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Articles 13861 - 13890 of 63035

Full-Text Articles in Computer Sciences

Investigating The Nuclear Properties Of 162-172 Er Isotopes Using Ibm-1, Sef, And Nee, Amal M. Al-Nuaimi, R.B. Alkhayat, Mushtaq Abed Al-Jubbori Aug 2022

Investigating The Nuclear Properties Of 162-172 Er Isotopes Using Ibm-1, Sef, And Nee, Amal M. Al-Nuaimi, R.B. Alkhayat, Mushtaq Abed Al-Jubbori

Karbala International Journal of Modern Science

The energy levels of the ground state band (GSB), , and γ-bands for 162-172Er isotopes are calculated in this work by adopting the Interacting Boson Model (IBM-1), the Semi-Empirical Formula (SEF) and the New Empirical Equation (NEE). The GSB, , and γ-bands results revealed that IBM-1, SEF, NEE, and the available experimental data are all in agreement with certain variations. The NEE is more compatible with the experimental data than the IBM-1 and SEF calculations. This study demonstrates that the SEF and NEE equations are able to describe the energy spectra of Er isotopes in comparison to IBM-1. The Er …

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Antimicrobial And Cytotoxic Properties Of Extracts From Over-Seasoned Worm-Casts Of The Earthworm Hyperiodrilus Africanus Beddard, 1891, Stephen Olugbemiga Owa, David Adeiza Otohinoyi, Theresa Ibibia Edewor-Ikupoyi, Adeolu Adeola Taiwo, Jenifer Akhere Okosun, Yvonne Oluchi Akujobi, Damilola Grace Oyewale, Tomilola Debby Olaolu, Damilare Emmanuel Rotimi, Osarenkhoe Omorefosa Osemwegie, Oluyomi Stephen Adeyemi Aug 2022

Antimicrobial And Cytotoxic Properties Of Extracts From Over-Seasoned Worm-Casts Of The Earthworm Hyperiodrilus Africanus Beddard, 1891, Stephen Olugbemiga Owa, David Adeiza Otohinoyi, Theresa Ibibia Edewor-Ikupoyi, Adeolu Adeola Taiwo, Jenifer Akhere Okosun, Yvonne Oluchi Akujobi, Damilola Grace Oyewale, Tomilola Debby Olaolu, Damilare Emmanuel Rotimi, Osarenkhoe Omorefosa Osemwegie, Oluyomi Stephen Adeyemi

Karbala International Journal of Modern Science

⦁ Background: Despite the continuous interest in the search for therapeutic agents, little attention has been given to the medicinal relevance of earthworm casts, with even less interest in over-seasoned worm-casts. Therefore, this study determined the phytochemical, antimicrobial, and cytotoxic properties of over-seasoned worm-casts of the earthworm Hyperiodrilus africanus (Eudrilidae). Methods: The earthworm casts were extracted with n-hexane, ethanol, and water and the crude extracts were evaluated for the presence of chemical constituents and antimicrobial properties. Cytotoxicity was inferred from the antimitotic effects of the extracts on the radicles of germinating seeds of Sorghum bicolor. Results: The chemical constituent determinations …

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A Review On The Ethnobotanical, Phytochemistry, And Pharmacological Activities Of Aristolochia Longa L., Oluwafemi Adeleke Ojo, Matthew Iyobhebhe, Bukola Atunwa, Adebola Busola Ojo Aug 2022

A Review On The Ethnobotanical, Phytochemistry, And Pharmacological Activities Of Aristolochia Longa L., Oluwafemi Adeleke Ojo, Matthew Iyobhebhe, Bukola Atunwa, Adebola Busola Ojo

