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- Creator:
- Al-barazanchi, Hussein Ali Kadhim
- Description:
- Plankton are a diverse group of organisms that live in large bodies of water. They are a primary source of food for fishes and other larger aquatic organisms. The distribution of plankton plays a significant role in the marine ecosystem. Therefore, the study of plankton distribution is an important tool used for assessing the changes in the marine ecosystem. The study of plankton distribution is based mostly on the classification of plankton images taken by underwater imaging systems. The images used in this study come from the SIPPER system. The challenges with SIPPER’s plankton image dataset are the low resolution of images, the high degree of similarities between different classes, high variability within the same class, partial occlusion, and noise. Also, traditional computer vision techniques require tedious work to find suitable features to represent plankton. Having a robust automated system for classification of plankton images will play a significant role in advancing marine biology research. To overcome those issues, we propose the use of Convolutional Neural Networks (CNN) and Hybrid-CNN for this task. Results of the experiments on SIPPER dataset show improvement in classification accuracy in comparison with other states of the art approaches. Another major advantage of this approach is the scalability for classification of new classes without the need for features engineering.
- Resource Type:
- Masters Thesis
- Campus Tesim:
- Fullerton
- Department:
- Department of Computer Science
- Creator:
- Dasamoni, Thanga Nirmaia
- Description:
- Many model-based approaches have been suggested to improve and accelerate the development process of complex distributed embedded systems (DES) from design to deployment. In this approach, abstract models of the system are created and then transformed systematically into concrete implementations. Modeling focuses on commands and information being distributed reliably throughout the system with minimized latency to maintain acceptable QoS. In this research, an irrigation system is developed. Model-based development was used to model the architecture and communication of distributed nodes. However, the complexity of the Bluetooth Low Energy (BLE) communications used by the irrigation system requires a model with very high sophistication in the bottom-up modeling approach. A distributed irrigation system is implemented as a proof of concept using an experimental Bluetooth Low Energy based network topology and protocol, and the data was observed to verify the correct operations.
- Resource Type:
- Masters Thesis
- Campus Tesim:
- Fullerton
- Department:
- Department of Computer Science
- Creator:
- Rahimi, Ahdel
- Description:
- Identifying the type of modulation scheme present on a signal is an integral part of any non-coherent receiver, especially in defense. Prior to signal processing, modulation schemes present on a received signal must be accurately identified. Finding a fast and accurate method for classifying the signal type can be very difficult. The use of machine learning algorithms has been explored as a solution for signal classification; however, many machine learning algorithms and their proposed applications are inadequate for real-time processing due to the complexity and overhead associated with the algorithms chosen. Here a supervised machine learning approach using a k-Nearest Neighbor (kNN) algorithm is efficiently applied to achieve very accurate modulation classification using only three features extracted from the signal. The use of a simpler machine learning algorithm such as kNN and a reduced feature set for classification allows for various optimization techniques to be applied in hardware for classification of a received signal. With the presented classification method, a hardware implementation can achieve the exact or better results than the simulated system by loading all of the classification data into content-addressable memory (CAM) based look-up table, and directly mapping a possible outcome to a particular group for classification. Ternary content-addressable memories (TCAMs) may also be used to help optimize this approach further through simplified search queries.
- Resource Type:
- Masters Thesis
- Campus Tesim:
- Fullerton
- Department:
- Department of Computer Science
- Creator:
- Tan, Ying Candy
- Description:
- This study will explore the shifting of Chinese K-12 principals’ understanding of instructional leadership after participating in a professional development (PD) program at an American university. China’s recent educational reform requires school principals to further develop their instructional leadership skills in order to better implement new policies. A qualitative research method has been used in this study. Pre-program interviews and post-program interviews provided the comparison between participants’ baseline understanding and new understanding of instructional leadership. This research is important and will make a significant contribution to educational leadership because there is minimal research that examines PD programs for international participants. This study fills a gap in the literature by exploring Chinese principals’ understanding of instructional leadership before and after attending the PD program hosted by an American university. Thus, it will provide suggestions for both Chinese K-12 principals and American universities in terms of the improvement of future PD programs.
- Resource Type:
- Dissertation
- Campus Tesim:
- Fullerton
- Department:
- Department of Educational Leadership
215. Developing Walking Groups for University Employees Using Group Cohesion and Team–building Concepts
- Creator:
- Nichelini-Bagshaw, Kristin D.
