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Numerical Solution Of Fractional Partial Differential Equations With Normalized Bernstein Wavelet Method, Mahsa Entezari, Saeid Abbasbandy, Esmail Babolian

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, normalized Bernstein wavelets are presented. Next, the fractional order integration and Bernstein wavelets operational matrices of integration are derived and finally are used for solving fractional partial differential equations. The operational matrices merged with the collocation method are used in order to convert fractional problems to a number of algebraic equations. In the suggested method the boundary conditions are automatically taken into consideration. An assessment of the error of function approximation based on the normalized Bernstein wavelet is also presented. Some numerical instances are given to manifest the versatility and applicability of the suggested method. Founded numerical …

Analysis Of Two Stage M[X1],M[X2]/G1,G2/1 Retrial G-Queue With Discretionary Priority Services, Working Breakdown, Bernoulli Vacation, Preferred And Impatient Units, G. Ayyappan, B. Somasundaram

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we study M^[X₁] , M^[X2] /G₁ ,G₂ /1 retrial queueing system with discretionary priority services. There are two stages of service for the ordinary units. During the first stage of service of the ordinary unit, arriving priority units can have an option to interrupt the service, but, in the second stage of service it cannot interrupt. When ordinary units enter the system, they may get the service even if the server is busy with the first stage of service of an ordinary unit or may enter into the orbit or leave …

Kernels And Beyond For Data Similarity Learning In Data Mining, Akshay Malhotra

Electrical Engineering Dissertations - Archive

This work discusses the problem of unsupervised clustering of signals/data vectors based on their information content. A correlation based perspective to the clustering problem has been considered, thus relying on the high correlation between data vectors from the same class rather than on the position of the vectors in the data space. In the past, correlation based clustering has been formulated using a canonical correlation framework or as a matrix factorization problem and has been solved with different variants of gradient descent. This work focuses on improving the clustering performance by modifying the framework to utilize non-linear associations or correlations. …

Parsing Code-Switched Taglish Language By Creating Constituents, Fadiah Qudah

Computer Science and Engineering Theses - Archive

When extracting meaning from language, a common first step is to break down language into constituents, or words that work together as a unit. This task, known as parsing, typically follows a specific grammar in order decompose the language into its underlying structure composed of constituents. Difficulties with this grammar-based parsing occur, however, with real-world natural language due to its unstructured nature. Code-switching, the phenomenon of alternating between languages while communicating, further complicates this task by requiring us to parse based on two (or more) languages instead of one. In this thesis, a data-driven method to parse code-switched language into …

Approxml: Efficient Approximate Ad-Hoc Ml Models Through Materialization And Reuse, Faezeh Ghaderi

Computer Science and Engineering Theses - Archive

Machine Learning (ML) has become an essential tool in answering complex predictive analytic queries. Model building for large scale datasets is one of the most time-consuming parts of the data science pipeline. Often data scientists are willing to sacrifice some accuracy in order to speed up this process during the exploratory phase. In this report, we aim to demonstrate ApproxML, a system that efficiently constructs approximate ML models for new queries from previously constructed ML models using the concepts of model materialization and reuse. ApproxML supports a wide variety of ML models such as generalized linear models for supervised learning …

Detect Traffic Signs From Large Street View Images With Deep Learning, Zhifei Deng

Computer Science and Engineering Theses - Archive

Autonomous driving is about to shaping the future of our life. Self-driving vehicles produced by Waymo or many other companies have demonstrated excellent driving capabilities on the road. However, accidents still happen. Correctly recognising the traffic signs, such as stop signs, is critical for a self-driving vehicle. Failing to recognise the traffic signs could lead to fatal accidents. Meanwhile, computer vision technology has made huge progress since the advent of deep learning, for example, image classification, object detection, and instance segmentation. Efforts have been made in developing faster and more accurate object detection methods. Faster R-CNN stands out as one …

Social Media Text Analysis Using Multi-Kernel Convolutional Neural Network, Anna Philips