Karbala International Journal of Modern Science

Aristolochia longa L. is a plant native to Algeria and Morocco that has been used by the locals to combat different arrays of infections and diseases found among them. This particular plant is well-known for its therapeutic qualities that could be traced back to the presence of many effective phytochemicals that have been extrapolated from the different parts of the plant, like the leaves and roots: flavonoids, saponins, tannins, 4-hydroxybenzoic acid, β-carotenes, limonenes, and palmitic acids. This plant has been identified in different research articles to be able to manage diseases effectively because it possesses some pharmacological attributes such as; …

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Thermal Aware Routing Protocols For Wireless Body Area Networks: Review And Open Research Issues, Samir Bouldjadj Aug 2022

Thermal Aware Routing Protocols For Wireless Body Area Networks: Review And Open Research Issues, Samir Bouldjadj

Karbala International Journal of Modern Science

Wireless Body Area Network (WBAN) is a promising technology that improves life quality and enhances medical healthcare services. The activities and communications of sensors lead to a temperature rise, which can be fatal for the human body. The heating problem is addressed by the thermal-aware strategy, which has great importance. This paper reviews sixteen thermal-aware routing protocols proposed for WBAN; it presents routing in WBAN and its associated challenges. It explains the principles and pros and cons of each protocol and compares the protocols studied using several criteria. Finally, the paper points out the open research issues and challenges. This …

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Applicability Limits Of The End Face Fiber-Optic Gas Concentration Sensor, Based On Fabry-Perot Interferometer, S.M.R.H. Hussein, A.Zh. Sakhabutdinov, O.G. Morozov, V.I. Anfinogentov, J.A. Tunakova, A.R. Shagidullin, A.A. Kuznetsov, K.A. Lipatnikov, A.R. Nasybullin Aug 2022

Applicability Limits Of The End Face Fiber-Optic Gas Concentration Sensor, Based On Fabry-Perot Interferometer, S.M.R.H. Hussein, A.Zh. Sakhabutdinov, O.G. Morozov, V.I. Anfinogentov, J.A. Tunakova, A.R. Shagidullin, A.A. Kuznetsov, K.A. Lipatnikov, A.R. Nasybullin

Karbala International Journal of Modern Science

The mathematical model of the fiber-optic sensor for gas concentration analysis is under study. The sensor is imple-mented as Fabry-Perot interferometer at the end face of the optical fiber by applying a thin polymer film, which permit-tivity depends on the tested gas concentration. It is shown, that a change in the properties of the optical fiber or the at-mosphere permittivity leads mainly to the spectrum contrast changing and does not change the period and the wave-length shift of its comb. The influence of the polymer film thickness, the environment temperature and humidity on the Fabry-Perot spectrum is analyzed. The necessity …

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Molecular Docking Reveals Phytoconstituents Of The Methanol Extract From Muntingia Calabura As Promising Α-Glucosidase Inhibitors, Nurlena Andalia, Muhammad N. Salim, Nurdin Saidi, Muhammad Ridhwan, Muhammad Iqhrammullah, Ummu Balqis Aug 2022

Molecular Docking Reveals Phytoconstituents Of The Methanol Extract From Muntingia Calabura As Promising Α-Glucosidase Inhibitors, Nurlena Andalia, Muhammad N. Salim, Nurdin Saidi, Muhammad Ridhwan, Muhammad Iqhrammullah, Ummu Balqis

Karbala International Journal of Modern Science

Inhibition of α-glucosidase has been used as a management of type 2 diabetes mellitus, where studies are focused on finding more efficacious and safe drugs. Herein, the research aimed to unveil the potential of phytoconstituents contained in methanol extract of Muntingia calabura leaves in inhibiting α-glucosidase through molecular docking simulation. From a systematic search (Scopus), we found 5 eligible articles and identified 28 phytocompounds. Fisetin, pinostrobin, and rhamnetin identified in M. calabura extract were predicted to have good bioavailability. Finally, fisetin was revealed as the most potential α-glucosidase inhibitor candidate with a binding affinity of -7.5 kcal/mol.