- Description:
- Over half of adults in the United States do not regularly meet the minimum number of minutes per week of moderate–to–vigorous physical activity (US Department of Health and Human Services, 2010). One promising intervention strategy for improving adherence to physical activity is using groups to promote physical activity (Gilson et al., 2013) as well as incorporating cognitive–behavioral skills (Kabaroff, Eys, Schinke, & Eger, 2013). The purpose of this study was to determine if there was an increase in physical activity and a decrease in sedentary behaviors in response to a group–based physical activity intervention program. Forty participants included full–time and part– time faculty and staff employees that were provided with a Fitbit Flex and instructed to walk as much as possible while wearing the provided Fitbit in order to track physical activity behaviors. Fitbit Flex data and a questionnaire including the International Physical Activity Questionnaire, sedentary behavior questions, cohesion, groupness and self–efficacy were assessed at week one, week five and week ten. Blood pressure and a 6- minute-walk-test were assessed at baseline and completion. Mixed factorial ANOVAs were performed to compare changes over time between groups. Results demonstrated an increase in self–reported physical activity, while cohesion and groupness decreased in the intervention group, but not in the control group. This study provides partial support for the effectiveness of a team–building approach that incorporates cognitive behavioral skills by increasing self–report physical activity when compared to a control group.
- Resource Type:
- Masters Thesis
- Campus Tesim:
- Fullerton
- Department:
- Department of Kinesiology
- Creator:
- Honea, Kryston
- Description:
- This study was a secondary analysis that examined potential parental and familial predictors of compliance and completion of a family home-based physical activity intervention. Participants (n = 105) were parents of youth with Prader-Willi Syndrome (PWS) (n = 41) and parents of youth with obesity but without PWS (n = 64). Participants completed a questionnaire that documented their demographic information and measured several psychological and environmental variables such as self-efficacy, social support, and family environment. The relationship between these factors with intervention completion and compliance was evaluated using logistic regression and multiple regression analyses. Results from the logistics regression analyses revealed that marital status, employment, employed hours per week, family environment, self-efficacy, and social support were not significant predictors of intervention completion. In parents of youth with PWS, self-efficacy, and social support were positively related with intervention compliance, while employment was negatively related (Model R² = .271, F(3,27) = 3.35, p < .05). In parents of obese youth, employment was negatively related with intervention compliance (Model R² = .125, F(1, 49) = 7.01, p < .05). The results suggest that compliance with a 24-week family home-based physical activity intervention is related to less hours of employment and more self-efficacy in parents, as well as family climate factors such as social support and familial cohesion. These are factors that should be considered for potential interventions requiring implementation in a home setting.
- Resource Type:
- Masters Thesis
- Campus Tesim:
- Fullerton
- Department:
- Department of Kinesiology
- Creator:
- Payton, Melissa
- Description:
- The purpose of the proposed study was to establish the inter-rater reliability of a modified version of the Fullerton Advanced Balance (mFAB) scale. Specifically, five of the 10 test items from the original Fullerton Advanced Balance (FAB) scale were modified (Rose, Lucchese, & Wiersma, 2006). Revisions to certain test items were warranted for the following reasons: (a) to reduce ceiling effects (Test Item 1); (b) increase the safety of the person being tested (substitute Test Item 8 with lower risk test item, modify test instructions for Test Item 10); (c) better evaluate the balance dimension of interest (Test Items 2 and 7); and (d) include a test of agility (substituted Test Item 8). Development of the mFAB scale involved a multi-stage process which included (a) creating test administration instructions and scoring criteria for the new test items to be revised or substituted; (b) pilot testing the five test items with 10 higher functioning older adults (60-90 years); (c) making further revisions to the mFAB scale prior to reliability phase of the study; (d) recruiting a sample of older adults and 3 trained test administrators; (e) administering the mFAB scale to participants who met the eligibility requirements; and (f) establishing inter-rater reliability using Spearman-Rank correlation analyses. The results of the analysis indicate consistency among the raters evaluating the same person (i.e., Rater 1 versus 2, Rater 2 versus 3, and Rater 1 versus 3). The modifications made to the FAB scale to create the mFAB scale will enhance the scale’s efficacy as a multidimensional measure of balance in higher functioning older adults.
- Resource Type:
- Masters Thesis
- Campus Tesim:
- Fullerton
- Department:
- Department of Kinesiology
- Creator:
- Carter, Dione M.
- Description:
- This study looks at different drug arrest patterns. While extensive research has been done on crime and drug mapping, very little has been done on drug arrests as a whole and even less has been done on specific drug types. This study addresses the following questions: are all drugs arrests located in the same part of the city? Has there been a spatial and or temporal trend in each type of drug arrest? In addition, this study will explore several different spatial statistical methods to determine if any one method is more appropriate for each type of drug, and if there are any temporal trends that might be apparent for each drug. San Francisco was picked as a case study city because of its cultural association with drugs, its dramatic economic change over the past 15 years and its accessibility of crime data. The results indicate that most drug arrests happen at the same times and in the same place in the city with little variation. Marijuana is the only drug that has a significantly different spatial pattern. Each test used produced the same results and it is appropriate to use each in further analysis. Further research is needed to determine what some of the causes might be and what methods could possibly best measure the factors that influence drug activity in the city of San Francisco.