Computer Science and Engineering Theses - Archive

Transportation planners and ride hailing platforms such as Uber and Lyft use their riders feedback to assess their services and monitor customer satisfaction. Social media websites such as Facebook, Instagram, LinkedIn and in particular Twitter provides a large dataset of micro-texts by users who regularly post to their social media accounts about their grievances with their ride experience. This data is often unorganized and intractable to process because of it’s extremely large size which is continuously increasing daily. In this project, we collected ride hailing service relevant text data from Twitter around New York and developed a novel Convolutional Neural …

Distributed Deep Neural Networks Training For Brain Imaging Applications, Sudheer Raja

Computer Science and Engineering Theses - Archive

Over the recent years, Deep Neural Networks (DNNs) have surpassed human-level intelligence in recognizing and interpreting complex patterns in data. Ever since the ImageNet competition in 2012, Deep Learning (DL) has become a promising approach for solving numerous problems in the field of Computer Science. However, the neuroscience community is not able to utilize the DL algorithms effectively because the brain imaging datasets are huge in terms of size, and the current sequential training techniques do not scale up well for such big datasets. Without the proper amount of training data, training DNN models to competitive accuracies is quite challenging. …

Comprehensive Study Of Generative Methods On Drug Discovery, Siyu Xiu

Computer Science and Engineering Theses - Archive

Observing the recent success of the deep learning (DL) technology in multiple life-changing application areas, e.g., autonomous driving, image/video search and discovery, natural language processing, etc., many new opportunities have presented themselves. One of the biggest ones lies in applying DL in accelerating the drug discovery, where millions of human lives could potentially be saved. However, applying DL into the drug discovery task turns out to be non-trivial. The most successful DL methods take fix-sized tensors/matrices, e.g., images, or sequences of tokens, e.g., sentences with variant numbers of words, as their inputs. However, none of these registers with the inputs …

Deduplication-Aware Page Cache In Linux Kernel For Improved Read Performance, Venkata Satya Ravi Kiran Boggavarapu

Computer Science and Engineering Theses - Archive

The amount of data being produced and consumed is increasing every day. As a result, there can be a large amount of redundant data in the storage system. Storing and accessing these duplicate data unnecessarily consumes disk space and I/O bandwidth. Deduplication techniques are widely deployed to remove the redundancy. In particular, the deduplication solutions that work at the block level are proven to be effective. These solutions aim to effectively use disk space and write bandwidth by avoiding duplicate data writes to the storage. However, such a design might not help in improving the read performance, which is critical …

Use Of Word Embedding To Generate Similar Words And Misspellings For Training Purpose In Chatbot Development, Sanjay Thapa

Computer Science and Engineering Theses - Archive

The advancement in the field of Natural Language Processing and Machine Learning has played a significant role in the huge improvement of conversational Artificial Intelligence (AI). The use of text-based conversation AI such as chatbots have increased significantly for the everyday purpose to communicate with real people for a variety of tasks. Chatbots are deployed in almost all popular messaging platforms and channels. The rise of chatbot development frameworks based on machine learning is helping to deploy chatbot easily and promptly. These chatbot development frameworks use machine learning and natural language understanding (NLU) to understand users' messages and intents and …

Hiding In Plain Sight? The Impact Of Face Recognition Services On Privacy, James Richard Ortega

Computer Science and Engineering Theses - Archive

The public at large is increasingly concerned with privacy online. While the focus is on the data privately collected by platforms, there are also privacy concerns in the realm of public data. Seemingly innocuous information shared in public, on online platforms, can be pieced together to detrimentally affect one's privacy in unexpected ways. On YouTube there exists a rich public dataset for adversaries to analyze for the purposes of breaching privacy; particularly due to the intersection of location and facial data. The goal of this work is to characterize the privacy risks that exists on YouTube, and explore the viability …

Using Property-Based Testing, Weighted Grammar-Based Generators, And A Consensus Oracle To Test Browser Rendering Engines And To Reproduce Minimized Versions Of Existing Test Cases, Joel David Martin