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Attack Prediction To Enhance Attack Path Discovery Using Improved Attack Graph, Zaid. J. Al-Araji, Sharifah Sakinah Syed Ahmad, Raihana Syahirah Abdullah Aug 2022

Attack Prediction To Enhance Attack Path Discovery Using Improved Attack Graph, Zaid. J. Al-Araji, Sharifah Sakinah Syed Ahmad, Raihana Syahirah Abdullah

Karbala International Journal of Modern Science

Organisations and governments constantly face potential security attacks. However, the need for next-generation cyber defence has become even more urgent in a day and age when attack surfaces that hackers can exploit have grown at an alarming rate with an increase in the number of devices that are connected to the Internet. As such, next-generation cyber defence that relies on predictive analysis is more proactive than existing technologies that rely on intrusion detection. Many approaches with which to detect and predict attacks have been proposed in recent times. One such approach is attack graphs. The primary purpose of an attack …

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Performance Simulation For Adaptive Optics Technique Using Oomao Toolbox, Mahmood Kareem Mirdan, Raaid Nawfee Hassan, Bushra Qassim Al-Aboodi Aug 2022

Performance Simulation For Adaptive Optics Technique Using Oomao Toolbox, Mahmood Kareem Mirdan, Raaid Nawfee Hassan, Bushra Qassim Al-Aboodi

Karbala International Journal of Modern Science

The Adaptive Optics technique has been developed to obtain the correction of atmospheric seeing. The purpose of this study is to use the MATLAB program to investigate the performance of an AO system with the most recent AO simulation tools, Objected-Oriented Matlab Adaptive Optics (OOMAO). This was achieved by studying the variables that impact image quality correction, such as observation wavelength bands, atmospheric parameters, telescope parameters, deformable mirror parameters, wavefront sensor parameters, and noise parameters. The results presented a detailed analysis of the factors that influence the image correction process as well as the impact of the AO components on …

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Artificial Intelligence In The Radiomic Analysis Of Glioblastomas: A Review, Taxonomy, And Perspective, Ming Zhu, Sijia Li, Yu Kuang, Virginia B. Hill, Amy B. Heimberger, Lijie Zhai, Shenjie Zhai Aug 2022

Artificial Intelligence In The Radiomic Analysis Of Glioblastomas: A Review, Taxonomy, And Perspective, Ming Zhu, Sijia Li, Yu Kuang, Virginia B. Hill, Amy B. Heimberger, Lijie Zhai, Shenjie Zhai

Electrical & Computer Engineering Faculty Research

Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches widely applied in neuro-oncology. Unfortunately, accurate interpretation of radiological imaging data is constantly challenged by the indistinguishable radiological image features shared by different pathological changes associated with tumor progression and/or various therapeutic interventions. In recent years, machine learning (ML)-based artificial intelligence (AI) technology has been widely applied in medical image processing and bioinformatics due to its advantages in implicit image feature extraction and integrative data analysis. Despite its recent rapid development, ML technology still faces many hurdles for its broader applications …

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Weighted Incremental–Decremental Support Vector Machines For Concept Drift With Shifting Window, Honorius Gâlmeanu, Răzvan Andonie Aug 2022

Weighted Incremental–Decremental Support Vector Machines For Concept Drift With Shifting Window, Honorius Gâlmeanu, Răzvan Andonie

Computer Science Faculty Scholarship

We study the problem of learning the data samples’ distribution as it changes in time. This change, known as concept drift, complicates the task of training a model, as the predictions become less and less accurate. It is known that Support Vector Machines (SVMs) can learn weighted input instances and that they can also be trained online (incremental–decremental learning). Combining these two SVM properties, the open problem is to define an online SVM concept drift model with shifting weighted window. The classic SVM model should be retrained from scratch after each window shift. We introduce the Weighted Incremental–Decremental SVM (WIDSVM), …

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Cyberbullying Detection Using Weakly Supervised And Fully Supervised Learning, Abhinav Abhishek Aug 2022

