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Transfer Learning and Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From EEG Signals
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Publication Date
Mon Jan 01 2018
Journal Name
Proceedings Of The 10th International Joint Conference On Computational Intelligence
Deep Classifier Structures with Autoencoder for Higher-level Feature Extraction
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Publication Date
Fri Jan 05 2018
Journal Name
International Journal Of Science And Research (ijsr)
Comparative Study of Some Antibiotic Resistance, Extended Spectrum ß-Lactamases (ESBLs), Metallo ß-Lactamases (MBLs) Produced in Pseudomonas aeruginosa Isolated from Clinical and Food Samples
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A total number of 33 isolates of Pseudomoans aeruginosa were collected from different clinical samples, such as: burn, wound and urine from patients attending Al-Yarmouk teaching hospital and some private clinical laboratories in Baghdad city through the period from October to December 2016. On the other hand, 21 isolates of P. aeruginosa were collected from 38 different food samples; such as: vegetables and fruits, from different local markets in Baghdad city during the period from November to December 2016. All isolates were identified by using different bacteriological and biochemical assays and confirmed by Vitek-2 identification system. The antimicrobial susceptibility test for clinical and food isolates towards 17 antimicrobial a

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Distributed Heuristic Algorithm for Migration and Replication of Self-organized Services in Future Networks
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Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

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Publication Date
Thu Oct 30 2025
Journal Name
Journal Of University Of Babylon For Engineering Sciences
Adaptive Beamforming and Ai-Driven Low-Power Signal Processing on ‎Fpga For 6G Networks
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As the demands of sixth-generation (6G) networks escalate towards achieving high speeds and improved energy efficiency, there is an increasing need for intelligent and real-time adaptive solutions within the physical processing layer. This study proposes an innovative engineering framework based on an encapsulated architecture utilising FBGA (micro-distributed spherical array) technology, integrated with an internal artificial intelligence module, to achieve adaptive beamforming with high efficiency in dense wireless environments. The primary objective of this research is to develop an intelligent communication architecture that determines the optimal transmission angles and regulates power consumption in real-time by integrating ar

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Publication Date
Mon Dec 30 2019
Journal Name
College Of Islamic Sciences
The matter, its wisdom, and models of its applications In Ahmadiyya interpretations Research drawn from a doctoral thesis
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This study examined the tagged (the matter, its ruling, and examples of its applications in Ahmadiyya interpretations), the study of devising formulas of commissioning, especially the matter from the book of interpretation, which is: (Ahmadiyyeh’s interpretations), and the contemplative of the nature of (Ahmadiyya’s interpretations) realizes that the cognitive, linguistic and juristic knowledge product and the verses of judgments And other is the focus of this immortal travel, as it is truly a comprehensive book containing what the students of knowledge, scholars and the general public need in terms of interpreting the legal verses, and it is not possible to reach an understanding of the Book of God Almighty, and to clarify his purpo

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Publication Date
Mon Apr 11 2011
Journal Name
Icgst
Employing Neural Network and Naive Bayesian Classifier in Mining Data for Car Evaluation
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In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.

Publication Date
Thu Oct 01 2015
Journal Name
Engineering And Technology Journal
Genetic Based Optimization Models for Enhancing Multi- Document Text Summarization
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Mathematical Models Used for Brachytherapy Treatment Planning Dose Calculation Algorithms
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Brachytherapy treatment is primarily used for the certain handling kinds of cancerous tumors. Using radionuclides for the study of tumors has been studied for a very long time, but the introduction of mathematical models or radiobiological models has made treatment planning easy. Using mathematical models helps to compute the survival probabilities of irradiated tissues and cancer cells. With the expansion of using HDR-High dose rate Brachytherapy and LDR-low dose rate Brachytherapy for the treatment of cancer, it requires fractionated does treatment plan to irradiate the tumor. In this paper, authors have discussed dose calculation algorithms that are used in Brachytherapy treatment planning. Precise and less time-consuming calculations

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Publication Date
Sat Nov 12 2016
Journal Name
International Journal Of Mechanical Engineering And Technology (ijmet)
PERFORMANCE OF TWO-WAY NESTING TECHNIQUES FOR SHALLOW WATER MODELS
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A new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.