Computer Science and Engineering Theses - Archive

Verifying that a web browser rendering engine correctly renders all valid web pages is challenging due to the size of the input space (valid web pages), the difficulty of determining correct rendering for any given web page (the test oracle problem), and the degree to which normal variation in browser rendering behavior can obscure other differences (fonts, bor- ders, input controls, etc). These challenges lead to manual human involvement during the testing process. We propose a new Property-Based Testing (PBT) approach that addresses these challenges in order to enable automated web browser render testing. Our approach is composed of the …

The Impact Of Toxic Replies On Twitter Conversations, Nazanin Salehabadi

Computer Science and Engineering Theses - Archive

Social media has become an empowering agent for individual voices and freedom of expression. Yet, it can also serve as a breeding ground for hate speech. According to a Pew Research Center study, 41% of Americans have been personally subjected to harassing behavior online, 66% have witnessed these behaviors directed at others, and 18% have been subjected to particularly severe forms of harassment online, such as physical threats, harassment over a sustained period, sexual harassment, or stalking. Recently, many research studies have tried to understand online hate speech and its implications, focusing on detecting and characterizing hate speech. One limitation …

Performance Modeling And Resource Provisioning For Data-Intensive Applications, Zhongwei Li

Computer Science and Engineering Theses - Archive

Performance evaluation and resource provisioning are two most critical factors to be considered for designers of distributed systems at modern warehouse data centers. The ever-increasing volumes of data in recent years have pushed many businesses to move their computing tasks to the Cloud, which offers many benefits including the low system management and maintenance costs and better scalability. As a result, most recent prominently emerging workloads are data-intensive, calling for scaling out the workload to a large number of servers for parallel processing. Questions can be asked as what factors impact the system scaling performance, and how to efficiently schedule …

Pulsed Detonation Engine Nozzle Design And Analysis, Rahul Kumar

Mechanical and Aerospace Engineering Dissertations - Archive

For a hypersonic flight mission, different flight regimes have been recognized. The successful and efficient operation of the aircraft to traverse through all the flight regimes requires the integration of various propulsion cycles into a single flow path. Using the phenomenon of detonation initiation and propagation, a multi-mode detonation based propulsion concept was proposed for hypersonic flight. Of the different modes proposed, it was recognized that the efficient operation of Normal Detonation Wave Engine (NDWE) mode and Oblique Detonation Wave Engine (ODWE) mode played an important role as they delivered thrust at critical parts of the trajectory. For this study, …

Numerical Study Of Detonation Flame Arrestor Performance And Detonation Interaction With The Arrestor Element, Hoden Ali Farah

Mechanical and Aerospace Engineering Dissertations - Archive

A numerical study of detonation propagation and interaction with a flame arrestor product in a combustible gas/vapor transport pipeline system is conducted. The flame arrestor element is modeled as a porous medium using the Forchheimer equation, which is incorporated in the governing conservation equations as a momentum sink. The Forchheimer porous medium model is then used to model the flow through a representative four-inch detonation flame arrestor and is validated with experimental data. The detonation propagation simulation is modeled with the Reynolds averaged Navier-Stokes (RANS) equations extended for reacting flow. A 21-step chemical kinetic mechanism with 10 species is used …

Dynamics Of A Pulse Detonation Engine Driven Linear Power Generator, Umang Umeshkumar Dighe

Mechanical and Aerospace Engineering Dissertations - Archive

The dynamics of a pulse detonation engine driven linear power generator were studied. For an ideal pulse detonation engine, the thrust generated is in the form of a piecewise function given by the Endo-Fujiwara model. Nonlinear electromagnetic damping is also introduced in the system due to the rare earth permanent magnets present in the linear generator architecture. Various linear generator topologies were studied using static magnetic analysis. Two configurations of a single degree-of-freedom oscillator system, one with a linear spring restoring force and another with geometric nonlinear spring restoring force, were investigated to study any potential advantages of using nonlinear …

