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2023

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3d Ar Reconstruction, Sneh Arvind Kothari Jan 2023

3d Ar Reconstruction, Sneh Arvind Kothari

Master's Projects

The goal of the project is to improve the shopping experience for users by using augmented reality technology. People generally want opinions from others when buying shoes offline. Clicking and sending images of a shoe is not an ideal solution as it does not give the complete feel of the shoe. We developed the 3D AR Reconstruction app to make this process better. A user of our app clicks photos of the shoe. This image data is converted to form a mesh that can be shared. On receiving a model the user can open it in the app and interact …

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Static Taint Analysis Via Type-Checking In Typescript, Abhijn Chadalawada Jan 2023

Static Taint Analysis Via Type-Checking In Typescript, Abhijn Chadalawada

Master's Projects

With the widespread use of web applications across the globe, and the ad- vancements in web technologies in recent years, these applications have grown more ubiquitous and sophisticated than ever before. Modern web applications face the constant threat of numerous web security risks given their presence on the internet and the massive influx of data from external sources. This paper presents a novel method for analyzing taint through type-checking and applies it to web applications in the context of preventing online security threats. The taint analysis technique is implemented in TypeScript using its built-in type-checking features, and then integrated into …

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Concept Drift Detection In Android Malware, Inderpreet Singh Jan 2023

Concept Drift Detection In Android Malware, Inderpreet Singh

Master's Projects

Machine learning and deep learning algorithms have been successfully applied to the problems of malware detection, classification, and analysis. However, most of such studies have been limited to applying learning algorithms to a static snapshot of malware, which fails to account for concept drift, that is, the non-stationary nature of the data. In practice, models need to be updated whenever a sufficient level of concept drift has occurred. In this research, we consider concept drift detection in the context of Android malware. We train a series of Support Vector Machines (SVM) over sliding windows of time and compare the resulting …

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Federated Learning For Protecting Medical Data Privacy, Abhishek Reddy Punreddy Jan 2023

Federated Learning For Protecting Medical Data Privacy, Abhishek Reddy Punreddy

Master's Projects

Deep learning is one of the most advanced machine learning techniques, and its prominence has increased in recent years. Language processing, predictions in medical research and pattern recognition are few of the numerous fields in which it is widely utilized. Numerous modern medical applications benefit greatly from the implementation of machine learning (ML) models and the disruptive innovations in the entire modern health care system. It is extensively used for constructing accurate and robust statistical models from large volumes of medical data collected from a variety of sources in contemporary healthcare systems [1]. Due to privacy concerns that restrict access …

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Keystroke Dynamics And User Identification, Atharva Sharma Jan 2023

Keystroke Dynamics And User Identification, Atharva Sharma

Master's Projects

We consider the potential of keystroke dynamics for user identification and authentication. We work with a fixed-text dataset, and focus on clustering users based on the difficulty of distinguishing their typing characteristics. After obtaining a confusion matrix, we cluster users into different levels of classification difficulty based on their typing patterns. Our goal is to create meaningful clusters that enable us to apply appropriate authentication methods to specific user clusters, resulting in an optimized balance between security and efficiency. We use a novel feature engineering method that generates image-like features from keystrokes and employ multiclass Convolutional Neural Networks (CNNs) to …

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On The Memory Scalability Of Spectral Clustering Algorithms, Ran Li Jan 2023

On The Memory Scalability Of Spectral Clustering Algorithms, Ran Li

Master's Projects

Spectral clustering has lots of advantages compared to previous more traditional clustering methods, such as k-means and Gaussian Mixture Models (GMM), and is popular since it was introduced. However, there are two major challenges, speed scalability and memory scalability, that impede the wide applications of spectral clustering. The first challenge has been addressed recently by Chen [1] [2] in the special setting of sparse or low dimensional data sets. In this work, we will first review the recent study by Chen that speeds up spectral clustering. Then we will propose three new computational methods for the same special setting of …

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Dynamic Predictions Of Thermal Heating And Cooling Of Silicon Wafer, Hitesh Kumar Jan 2023