- Resource Type:
- Dissertation
- Campus Tesim:
- Fullerton
- Department:
- Department of Educational Leadership
- Creator:
- Sakban, Haider Kadhem
- Description:
- Reinforced concrete (RC) walls are the most commonly used structural elements in buildings for resisting lateral forces induced by earthquakes. Therefore, reliable and robust analytical models that can predict their behavior under earthquake actions are essential for the design of new buildings and evaluation of existing buildings. Performance-Base Seismic Design (PBSD) and evaluation currently of RC structural walls typically relies on analytical models that do not capture the interaction between shear and flexural responses. Previous experimental and analytical studies showed that this interaction could be important for walls with shear span ratio ranges between 1.5 and 3.0 and that models which do not capture this interaction can overestimate wall strength and stiffness by 30 to 50%. A novel modeling approach that captures shear-flexure interaction (SFI) has been recently developed and implemented in computational platform OpenSees. The model has been previously validated against five RC wall specimens with aspect ratios of 1.5 and 2.0 that experienced significant SFI, and it showed to be capable of reproducing successfully experimentally measured global and local wall responses. However, the model has not been validated extensively over a wide range of wall characteristics, aspect ratio, axial load, reinforcement configuration and shape of the cross-section.The objective of this study is to calibrate and validate the SFI modeling approach recently implemented in computational platform OpenSees against a great number of specimens to assess its capability of successfully reproducing experimentally measured wall responses over a range of wall characteristics. The model was validated against 12 RC wall specimens tested under cyclic loading conditions. Comparison of experimental and analytical wall behavior focused on the overall load versus total top wall displacement and load versus shear displacement (global response) over the plastic hinge region (local response). Based on the results presented, it can be concluded that the model is capable of reproducing successfully experimentally measured wall behavior over a range of considered wall characteristics, including lateral load, stiffness, stiffness degradation and shear displacement within plastic hinge. It has also been observed that the model tends to overestimate the area of the hysteretic loops (i.e., underestimate pinching) for specimens with zero axial load, due to currently implemented models that represent shear transfer mechanisms along concrete cracks. Based on the results presented, future model improvements are suggested. The objective of this study is to calibrate and validate the SFI modeling approach recently implemented in computational platform OpenSees against a great number of specimens to assess its capability of successfully reproducing experimentally measured wall responses over a range of wall characteristics. The model was validated against 12 RC wall specimens tested under cyclic loading conditions. Comparison of experimental and analytical wall behavior focused on the overall load versus total top wall displacement and load versus shear displacement (global response) over the plastic hinge region (local response). Based on results presented, it can be concluded that the model is capable of reproducing successfully experimentally measured wall behavior over a range of considered wall characteristics, including lateral load, stiffness, stiffness degradation and shear displacement within plastic hinge. It has also been observed that the model tends to overestimate area of the hysteretic loops (i.e., underestimate pinching) for specimens with zero axial load, due to currently implemented models that represent shear transfer mechanisms along concrete cracks. Based on results presented, future model improvements are suggested.
- Resource Type:
- Masters Thesis
- Campus Tesim:
- Fullerton
- Department:
- Department of Civil and Environmental Engineering
- Creator:
- Sajit, Ahmed Sattar
- Description:
- The 21st century is witnessing a tremendous demand for transistors. Life amenities have incorporated the transistor in every aspect of daily life, ranging from toys to rocket science. Day by day, scaling down the transistor is becoming an imperious necessity. However, it is not a straightforward process; instead, it faces overwhelming challenges. Due to these scaling changes, new technologies, such as FinFETs for example, have emerged as alternatives to the conventional bulk-CMOS technology. FinFET has more control over the channel, therefore, leakage current is reduced. FinFET could bridge the gap between silicon devices and non-silicon devices. The semiconductor industry is now incorporating FinFETs in systems and subsystems. For example, Intel has been using them in their newest processors, delivering potential saving powers and increased speeds to memory circuits. Memory sub-systems are considered a vital component in the digital era. In memory, few rows are read or written at a time, while the most rows are static; hence, reducing leakage current increases the performance. However, as a transistor shrinks, it becomes more vulnerable to the effects from radioactive particle strikes. If a particle hits a node in a memory cell, the content might flip; consequently, leading to corrupting stored data. Critical fields, such as medical and aerospace, where there are no second chances and cannot even afford to operate at 99.99% accuracy, has induced me to find a rigid circuit in a radiated working environment. This research focuses on a wide spectrum of memories such as 6T SRAM, iii 8T SRAM, and DICE memory cells using FinFET technology and finding the best platform in terms of Read and Write delay, susceptibility level of SNM, RSNM, leakage current, energy consumption, and Single Event Upsets (SEUs). This research has shown that the SEU tolerance that 6T and 8T FinFET SRAMs provide may not be acceptable in medical and aerospace applications where there is a very high likelihood of SEUs. Consequently, FinFET DICE memory can be a good candidate due to its high ability to tolerate SEUs of different amplitudes and long periods for both read and hold operations.
- Resource Type:
- Masters Thesis
- Campus Tesim:
- Fullerton
- Department:
- Department of Computer Science