Digital Commons Network^™

A Comparison Of Cooperative Learning And Collaboration In High School Geometry Classes Including Geometry In Construction, Shelley Gates

Dissertations

Currently offered at over 450 high schools in the United States, Geometry in Construction is an interdisciplinary course that provides students with the opportunity to learn Geometry content through the process of constructing a single-family home. Highly functioning cooperative groups are a critical element of the Geometry in Construction program. Cooperative learning is an effective instructional strategy that increases student achievement (Slavin, 2011) and also provides opportunities for students to develop collaboration and teamwork skills. Collaboration and teamwork are critical 21st century skills that are highly valued by employers and therefore worthy of consideration as foundational skills to be taught …

Advocating For The Adoption Of A Comprehensive Work-Based Learning System, Shelley Gates

Dissertations

Work-Based Learning (WBL) is an instructional strategy that has the potential to help students make powerful connections to the world of work leading to the development of viable post-secondary plans and successful careers. This study advocates for the implementation of a structured continuum of WBL experiences for all students at a large suburban high school. The benefits of WBL for students, the school, the community, and employers are examined. The impact of WBL is analyzed through the lenses of educational, economic, social, political, and ethical perspectives. The negative aspects of the prevailing culture of college for all is discussed. The …

Best Practices For Addressing The Achievement Gap For Hispanic Elementary Students, Megan C. Greene

Dissertations

Purpose: The purpose of this qualitative phenomenological study was to identify and describe effective instructional strategies for English language arts and mathematics perceived by expert fourth and fifth grade elementary teachers in southern California to reduce the achievement gap in high poverty and high English language learner (ELL) elementary schools.

Methodology: The researcher selected a qualitative research design to describe the instructional strategies used by teachers in three southern California school districts. Through in-depth, semi-structured, open-ended interviews, the researcher provided an examination of the instructional strategies used to address the needs of high poverty and high ELL elementary schools. Teachers …

Development Of Piezoelectric Sensors And Methodology For Noninvasive Simultaneous Detection Of Multiple Vital Signs, Areen Abdallah Romi Allataifeh

Dissertations

The activity of piezoelectric material linked the applied electric field with the strain generated that can be translated into geometrical variations. Flexible steel substrate exhibits fascinating mechanical properties which enable their integration into the emerging field of flexible microelectronics. This work presents an extended technique based on capacitance-voltage dependency to extract the geometrical variations in thin-film piezoelectric materials deposited on a flexible steel. A 50 μm flexible steel sheet has been sandwiched by two PZT film layers, each of 2.4 μm in thickness deposited by sputtering. An aluminum layer of 370 nm has been deposited above each PZT layer to …

The Connection Between Learning And Achievement Of Gifted And Talented (Gate) High School Students Using A Personalized Learning Framework From The Perspective Of High School Teachers, Roseellen Shea

Dissertations

Purpose: The purpose of this phenomenological qualitative study was to describe how expert teachers at the high school level perceive the impact of rigor, relevance, and personalized learning on the learning experience and achievement of gifted and talented (GATE) students.

Methodology: Data collected for this study included classroom observations, interviews, and documents. The target population consisted of public high school teachers of gifted learners in grades 9-12. Moreover, teacher participants were chosen using both purposeful and emergent sampling procedures.

Findings: For this phenomenological study, there were 15 teacher participants from both Los Angeles and Orange County. The …

Multi-Sensory Deep Learning Architectures For Slam Dunk Scene Classification, Paul Minogue

Dissertations

Basketball teams at all levels of the game invest a considerable amount of time and effort into collecting, segmenting, and analysing footage from their upcoming opponents previous games. This analysis helps teams identify and exploit the potential weaknesses of their opponents and is commonly cited as one of the key elements required to achieve success in the modern game. The growing importance of this type of analysis has prompted research into the application of computer vision and audio classification techniques to help teams classify scoring sequences and key events using game footage. However, this research tends to focus on classifying …

Predicting Customer Retention Of An App-Based Business Using Supervised Machine Learning, Jeswin Jose

Dissertations

Identification of retainable customers is very essential for the functioning and growth of any business. An effective identification of retainable customers can help the business to identify the reasons of retention and plan their marketing strategies accordingly. This research is aimed at developing a machine learning model that can precisely predict the retainable customers from the total customer data of an e-learning business. Building predictive models that can efficiently classify imbalanced data is a major challenge in data mining and machine learning. Most of the machine learning algorithms deliver a suboptimal performance when introduced to an imbalanced dataset. A variety …

An Evaluation Of Learning Employing Natural Language Processing And Cognitive Load Assessment, Mrunal Tipari