Dynamic Predictions Of Thermal Heating And Cooling Of Silicon Wafer, Hitesh Kumar

Master's Projects

Neural Networks are now emerging in every industry. All the industries are trying their best to exploit the benefits of neural networks and deep learning to make predictions or simulate their ongoing process with the use of their generated data. The purpose of this report is to study the heating pattern of a silicon wafer and make predictions using various machine learning techniques. The heating of the silicon wafer involves various factors ranging from number of lamps, wafer properties and points taken in consideration to capture the heating temperature. This process involves dynamic inputs which facilitates the heating of the …

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Security And Routing In A Disconnected Delay Tolerant Network, Anirudh Kariyatil Chandakara Jan 2023

Security And Routing In A Disconnected Delay Tolerant Network, Anirudh Kariyatil Chandakara

Master's Projects

Providing internet access in disaster-affected areas where there is little to no internet connectivity is extremely difficult. This paper proposes an architecture that utilizes existing hardware and mobile applications to enable users to access the Internet while maintaining a high level of security. The system comprises a client application, a transport application, and a server running on the cloud. The client combines data from all supported applications into a single bundle, which is encrypted using an end-to-end encryption technique and sent to the transport. The transport physically moves the bundles to a connected area and forwards them to the server. …

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Image-Based Malware Detection Using Convolutional Neural Network Techniques, Brandon Palomino Jan 2023

Image-Based Malware Detection Using Convolutional Neural Network Techniques, Brandon Palomino

Master's Projects

In this study, we delve into the realm of malware detection and classification, leveraging the capabilities of different Convolutional Neural Networks (CNNs). Our approach involves transforming executable files into image formats and subsequently applying advanced CNN techniques for image recognition. The study emphasizes the use of two distinct CNN architectures: a traditional CNN model and a modified CNN variant known as a convolutional recurrent neural network (CRNN), each with unique structural and functional attributes. To effectively train these models, we adopt a transfer learning strategy, utilizing pre-existing CNN models that have been extensively trained on large-scale image datasets. This methodology …

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Pygrapherconnect, Shubham Jain Jan 2023

Pygrapherconnect, Shubham Jain

Master's Projects

The evolving landscape of backend computational systems especially in biomedical research involving heavy data operations which have a gap of not being used properly. It is due to the lack of communication standard between the frontend and backend. This gap presents a problem to researchers who need to use the frontend for visualizing and manipulating their data but also want to do complex analysis. CAPRI a python-based backend system specializing in analyzing Evidential Reasoning data also has the same issue. This project offers a solution PyGrapherConnect module acting as a data conversion layer between CAPRI and PyGrapher, its frontend interface. …

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Romeo And Juliet Word Cloud, Ml Tlachac Jan 2023

Romeo And Juliet Word Cloud, Ml Tlachac

Center for Teaching Excellence (CTE)

PowerPoint presented at the Annual Spring Teaching Summit: Teaching and Learning Demos produced by the Center for Teaching Excellence.

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Thinking Local With Original Data In Ai And Machine Learning Research, David G. Taylor, Robert Mccloud Jan 2023

Thinking Local With Original Data In Ai And Machine Learning Research, David G. Taylor, Robert Mccloud

WCBT Working Papers

Sacred Heart University spent significant funds to establish an AI lab. Initially there is no ongoing research and no real plan for a research agenda. This paper details how the Jack Welch College of Business and Technology created and implemented an active meaningful research plan. It involves two key elements: thinking local and using business connections to foster active, impactful research. Surrounding communities, business connections, area environment, and other Sacred Heart University departments all played a part. The research plan also identifies a specific issue in working with local and business contact sources: the AI researcher almost never gets data …

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A Survey And Evaluation Of Android-Based Malware Evasion Techniques And Detection Frameworks, Parvez Faruki, Rhati Bhan, Vinesh Jain, Sajal Bhatia, Nour El Madhoun, Rajendra Pamula Jan 2023

A Survey And Evaluation Of Android-Based Malware Evasion Techniques And Detection Frameworks, Parvez Faruki, Rhati Bhan, Vinesh Jain, Sajal Bhatia, Nour El Madhoun, Rajendra Pamula

