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Nondestructive Testing Technologies for Rail Inspection: A Review
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Alongside the development of high-speed rail, rail flaw detection is of great importance to ensure railway safety, especially for improving the speed and load of the train. Several conventional inspection methods such as visual, acoustic, and electromagnetic inspection have been introduced in the past. However, these methods have several challenges in terms of detection speed and accuracy. Combined inspection methods have emerged as a promising approach to overcome these limitations. Nondestructive testing (NDT) techniques in conjunction with artificial intelligence approaches have tremendous potential and viability because it is highly possible to improve the detection accuracy which has been proven in various conventional nondestructive testing techniques. With the development of information technology, communication technology, and sensor technology, rail health monitoring systems have been evolving, and have become equally significant and challenging because they can achieve real-time detection and give a risk warning forecast. This paper provides an in-depth review of traditional nondestructive techniques for rail inspection as well as the development of using machine learning approaches, combined nondestructive techniques, and rail health monitoring systems.

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Publication Date
Wed Dec 31 2025
Journal Name
Enquiry The Arcc Journal For Architectural Research
Graph-Theoretic Analysis for Sustainable Urban Structure
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A significant challenge arises in the characterization of urban systems, especially regarding the intricate structures of Central Business Districts (CBDs). Conventional models seem insufficient, failing to comprehend the non-linear, network-oriented structure of the city's economic and social dynamics. This creates a disparity between the city's physical, geographical structure and the unseen processes occurring within it. The fundamental inquiry is thus configurational: how can we systematically examine the inherent spatial logic of the CBD to develop a more efficient and predictive planning model? This paper presents a theoretical and methodological model to explore this inquiry, which focuses on Lower Manhattan as the primary su

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Publication Date
Mon Jun 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Modeling and Filtering for Tracking Maneuvering Targets
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     A new mathematical model describing the motion of manned maneuvering targets is presented. This model is simple to be implemented and closely represents the motion of maneuvering targets. The target maneuver or acceleration is correlated in time. Optimal Kalman filter is used as a tracking filter which results in effective tracker that prevents the loss of track or filter divergency that often occurs with conventional tracking filter when the target performs a moderate or heavy maneuver. Computer simulation studies show that the proposed tracker provides sufficient accuracy.

 

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Publication Date
Wed Apr 01 2026
Journal Name
Neurocomputing
Minion gated recurrent unit for continual learning
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The increasing demand for continual learning in sequential data processing has led to progressively complex training methodologies and larger recurrent network architectures. Consequently, this has widened the knowledge gap between continual learning with recurrent neural networks (RNNs) and their ability to operate on devices with limited memory and compute. To address this challenge, we investigate the effectiveness of simplifying RNN architectures, particularly gated recurrent unit (GRU), and its impact on both single-task and multitask sequential learning. We propose a new variant of GRU, namely the minion recurrent unit (MiRU). MiRU replaces conventional gating mechanisms with scaling coefficients to regulate dynamic updates of hidden

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Intelligent Systems And Internet Of Things
Enhancing Convolutional Neural Network for Image Retrieval
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With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases

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Publication Date
Fri Jan 19 2024
Journal Name
Turkish Journal Of Pharmaceutical Sciences
Taste Masking of Steroids for Oral Formulations
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Publication Date
Mon Jun 30 2025
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Green-driven CaO catalyst for biodiesel production
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   With increasing population and development, the resources of fossil fuels decreased, leading to the need to find alternative sources of energy. Furthermore, the use of fossil fuels is accompanied by several downsides including environmental fatality associated with toxic gas emissions from diesel engines and continuous increase of the price of diesel fuel. Biodiesel is one of the most important types of renewable energy that replaces the fossil fuel requirement (mineral diesel) and maintains eco-friendly sustainability. Calcium is an essential plant nutrient as it plays an important role in the formation of plant cell walls and membranes. Therefore, the fallen leaves of mango tree can be utilized to produce nano calcium oxide a

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Publication Date
Thu Oct 18 2018
Journal Name
Proceedings Of The Future Technologies Conference (ftc) 2018
Using Mouse Dynamics for Continuous User Authentication
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Publication Date
Fri Feb 01 2019
Journal Name
Ieee Transactions On Emerging Topics In Computational Intelligence
Neuromorphic Architecture for the Hierarchical Temporal Memory
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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The economic effects of money laundering and the role of banking service in combat it: a prospective study of a sample
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Money laundering is consider a crime in legal perspective and aphenomenon of negative effects in economic and Social perspective for thevarious countries of the world by the diversity of their economies to make thebadly damaged in the banking service and its reputation in some cases may leadto bankruptcy of banks, and the fact that banks is one of the most importantcircles that revolve the illicit funds, Due to its branched the banking operations,speed and overlap and increase it's complicated with the progress of bankingoperations and the use of electronic services modern here's challenges atvarious levels between the application of the legislation to combat moneylaundering and between actual fact it must find ways and means of legislat

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Publication Date
Wed Jan 01 2025
Journal Name
Socar Proceedings
Enhanced permeability estimation in non-cored wells using a modified flow zone index-permeability crossplot: a case study of carbonate reservoirs
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The permeability estimates for the uncored wells and a porosity function adopting a modified flow zone index-permeability crossplot are given in this work. The issues with implementing that approach were mostly crossplots, due to the influence of geological heterogeneity, did not show a clear connection (scatter data). Carbonate reservoir flow units may now be identified and characterized using a new approach, which has been formally confirmed. Due to the comparable distribution and flow of clastic and carbonate rock fluids, this zoning method is most effective for reservoirs with significant primary and secondary porosity. The equations and correlations here are more generalizable since they connect these variables by combining cor

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