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Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is suitable for multi-objective optimisation based on cooperative multi-agent systems (CMAS). The framework of DCLTML is used greedy iterative training to get an optimal set of weights and tabulated as a layer for each clustering structure. Such layers can deal with the challenges of large space and its massive data. Then the layer weights of each cluster are tuned by the Quasi-Newton (QN) algorithm to make the action sequence of CMAS optimal. Such a policy of CMAS effectively manipulates the inputs of the AHU, where the agents of the AHU activate the natural ventilation and set chillers into an idle state when the outdoor temperature crosses the recommended value. So, it is reasonable to assess the impact potential of thermal mass and hybrid ventilation strategy in reducing cooling energy; accordingly, the assigning results of the proposed DCLTML show that its main cooling coil saves >40% compared to the conventional benchmarks. Besides significant energy savings and improving environmental comfort, the DCLTML exhibits superior high-speed response and robustness performance and eliminates fatigue and wear due to shuttering valves. The results show that the DCLTML algorithm is a promising new approach for controlling HVAC systems. It is more robust to environmental variations than traditional controllers, and it can learn to control the HVAC system in a way that minimises energy consumption. The DCLTML algorithm is still under development, but it can potentially revolutionise how HVAC systems are controlled.

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
3-D Packing in Container using Teaching Learning Based Optimization Algorithm
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The paper aims to propose Teaching Learning based Optimization (TLBO) algorithm to solve 3-D packing problem in containers. The objective which can be presented in a mathematical model is optimizing the space usage in a container. Besides the interaction effect between students and teacher, this algorithm also observes the learning process between students in the classroom which does not need any control parameters. Thus, TLBO provides the teachers phase and students phase as its main updating process to find the best solution. More precisely, to validate the algorithm effectiveness, it was implemented in three sample cases. There was small data which had 5 size-types of items with 12 units, medium data which had 10 size-types of items w

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Publication Date
Fri Aug 30 2024
Journal Name
Iraqi Journal Of Science
The Dissipation of the Kinetic Energy for 2D Bounded Flow by Using Moment-Based Boundary Conditions with Burnett Order Stress for LBM
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     In this article, the lattice Boltzmann method with two relaxation time  (TRT)  for the  D2Q9 model is used to investigate numerical results for 2D flow. The problem is performed to show the dissipation of the kinetic energy rate and its relationship with the enstrophy growth for 2D dipole wall collision. The investigation is carried out for normal collision and oblique incidents at an angle of . We prove the accuracy of moment -based boundary conditions with slip and Navier-Maxwell slip conditions to simulate this flow. These conditions are under the effect of Burnett-order stress conditions that are consistent with the discrete Boltzmann equation. Stable results are found by using this kind of boundary condition where d

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Overview of seismic performance assessment of reinforced concrete buildings
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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
The Impact of Materials’ Technology on Sustainability of Buildings
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The evolution in materials’ technology in the last decades resulted in interesting projects that aimed at preserving the environment and energy and reduce pollution. They have been taken the principles of environmental design as a basis for architectural thought, starting from the early stages of the design process ending in choosing appropriate building materials to achieve sustainable buildings, but these trying are limited in our local environment and there isn’t demanded seriousness. The research problem emerges in the ignorance of the environmental aspect (ecological system) when selecting building materials during design process to achieve sustainable buildings. The aim of this research is revealing the mechanisms of selecting

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Publication Date
Mon Aug 01 2022
Journal Name
Journal Of Engineering
The Causes Influencing the Occurrence of Variation Orders in the Construction of Buildings
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In the construction of buildings usually, problems occur because of the causes of change orders. The main causer of change orders is the owners, consultants, and contractors. These changes lead to conflicts among them which result in influencing building projects. Therefore, it is necessary to analyze the causes of change orders to reduce them and facilitate management. This paper determines the most critical factors that cause change orders from a different point of view, a consulting owner and a contractor, and a study of the reality of the management of change orders when constructing public buildings. The method employed in this research is a field survey using interviews with experts working in the construction of p

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Publication Date
Sun May 22 2022
Journal Name
International Journal Of Early Childhood Special Education
The impact of using learning acceleration model on the achievement of mathematics for third intermediate grade students
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The current study aims at identifying the impact of using learning acceleration model on the achievement of mathematics for third intermediategrade students. Forachieving this, the researchers chose the School (Al-Kholood Secondary School for Girls) affiliated to the General Directorate of Babylon Education / Hashemite Education Department for the academic year (2021/2021), The sample reached to (70) female students from the third intermediate grade, with (35) female students for each of the two research groups. The two researchers prepared an achievement test consisting of (25) objective items of multiple choice type, The psychometric properties of the test were confirmed, and after the completion of the experiment, the achievement test wa

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Publication Date
Sun Sep 03 2023
Journal Name
Wireless Personal Communications
Application of Healthcare Management Technologies for COVID-19 Pandemic Using Internet of Things and Machine Learning Algorithms
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Publication Date
Fri Jan 01 2016
Journal Name
Sciences Journal Of Physical Education
The effect of using intellectual map according to the feedback (verbally and writhingly ) in the learning some skills of floor exercises in the women's artistic gymnastics
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Abstract The aim of this study is preparing an intellectual map according to the feedback (verbally and writhingly ) in order to learn some skills of floor exercises in the women's artistic gymnastics , In addition to that the aim of this study defines on the impacts of intellectual map according to the feedback approach, and to identify the best group between the three groups study in the learning of skills approach in this study, the researchers used the experimental method, the subject of the study included on students second class in physical education and sport sciences , Baghdad University (2014-2015) , and divided into three groups for teaching skills which was under studied .The species used the specific manner by lot for selection

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Publication Date
Wed Jan 01 2025
Journal Name
Iv. International Rimar Congress Of Pure, Applied Sciences
A New Intrusion Detection Approach Based on RNA Encoding and K-Means Clustering Algorithm Using KDD-Cup99 Dataset
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Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of The Iraqi University
Exclusion optimal portfolio from outlier by using fuzzy c-means clustering - analytical research at the Iraqi Stock Exchange
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This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio

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