissions, posing serious environmental concerns. Additionally, the rising demand for concrete is straining the limited supply of essential raw materials, such as aggregates. Researchers are examining alternative materials to improve Sustainability while maintaining structural strength to address these issues. This research aims to improve concrete performance by enhancing cement durability with nano-silica. Coconut shell, an agricultural by-product, functions as an eco-friendly alternative to conventional coarse aggregates, alleviating their scarcity. Microbiologically induced calcium carbonate precipitation …
A Dual-Domain Face Forgery And Deepfake Detection Framework, Neha Pradyumna Bora, Pradyumna Mulchand Bora, Rushikesh Sanjay Kumavat, Raunak Manoj Gangwal, Prit Sandesh Jain, Hardik Vijay Ostwal
A Dual-Domain Face Forgery And Deepfake Detection Framework, Neha Pradyumna Bora, Pradyumna Mulchand Bora, Rushikesh Sanjay Kumavat, Raunak Manoj Gangwal, Prit Sandesh Jain, Hardik Vijay Ostwal
Mansoura Engineering Journal
Concerns about media authenticity, privacy, and information security arising from rapid advances in deepfake technology have made it increasingly important to detect manipulated facial content reliably. The primary goal of our work was to develop a deepfake detection model with high generalization across multiple datasets. To achieve this, we developed a hybrid detection approach that combines spatial visual texture analysis and frequency-domain analysis to detect manipulated facial images. Our approach includes convolutional spatial feature extraction from facial images and frequency—domain representations of the same images obtained by applying the fast Fourier transform. To help alleviate concerns about overreliance on frequency—domain …
Edge Guided Channel Attention In Fsrcnn: A Novel Approach For Depth Super Resolution, Yagneshkumar Jayantilal Parmar, Paresh M. Dholakia
Edge Guided Channel Attention In Fsrcnn: A Novel Approach For Depth Super Resolution, Yagneshkumar Jayantilal Parmar, Paresh M. Dholakia
Mansoura Engineering Journal
Depth images from low-cost sensors often suffer from blurred edges and structural distortions when processed with standard super-resolution models. While FSRCNN is efficient for RGB images, it struggles to handle the unique geometric requirements of depth maps. To solve this, we propose the Edge Guided Channel Attention FSRCNN (EGCA FSRCNN). This method incorporates an edge-guided modulation mechanism to preserve object boundaries and a Squeeze and Excitation (SE) block to focus on critical structural features. A major benefit of this framework is the use of frozen, pretrained FSRCNN weights, which bypasses the requirement for retraining. Our evaluation on the UTKinect, Middlebury, …
Multi-Method Energy Optimization: Linear Programming, Hmm Modeling And Arduino-Based Simulations, A.E. El-Alfy, Eman Elayat, M. A. E. Sheta
Multi-Method Energy Optimization: Linear Programming, Hmm Modeling And Arduino-Based Simulations, A.E. El-Alfy, Eman Elayat, M. A. E. Sheta
Mansoura Engineering Journal
This paper presents the simulation and optimization of hybrid energy systems integrating renewable energy and storage technologies. Linear Programming (LP) is utilized to minimize operational costs, while a Hidden Markov Model (HMM) improves reliability by accurately predicting energy flow. Hardware-in-the-loop simulation in Proteus demonstrates efficient energy trading, significantly reducing dependence on conventional sources. The results from a 24-hour analysis show that the system achieves an 87.14% load factor, indicating high efficiency in utilizing the system's rated capacity, 26.23 system reliability, and a 20% improvement in cost efficiency and enhanced sustainability, providing a robust and practical framework for hybrid energy solutions …
Trident-Bladder: A Resolution-Aware Multimodal System For Robust, Calibrated Bladder Cancer Diagnosis Across Endoscopy, Histopathology, And Liquid Biopsy, K. Sankar, S. Venkata Lakshmi, Gummadi Reshma, V. Gokula Krishnan, M. Ganesan, V. Vijayaraja