School of Computer Science & Engineering Faculty Publications

Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware. Adversaries are constantly in charge of employing innovative techniques to avoid or prolong malware detection effectively. Past studies have shown that malware detection systems are susceptible to evasion attacks where adversaries can successfully bypass the existing security defenses and deliver the malware to the target system without being detected. The evolution of escape-resistant systems is an open research problem. This paper presents a detailed taxonomy and evaluation of Android-based malware evasion …

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A Survey And Evaluation Of Android-Based Malware Evasion Techniques And Detection Frameworks, Parvez Faruki, Rhati Bhan, Vinesh Jain, Sajal Bhatia, Nour El Madhoun, Rajendra Pamula Jan 2023

A Survey And Evaluation Of Android-Based Malware Evasion Techniques And Detection Frameworks, Parvez Faruki, Rhati Bhan, Vinesh Jain, Sajal Bhatia, Nour El Madhoun, Rajendra Pamula

School of Computer Science & Engineering Faculty Publications

Android platform security is an active area of research where malware detection techniques continuously evolve to identify novel malware and improve the timely and accurate detection of existing malware. Adversaries are constantly in charge of employing innovative techniques to avoid or prolong malware detection effectively. Past studies have shown that malware detection systems are susceptible to evasion attacks where adversaries can successfully bypass the existing security defenses and deliver the malware to the target system without being detected. The evolution of escape-resistant systems is an open research problem. This paper presents a detailed taxonomy and evaluation of Android-based malware evasion …

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E-Learning Course Recommender System Using Collaborative Filtering Models, Kalyan Kumar Jena, Sourav Kumar Bhoi, Tushar Kanta Malik, Kshira Sagar Sahoo, N. Z. Jhanjhi, Sajal Bhatia, Fathi Amsaad Jan 2023

E-Learning Course Recommender System Using Collaborative Filtering Models, Kalyan Kumar Jena, Sourav Kumar Bhoi, Tushar Kanta Malik, Kshira Sagar Sahoo, N. Z. Jhanjhi, Sajal Bhatia, Fathi Amsaad

School of Computer Science & Engineering Faculty Publications

e-Learning is a sought-after option for learners during pandemic situations. In e-Learning platforms, there are many courses available, and the user needs to select the best option for them. Thus, recommender systems play an important role to provide better automation services to users in making course choices. It makes recommendations for users in selecting the desired option based on their preferences. This system can use machine intelligence (MI)-based techniques to carry out the recommendation mechanism. Based on the preferences and history, this system is able to know what the users like most. In this work, a recommender system is proposed …

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Increasing Historically Underserved And Underrepresented Student Completion In Stem Pathways At A Hispanic-Serving Institution: An Action Research Study, Inez F. Olive, Kyle J. Winslow, Osurè L. Brown, Eric R. Marshall Jan 2023

Increasing Historically Underserved And Underrepresented Student Completion In Stem Pathways At A Hispanic-Serving Institution: An Action Research Study, Inez F. Olive, Kyle J. Winslow, Osurè L. Brown, Eric R. Marshall

Educational and Organizational Learning and Leadership Dissertations

There is a demand for accountability for higher education institutions to increase student completion, specifically for institutions that enroll many students from historically underserved and underrepresented populations (HUUP). Meanwhile, labor market analysis presents a demand for skilled and diverse workers in science, technology, engineering, and mathematics (STEM) fields. Hispanic-serving institutions (HSI) have an advantage when supporting student completion to meet this workforce demand. This inquiry employed participatory action research (PAR) through a partnership with an HSI in rural Washington State. Using transformative worldview as the theoretical framework, this study aimed to determine the influence of completion planning for STEM students …

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Blockchain, The Superhero That The Healthcare Industry Needs, Victor Wang Jan 2023

Blockchain, The Superhero That The Healthcare Industry Needs, Victor Wang

Cardozo Arts & Entertainment Law Journal

The note argues that blockchain technology holds significant potential for transforming the healthcare industry by enhancing data security and efficiency. However, its integration faces legal challenges due to conflicts with existing healthcare laws, particularly the Health Insurance Portability and Accountability Act (HIPAA) and the HITECH Act. The note contends that blockchain's decentralized and immutable nature violates key HIPAA requirements, such as data disposal and accountability standards. It advocates for updating these laws to accommodate blockchain technology and ensure compliance, emphasizing the need for legal frameworks to evolve alongside technological advancements.

