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Selecting Appropriate Delivery System for Implementation of Green Buildings
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Green buildings are considered more efficient than traditional buildings due to the incorporated techniques and the multidisciplinary specializations required to comply with their specifications, in addition to the advanced commissioning, which undergoes before handing over the buildings to the owners to ensure requirements conformance. As a result, the appropriate selection of a project delivery system acts as the essential factor that affects the performance of the project. This research aims at building a system that helps to select the best method to implement green buildings. Through studying the recent research approaches in project delivery systems, the factors that affect the selection of the optimal implementation method for green buildings have been identified; expert interviews have been done to study and analyze the main influential factors that affect the selection of the best method for implementing green buildings. The results of interviews indicate that the main influential factors are as follows: The occurrence of economic crises in the country, availability of financial capacity for the contractor and the owner, the lack of previous experience in similar projects, hiring an incompetent contractor, differences between design drawings among all disciplines, and providing qualified contractors, subcontractors, suppliers and craftsmen with sufficient qualifications early in the project. Depending on these main factors, a software system is built to choose the best delivery system for green building projects. This research encourages future works to focus on the quality and performance of green buildings and lays out the foundation for academic researchers to explore new techniques for evaluating the project delivery systems as well as supporting the decision-makers to choose the best.

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Publication Date
Tue Jan 01 2019
Journal Name
Aip Conference Proceedings
Highly selective CdS:Ag heterojunction for photodetector applications
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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
Wed Jul 17 2019
Journal Name
Advances In Intelligent Systems And Computing
A New Arabic Dataset for Emotion Recognition
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In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

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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
Fri Jul 31 2020
Journal Name
Iraqi Geological Journal
APPLICATION OF TRIANGLES METHOD FOR QUANTITATIVE ESTIMATION OF MARL RESERVE IN EUPHRATES FORMATION, MIDDLE OF IRAQ
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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Prediction of the number of births in the Governorate of Basra for the period (1998-2050)
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The adoption of many mathematical concepts contributes to the construction of models of sports and the population can be interpreted to explain the movement and growth of the population lead to proper planning to manage the requirements of the population and meet their needs of providing education or providing medical services, health and others. In this study, the number of births in the Governorate of Basrah for the period (1998-2050) is estimated to be based on the assumption that the population of the visually impaired is a stable society. If the rate of growth is (0.0492), some demographic indicators are important for maintaining the average age of women at pregnancy (27.817). Each woman will give birth (3.74) female birth d

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