The Effect Of The Spirit Of The Place On The Formulation Of Emotion In Contemporary Arab-Islamic Architecture, Mahdi Saleh Al-Faraj, Dania Saleh Yaheia

Al-Esraa University College Journal for Engineering Sciences

Arab-Islamic architecture is characterized by both constants and variables, with spiritual aspects (content) representing the constants and physical aspects (form) representing the variables. It evolves based on changing times and needs, with compassion being a significant feature associated with its spiritual aspects. Compassion is essential for collective agreement and individual emotional connection in Arab-Islamic architecture. The present research aims to investigate the influence of the spirit of the place, as embraced by designers, on the emotional characteristics of contemporary Arab-Islamic architecture. The research problem identified is the lack of a theoretical concept regarding the impact of the spirit of the …

The Effect Of Bioenergy Systems On The Architectural Product The Effect Of Fung Shui And Biogetric To Achieve The Performance Of Architectural Space, Abdullah Saadon Al-Mamoory, Ann Samari Ibrahim

Al-Esraa University College Journal for Engineering Sciences

This research presents an analytical study exploring the vital systems of energy science and their influence on architecture by examining ancient environmental philosophies like Feng Shui in China and bio-geometry in Egypt. These philosophies serve as guiding principles for studying energy and its impact on human daily life, highlighting their effects on integrated ecosystems in the design of residential buildings at both external and internal levels. The study examines key aspects such as the influence of energy on furniture arrangement in living spaces. The primary objective is to establish a synergistic relationship between architectural design of residential spaces during occupancy …

Some Aspects Of The Suitability Of Three-Story Residential Buildings For Vertical Housing In Iraq, Wisam William Saleem Al-Ayoubi

Al-Esraa University College Journal for Engineering Sciences

This research initially aimed to examine the changes in housing since the 1930s, driven by rapid population growth and evolving lifestyles, juxtaposed with advancements in contemporary building materials that are environmentally compatible. After a comprehensive analysis of housing and living arrangements throughout history, including the evolution of open house units towards more interior-focused designs such as the Baghdadi house with its central courtyard, the study delved into the significant changes and the challenges posed by the rapid population growth. The focus of the study was on the viability of vertical housing in Iraq and the considerations related to low-rise residential …

Role Of Iconic Architecture In Sustainable Tourism Development, Basim H. H. Al-Majidi, Ann Samari Ibrahim

Al-Esraa University College Journal for Engineering Sciences

Architecture "is an expression of the way of life and the spirit of the ages and cultures in which I grew up" as the buildings speak for themselves. While tourism is a scenario "to define a city to an unfamiliar audience and acquire an identity for a citizen". Both architecture and tourism have been linked together since time immemorial. Architecture was the main aspect of attracting crowds, while tourism helped architecture survive the test of time as well as money. Both tourism and architecture operate in a symbiotic manner to break the lack of familiarity with any culture and to …

Machine Learning Based Model For The Detection Of Brain Aneurysms From Mr Angiography, Katherine Becknell, Claire Bushnell, Rachel Fitzsimmons, Emily Sumner

Interdisciplinary Design Senior Theses

A brain aneurysm is a thin or weak spot on a blood vessel wall that expands and fills with blood. Brain aneurysms are very dangerous due to the fact that in most cases, patients do not show any symptoms. Because of this, aneurysms are difficult to diagnose unless it becomes very large or ruptures, resulting in fatal hemorrhage.

Aneurysms can be detected by a number of different brain imaging methods including Magnetic Resonance Imaging (MRI), Magnetic Resonance Angiography (MRA), Computed Tomography Angiography (CTA) and other imaging methods but for the sake of this report we will only be focusing on …

Breast Cancer Detection From Histopathology Images Using Machine Learning Techniques: A Bibliometric Analysis, Shubhangi A. Joshi, Anupkumar M. Bongale Dr., Arunkumar M. Bongale Dr.

