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Sappling: An Interactive Platform for Creative Expression and Collaboration
Get PDFSappling is a new application that aims to tackle some of the shortcomings of traditional social media, which currently dominates the way we interact with friends and other users online. In its initial phase, we plan to target a certain demographic of people that we feel would benefit most from the platform, such as engineers or musicians. As a part of my project, I plan to help identify which group we want to target in this development stage, using survey data and other metrics to measure different groups and their likelihood to benefit from this new platform. As some research suggests social media platforms are not simply ‘tools’ for engagement, but they are also part of a rapidly changing institutional and political landscape where they can influence both supportive and critical attitudes towards education (Van Dijck & Poell, 2018). Sappling aims to capitalize on this area of the social media space, where users are more likely to engage with each other and promote collaboration and positive social engagement that will drive higher levels of creativity and unfiltered expression. Along with determining the ideal user base for the initial launch of this project, the current application design will also require user testing and basic modifications to ensure that the design at launch is fit to accompany a variety of marketing efforts to promote the app to new users and make it attractive and intuitive. The user interface and experience design will be my main focus for the project, as it aligns with the concentration I have chosen and the career I plan to pursue after graduation. Based on the current design, there are some key areas for improvement that I noticed in my initial evaluation. Some of these include: allowing the user to put the current task into a meaningful context, disclosing information in a progressive fashion, and defining shortcuts that are intuitive (Sridevi, 2014). I plan to create medium and high-fidelity prototypes of the application based on the current design, and perform user testing to measure the success of these 4 proposed changes and collect data on how the usability of the design can be improved. These prototypes and user tests will be completed by the end of this academic quarter, around the second week of March in preparation for the compilation of results and presentation before the quarter concludes. The current design and functionality will be compared to the new prototype to evaluate the effectiveness and usability of the new design, using data from a variety of different potential users. The project will also include a limited branding overhaul to create a more effective logo and marketing collateral to accompany the launch of the app to new users
LONG STORY SHORT
Get PDFLong Story Short and is a vintage up-cycling art brand. Our mission is to breathe new life into vintage pieces, crafting them into modern wearable art. As the name suggests, each creation tells a story while being revitalized for today’s fashion forward community.
Fast fashion and trend cycling has been a growing problem in today’s society. Things are going ‘in’ and ‘out’ quicker than they ever have. Trend cycling usually operates on a 20-year timeline. But, today’s sped up cycle encourages people to constantly over-consume in chase of the next cool thing. It’s unsustainable and an impossible chase. With a growing digital community and rise of social media, online shopping and influencer culture is bigger than ever. This mentality is ultimately starting to wipe out individuality in innovative fashion design.
Long Story Short aims to be a safe landing place for others finding their way back to inspiration and sustainability in fashion
Water Quality Assessment for San Luis Obispo Creek and Stenner Creek
Get PDFWater quality was assessed in five stream segments in San Luis Obispo and Stenner Creeks in Spring of 2023. Two of the five sites were located along San Luis Obispo Creek, and three located along Stenner Creek. Criteria to evaluate these aquatic systems was provided by the Standard Operating Procedures of the Surface Water Ambient Monitoring Program, formulated by the State Water Resources Control Board. These procedures describe the methodology surrounding the collection of chemical, physical, and biological parameters of stream systems; streamflow, substrate, flow habitat, chemical water quality, and benthic macroinvertebrates are some of the criteria collected that allows for the quantification of the California Stream Condition Index (CSCI). The Stream Measurements and Water Quality Monitoring Course at California Polytechnic State University, San Luis Obispo, provided student labor for the collection and organization of data. Based on CSCI scores, water quality of the five-stream segments ranged from “Likely Altered” to “Very Likely Altered.