Dissertations

One of the key goals of Pedagogy is to assess learning. Various paradigms exist and one of this is Cognitivism. It essentially sees a human learner as an information processor and the mind as a black box with limited capacity that should be understood and studied. With respect to this, an approach is to employ the construct of cognitive load to assess a learner's experience and in turn design instructions better aligned to the human mind. However, cognitive load assessment is not an easy activity, especially in a traditional classroom setting. This research proposes a novel method for evaluating learning …

A Self Study Of My Leadership As Principal To Improve Student Achievement In Literacy In The Middle Grades, Latrese Tonya Mathis

Dissertations

This self-study examined my leadership practices as a principal and researcher. Herr and Anderson (2005) define self-study as "a focus on one's own personal and professional self." Through reflective analysis of my leadership practices, the Instructional Leadership and Grade Level Teams were supported with protocols and leadership methods to improve literacy instruction at middle grades. Upon reflection, concerns existed regarding inadequate and inconsistent student growth through the lens of school wide assessments. The examination of student data, root cause identification, and the development and monitoring of action items assisted to investigate my analysis of this concern. The significance of this …

An Examination Of The Theoretical Basis For Agile Engineering Using Function-Behavior-Structure Framework And Agent-Based Modeling, Mitchell James Bott

Dissertations

Traditional systems engineering methods have been shown to not scale well to very large and complex projects. There is a need for methods that can adapt to changing technology, deliver robust solutions, and provide consistent results. Agile methods, used in the software development domain, offer one possible solution to this need. Often, new methods are developed and deployed with little examination and testing. This is partly due to the impracticality of thorough testing of engineering methods on large and complex projects. This research uses agent-based modeling and simulation to examine the suitability and advantages of Agile methods for large and …

An Industrially Applicable Approach To Transient Thermal Modeling In Additive Manufacturing Using A Mass-Added Finite Difference Method, Tom James Stockman Iii

Dissertations

No abstract provided.

Stochastic Simulation Optimization By Filtering Static Surrogate Models, William T. Garrison

Dissertations

Optimization is the search for the input settings or configuration that will produce a desired result from the system of interest. When direct system experimentation is prohibitive, experts construct a system model that represents those aspects relevant to the problem and abstracts those that are not. This model serves as an objective function, a mapping from input settings or configuration to the value of a system. Most objective functions are deterministic; however, some objective functions represent variability through stochastic behavior. An optimization algorithm determines the optimal system inputs through repeated evaluation of the objective function with different input values. Response …

Modeling And Evaluating Cost-Effectiveness Of Host-Microbiome Investigations, Renuka Panchagavi

Dissertations

Cost-effectiveness modeling accounts for how expenditures impact outcomes and is an appropriate step towards efficacy of the different methods used for modeling the dynamics of microbial communities. This will help to identify challenging aspects of microbiome studies and the associated costs, including the major differences in research designs (cross-sectional or time series-based) used for conducting such studies. The two major stages of our investigation were to first collect and model cost variable data for microbiome investigations, and then to evaluate how trade-offs related to sample size and expenditures impact investigational outcomes. We screened different potential sources of data for microbiome …

Analysis Of Acoustic Emission Signals In Aluminum And Composite Structures, Duy Quang Tran

Dissertations

Acoustic emission signal in aluminum plates and composite specimens are examined in this dissertation. The first part of the dissertation examines the symmetric lamb wave modes generated by the spontaneous appearance of a central microcrack in an aluminum plate. The detected acoustic emission amplitude of these waves with radial and angular position of the sensing location was analyzed using finite element analysis. An important aspect of this study is the detailed characterization of the shear horizontal mode of the Lamb wave that is generated by simulated crack growth. This analysis indicates that the amplitude of the shear horizontal mode remains …

Mechanical Behavior Of Cement Paste At Nanoscale - Reactive Molecular Dynamics Modeling And Experimental Corroborations, Ingrid M. Padilla Espinosa

Dissertations

Concrete is the most used material for construction, and it is the most produced man-made product in the world. Concrete makes the contemporary architecture of the world conceivable and brings significant development to communities. Nevertheless, there are many downsides to the use of concrete such as the large amount of energy and water used in its production, large carbon footprint, shrinkage and expansion that can cause cracking and other failure mechanisms, and the required use of large amounts of material to ensure stability of concrete structures. These drawbacks create the need for engineering and tailoring the properties of concrete. An …

Managing Uncertainty In Sensor Data: An Evidence Theory Based Multisensor Data Fusion Approach, Gabriel Idowu Awogbami