Library Philosophy and Practice (e-journal)

Computer aided diagnosis has become upcoming area of research over past few years. With the advent of machine learning and especially deep learning techniques, the scenario of work flow management in healthcare sector is changing drastically. Artificial intelligence has shown potential in the field of breast cancer care. With datasets for machine learning frameworks getting eventually richer with time, we can definitely get newer insights in the field of breast cancer care. This will help in narrowing down the treatment range for patients and increasing patient survivability. The purpose of this study was to perform bibliometric analysis of the literature …

Machine Learning Approaches For Lung Cancer Diagnosis., Ahmed Mahmoud Ahmed Shaffie

Electronic Theses and Dissertations

The enormity of changes and development in the field of medical imaging technology is hard to fathom, as it does not just represent the technique and process of constructing visual representations of the body from inside for medical analysis and to reveal the internal structure of different organs under the skin, but also it provides a noninvasive way for diagnosis of various disease and suggest an efficient ways to treat them. While data surrounding all of our lives are stored and collected to be ready for analysis by data scientists, medical images are considered a rich source that could provide …

A Brief Bibliometric Survey Of Explainable Ai In Medical Field, Nilkanth Mukund Deshpande, Shilpa Shailesh Gite

Library Philosophy and Practice (e-journal)

_{^{Background: This study aims to analyze the work done in the field of explainability related to artificial intelligence, especially in the medical field from 2004 onwards using the bibliometric methods.}}

_{^{Methods: different articles based on the topic leukemia detection were retrieved using one of the most popular database- Scopus. The articles are considered from 2004 onwards. Scopus analyzer is used for different types of analysis including documents by year, source, county and so on. There are other different analysis tools such as VOSviewer Version 1.6.15. This is used for the analysis of different units such as co-authorship, co-occurrences, citation analysis …}}

Scalable Approaches For Auditing The Completeness Of Biomedical Ontologies, Fengbo Zheng

Theses and Dissertations--Computer Science

An ontology provides a formalized representation of knowledge within a domain. In biomedicine, ontologies have been widely used in modern biomedical applications to enable semantic interoperability and facilitate data exchange. Given the important roles that biomedical ontologies play, quality issues such as incompleteness, if not addressed, can affect the quality of downstream ontology-driven applications. However, biomedical ontologies often have large sizes and complex structures. Thus, it is infeasible to uncover potential quality issues through manual effort. In this dissertation, we introduce automated and scalable approaches for auditing the completeness of biomedical ontologies. We mainly focus on two incompleteness issues -- …

A Deep Learning Approach To Lncrna Subcellular Localization Using Inexact Q-Mer, Weijun Yi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Long non coding Ribonucleic Acids (lncRNAs) can be localized to different cellular components, such as the nucleus, exosome, cytoplasm, ribosome, etc. Their biological functions can be influenced by the region of the cell they are located. Many of these lncRNAs are associated with different challenging diseases. Thus, it is crucial to study their subcellular localization. However, compared to the vast number of lncRNAs, only relatively few have annotations in terms of their subcellular localization. Conventional computational methods use q-mer profiles from lncRNA sequences and then train machine learning models, such as support vector machines and logistic regression with the profiles. …

Improve The Prototype Of Low-Cost Near-Infrared Diffuse Optical Imaging System, Chen Xu, Mohammed Z. Shakil

Publications and Research

Diffuse Optical Tomography (DOT) and Optical Spectroscopy using near-infrared (NIR) diffused light has demonstrated great potential for the initial diagnosis of tumors and in the assessment of tumor vasculature response to neoadjuvant chemotherapy. The aims of this project are 1) to test the different types of LEDs in the near-infrared range, and design the driving circuit, and test the modulation of LEDs at different frequencies; 2) to test the APDs as a detector, and build the receiver system and compare efficiency with pre-built systems. In this project, we are focusing on creating a low-cost infrared transmission system for tumor and …

Imparting 3d Representations To Artificial Intelligence For A Full Assessment Of Pressure Injuries., Sofia Zahia

Electronic Theses and Dissertations

During recent decades, researches have shown great interest to machine learning techniques in order to extract meaningful information from the large amount of data being collected each day. Especially in the medical field, images play a significant role in the detection of several health issues. Hence, medical image analysis remarkably participates in the diagnosis process and it is considered a suitable environment to interact with the technology of intelligent systems. Deep Learning (DL) has recently captured the interest of researchers as it has proven to be efficient in detecting underlying features in the data and outperformed the classical machine learning …