A SINDy Hardware Accelerator For Efficient System Identification On Edge Devices
Get PDFThe SINDy (Sparse Identification of Non-linear Dynamics) algorithm is a method of turning a set of data representing non-linear dynamics into a much smaller set of equations comprised of non-linear functions summed together. This provides a human readable system model the represents the dynamic system analyzed. The SINDy algorithm is important for a variety of applications, including high precision industrial and robotic applications. A Hardware Accelerator was designed to decrease the time spent doing calculations. This thesis proposes an efficient hardware accelerator approach for a broad range of applications that use SINDy and similar system identification algorithms. The accelerator is leverages both systolic arrays for integrated neural network models with other numerical solvers. The novel and efficient reuse of similar processing elements allows this approach to only use a minimal footprint, so that it could be added to microcontroller devices or implemented on lower cost FPGA devices. Our proposed approach also allows the designer to offload calculations onto edge devices from controller nodes and requires less communication from those edge devices to the controller due to the reduced equation space
Power Flow Modeling And Analysis Of A Green Seaport Power System
Get PDFIndonesia has committed to achieving Net-Zero emissions by 2060, signaling a significant shift towards sustainability, which includes impactful initiatives such as the implementation of Green Seaports. This thesis focuses on designing and developing a model for a proposed Green Seaport power system and the subsequent performance of power flow analysis under various operating conditions. The model, constructed using MATLAB Simulink, underwent extensive testing and analysis, with a specific emphasis on the Battery Energy Storage System (BESS) operating modes, including individual charging, discharging, and simultaneous charging and discharging. This comprehensive investigation and analysis, involving 62 separate simulations, evaluated the impact of variations in solar irradiance, BESS state of charge (SoC), load levels, and power factor on the system across each BESS operating mode. The results conclusively demonstrated that the designed system is healthy, enabling reliable electricity delivery with minimal losses, maintaining stable voltage levels within acceptable limits, and operating efficiently with minimal instances of component overloading
Development Of A Deep Learning Algorithm Using Electromyography (EMG) And Acceleration To Monitor Upper Extremity Behavior With Application To Individuals Post-Stroke
Get PDFStroke is a chronic illness which often impairs survivors for extended periods of time,
leaving the individual limited in motor function. The ability to perform daily activities
(ADL) is closely linked to motor recovery following a stroke. The objective of
this work is to employ surface electromyography (sEMG) gathered through a novel,
wearable armband sensor to monitor and quantify ADL performance. The first contribution
of this work seeks to develop a relationship between sEMG and and grip
aperture, a metric tied to the success of post-stroke individuals’ functional independence.
The second contribution of this work aims to develop a deep learning model
to classify RTG movements in the home setting using continuous EMG and acceleration
data. In contribution one, ten non-disabled participants (10M, 22.5 0.5 years)
were recruited. We performed a correlation analysis between aperture and peak EMG
value, as well as a one-way non parametric analysis to determine cylinder diameter
effect on aperture. In contribution two, one non-disabled participant is instructed to
wash a set of dishes. The EMG and acceleration data collected is input into a recurrent
neural network (RNN) machine learning model to classify movement patterns.
The first contribution’s analysis demonstrated a strong positive correlation between
aperture and peak EMG value, as well as a statistically significant effect of diameter
(p \u3c 0.001). The RNN model built in contribution two demonstrated high capability
at classifying movement at 94% accuracy and an F1-score of 86%. These results
demonstrate promising feasibility for long-term, in-home classification of daily tasks.
Future applications of this approach should consider extending the procedure to
include post-stroke individuals, as this could offer valuable insight into motor recovery
within the home setting
A 4-Switch Buck-Boost DC/DC Converter for Electric Vehicle Applications
Get PDFIn this project, we develop a four switch buck-boost DC/DC converter that is to be integrated into a microgrid-inspired power distribution architecture for electric vehicles. The overall architecture includes DC/DC and DC/AC converters for bi-directional energy transfer between the DC and AC ports along with a communications port to control each energy interface. There is also the onboard battery and the internal combustion engine power exchange being done with DC/DC converters and AC/DC inverters to connect to the centralized DC bus. Hardware prototypes using an Arduino and Raspberry Pi for the 500 W DC/DC and DC/AC converters have been previously developed. Our project extends this work by developing a DC/DC four switch buck-boost converter that will be utilized to interface an internal combustion engine with the high-voltage DC bus. With the rise of EVs and the advancements in energy storage, this project holds importance for enabling more efficient and multi-functional electric vehicles
Analyzing Hubble Space Telescope Images of AGN Host Galaxies with Keck Integral Field Spectra
Get PDFIn the center of most massive galaxies is a supermassive black hole (SMBH) with a mass that can range from millions to billions of solar masses. It has been observed that more massive SMBHs have a more massive host galaxy bulge, as evidenced by the larger bulge luminosity and stellar velocity dispersion, a correlation known as the BH mass - host-galaxy scaling relation. It suggests a close evolutionary connection between the growth of the SMBH and the growth of its host galaxy. If a SMBH develops an accretion disk to fuel an active galactic nucleus (AGN), it will emit radiation across the electromagnetic spectrum. For broad-line AGNs, the mass of the SMBH can be determined using a technique called Reverberation Mapping (RM).
This project presents 15 AGN host-galaxies which were imaged by the Hubble Space Telescope (HST) and have Keck/KWCI spectra. The images are analyzed using GALFIT, a program that performs 2-dimensional decompositions of the images, extracting the structural properties of the galaxy’s components such as its bulge, disk, and bar if present.
The goal of this project is to determine the effective radii of the bulges in order to contribute to the BH mass - host-galaxy scaling relation. Out of the 15 objects analyzed, 9 of them have had their stellar-velocity dispersion calculated which are plotted against the mass of the BH at the center of their respective galaxy