Dissertations

Sensors play a critical role in the development of intelligent systems. Intelligent agents are equipped with an array of sensors to acquire information about themselves and the environment to make a reasonable decision. Information extracted from the sensor data is often characterized by uncertainty. Modeling and reasoning under such uncertainty poses a great challenge. Multisensor data fusion is a viable approach to address this problem. The Dempster Shafer (DS) theory of belief functions, also known as the evidence theory, is a well-known data fusion formalism due to its close relationship with other mathematical theories of uncertainty and its elegant way …

A Formal Systems Engineering Methodology For Cyber-Physical Systems: The Verifiable Design Process, Nadew S. Kibret

Dissertations

Cyber-physical systems (CPS) are systems that exhibit tight integration between their physical and computational components. They are hybrid systems containing continuous states and discrete states emanating from the physical and computational components, respectively. Systems engineering of these systems is challenging due to the tight integration of their computational, physical and communication technologies. As their level of acceptance increases in mission critical applications such as health care, smart grid, autonomous vehicles and smart cities, the need to ensure their safe operation is paramount importance as well. Therefore, design methodologies followed in their development are required to result in system behavior that …

The Effects Of A Transition Program On The Academic Achievement Of Ninth Grade Students In A California Suburban High School, Igor Nicholas Milosavljević

Dissertations

Problem

High school graduation rates have improved over the last decade. However, approximately one-fourth of U.S. high school students still do not graduate within four years. The rates are higher especially among minority and low socioeconomic status students, including students with special needs and English Language Learners. More ninth graders fail than any other grade in high school. A disproportionate number of students held back in ninth grade subsequently drop out. Students who do not complete high school face significant social, financial, and health challenges. Programs have been developed to address this need. One of those is the Accelerated Academic …

Sources And Atmospheric Oxidation Of Sulfur Dioxide And Formaldehyde Based On Wintertime Aircraft Observations Over The Eastern United States, Jaime R. Green

Dissertations

Plume intercepts from flights on the NSF-C-130 during the Wintertime Investigation of Transport, Emission and Reactivity (WINTER) campaign were used to estimate (1) the oxidation rates of Sulfur Dioxide (SO₂) under wintertime conditions and the factors that determine SO₂ removal; and (2) to examine the oxidation, lifetime and source apportionment of formaldehyde (HCHO). Observations suggest that OH governs the rate SO₂ oxidation in the eastern United States during winter. The range of mean oxidation rates during the day from power plants were 0.22–0.71%/hr, producing SO₂ lifetimes of 13–43 days, if SO₂ consumption is assumed …

Multi-Scale Interactions Between The Diurnal Cycle, The Mjo, And Convectively Coupled Equatorial Waves Over The Maritime Continent, Lakemariam Yohannes Worku

Dissertations

Given the Maritime Continent’s (MC’s) critical role in the global climate, examining variations in diurnal cycle and its interaction with the Madden–Julian Oscillation (MJO), Kelvin and Equatorial Rossby waves may lead to improved sub-seasonal forecasts. This study used satellite data of TRMM, TRMM Precipitation Features (PFs), and convective classifications from ISCCP. The convection becomes more organized through the afternoon and evening, leading to peak rainfall over the islands around 1800–2100 local standard time (LST). Over the next few hours, some of that rainfall transitions to stratiform rain over land. The convection then propagates offshore overnight with rainfall peaking along the …

Investigation Into The Perceptually Informed Data For Environmental Sound Recognition, Chenglin Kang

Dissertations

Environmental sound is rich source of information that can be used to infer contexts. With the rise in ubiquitous computing, the desire of environmental sound recognition is rapidly growing. Primarily, the research aims to recognize the environmental sound using the perceptually informed data. The initial study is concentrated on understanding the current state-of-the-art techniques in environmental sound recognition. Then those researches are evaluated by a critical review of the literature. This study extracts three sets of features: Mel Frequency Cepstral Coefficients, Mel-spectrogram and sound texture statistics. Two kinds machine learning algorithms are cooperated with appropriate sound features. The models are …

Hierarchical Cluster Analysis: A New Type Of Ranking Criteria Based On Arwu Ranking Data, Zhengshuo Li

Dissertations

The advent of big data leads to many applications of Machine Learning techniques. University rankings is one of the applicable domains, which is currently playing a crucial role in the assessment of the universities' performance. Currently, the rankings are usually carried out by some authoritative ranking institutions by means of weighting techniques and the results are conveyed in numerical rankings. Three of the most famous university ranking institutions have been introduced from a technical perspective. However, these institutions have been proven to be subjective in relation to their data selection and weighting method.