Phenotyping Of Hypertensive Heart Disease And Hypertrophic Cardiomyopathy Using Personalized 3d Modeling And Cardiac Magnetic Resonance Imaging, Chuah Shoon Hui

Student Works (2020-2029)

Differential diagnosis of hypertensive heart disease (HHD) and hypertrophic cardiomyopathy (HCM) is clinically challenging but important for treatment management. This study aims to phenotype HHD and HCM in 3D+time domain by using a multiparametric motion-corrected personalized modeling algorithm and cardiac magnetic resonance (CMR). 44 CMR data, including 12 healthy, 16 HHD and 16 HCM cases, were examined. Multiple CMR phenotype data consisting of geometric and dynamic variables were extracted globally and regionally from the models over a full cardiac cycle for comparison against the healthy models and clinical reports. Statistical classifications were used to identify the distinctive characteristics and disease …

Wetting-Driven Formation Of Present-Day Loess Structure, Yanrong Li, Weiwei Zhang, Shengdi He, Adnan Aydin

Faculty and Student Publications

© 2020 The Authors Present-day loess, especially Malan loess formed in Later Quaternary, has a characteristic structure composed of vertically aligned strong units and weak segments. Hypotheses describing how this structure forms inside original loess deposits commonly relate it to wetting-drying process. We tested this causal relationship by conducting unique experiments on synthetic samples of initial loess deposits fabricated by free-fall of loess particles. These samples were subjected to a wetting-drying cycle, and their structural evolutions were documented by close-up photography and CT scanning. Analysis of these records revealed three key stages of structural evolution: initiation (evenly distributed cracks appear …

A Mathematical Framework For Estimating Risk Of Airborne Transmission Of Covid-19 With Application To Face Mask Use And Social Distancing, Rajat Mittal, Charles Meneveau, Wen Wu

Faculty and Student Publications

© 2020 Author(s). A mathematical model for estimating the risk of airborne transmission of a respiratory infection such as COVID-19 is presented. The model employs basic concepts from fluid dynamics and incorporates the known scope of factors involved in the airborne transmission of such diseases. Simplicity in the mathematical form of the model is by design so that it can serve not only as a common basis for scientific inquiry across disciplinary boundaries but it can also be understandable by a broad audience outside science and academia. The caveats and limitations of the model are discussed in detail. The model …

A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman

Library Philosophy and Practice (e-journal)

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is …

Three-Dimensional (3d) Reconstruction Of Computed Tomography (Ct) Abdominal Images Using Visualization Toolkit (Vtk), Mat Saad Afifah Husna

Student Works (2020-2029)

A computerized tomography (CT) or computerized axial tomography (CAT) scan combines data from several X-raysito produce a detailed image of structures inside the body. CT scans produce 2D of a “slice” or section of the abdomen but the data can also be used to construct 3-dimensional images. However, CT scan unable to accurately represent the internal structure of soft tissues and soft-tissue lesions. Therefore, using the program in Visualization Tool Kit (VTK) is needed to construct a much more clearer 3D image. To reconstruct 3D images from 2D images of a “slice” or section of abdomen which will be resulting …

Machine Learning Approaches For Fracture Risk Assessment: A Comparative Analysis Of Genomic And Phenotypic Data In 5130 Older Men, Qing Wu, Fatma Nasoz, Jongyun Jung, Bibek Bhattarai, Mira V. Han

School of Public Health Faculty Research

The study aims were to develop fracture prediction models by using machine learning approaches and genomic data, as well as to identify the best modeling approach for fracture prediction. The genomic data of Osteoporotic Fractures in Men, cohort Study (n = 5130), were analyzed. After a comprehensive genotype imputation, genetic risk score (GRS) was calculated from 1103 associated Single Nucleotide Polymorphisms for each participant. Data were normalized and split into a training set (80%) and a validation set (20%) for analysis. Random forest, gradient boosting, neural network, and logistic regression were used to develop prediction models for major osteoporotic fractures …