Cyberbullying Detection Using Weakly Supervised And Fully Supervised Learning, Abhinav Abhishek

ETD Archive

Machine learning is a very useful tool to solve issues in multiple domains such as sentiment analysis, fake news detection, facial recognition, and cyberbullying. In this work, we have leveraged its ability to understand the nuances of natural language to detect cyberbullying. We have further utilized it to detect the subject of cyberbullying such as age, gender, ethnicity, and religion. Further, we have built another layer to detect the cases of misogyny in cyberbullying. In one of our experiments, we created a three-layered architecture to detect cyberbullying , then to detect if it is gender based and finally if it …

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Perturbation Modeling For Molecular Design Of Protein Tyrosine Kinase Inhibitors Using Unsupervised Machine Learning, Keerthi Krishnan Aug 2022

Perturbation Modeling For Molecular Design Of Protein Tyrosine Kinase Inhibitors Using Unsupervised Machine Learning, Keerthi Krishnan

Computational and Data Sciences (MS) Theses

The field of computational drug discovery and development has grown, with the aid of new computational tools for novel molecule discovery. In specific, generative deep learning models have excelled as tools to aid in navigating the large space of known molecules and in the creation of new molecules. These models are fed various representations of molecules as inputs and learn to perform a variety of things, such as the optimization of these molecules towards a targeted property. Ultimately, these generative learning models allow us to build bridges between chemical and continuous spaces to understand the compromise between invoking small incremental …

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Data Collection And Machine Learning Methods For Automated Pedestrian Facility Detection And Mensuration, Joseph Bailey Luttrell Iv Aug 2022

Data Collection And Machine Learning Methods For Automated Pedestrian Facility Detection And Mensuration, Joseph Bailey Luttrell Iv

Dissertations

Large-scale collection of pedestrian facility (crosswalks, sidewalks, etc.) presence data is vital to the success of efforts to improve pedestrian facility management, safety analysis, and road network planning. However, this kind of data is typically not available on a large scale due to the high labor and time costs that are the result of relying on manual data collection methods. Therefore, methods for automating this process using techniques such as machine learning are currently being explored by researchers. In our work, we mainly focus on machine learning methods for the detection of crosswalks and sidewalks from both aerial and street-view …

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How Order And Disorder Affect People's Behavior: An Explanation, Sofia Holguin, Vladik Kreinovich Aug 2022

How Order And Disorder Affect People's Behavior: An Explanation, Sofia Holguin, Vladik Kreinovich

Departmental Technical Reports (CS)

Experimental data shows that people placed in orderly rooms donate more to charity and make healthier food choices that people placed in disorderly rooms. On the other hand, people placed in disorderly rooms show more creativity. In this paper, we provide a possible explanation for these empirical phenomena.

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Why Decision Paralysis, Sean Aguilar, Vladik Kreinovich Aug 2022

Why Decision Paralysis, Sean Aguilar, Vladik Kreinovich

Departmental Technical Reports (CS)

If a person has a small number of good alternatives, this person can usually make a good decision, i.e., select one of the given alternatives. However, when we have a large number of good alternatives, people take much longer to make a decision -- sometimes so long that, as a result, no decision is made. How can we explain this seemingly no-optimal behavior? In this paper, we show that this "decision paralysis" can be naturally explained by using the usual decision making ideas.

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Why Five Stages Of Solar Activity, Why Five Stages Of Grief, Why Seven Plus Minus Two: A General Geometric Explanation, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich Aug 2022

Why Five Stages Of Solar Activity, Why Five Stages Of Grief, Why Seven Plus Minus Two: A General Geometric Explanation, Miroslav Svitek, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

A recent paper showed that the solar activity cycle has five clear stages, and that taking theses stages into account helps to make accurate predictions of future solar activity. Similar 5-stage models have been effective in many other application area, e.g., in psychology, where a 5-stage model provides an effective description of grief. In this paper, we provide a general geometric explanations of why 5-stage models are often effective. This result also explains other empirical facts, e.g., the seven plus minus two law in psychology and the fact that only five space-time dimensions have found direct physical meaning.

