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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 with 106 units, and large data which had 20 size-types of items with 110 units. Moreover, it was also compared with another algorithm called Gravitational Search Algorithm (GSA). According to the computational results in those example cases, it can be concluded that higher number of population and iterations can bring higher chances to obtain a better solution. Finally, TLBO shows better performance in solving the 3-D packing problem compared with GSA.          

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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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
Optimal characteristics of wind turbine to maximize capacity factor
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The capacity factor is the main factor in assessing the efficiency of wind Turbine. This paper presents a procedure to find the optimal wind turbine for five different locations in Iraq based on finding the highest capacity factor of wind turbine for different locations. The wind data for twelve successive years (2009-2020) of five locations in Iraq are collected and analyzed. The longitudes and latitudes of the candidate sites are (44.3661o E, 33.3152o N), (47.7738o E, 30.5258o N), (45.8160o E, 32.5165o N), (44.33265o E, 32.0107o N) and (46.25691o E, 31.0510o N) for Baghdad, Basrah, Al-Kut, Al-Najaf, and Al-Nasiriyah respectively. The average wind velocity, standard deviation, Weibull shape and scale factors, and probability density functi

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
THE EFFECT OF CUTOFF WALL ANGLE ON SEEPAGE UNDER DAMS
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Flow of water under concrete dams generates uplift pressure under the dam, which may cause the dam to function improperly, in addition to the exit gradient that may cause piping if exceeded a safe value. Cutoff walls usually used to minimize the effect of flow under dams. It is required to
1)minimize the flow quantity to conserve water in the reservoir, it is also required to
2)minimize the uplift pressure under the dam to maintain stability of the dam, and it is required to

3) minimize the exit gradient to prevent quick condition to occur at the toe of the dam where piping may occur and may cause erosion of the soil. Varying the angle of cutoff walls affects its influence on the factors aforementioned that are required to

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
Cluster Analysis of Biochemical Markers as Predictor of COVID-19 Severity
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Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patien

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Publication Date
Wed Nov 29 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering (ijasre), Issn:2454-8006, Doi: 10.31695/ijasre
Yolo Versions Architecture: Review
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Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Advances In Scientific Research And Engineering
Yolo Versions Architecture: Review
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Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec

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Publication Date
Fri Feb 21 2025
Journal Name
Applied System Innovation
Utilizing Soft Computing Techniques to Estimate the Axial Permanent Deformation of Asphalt Concrete
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Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R

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Publication Date
Tue Jun 15 2021
Journal Name
Al-academy
The Physical Performance Of The Actor Within The Shows Of Anas Abdul Samad ( the play silence as the cry as a model): حليم هاتف جاسم
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The body has the ability to effect the audience in the the theatrical show , since he or she is transmitter , sender , seen and viewer of the humanitarian discourse as well the the images and connotations of the theatrical show, it is a tool of communication that substitutes for millions of spoken words, the modern schools of direction focused on the body language of the actor and gave it prominence in depicting facts by different connotations. The researcher studies the physical performance of the actor throughout focusing on the connotational dimensions of the body within the theatrical show , as well as the positioning of performative body within the modern schools of direction depending on the theatrical show (Rebuke ) of the Iraqi d

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Publication Date
Wed Dec 29 2021
Journal Name
Journal Of The College Of Education For Women
A Speech Acts Analysis of English COVID-19 News Headlines: مثنى نجيب المرسومي, جمعة قادر حسين
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News headlines are key elements in spreading news. They are unique texts written in a special language which enables readers understand the overall nature and importance of the topic. However, this special language causes difficulty for readers in understanding the headline. To illuminate this difficulty, it is argued that a pragmatic analysis from a speech act theory perspective is a plausible tool for a headline analysis. The main objective of the study is to pragmatically analyze the most frequently employed types of speech acts in the news headlines covering COVID-19 in Aljazeera English website. To this end, Bach and Harnish's (1979) Taxonomy of Speech Acts has been adopted to analyze the data. Thirty headlines have been collected f

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Publication Date
Thu Mar 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
تأثير تدفق القروض الخارجية في تحقيق التحولات الهيكلية لاقتصادات بعض دول الاسكوا للمدة (1990 ـ 2002)
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تتطلب عملية التنمية الاقتصـادية في الدول النامية مبالغ كبيرة من رؤوس الأمـوال اللازمة لتنفيذ البرامج والخطط الاقتصادية، ولما كانت الاسـتثمارات التي تنفذها هذه الدول خلال حقبة معينة، تزيد على ما تم  تحقيقه من موارد مالية محلية، فلابد أنْ يمول الفرق من خلال انسياب صافٍ لرأس المال الأجنبي (قروض ومساعدات) إلى الداخل خلال المدة نفسها، لغـرض سَدّ الفجوة في المـوارد المحلية المعدة للاسـتثمار، وعانت بعض د

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