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Multiple Interacting Stressors Influence Development, Growth, And Morphology Of Pacific Chorus Frog (Pseudacris Regilla) Larvae, Abby Dalke, Allie M. Erickson, Bailey R. Tasker, Skylar Riley, Paul Hurst, Sarah Cooney, Scott A. Griffith, Betsy A. Bancroft Jan 2023

Multiple Interacting Stressors Influence Development, Growth, And Morphology Of Pacific Chorus Frog (Pseudacris Regilla) Larvae, Abby Dalke, Allie M. Erickson, Bailey R. Tasker, Skylar Riley, Paul Hurst, Sarah Cooney, Scott A. Griffith, Betsy A. Bancroft

Biology Faculty Scholarship

Freshwater ecosystems are threatened by climate change and invasive species. Amphibians are important members of freshwater communities and are susceptible to negative effects of climate change and invasion. Furthermore, both climate change and invasion can influence density of amphibian larvae at the microhabitat scale because of larval clustering. To understand the effects of climate change and invasion on Pacific Chorus Frog Pseudacris regilla (Baird and Girard, 1852) larvae, a 2 × 2 × 2 factorial experiment was carried out with a climate treatment (future/historical; simulated as changes in both temperature and hydroperiod), indirect exposure to the invasive Brook Stickleback Culaea …

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Artificial Intelligence Solutions For Health 4.0: Overcoming Challenges And Surveying Applications, Abdel-Hameed Al-Mistarehi, Maad M. Mijwil, Youssef Filali, Mariem Bounabi, Guma Ali, Mostafa Abotaleb Jan 2023

Artificial Intelligence Solutions For Health 4.0: Overcoming Challenges And Surveying Applications, Abdel-Hameed Al-Mistarehi, Maad M. Mijwil, Youssef Filali, Mariem Bounabi, Guma Ali, Mostafa Abotaleb

Mesopotamian Journal of Artificial Intelligence in Healthcare

In recent years, the term Health 4.0 has appeared in health services and is related to the concept of Industry 4.0. The term Health 4.0 focuses on replacing traditional care in hospitals and medical clinics with home health services that are based on artificial intelligence techniques through the use of telemedicine applications that allow the monitoring of patients in a virtual environment. This term is utilized to represent digital change in the healthcare sector. Governments aim to develop the level of medical care in hospitals and clinics to ensure the provision of healthcare benefits at low costs and increase patient …

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Discussing Artificial Intelligence's Role In Combatting The Covid-19 Pandemic: A Review, Rusul Ali Radhi Jan 2023

Discussing Artificial Intelligence's Role In Combatting The Covid-19 Pandemic: A Review, Rusul Ali Radhi

Mesopotamian Journal of Artificial Intelligence in Healthcare

The COVID-19 pandemic is considered one of the most dangerous diseases that have emerged in recent years, as it began at the end of 2019 in China and quickly spread to become a severe epidemic. This virus has become, in a short period of time, threatening millions of the earth's populations, and infected individuals show symptoms that may lead to the loss of their lives. In this article, the author concentrates on the significance and methods of artificial intelligence strategies in facing COVID-19 and the primary role of these technologies. AI techniques have been applied in various areas, including creating …

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Schizophrenia And The Role Of Artificial Intelligence In Detecting And Treating It: Cognitive Frontiers, Mohanad G. Yaseen, Saad Abas Abed Jan 2023

Schizophrenia And The Role Of Artificial Intelligence In Detecting And Treating It: Cognitive Frontiers, Mohanad G. Yaseen, Saad Abas Abed