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Understanding The Assumptions Of An Seir Compartmental Model Using Agentization And A Complexity Hierarchy, Elizabeth Hunter, John D. Kelleher Aug 2022

Understanding The Assumptions Of An Seir Compartmental Model Using Agentization And A Complexity Hierarchy, Elizabeth Hunter, John D. Kelleher

Articles

Equation-based and agent-based models are popular methods in understanding disease dynamics. Although there are many types of equation-based models, the most common is the SIR compartmental model that assumes homogeneous mixing and populations. One way to understand the effects of these assumptions is by agentization. Equation-based models can be agentized by creating a simple agent-based model that replicates the results of the equationbased model, then by adding complexity to these agentized models it is possible to break the assumptions of homogeneous mixing and populations and test how breaking these assumptions results in different outputs. We report a set of experiments …

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Understanding Learners' Motivation Through Machine Learning Analysis On Reflection Writing, Elizabeth Pluskwik, Yuezhou Wang, Lauren Singelmann Aug 2022

Understanding Learners' Motivation Through Machine Learning Analysis On Reflection Writing, Elizabeth Pluskwik, Yuezhou Wang, Lauren Singelmann

Integrated Engineering Department Publications

Educational data mining (EDM) is an emerging interdisciplinary field that utilizes a machine learning (ML) algorithm to collect and analyze educational data, aiming to better predict students' performance and retention. In this WIP paper, we report our methodology and preliminary results from utilizing a ML program to assess students’ motivation through their upper-division years in the XYZ project-based learning (PBL) program. ML, or more specifically, the clustering algorithm, opens the door to processing large amounts of student-written artifacts, such as reflection journals, project reports, and written assignments, and then identifies keywords that signal their levels of motivation (i.e., extrinsic vs. …

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Data-Driven Research On Engineering Design Thinking And Behaviors In Computer-Aided Systems Design: Analysis, Modeling, And Prediction, Molla Hafizur Rahman Aug 2022

Data-Driven Research On Engineering Design Thinking And Behaviors In Computer-Aided Systems Design: Analysis, Modeling, And Prediction, Molla Hafizur Rahman

Graduate Theses and Dissertations

Research on design thinking and design decision-making is vital for discovering and utilizing beneficial design patterns, strategies, and heuristics of human designers in solving engineering design problems. It is also essential for the development of new algorithms embedded with human intelligence and can facilitate human-computer interactions. However, modeling design thinking is challenging because it takes place in the designer’s mind, which is intricate, implicit, and tacit. For an in-depth understanding of design thinking, fine-grained design behavioral data are important because they are the critical link in studying the relationship between design thinking, design decisions, design actions, and design performance. Therefore, …

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Saturation And Periodic Self-Stress In Geometric Auxetics, Ciprian S. Borcea, Ileana Streinu Aug 2022

Saturation And Periodic Self-Stress In Geometric Auxetics, Ciprian S. Borcea, Ileana Streinu

Computer Science: Faculty Publications

The auxetic structures considered in this paper are three-dimensional periodic bar-and-joint frameworks. We start with the specific purpose of obtaining an auxetic design with underlying periodic graph of low valency. Adapting a general methodology, we produce an initial framework with valency seven and one degree of freedom. Then, we describe a saturation process, whereby edge orbits are added up to valency 16, with no alteration of the deformation path. This is reflected in a large dimension for the space of periodic self-stresses. The saturated version has higher crystallographic symmetry and allows a precise description of the deformation trajectory. Reducing saturation …

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Why Micro-Size Objects Affect The Flow Much More Than Larger Ones: A Geometric Explanations With Applications Ranging From Volcanoes And Tornadoes To Blood, Fish, And Building Preservation, Laxman Bokati, Vladik Kreinovich Aug 2022