Analysis Of Information Security Methods In Biosystems And Application Of Intelligent Tools In Information Security Systems, Sherzod Sayfullaev

Chemical Technology, Control and Management

In this paper, the methods of information protection in bio systems are studied. The paper considers the use of intelligent tools in information security systems and the use of adaptive information security systems. Several articles on the field of information protection in bio systems are analyzed. Disadvantages and advantages of neural network technologies in modern information security systems are described. The characteristics of bio systems and the specificity of DNA, the main features of the DNA code that provide information security and functional stability of bio systems data protection structure. Application of intelligent tools to create a comprehensive adaptive protection …

Reading Robot, Gillian Watts, Andrew Myers, Sabrinna Tan, Taylor Klein, Omeed Djassemi

General Engineering

Presently, there is an insufficient availability of human experts to assist students in reading competency and comprehension. Our team’s goal was to create an improved socially assistive robot for use by therapists, teachers, and parents to help children and adults develop reading skills while they do not have access to specialists. HAPI is a socially assistive robot that we created with the goal of helping students practice their reading comprehension skills. HAPI enables a student to improve their reading skills without an educator present, while enabling educators to review the student's performance remotely. Design constraints included: physical size, weight, duration …

Ml-Medic: A Preliminary Study Of An Interactive Visual Analysis Tool Facilitating Clinical Applications Of Machine Learning For Precision Medicine, Laura Stevens, David Kao, Jennifer Hall, Carsten Görg, Kaitlyn Abdo, Erik Linstead

Engineering Faculty Articles and Research

Accessible interactive tools that integrate machine learning methods with clinical research and reduce the programming experience required are needed to move science forward. Here, we present Machine Learning for Medical Exploration and Data-Inspired Care (ML-MEDIC), a point-and-click, interactive tool with a visual interface for facilitating machine learning and statistical analyses in clinical research. We deployed ML-MEDIC in the American Heart Association (AHA) Precision Medicine Platform to provide secure internet access and facilitate collaboration. ML-MEDIC’s efficacy for facilitating the adoption of machine learning was evaluated through two case studies in collaboration with clinical domain experts. A domain expert review was also …

Implementation Of A Computer-Vision System As A Supportive Diagnostic Tool For Parkinson’S Disease, Diego Machado Reyes

Honors Theses

Parkinson’s disease is the second most common neurodegenerative disorder, affecting nearly 1 million people in the US and it is predicted that the number will keep increasing. Parkinson’s disease is difficult to diagnose due to its similarity with other diseases that share the parkinsonian symptoms and the subjectivity of its assessment, thus increasing the probabilities of misdiagnosis. Therefore, it is relevant to develop diagnostic tools that are quantitatively based and monitoring tools to improve the patient’s quality of life. Computer-based assessment systems have shown to be successful in this field through diverse approaches that can be classified into two main …

Deep Cellular Recurrent Neural Architecture For Efficient Multidimensional Time-Series Data Processing, Lasitha S. Vidyaratne

Electrical & Computer Engineering Theses & Dissertations

Efficient processing of time series data is a fundamental yet challenging problem in pattern recognition. Though recent developments in machine learning and deep learning have enabled remarkable improvements in processing large scale datasets in many application domains, most are designed and regulated to handle inputs that are static in time. Many real-world data, such as in biomedical, surveillance and security, financial, manufacturing and engineering applications, are rarely static in time, and demand models able to recognize patterns in both space and time. Current machine learning (ML) and deep learning (DL) models adapted for time series processing tend to grow in …

Design And Development Of A Robotic Platform For General Neurosurgical Procedures, Mehbodniya Amir Hossein

Student Works (2020-2029)

For the first time in 1985, robots were introduced to the neurosurgical operating rooms. Since then this field of robotics have advanced with new technologies with better accuracy and safety. However, developing robots for neurosurgery is a challenging task due to the sensitive nature of these applications and additionally their high cost of development. A typical neurosurgical robot costs millions of dollars in 2018, even though the costs of components and calculations have been lowered tremendously. This is mainly due to focus of current neurosurgical robots on few highly precise and specific surgical tasks which makes their use limited. In …