Mesopotamian Journal of Artificial Intelligence in Healthcare

A persistent mental illness that changes thoughts, feelings, behaviour, and communication with people is schizophrenia. Delusions, hallucinations, distorted thinking, lack of motivation, and fear of society are often its hallmarks. Although there is currently no cure for schizophrenia, patients can greatly benefit from early diagnosis and treatment. The field of artificial intelligence (AI) is very promising for the diagnosis and treatment of schizophrenia. Artificial intelligence systems can scan and analyse vast amounts of data, including genetic and hereditary data, brain scans, and medical records, and predict when a person might develop schizophrenia if the factor is hereditary. This can help …

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The Modern Impact Of Artificial Intelligence Systems In Healthcare: A Concise Analysis, Habeeb Omotunde, Mourad R. Mouhamed Jan 2023

The Modern Impact Of Artificial Intelligence Systems In Healthcare: A Concise Analysis, Habeeb Omotunde, Mourad R. Mouhamed

Mesopotamian Journal of Artificial Intelligence in Healthcare

Artificial intelligence systems are receiving significant attention in the healthcare domain because they have a considerable impact on the development of patients' electronic medical records (EMRs). Artificial intelligence systems have the ability to develop healthcare institutions and assist physicians in making the proper decisions. These systems have the ability to perform diagnosis, provide appropriate treatment, and perform administrative tasks in hospitals. Healthcare institutions seek to integrate hospital systems with computer systems and construct large warehouses to store data and medical records for each patient. These methods allow machine learning and deep learning algorithms to analyse diseases, predict and determine new …

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Lateral Spacing Of Subsurface Poultry Litter Bands: Effect On Gaseous Nitrogen Emissions, Nutrient Uptake, And Maize Yield, Jason R. Simmons Jan 2023

Lateral Spacing Of Subsurface Poultry Litter Bands: Effect On Gaseous Nitrogen Emissions, Nutrient Uptake, And Maize Yield, Jason R. Simmons

Theses and Dissertations--Plant and Soil Sciences

Poultry litter (PL) is traditionally applied to no-till maize (Zea mays L.) cropping systems by surface broadcast. Poultry litter is nutrient dense, and it has been repeatedly shown that surface applied PL nitrogen (N) is vulnerable to losses to the atmosphere and nearby water systems. An application method was developed by USDA-Agricultural Research Service scientists for banding poultry litter (PL) below the soil surface with minimal soil disturbance to reduce ammonia (NH3) volatilization and surface run-off. It is well documented that subsurface applied poultry litter (PL) reduces N losses by ammonia (NH3) volatilization; however, the …

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Universal Design For Learning Implementation In Higher Education: Survey Of Faculty And Instructional Designers, Breanne A. Kirsch, Tian Luo Jan 2023

Universal Design For Learning Implementation In Higher Education: Survey Of Faculty And Instructional Designers, Breanne A. Kirsch, Tian Luo

STEMPS Faculty Publications

Universal design for learning (UDL) is an inclusive design framework. Faculty and instructional designers were surveyed to investigate UDL implementation in higher education. This survey was based on one used by Westine et al. (2019). Results about how faculty and instructional designers learn about UDL, how instructional designers train and support faculty in UDL, and why and how participants choose to employ UDL are shared. The results from this study have provided new findings in relation to faculty and instructional designer UDL implementation efforts in higher education that have implications for training and supporting faculty with UDL application efforts.

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Exploring Grades 3-5 Mathematics Activities Found Online, Lara Dick, Amanda Sawyer, Margaret Macneille, Emily Shapiro, Tabitha Wismer Jan 2023

Exploring Grades 3-5 Mathematics Activities Found Online, Lara Dick, Amanda Sawyer, Margaret Macneille, Emily Shapiro, Tabitha Wismer

Faculty Journal Articles

We investigate resources on TeachersPayTeachers and discuss how what is available affects our teaching practices.

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Math 301: Abstract Algebra I, Nicholas Vlamis Jan 2023

Math 301: Abstract Algebra I, Nicholas Vlamis

Open Educational Resources

No abstract provided.