Trident-Bladder: A Resolution-Aware Multimodal System For Robust, Calibrated Bladder Cancer Diagnosis Across Endoscopy, Histopathology, And Liquid Biopsy, K. Sankar, S. Venkata Lakshmi, Gummadi Reshma, V. Gokula Krishnan, M. Ganesan, V. Vijayaraja
Mansoura Engineering Journal
Bladder cancer diagnosis demands the integration of cystoscopy, histopathology, and biomarker testing, yet the majority of AI systems continue to be modality, specific and sensitive to acquisition variations. TRIDENT, Bladder is a resolution, aware multimodal framework that we have developed to address this issue. The method combines cystoscopic lesion segmentation, whole, slide image (WSI) molecular subtype prediction, and urine miRNAclinical data through reliability, weighted fusion and a utility, aware decision policy. The endoscopic branch features a quality, gated super, resolution component, resulting in mDice 87.5, sensitivity 92.1%, precision 91.4%, boundary, F1 85.3%, and ECE 0.023 at 32 FPS. mDice on …
Green Hydrogen-Based Decarbonization Approach For Steel Industry With Hybrid Renewable Energy Sources, Raju Kumar Maurya, Dharmbir Prasad, Rudra Pratap Singh
Green Hydrogen-Based Decarbonization Approach For Steel Industry With Hybrid Renewable Energy Sources, Raju Kumar Maurya, Dharmbir Prasad, Rudra Pratap Singh
Mansoura Engineering Journal
This work provides a micro-pilot techno-economic and environmental assessment of a green hydrogen-driven decarbonization scenario for low-carbon steel production at the capacity of 1 ton steel produced (i.e., requiring 50 kg of green hydrogen). In this work an integrated renewable energy (RE) scenario for the steel production site at Jamuria, West Bengal, India is planned to utilize solar photovoltaic (PV), wind turbines (WTs), battery storage and a diesel backup generator to meet the hydrogen production load from an electrolyzer using HOMER Pro software. The results show that the proposed micro-pilot system produces excess electricity with respect to the plant's operating …
Finite Element Analysis Of Oxygen Transport In Tissue And Capillaries With A Second Order Metabolic Consumption, Vikash Ramcharitar, Sreedhara Rao Gunakala, Reddappa Bandi, Donna M. G. Dyer, Jagdesh Ramnanan
Finite Element Analysis Of Oxygen Transport In Tissue And Capillaries With A Second Order Metabolic Consumption, Vikash Ramcharitar, Sreedhara Rao Gunakala, Reddappa Bandi, Donna M. G. Dyer, Jagdesh Ramnanan
Mansoura Engineering Journal
This study presents a numerical investigation into the oxygen transport through a Krogh-type capillary-tissue model with second-order tissue metabolism. The governing non-linear equations are solved by implementing a Galerkin finite element method with a fixed-point iteration scheme. The resulting code and solution algorithm were successfully validated against available analytical solutions for zeroth- and first-order kinetics, showing very good agreement. Numerical simulations indicated, that under the parameters investigated, relative to zeroth- and first-order kinetics, a second-order metabolism leads to less overall oxygen consumption within the tissue phase. This yields higher oxygen partial pressures at the outer tissue boundary and higher oxygen …
Elli’S Liquid Flow In A Wavy Channel With Slip Effect, Wall Properties, And Heat Transfer, P. Devaki, Yatin Sood
Elli’S Liquid Flow In A Wavy Channel With Slip Effect, Wall Properties, And Heat Transfer, P. Devaki, Yatin Sood
Mansoura Engineering Journal
The dual behavior of Elli’s fluid motivated us to work on it. The fluid behaves as both Newtonian/ non-Newtonian based on the low and high shear rates, respectively. The paper focused on the flow of Ellis fluid in a peristaltic channel with wall properties and heat transfer. The channel is symmetric in nature, and slip conditions are considered near the elastic walls. The governing equations of the flow are solved analytically using suitable boundary conditions, which yield velocity and temperature functions. The novelty of the paper is to analyze the nature of Newtonian/non-Newtonian fluids under the same conditions so that …
