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Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning models for a variety of tasks under the control of a unified architecture for each proposed model.

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Publication Date
Sat Apr 01 2017
Journal Name
International Journal Of Science And Research
Evaluating the Behavior of Ring Footing on Two-Layered Soil Subjected to Inclined Load
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Evaluating the behavior of a ring foundation resting on multi-layered soil is one of the important issues facing civil engineers. Many researchers have studied the behavior of ring foundation rests on multi-layered soil with vertical loads acting on the foundation. In real life ring foundation can be subjected to both vertical and horizontal loads at the same time due to wind or the presence of soil. In this research, the behavior of ring footing subjected to inclined load has been studied using PLAXIS software. Furthermore, the effect of multi-layered soil has been simulated in the model. The results showed that both vertical and horizontal stresses are mainly affected when the inclination angle of the load exceeded 45 degrees with a reduc

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Evaluating the strategic performance of agricultural projects by adopting international indicators
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The aim of this research is to test the relationship of influence and correlation between strategic performance and its five dimensions (financial dimension, after internal processes, after internal customer satisfaction, after learning and growth, environmental and social dimension), by adopting international indicators in agricultural projects To determine the extent of the differences between the research variable and its dimensions, and then try to come out with a number of recommendations that contribute to the evaluation of agricultural projects and their performance by diagnosing and treating deviations, and based on the importance of the research topic in agricultural institutions. Institutions of the Environment and Soci

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Publication Date
Sun Jan 04 2026
Journal Name
The Iraqi Journal For Information And Documentation Studies
The role of performance indicators in evaluating the performance of the University of Technology's Central Library
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University libraries seek to evaluate their performance in order to correct their path and adjust it in the right direction. Therefore, they use (performance indicators), which are a tool used by institutions to evaluate the weaknesses and strengths in their work and the reasons for failure to achieve some goals sometimes. They convert (goals, procedures and actions) into a formula that can be measured mathematically, which contributes to the library determining the gap between its current performance and what those libraries are supposed to be on, clarifying the path that the library is following, controlling the risks that may befall it, and thus enhancing the process of continuous improvement to avoid areas of failure and weakness becaus

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Publication Date
Sun Jan 01 2017
Journal Name
Research Journal Of Pharmacy And Technology
Estimating the plain and negative tendonography techniques for evaluating injured tendon in rabbit
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Publication Date
Wed Dec 08 2021
Journal Name
J. Inf. Hiding Multim. Signal Process.
Predication of Most Significant Features in Medical Image by Utilized CNN and Heatmap.
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The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co

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Publication Date
Sun Dec 01 2024
Journal Name
Journal Of The Iraqi Translators Association Translation And Linguistics
COMPARISON OF THE IDEOLOGICAL DISCOURSE OF THE RUSSIAN-UKRAINIAN WAR IN REPORTS FROM NEWS CHANNELS CNN AND RT
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This study conducts a systematic comparative critical discourse analysis of news reports from prominent American (CNN) and Russian (RT) media sources covering the Russia-Ukraine conflict. Utilizing the theoretical frameworks of Norman Fairclough's multidimensional model and Teun van Dijk's socio-cognitive approach, the research examines the underlying ideological assumptions and discursive strategies employed by the two contrasting news channels. Quantitative analysis of discursive techniques and linguistic features provides insights into how each channel selectively utilizes language to convey distinct ideological positions. The findings demonstrate how media discourse constructs and normalizes particular ideological representations of pol

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Evaluating the Knowledge for Integrating RM and VM Using BIM in the Iraqi Construction Sector
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The construction industry plays a crucial role in the countries' economy, especially in the developed country. This point encourages the concerned institution to use new techniques and integrate many techniques and methods to maximize the benefits. The main objective of this research is to evaluate the use of risk management, value management, and building information modeling in the Iraqi construction industry. The evaluation process aims at two objectives. The direct objective was to evaluate the knowledge in risk management (RM), value management (VM), and building information modeling (BIM). The indirect objective was to support the participants with information related to the main items mentioned. The questionnaire

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Publication Date
Sat Apr 05 2025
Journal Name
2025 Ieee 4th International Conference On Computing And Machine Intelligence (icmi)
From Pixels to Diagnosis: AI-Powered CNN for Pneumonia Detection
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Publication Date
Tue Aug 01 2023
Journal Name
Advances In Mechanical Engineering
Using a spherical inverted pendulum and statokinesigram for modeling and evaluating quiet standing posture
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This paper proposes a new approach to model and analyze erect posture, based on a spherical inverted pendulum which is used to mimic the body posture. The pendulum oscillates in two directions, [Formula: see text] and [Formula: see text], from which the mathematical model was derived and two torque components in oscillation directions were introduced. They are estimated using stabilometric data acquired by a foot pressure mapping system. The model was quantitatively investigated using data from 19 participants, who were first were classified into three groups, according to the foot arch-index. Stabilometric data were then collected and fed into the model to estimate the torque’s components. The components were statistically proce

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Publication Date
Tue Aug 01 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
End-to-End Speaker Profiling Using 1D CNN Architectures and Filter Bank Initialization
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The automatic estimation of speaker characteristics, such as height, age, and gender, has various applications in forensics, surveillance, customer service, and many human-robot interaction applications. These applications are often required to produce a response promptly. This work proposes a novel approach to speaker profiling by combining filter bank initializations, such as continuous wavelets and gammatone filter banks, with one-dimensional (1D) convolutional neural networks (CNN) and residual blocks. The proposed end-to-end model goes from the raw waveform to an estimated height, age, and gender of the speaker by learning speaker representation directly from the audio signal without relying on handcrafted and pre-computed acou

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