Development And Testing Of A Control Strategy For Dynamic Cooling At Rack Level In Data Centers, Amrutha Valli Rachakonda

Mechanical and Aerospace Engineering Theses - Archive

Cooling is a critical part of data center’s infrastructure, and with ongoing demands in data processing and storage, thermal management issues are of great concern. Some imperative methods of removing heat are either using air or liquid (preferably water or refrigerant). When high power density modules are involved, liquid cooling addresses some of the problems faced by air cooling as liquid coolants have higher thermal capacitance. Also, in the case of multi-chip modules, a non-uniform heating due to multi-core generates hot-spots and increases temperature gradients across the module. A dynamic cold plate along with a self-regulated flow control device was …

Assessing The Impact Of Principal Component Analysis On Accurately Predicting Melanoma Diagnosis Applied On Different Classification Models, Juan Cristobal Olmedo Rivera

Industrial, Manufacturing, and Systems Theses - Archive

With huge amounts of data at our disposal in the medical field, mathematical models are built to diagnose diseases. This study focuses on melanoma because it’s the type of skin cancer that accounts for most deaths, up to 7,230 in 2019 according to the American Cancer Society. The study focuses on the effectiveness on diagnosing melanoma and how Principal Component Analysis (PCA) impacts the performance of four models being assessed, which are: K Nearest Neighbor (KNN), Logistic Regression (LR), Support Vector Machines (SVM), and Artificial Neural Networks (ANN). Each model evaluates the melanoma dataset before and after performing the PCA …

Autonomous Carrier Landing Of A Fixed-Wing Uav With Airborne Deck Motion Estimation, Metin Kus

Mechanical and Aerospace Engineering Theses - Archive

This study focuses on the design, implementation, and evaluation of an autonomous carrier landing system featuring an airborne deck motion estimation module. The three-dimensional dynamics of a fixed-wing UAV with the actuator and engine dynamics are considered. A carrier motion model that accounts for the perturbations caused by various sea states is built. An airborne measurement system, which is composed of a calibrated camera and light-emitting beacons, is utilized to detect several coplanar target points on the moving carrier deck. The known correspondence between the locations of the target points and their coordinates on the focal plane of the camera …

Static Response Calibration Of 3d Printed Thin Walled Structures Using Fused Deposition Modelling, Akhilesh Ravindra Kulkarni

Mechanical and Aerospace Engineering Theses - Archive

3-D printing has enabled flexible, tool-less fabrication that yields numerous benefits. One benefit is unique and complex structural arrangements that increase design freedom to minimize weight. Such arrangements can be guided by advanced topology, shape, and sizing optimization tools using appropriate process constraints to ensure a printable design and can include highly integrated structural details such as stiffeners, flanges, frames, and other connections. 3D printing thin wall aircraft structures presents challenges for material and structural characterization. 3D printing enables integrated structural details, each detail is affected by the print process capability to fabricate the local geometry and deviations from designed …

Backstepping Approach For Design Of Cascaded Pid Controller With Guaranteed Trajectory Tracking Performance For Micro-Air Uav, Yusuf Kartal

Mechanical and Aerospace Engineering Theses - Archive

Flight controllers for micro-air UAVs are generally designed using Proportional- Integral-Derivative (PID) methods, where the tuning of gains is difficult and time-consuming, and performance is not guaranteed. In this thesis, we develop a rigorous method based on the sliding mode analysis and nonlinear backstepping to design a PID controller with guaranteed performance. This technique provides the structure and gains for the PID controller, such that a robust and fast response of the UAV for trajectory tracking is achieved. First, the second-order sliding variable errors are used in a rigorous nonlinear backstepping design to obtain guaranteed performance for the nonlinear UAV …

Teacher Perceptions Of Looping In Relation To Their Professional Growth And Development, Staci Sellers