Intelligent Audio‑To‑Indian Sign‑Language And Sign‑To‑Audio Translation System Using Mediapipe, Tensorflow, Whisper And Google Tts, N. Pothanna, T. Kusuma, S. Haindavi, T. Sreeja, Shaik Shaheem Taj
Intelligent Audio‑To‑Indian Sign‑Language And Sign‑To‑Audio Translation System Using Mediapipe, Tensorflow, Whisper And Google Tts, N. Pothanna, T. Kusuma, S. Haindavi, T. Sreeja, Shaik Shaheem Taj
Mansoura Engineering Journal
Communication barriers between the Deaf community and the general public remain a persistent challenge, particularly in multilingual settings where Indian Sign Language (ISL) is the primary mode of interaction. We propose a real-time bidirectional translation framework integrating MediaPipe for hand landmark extraction, a Convolutional Neural Network (CNN) classifier built with TensorFlow/Keras for gesture recognition, OpenAI Whisper for robust multilingual speech-to-text transcription, and Google TTS for naturalistic speech synthesis. The system achieves 93% classification accuracy across 35 ISL classes (alphabets A–Z and numerals 1–9) on a dataset of 42,700 images, with macro and weighted F1-scores of 0.93. Deployed as a Flask …
Code-Net++: An Attention-Guided Deep Learning Framework With Grad-Cam-Based Explainability For Covid-19 Detection Using Chest X-Ray Images, Fareesa Amina, Dr Krishnanaik Vankdoth
Code-Net++: An Attention-Guided Deep Learning Framework With Grad-Cam-Based Explainability For Covid-19 Detection Using Chest X-Ray Images, Fareesa Amina, Dr Krishnanaik Vankdoth
Mansoura Engineering Journal
Chest radiograph imaging has emerged as a practical and scalable diagnostic modality for respiratory diseases, including COVID-19. However, accurate discrimination of COVID-19 manifestations from other pulmonary abnormalities remains challenging because of low contrast, imaging noise, and overlapping radiographic patterns. This work presents CODE-NET++, an enhanced attention-guided deep learning framework with Grad-CAM-based explainability for reliable COVID-19 detection using chest X-ray images. The proposed framework integrates adaptive trilateral filtering for image enhancement, Reverse Edge Attention Network (RE-Net) for lesion-aware segmentation, and an Enhanced LinkNet architecture with dilated convolutions for multiscale feature extraction and classification. Grad-CAM-based explainable artificial intelligence visualization is incorporated to …
A Multi-Valued Fixed Point Theorem For Quasi-Contractions On A Cone Metric Space, Regina Mahadewsing, Sreedhara Rao Gunakala, Vikash Ramcharitar, Reddappa Bandi, Akhenaton Daaga, Thameem Basha H
A Multi-Valued Fixed Point Theorem For Quasi-Contractions On A Cone Metric Space, Regina Mahadewsing, Sreedhara Rao Gunakala, Vikash Ramcharitar, Reddappa Bandi, Akhenaton Daaga, Thameem Basha H
Mansoura Engineering Journal
A set-valued (multi-valued) mapping assigns to each a nonempty closed and bounded subset . Using this notion, the present work broadens classical fixed point theory by proving a fixed point theorem for multi-valued quasi-contractive mappings in cone metric spaces. The developed argument extends several earlier results that were restricted to single-valued maps and more familiar set-valued settings, thereby providing a wider analytical framework within ordered Banach-space structures. These contributions enrich fixed point theory in generalized metric environments and can be relevant to problems in nonlinear analysis and optimization
A Hybrid Object Detection And Temporal Attention Framework For Intelligent Video Surveillance, Sudheer Reddy Bandi, Eswari Vanaparthi, Yakshini Edapalli, Roshan Kavuri
A Hybrid Object Detection And Temporal Attention Framework For Intelligent Video Surveillance, Sudheer Reddy Bandi, Eswari Vanaparthi, Yakshini Edapalli, Roshan Kavuri