Using Supervised Learning To Predict English Premier League Match Results From Starting Line-Up Player Data, Runzuo Yang

Dissertations

Soccer is one of the most popular sports around the world. Many people, whether they are a fan of a soccer team, a player of online soccer games or even the professional coach of a soccer team, will attempt to use some relevant data to predict the result of a match. Many of these kinds of prediction models are built based on data from the match itself, such as the overall number of shots, yellow or red cards, fouls committed, etc. of the home and away teams. However, this research attempted to predict soccer game results (win, draw or loss) …

Comparing Defeasible Argumentation And Non-Monotonic Fuzzy Reasoning Methods For A Computational Trust Problem With Wikipedia, Ryan Kirwan

Dissertations

Computational trust is an ever-more present issue with the surge in autonomous agent development. Represented as a defeasible phenomenon, problems associated with computational trust may be solved by the appropriate reasoning methods. This paper compares two types of such methods, Defeasible Argumentation and Non-Monotonic Fuzzy Logic to assess which is more effective at solving a computational trust problem centred around Wikipedia editors. Through the application of these methods with real-data and a set of knowledge-bases, it was found that the Fuzzy Logic approach was statistically significantly better than the Argumentation approach in its inferential capacity.

Predicting Violent Crime Reports From Geospatial And Temporal Attributes Of Us 911 Emergency Call Data, Vincent Corcoran

Dissertations

The aim of this study is to create a model to predict which 911 calls will result in crime reports of a violent nature. Such a prediction model could be used by the police to prioritise calls which are most likely to lead to violent crime reports. The model will use geospatial and temporal attributes of the call to predict whether a crime report will be generated. To create this model, a dataset of characteristics relating to the neighbourhood where the 911 call originated will be created and combined with characteristics related to the time of the 911 call. Geospatial …

Enhancing Partially Labelled Data: Self Learning And Word Vectors In Natural Language Processing, Eamon Mcentee

Dissertations

There has been an explosion in unstructured text data in recent years with services like Twitter, Facebook and WhatsApp helping drive this growth. Many of these companies are facing pressure to monitor the content on their platforms and as such Natural Language Processing (NLP) techniques are more important than ever. There are many applications of NLP ranging from spam filtering, sentiment analysis of social media, automatic text summarisation and document classification.

Performance Comparison Of Hybrid Cnn-Svm And Cnn-Xgboost Models In Concrete Crack Detection, Sahana Thiyagarajan

Dissertations

Detection of cracks mainly has been a sort of essential step in visual inspection involved in construction engineering as it is the commonly used building material and cracks in them is an early sign of de-basement. It is hard to find cracks by a visual check for the massive structures. So, the development of crack detecting systems generally has been a critical issue. The utilization of contextual image processing in crack detection is constrained, as image data usually taken under real-world situations vary widely and also includes the complex modelling of cracks and the extraction of handcrafted features. Therefore the …

An Initial Investigation Of The Role Of The Northeastern Alabama Plateaus In Modifying The Near-Storm Environment Of Potentially Tornadic Storms, Anthony Walter Lyza

Dissertations

The effects of terrain on tornadoes are poorly understood. Efforts to understand terrain effects on tornadoes have been limited in scope, typically examining a small number of cases with limited observations or idealized numerical simulations. One region where topography has been thought to potentially impact tornado frequency is along the Sand Mountain and Lookout Mountain plateaus in northeastern Alabama. It has been suspected that storms often intensify and produce tornadoes upon reaching these plateaus, particularly Sand Mountain. The role of these plateaus in modifying the near-storm environment and storm evolution became a focus of the VORTEX-SE field campaign beginning in …

Generating Cyberattack Model Components From An Attack Pattern Database, Tymaine S. Whitaker

Dissertations

The number, variety, sophistication, and consequences of cyberattacks are all growing. The developers and users of computer systems should have some knowledge of the different types of cyberattacks that can occur. Models of cyberattack patterns can contribute to that knowledge. Executable models of cyberattacks used to simulate the attacks can reveal system vulnerabilities and improve decisions made by both attackers and defenders during attacks. One type of cyberattack model, Attack Trees, supports visualization and formal analysis of cyberattacks. A second type of model, Petri nets with Players, Strategies, and Costs (PNPSC), was developed specifically for cyberattack modeling as part of …

Reinforcement Learning Applied To Manufacturing Material Handling, Swetha Govindaiah

Dissertations

Applying machine learning methods to improve the efficiency of complex manufacturing processes, such as material handling, can be challenging. The interconnectedness of the multiple components that make up such processes and the typically large number of variables required to specify procedures and plans within them combine to make it very difficult to map the details of a real-world manufacturing process to an abstract mathematical representation suitable for machine learning methods. This work comprises both applied and theoretical results. On the applied side, machine learning, in particular reinforcement learning, was used to generate increasingly efficient plans for material handling to satisfy …