Educational Leadership & Policy Studies Dissertations - Archive

The purpose of this phenomenological study was to understand better the lived experiences of seven elementary looping teachers. Specifically, their perceptions of whether or not the participation of looping facilitated their professional growth as it relates to the four primary areas of T-TESS. Previous studies in the realm of looping have a focus on student experiences and achievement. Although looping is research-based and shown to enhance student achievement, no known researcher had examined how looping teachers perceive the experience in terms of their professional being. This study was an opportunity to fill the gap in literature based on experiential learning …

Impacts Of Construction Material Delay In Iraq, Omar Raad Abdullah

Civil Engineering Theses - Archive

The construction industry is considered one of the most important industries in Iraq. It is well known that most construction projects in this country can experience missed deadlines and cost overruns or both. The main objectives of this study are to evaluate the impact of construction material shortages and to determine the most important problems causing these shortages in Iraq. Above objectives are achieved through a literature review and a survey, which include a questionnaire used to assess the perceptions of the main participants involved in the construction of different types of projects, such as infrastructure, residential, highways and medical …

Some Quadratic Regular Algebras On Four Generators Wtih A 1-Dimensional Nonreduced Line Scheme, Anthony Iv Mastriania

Mathematics Dissertations - Archive

In the 1980s, M. Artin, J. Tate, and M. Van den Bergh applied geometric techniques to noncommutative algebras. Their work introduced algebraic concepts called point modules and line modules and an associated geometric concept, which was later called the point scheme. In 2002, Shelton and Vancliff defined the concept of line scheme and developed a method for computing the line scheme of any quadratic algebra that satisfies certain conditions. Artin, Tate, and Van den Bergh were able to classify so-called quantum P²s by their point scheme; quantum P³s however are much more challenging and involve computing the line scheme. In …

Nano-Petrophysical Study Of The Dean, Wolfcamp, And Canyon Formations Of The Midland Basin, Texas, Usa., Benton M. Mowrey

Earth & Environmental Sciences Theses - Archive

The prolific levels of oil and gas production from the shale revolution have been plagued by steep initial production decline and inefficiencies in recovering the total hydrocarbons in place. Even the widespread practice of using multi-well sites with closely spaced wellbores has failed to yield a moderate fraction of the potential resources. It is hypothesized that the constraints of shale production arise from its nano-pore structure. Slow, diffuse hydrocarbon transport from the shale matrix to the stimulated fracture network is a likely production bottleneck. Understanding transport phenomena from this tight, porous matrix to the fracture via nanometer-scale pathways is essential …

Clarifying Vagueness: Rethinking The Supreme Court’S Vagueness Doctrine, Emily M. Snoddon

University of Chicago Law Review

For over a hundred years, the Supreme Court has struggled to articulate a coherent test for analyzing constitutional challenges based on vagueness. The current formulation of the vagueness test is rooted in due process principles and calls for invalidation of laws when they either (1) fail to “give a person of ordinary intelligence fair notice that his contemplated conduct is forbidden” by the law, or (2) encourage “arbitrary arrests and convictions.” Certain aspects of this test suggest that the separation of powers is relevant to the analysis. Nevertheless, it is currently unclear what role this constitutional protection plays.

Recent Supreme …

The Monadnock Volume 61, December 2019, Clark University Geographical Society

The Monadnock (Clark Geographical Society)

Volume 61 of The Monadnock. The Monadnock was the alumni magazine of the Clark University Geographical Society (1927-1985) (2014-present).

An Analysis Of Open Innovation Determinants: The Case Study Of Singapore Based Family Owned Enterprises, Annie Koh, Esther Kong, Giuseppe Timperio

Research Collection Lee Kong Chian School Of Business

Family businesses play an important role in the growth of global economy, and while they are arguably perceived as a conservative form of organization with high risk aversion and reluctance to change, counterintuitive empirical evidence show that they are most effective in ideation and commercialization of innovation projects. In the current business environment of rapid change in work patterns, fast adoption of enabling technologies for seamless collaborations across industry and geography, along with intense competition and high uncertainty, enterprises have no choice but to maximize returns on innovation investments. Therefore, they are increasingly dependent on an ecosystem-based approach to innovation …