Why Micro-Size Objects Affect The Flow Much More Than Larger Ones: A Geometric Explanations With Applications Ranging From Volcanoes And Tornadoes To Blood, Fish, And Building Preservation, Laxman Bokati, Vladik Kreinovich

Departmental Technical Reports (CS)

At first glance, the larger the object, the larger should be its effect on the surroundings -- in particular, the larger should be its effect on the surrounding flow. However, in many practical situations, we observe the opposite effect: micro-size particles affect the flow much more than larger-size particles. This seemingly counterintuitive phenomena has been observed in many situations: lava flow in the volcanoes, air circulation in tornadoes, blood flow in a body, the effect of fish on water circulation in the ocean, and the effect of added particles on seeping water that damages historic buildings. In this paper, we …

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How To Make Inflation Optimal And Fair, Sean Aguilar, Vladik Kreinovich Aug 2022

How To Make Inflation Optimal And Fair, Sean Aguilar, Vladik Kreinovich

Departmental Technical Reports (CS)

A reasonably small inflation helps economy as a whole -- by encouraging spending, but it also hurts people by decreasing the value of their savings. It is therefore reasonably to come up with an optimal (and fair) level of inflation, that would stimulate economy without hurting people too much. In this paper, we describe how this can be potentially done.

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Semi Automatic Hand Pose Annotation Using A Single Depth Camera, Marnim Galib Aug 2022

Semi Automatic Hand Pose Annotation Using A Single Depth Camera, Marnim Galib

Computer Science and Engineering Dissertations - Archive

This thesis investigates the problem of 3D hand pose annotation using a single depth camera. While hand pose annotations are critically important for training deep neural networks, creating such reliable training data is challenging and manual labor intensive. Current datasets that rely on manual annotation on real images are limited in size due to the difficulty of annotating them. Although, large datasets have been generated using tracking based methods followed by manual refinement, these methods are prone to annotation errors due to tracking failure. Synthetic images have also been used to create large datasets but synthetic frames does not capture …

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Quantum Algorithms For Attacking Hardness Assumptions In Classical And Post‐Quantum Cryptography, J.-F. Biasse, X. Bonnetain, E. Kirshanova, A. Schrottenloher, Fang Song Aug 2022

Quantum Algorithms For Attacking Hardness Assumptions In Classical And Post‐Quantum Cryptography, J.-F. Biasse, X. Bonnetain, E. Kirshanova, A. Schrottenloher, Fang Song

Computer Science Faculty Publications and Presentations

In this survey, the authors review the main quantum algorithms for solving the computational problems that serve as hardness assumptions for cryptosystem. To this end, the authors consider both the currently most widely used classically secure cryptosystems, and the most promising candidates for post-quantum secure cryptosystems. The authors provide details on the cost of the quantum algorithms presented in this survey. The authors furthermore discuss ongoing research directions that can impact quantum cryptanalysis in the future.

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Effective Sequence Models And Graph Neural Networks For Molecular Data Analysis, Chaochao Yan Aug 2022

Effective Sequence Models And Graph Neural Networks For Molecular Data Analysis, Chaochao Yan

Computer Science and Engineering Dissertations - Archive

Drug discovery is the process of discovering new candidate medications. New drugs are continually developed by pharmaceutical industries to address increasing medical needs. Drug discovery involves a series of processes including target identification and validation, hit identification, lead generation and optimization, and finally the identification of a candidate for further development. The development further includes optimization of chemical synthesis and its formulation, toxicological studies in animals, clinical trials, and eventually regulatory approval. Both of these processes are time-consuming and cost-expensive. Computer-aided drug discovery mainly relies on modern computers to model drug molecules, which can speed up the process of drug …

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A Real-Time Activity Recognition In A Congested Wireless Environment, Israel Oludayo Elujide Aug 2022

