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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
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Experimental Study on the Effect of Using Metallic Brushes on the Charging and Discharging Time of Thermal Energy Storage Unit
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Phase change materials are known to be good in use in latent heat thermal energy storage (LHTES) systems, but one of their drawbacks is the slow melting and solidification processes. So that, in this work, enhancing heat transfer of phase change material is studied experimentally for in charging and discharging processes by the addition of high thermal conductive material such as copper in the form of brushes, which were added in both PCM and air sides. The additions of brushes have been carried out with different void fractions (97%, 94% and 90%) and the effect of four different air velocities was tested. The results indicate that the minimum brush void fraction gave the maximum heat transfer in PCM and reduced the time

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Publication Date
Thu Oct 01 2009
Journal Name
Iraqi Journal Of Physics
Effect of Glass Inclination of Windows Facing East and West on Solar Radiation Transmittance into Buildings
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To reduce solar radiation transmittance into buildings through windows facing east or west during summer, a window inclination from vertical position is suggested. The inclination of the window glazing and the rate of unwanted solar radiation during summer can be calculated knowing the dialy inclination of the sun rays. The inclination of window glazing depends on the latitude of the position required. For instance in Baghdad which is at about 33o north latitude a slope of 15o for window glazing is sufficient to prevent about 419 MJ/m2 of total solar radiation energy from penetration during summer for clear glazing of window facing east. This value drops to about 96 MJ/m2 during winter. Therefore the ratio between the energy saved for co

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Energy band diagram of In2O3/ Si heterojunction
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Crystalline In2O3 Thin films have been prepared by flash evaporation. We have studied the crystal structure of as deposited at 303K and annealed at 523K using X-ray diffraction. The Hall Effect measurements confirmed that electrons were predominant charges in the conduction process (i.e n-type).It is found that the absorption coefficient of the prepared films decreases with increasing Ta. The d.c conductivity study showed that the conductivity increase with increasing Ta , whereas the activation energy decreases with increasing Ta. Also we study the barrier tunneling diode for In2O3/Si heterostructure grown by Flash evaporation technique. (capacitance-voltage C-V) spectroscopy measurements were performed at 303 K and at the annealing temper

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
(Energy alternatives and the possibility of substitution)
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Many of the signs that the global energy system indicate the start of a period of transition from total dependence on fossil energy sources, especially oil, into a new era in which alternative energy sources play an important role in meeting the growing needs of energy demand, so sought many of the developed countries through research the studies carried out to try to bring renewable energy sources and non-renewable (shale oil, oil sands, solar energy, wind energy .... etc) replace traditional fossil energy sources (oil, gas, coal) and despite the recent availability dramatically and spread throughout the the world, but they are going to dry up in the foreseeable future. So many countries, especially the developed sought to find

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Publication Date
Fri Jan 24 2025
Journal Name
Journal Of The American Oil Chemists' Society
Development of natural deep eutectic solvent‐assisted liquid–liquid extraction method for soap removal from biodiesel: Optimization and kinetics
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Abstract<p>The soap content in biodiesel is an important challenge during the production and purification processing of biodiesel. Natural deep eutectic solvents (NADES) have recently attracted considerable interest as an environmentally suitable substitute for traditional solvents in the biodiesel industry. This work investigates the soap removal from the contaminated biodiesel using NADES. Eight choline chloride‐based deep eutectic solvents (DESs) were screened using the conductor‐like screening model for real solvents (COSMO‐RS) to identify the most suitable solvent for soap removal and were validated experimentally. The effect of NADES molar ratio, NADES:biodiesel ratio, mixing speed and extraction ti</p> ... Show More
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Publication Date
Sun Jun 01 2008
Journal Name
Baghdad Science Journal
The role of annealing temperature on the optical energy gap and Urbach energy of Se:2%Sb thin films
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The optical energy gap(Eopt) and the width of the tails of localized states in the band gap (?E) for Se:2%Sb thin films prepared by thermal co-evaporation method as a function of annealing temperature are studied in the photon energy range ( 1 to 5.4)eV.Se2%Sb film was found to be indirect transition with energy gap of (1.973,2.077, 2.096, 2.17) eV at annealing temperature (295,370,445,520)K respectively. The Eopt and ?E of Se:2%Sb films as a function of annealing temperature showed an increase in Eopt and a decrease in ?E with increasing the annealing temperature. This behavior may be related to structural defects and dangling bonds.

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Constructing a Software Tool for Detecting Face Mask-wearing by Machine Learning
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       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

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Publication Date
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Electrical Engineering &amp; Technology
ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System
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Publication Date
Thu Aug 31 2023
Journal Name
Journal Européen Des Systèmes Automatisés​
An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com

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