Architecture And Trilogy Of (Law, Theory And Hypothesis), Ahmed Hashim Hameed

Al-Esraa University College Journal for Engineering Sciences

The general cognitive expositions had focused on the study of the general knowledge frameworks of the field of architecture, with both concepts that influencing and influenced by them, which used to contain them without referring to their intellectual origins in order to understand their general effect and their role in the cognitive enrichment to the architectural field. This, in return, showed the importance of direction to study the role, influence and effect of trilogy (Law, theory and hypothesis) in the field of architecture, according to their general reality knowledge and their specific theoretical and intellectual characteristics. This research deals with …

The Impact Of Spatial Location Of Functions To Identify Architectural Forms As A Landmark (Case Study - Contemporary Islamic Architecture -), Ibtisam Abdulelah Mohammed Al Khafaji, Maha Haki Ismaeil

Al-Esraa University College Journal for Engineering Sciences

This research discusses the impact of spatial location of functions inside architectural form to enhance visual legibility and how it can improve the possibilities of identifying them as a landmark. The absence of a clear conceptual frame which can be used to describe this impact forms the basic research problem. The objective aim of the research is to clarify and describe this impact. To achieve this objective aim, an analytical process was used. We supposed that spatial location of functions enhances visual legibility of forms, then improves our possibility of identifying them as a landmark. For applying the conceptual frame, …

Effect Of Loading Level Of Hybrid Reinforced Concrete Deep Beams Under Repeated Loading, Sawsan Akram Hassan, Ghsoon Ali Faroun

Al-Esraa University College Journal for Engineering Sciences

This research is devoted to investigating the experimental and theoretical behavior of hybrid deep beams under monotonic and repeated two-point loading. The dimensions and the flexural reinforcement of the deep beams were kept constant. In this work, the idea of a hybrid beam is completely different. Two types of concrete were used but not in the cross-section. The first type, which is fiberous concrete (FC), was used in casting beam sides (shear spans), while the second type was conventional concrete (CC) which was used in the middle portion of the beam (between two shear spans). This was done to strengthen …

Reverse Osmosis Method For Sulphate Re-Moval From Treated Wastewater Of Al-Doura Refinery, Rana Mohammed Rasheed

Al-Esraa University College Journal for Engineering Sciences

The treated wastewater by the industrial Wastewater Treatment Plant (WWTP) commonly named (INGECO) in Al-Doura refinery suffers from highly sulfate concentrations that exceed the EPA specified limits of 250 mg/L. Therefore, laboratory water quality historical data have been reviewed and analyzed to determine the annual rate, maximum, and peak sulfate concentrations that were found to be 360 mg/L, 425 mg/L, and 550 mg/L, respectively. Through field inspection aimed at specifying the reasons for the high sulfate concentrations in the wastewater of most refinery process units, it was found that the maximum required sulfate remaining concentration should not exceed 10 mg/L …

Comparison Between Regular And Irregular Configuration In Earthquake Resistant Design, Ali Nur-Aldeen Azeez, Ali Mohsen Jaafer Al-Khafaji

Al-Esraa University College Journal for Engineering Sciences

Earthquake-resistant design is one of the greatest challenges that must be considered by the Architect because it is a serious natural disaster that affects the stability and durability of the building. Due to the connection between the seismic behavior of buildings with its formal configuration and the differences in seismic resistance between regular and irregular buildings, the research problem presented as the confusion of seismic behavior of irregular buildings and their difference from the regular buildings when earthquakes occur. The aim of the research is to clarify the differences between regular and irregular configurations, also clarifying the design considerations in …

Pedestrian Movement Within Residential Areas, Abd Alali Hamza Mohamed

Al-Esraa University College Journal for Engineering Sciences

The network of transport within residential areas, especially within residential neighborhoods, consists mainly of roads designed to provide relative safety for road users and to prioritize solutions that enhance safety. It is believed that the pedestrian movement network should be separated from the car movement network, with a focus on road design, pedestrian paths, and the types of vehicles used in these areas to ensure safety. This research explores the solutions developed in the planning of roads and walkways in traditional housing schemes within the urban fabric of old cities. It examines the approaches and conclusions of modern models of …