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Signal compression and enhancement using a new orthogonal‐polynomial‐based discrete transform
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Cosmetics, Dermatological Sciences And Applications
A New Regimen in the Treatment of Psoriasis Using Oral Methotrexate
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Publication Date
Mon Jan 01 2024
Journal Name
Aims Energy
The impact of different compression ratios on emissions, and combustion characteristics of a biodiesel engine
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<p>The current work investigated the combustion efficiency of biodiesel engines under diverse ratios of compression (15.5, 16.5, 17.5, and 18.5) and different biodiesel fuels produced from apricot oil, papaya oil, sunflower oil, and tomato seed oil. The combustion process of the biodiesel fuel inside the engine was simulated utilizing ANSYS Fluent v16 (CFD). On AV1 diesel engines (Kirloskar), numerical simulations were conducted at 1500 rpm. The outcomes of the simulation demonstrated that increasing the compression ratio (CR) led to increased peak temperature and pressures in the combustion chamber, as well as elevated levels of CO<sub>2</sub> and NO mass fractions and decreased CO emission values un

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Publication Date
Fri Mar 20 2020
Journal Name
Remote Sensing
Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics
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The smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, rec

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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science &amp; Technology
Illumination - Invariant Facial Components Extraction Using Adaptive Contrast Enhancement Methods
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The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material

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Publication Date
Thu Feb 01 2024
Journal Name
Ain Shams Engineering Journal
Performance enhancement of high degree Charlier polynomials using multithreaded algorithm
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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
An Investigation into Heat Transfer Enhancement by Using Oscillating Fins
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The present work describes numerical and experimental investigation of the heat transfer characteristics in a plate-fin, having built-in piezoelectric actuator mounted on the base plate (substrate). The geometrical configuration considered in the present work is representative of a single element of the plate-fin and triple fins. Air is taken as the working fluid. A performance data for a single rectangular fin and triple fins are provided for different frequency levels (5, 30 and
50HZ) , different input power (5,10,20,30,40 and 50W) and different inlet velocity (0.5, 1, 2, 3, 4, 5 and 6m/s) for the single rectangular fin and triple fins with and without oscillation. The investigation was also performed with different geometrical fin

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Publication Date
Mon Jun 01 2009
Journal Name
2009 Etp International Conference On Future Computer And Communication
Signal Processing Techniques for Robust Spectrum Sensing
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Cognitive radios have the potential to greatly improve spectral efficiency in wireless networks. Cognitive radios are considered lower priority or secondary users of spectrum allocated to a primary user. Their fundamental requirement is to avoid interference to potential primary users in their vicinity. Spectrum sensing has been identified as a key enabling functionality to ensure that cognitive radios would not interfere with primary users, by reliably detecting primary user signals. In addition, reliable sensing creates spectrum opportunities for capacity increase of cognitive networks. One of the key challenges in spectrum sensing is the robust detection of primary signals in highly negative signal-to-noise regimes (SNR).In this paper ,

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Digital Data Encryption Using a Proposed W-Method Based on AES and DES Algorithms
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This paper proposes a new encryption method. It combines two cipher algorithms, i.e., DES and AES, to generate hybrid keys. This combination strengthens the proposed W-method by generating high randomized keys. Two points can represent the reliability of any encryption technique. Firstly, is the key generation; therefore, our approach merges 64 bits of DES with 64 bits of AES to produce 128 bits as a root key for all remaining keys that are 15. This complexity increases the level of the ciphering process. Moreover, it shifts the operation one bit only to the right. Secondly is the nature of the encryption process. It includes two keys and mixes one round of DES with one round of AES to reduce the performance time. The W-method deals with

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

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Publication Date
Fri May 16 2025
Journal Name
Asean Journal Of Science And Engineering
Enhancing Predictive Maintenance in Energy Systems Using a Hybrid Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) Framework for Rotating Machinery
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This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

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