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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 Dec 01 2010
Journal Name
Iraqi Journal Of Physics
Study of electron energy distribution function and transport parameters for CF4 and Ar gases discharge by using the solution of Boltzmann equation-Part I
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The Boltzmann transport equation is solved by using two- terms approximation for pure gases . This method of solution is used to calculate the electron energy distribution function and electric transport parameters were evaluated in the range of E/N varying from . 172152110./510.VcmENVcm
From the results we can conclude that the electron energy distribution function of CF4 gas is nearly Maxwellian at (1,2)Td, and when E/N increase the distribution function is non Maxwellian. Behavior of electrons transport parameters is nearly from the experimental results in references. The drift velocity of electron in carbon tetraflouride is large compared with other gases

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Publication Date
Thu Aug 01 2013
Journal Name
Journal Of The College Of Basic Education
The antimicrobial activity of salvia pratensis extracts against some microbial agent
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The effectiveness inhibitory to extract alcohol for the leaf and flower to plant sage Salvia pratensis each of Staphylococcus aureus, streptococcus epidermidis, Salmonella typhi, Pseudomonas aeroginosa, Escherichia coli, Aspergillus niger and Candida albicans whom had any inhibition to aqueous extracts of the parts itself species bacterial and fungal. The study also demonstrated that the extract of plant containing compounds chemical such as tannins, Alkaloids, Flavonoieds, and saponins, which owns effectiveness of medical. The MIC, MBC and inhibition zones for crud extract were determinated for microbial agents.

Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
A Spotlight on the Experience of E-learning as a Learning Method for the Undergraduate Pediatric Nursing Students in Iraq during the COVID-19 Pandemic
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    The emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t

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Publication Date
Mon Oct 04 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Perforation location optimization through 1-D mechanical earth model for high-pressure deep formations
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Optimum perforation location selection is an important study to improve well production and hence in the reservoir development process, especially for unconventional high-pressure formations such as the formations under study. Reservoir geomechanics is one of the key factors to find optimal perforation location. This study aims to detect optimum perforation location by investigating the changes in geomechanical properties and wellbore stress for high-pressure formations and studying the difference in different stress type behaviors between normal and abnormal formations. The calculations are achieved by building one-dimensional mechanical earth model using the data of four deep abnormal wells located in Southern Iraqi oil fields. The magni

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Publication Date
Fri Jul 28 2023
Journal Name
Journal Of Optics
Estimated the nanoparticles size of CdS from UV–Vis spectrum absorption by effective mass approximation model (EMA) using capping and complex agent
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Publication Date
Mon Jun 30 2014
Journal Name
Al-kindy College Medical Journal
Evaluation of D-Dimer in the diagnosis of suspected deep vein thrombosis
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Background: Deep vein thrombosis is a multi causal disease and its one of most common venous disorder, but only one quarter of the patients who have signs and symptoms of a clot in the vein actually have thrombosis and need treatment .The disease can be difficult to diagnose. Venous ultrasound in combination with clinical finding is accurate for venous thromboembolism, its costly because a large number of patients with suspicious signs and symptoms. Venography still the gold standard for venous thromboembolism but it is invasive. The D-dimer increasingly is being seen as valuable tool rolling out venous thromboembolism and sparing low risk patients for further workup.Objectives: this study has designed the role of D-dimer to confirm diag

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of Using Information and Communication Technology to Improving the Quality of Blended Learning Elements’, a Survey Study at the Technical College of Management /Baghdad
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 The research has been based on two main variables (information and communication technology) and the quality of blended education (physical and electronic), aiming to reveal the relationship between four dimensions (physical devices, software, databases, communication networks) and the elements of education represented by (the teacher, the student, the teaching process, curriculum).  The methodology and post-analysis-based research were conducted at the Technical College of Management / Baghdad through polling the opinions of a random sample that included (80) teachers out of (86) and the number of students (276) representing a random sample from all departments of the college (for the morning study) out of (3500) stud

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Impact of the Strategy of Cooperative Integration of Fragmented Information in the Acquisition of Physical Concepts and Science Processes among Fourth Scientific Students
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The current research aims to reveal the impact of the strategy of cooperative integration of fragmented information in the acquisition of physical concepts and science processes among fourth scientific students through the null hypotheses:

1- There is no statistically significant difference at the level of significance (0.05) between the average grades of female students of the experimental group studying physics according to the strategy of cooperative integration of fragmented information and those who follow the traditional method in the test of acquiring physical concepts.

2-There is no statistically significant difference at the level of indication (0.05) between the average grades of female students of the experimen

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Publication Date
Fri Oct 01 2010
Journal Name
Iraqi Journal Of Physics
Statistical Fluctuations of Energy Spectrum, Electromagnetic Transitions and Electromagnetic Moments in 136Xe Nucleus Using the Framework of Nuclear Shell Model
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The fluctuation properties of energy spectrum, electromagnetic transition intensities and electromagnetic moments in nucleus are investigated with realistic shell model calculations. We find that the spectral fluctuations of are consistent with the Gaussian orthogonal ensemble of random matrices. Besides, we observe a transition from an order to chaos when the excitation energy is increased and a clear quantum signature of the breaking of chaoticity when the single-particle energies are increased. The distributions of the transition intensities and of the electromagnetic moments are well described by a Porter-Thomas distribution. The statistics of electromagnetic transition intensities clearly deviate from a Porter-Thomas distribution (i

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