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Towards Artificial Intelligence-Based Cybersecurity: The Practices And Chatgpt Generated Ways To Combat Cybercrime, Maad M. Mijwil, Mohammad Aljanabi, Chatgpt Chatgpt Jan 2023

Towards Artificial Intelligence-Based Cybersecurity: The Practices And Chatgpt Generated Ways To Combat Cybercrime, Maad M. Mijwil, Mohammad Aljanabi, Chatgpt Chatgpt

Iraqi Journal for Computer Science and Mathematics

Today, cybersecurity is considered one of the most noteworthy topics that are circulated frequently among companies in order to protect their data from hacking operations. The emergence of cyberspace contributed to the growth of electronic systems.It is a virtual digital space through which interconnection is established between computers and smartphones connected within the Internet of Things environment.This space is critical in building a safe digital environment free of threats and cybercrime.It is only possible to make a digital environment with the presence of cyberspace, which contains modern technologies that make this environment safe and far from unauthorized individuals.Cybersecurity has a …

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The Significance Of Machine Learning And Deep Learning Techniques In Cybersecurity: A Comprehensive Review, Maad M. Mijwil, Israa Ezzat Salem, Marwa M. Ismaeel Jan 2023

The Significance Of Machine Learning And Deep Learning Techniques In Cybersecurity: A Comprehensive Review, Maad M. Mijwil, Israa Ezzat Salem, Marwa M. Ismaeel

Iraqi Journal for Computer Science and Mathematics

People in the moderneraspendmost of their lives in virtual environments that offer a range of public and private servicesand social platforms. Therefore, these environments need to be protected from cyber attackers that can steal data or disruptsystems. Cybersecurity refers to a collection of technical, organizational, andexecutive means for preventing the unauthorized use or misuse of electronic informationand communication systems to ensure the continuityof their work, guarantee the confidentialityand privacy of personal data, and protect consumers from threats and intrusions. Accordingly, this articleexplores the cybersecurity practices that protect computer systemsfrom attacks, hacking,and data thefts and investigates the role of artificial intelligence …

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Elementary Treatise On Melted-Like Curves Derived From Centerellipse And Circle, Laith H. M Al-Ossmi Jan 2023

Elementary Treatise On Melted-Like Curves Derived From Centerellipse And Circle, Laith H. M Al-Ossmi

Iraqi Journal for Computer Science and Mathematics

This studydeals with a special case in the geometry of 2Dspecial plane curves. The research treaties the development of a method for locating points and drawing curves derived from moving points on two curved paths of conic sections, namely,circle and ellipse. The paperpresentsgeometrical methodsto determine pointsandnodes and todraw these melted-like curvesin two cases. Parametric equationsare also usedto determine the ordinates of the points of each curve of the two casesof the curves. Thisresearchis the initialphase for thenew typeof curves and awaits future studiesthat will deal on 3Dsurfaces,such as a sphere, a right cone, or a right cylinder.

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A Systematic Survey On The Research Of Ai-Predictivemodelsforwastewater Treatment Processes, Varun Geetha Mohan, Al-Fahim Mubarak Ali, Mohamed Ariff Ameedeen Jan 2023

A Systematic Survey On The Research Of Ai-Predictivemodelsforwastewater Treatment Processes, Varun Geetha Mohan, Al-Fahim Mubarak Ali, Mohamed Ariff Ameedeen

Iraqi Journal for Computer Science and Mathematics

Context:To increase the efficiencyof wastewater treatment, modeling and optimization of pollutant removal processes are the best solutions. The relationship between input and output parameters inwastewater treatment processes (WWTP) is a complicated one, and it is difficult for designing models using statistics. Artificial Intelligence (AI)models are generally more flexible when compared with statistical models while modeling complex datasets with nonlinearityand missing data.Objective:Studies on WWTP of AI-basedare increasing day by day. Therefore,it is crucialto systematically review the AI techniquesavailablewhich are implemented for WWTP. Such kind of review helpsforclassifyingthetechniques that are invented andhelpsto identify challenges as well asgaps for future studies.Lastly, cansort out …

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