A Real-Time Activity Recognition In A Congested Wireless Environment, Israel Oludayo Elujide

Computer Science and Engineering Dissertations - Archive

ABSTRACT: This dissertation reports on how to achieve real-time activity recognition in a congested wireless environment. Recently, human activity recognition with WiFi has been the focus of many researchers due to the limitations of legacy approaches like video cameras and sensors. Users have concerns with privacy when it comes to video activity recognition. Likewise, activity recognition sensors can be expensive, obtrusive, and inconvenient to be worn for an extended period of time. The urgency for implementing contactless activity recognition has also been accelerated due to changes in society and social interaction because of the COVID-19 pandemic. Many public facilities like …

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Hand Analysis From Depth Images, Mohammad Rezaei Aug 2022

Hand Analysis From Depth Images, Mohammad Rezaei

Computer Science and Engineering Dissertations - Archive

Hand analysis using vision systems is necessary for interaction between people and digital devices and thus is crucial in many applications relating to computer vision and human computer interaction (HCI). The proposed dissertation will explore hand analysis from depth images along two lines: hand part segmentation and 3D hand pose estimation. First, we investigate hand part segmentation from depth images, which is formulated as a semantic segmentation task. We explore a method aimed at determining for every pixel what hand part it belongs to. This method attempts to perform this task without requiring the ground-truth segmentation labels for training. It …

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Towards High Performance Cancer Staging From Histology Images, Ashwin Raju Aug 2022

Towards High Performance Cancer Staging From Histology Images, Ashwin Raju

Computer Science and Engineering Dissertations - Archive

Digital Pathology (DP) has been recently used in replacement to traditional microscopy samples as it easy to navigate and can be analysed, processed and saved. With the invention of Digital pathology, there has been exponential increase of automated process to make the life of Doctors easier. One such automated process is Artificial Intelligence (AI) where the AI is used as an assistant to Humans and to make the analysis and guide the experts. With the advent of AI and in particular Deep Learning, research has been divided and focused to solve multiple problems in Digital Pathology. One such important application …

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Gan-Based Domain Translation For Hand Pose Estimation And Face Reconstruction, Farnaz Farahanipad Aug 2022

Gan-Based Domain Translation For Hand Pose Estimation And Face Reconstruction, Farnaz Farahanipad

Computer Science and Engineering Dissertations - Archive

Deep learning solutions for hand pose estimation are now very reliant on comprehensive datasets covering diverse camera perspectives, lighting conditions, shapes, and pose variations. Since, acquiring such datasets is a challenging task that may be infeasible for many novel applications, several studies aim to develop semi/self supervised learning methods, that learn to estimate hand pose from a few labeled/unlabeled data. Therefore, in this dissertation, we investigate new advances in semi/self supervised learning which will remove the bottleneck of obtaining time-consuming frameby- frame manual annotations through generative adversarial networks (GANs). To handle above mentioned challenges, this thesis makes the following contributions. …

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Dynamic Path Planning For Unmanned Aerial Vehicles Under Deadline And Sector Capacity Constraints, Sudharsan Vaidhun, Zhishan Guo, Jiang Bian, Haoyi Xiong, Sajal K. Das Aug 2022

Dynamic Path Planning For Unmanned Aerial Vehicles Under Deadline And Sector Capacity Constraints, Sudharsan Vaidhun, Zhishan Guo, Jiang Bian, Haoyi Xiong, Sajal K. Das

Computer Science Faculty Research & Creative Works

The US National Airspace System is currently operating at a level close to its maximum potential. The limitation comes from the workload demand on the air traffic controllers. Currently, the air traffic flow management is based on the flight path requests by the airline operators, whereas the minimum separation assurance between flights is handled strategically by air traffic control personnel. In this paper, we propose a scalable framework that allows path planning for a large number of unmanned aerial vehicles (UAVs) taking into account the deadline and weather constraints. Our proposed solution has a polynomial-time computational complexity that is also …

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