Mansoura Engineering Journal
The rapid growth of urban areas has greatly heightened the need for smart video surveillance systems that can automatically process extensive amounts of CCTV footage. Traditional surveillance methods largely depend on human monitoring, which is not only inefficient but also susceptible to human mistakes, especially in intricate and crowded environments. To tackle these issues, this paper introduces a combined object detection and temporal attention for intelligent video surveillance that concurrently analyzes spatial and temporal data from video streams. The proposed system analyzes real-time CCTV footage utilising a multi-pathway frame extraction technique that includes slow, fast, and full-frame sampling to capture …
An Intuitionistic Fuzzy Hypergraph Model Enhanced By Forest-Of-Walks Dynamics For Medical Image Segmentation, Brinthaguru Thangaraj, Karthick Palanisamy
An Intuitionistic Fuzzy Hypergraph Model Enhanced By Forest-Of-Walks Dynamics For Medical Image Segmentation, Brinthaguru Thangaraj, Karthick Palanisamy
Mansoura Engineering Journal
The process of accurately segmenting Urolithiasis and pulmonary nodules from medical images presents significant difficulties because of three main factors which include nonuniform intensity distribution and the presence of weak object borders and the uncertainty caused by anatomical structure overlaps. The study introduces F-Zinhger as a solution to these problems through its application of the Forest of Walks technology. The method uses superpixels as fundamental elements which form a multi-scale hypergraph that establishes hyperedges through three criteria: intensity similarity, spatial proximity, and Z-intuitionistic fuzzy hesitation to capture complex contextual connections. The system incorporates a random walk-based label propagation system. The …
Mathematical Analysis Of The Slip Flow Due To A Cylinder Oscillating In Different Directions With Independent Amplitudes, Alana Sankar, Karim Rahaman
Mathematical Analysis Of The Slip Flow Due To A Cylinder Oscillating In Different Directions With Independent Amplitudes, Alana Sankar, Karim Rahaman
Mansoura Engineering Journal
This study examines the incompressible viscous fluid flow in an infinitely long cylinder, with slip occurring at the cylinder’s surface, undergoing longitudinal and torsional oscillations of independent amplitudes. The proposed governing equations are solved subject to the Basset slip condition. Analytical expressions for the velocity field, shear stresses, drag force on the cylinder, work done and the drag coefficient are obtained. Velocity components, drag and work done are illustrated graphically. The magnitude of the velocity increases as slip decreases and as the frequency of oscillations increases. Drag increases in both directions as the slip decreases and as the frequency of …
Smart Dynamic Concrete: Effect Of Coarse Aggregate Size Distribution On Fresh, Mechanical And Durability Properties, Venu Sipelli, Kamineni Aditya, Shravya Sripadapu
Smart Dynamic Concrete: Effect Of Coarse Aggregate Size Distribution On Fresh, Mechanical And Durability Properties, Venu Sipelli, Kamineni Aditya, Shravya Sripadapu
Mansoura Engineering Journal
SDC is a self-flowing concrete that demonstrates improved material efficiency through optimized aggregate gradation. Unlike SCC, which relies on high powder content for improved flowability, SDC provides improved flowability by optimized aggregate gradation, making it a promising alternative to SCC. This paper presents the fresh, mechanical, and durability performance of M40-grade SDC using OPC 53 grade cement, GGBS, CRF, and polycarboxylate-based superplasticizer. A constant cementitious content of 470 kg/m³ and water–cement ratio of 0.38 were maintained. The fresh, mechanical, and durability performances of SDC using three types of coarse aggregate combinations, namely, 70% 10 mm + 30% 20 mm, 75% …