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  Financial Discrimination in Bangladesh

  Sydni Dionna Kidd, Elenore L. Stebbins

  Based on the work and data gathered by Counterpart International, a development agency funded by USAID, this presentation examines how financial discrimination in Bangladesh impact gender equality. This is part of a larger program Counterpart International has implemented since 2018, titled, ‘Promoting Advocacy and Rights’ (PAR) in collaboration with local non-government organizations (NGOs). Anchored in the Gender/Women in Development (GID/WID) approach, PAR aims to deepen democratic values within civil society to improve public governance. Financial discriminations are economic factors based on race, gender, economic status, and amount of investment in an area or region. In Bangladesh, rural women have been the most affected by financial discrimination from NGOs and the banks. Several factors are in play when someone experiences discrimination. Counterpart International has done significant work and research for the Bangladeshi people and in fact Bangladesh is also a signatory of major human rights conventions including the International Covenant on Civil and Political Rights (ICCPR); International Covenant on Economic, Social, and Cultural Rights (ICESCR) and International Convention on the Elimination of All Forms of Racial Discrimination (ICERD). These three particular United Nations treaties help protect citizens from discrimination and crime committed against them by their own country. Counterpart has created different evaluations and reward systems that help monitor this financial discrimination through programs such as Reporting Total Compensation of Recipient Executives, Electronic Payments System, Salary Supplement Guidance and more.

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  Flexibility, Creativity, and Adaptability in the Sunshine State: A Local Study of Nonprofit Organizations During the COVID-19 Pandemic

  Lauren Elizabeth Tobal

  Nonprofit organizations are integral parts of communities across the world and often serve as safety nets for vulnerable populations. From healthcare to housing, nonprofits have the ability to make tremendous differences in people’s lives. This research, examined through the lens of civil society, helps to understand the ways in which nonprofit organizations contribute to society in unprecedented times. This study examines the effects of the COVID-19 pandemic on nonprofit organizations through in-depth interviews with leaders of four local nonprofits in Naples, FL. The organizations interviewed vary by the services they provide, but each support at-risk populations in a variety of ways. Participants were chosen based on convenience sampling and recommendations from other interviewees. Results from this research show increases in the number of individuals and families the nonprofits served, increases in the amount of collaboration between local nonprofit organizations, as well as some interesting positives that arose from the COVID-19 pandemic. From these findings, I conclude that nonprofit organizations are an integral part of supporting local communities, especially in times of crisis.

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  From Prop to Partner: the Evolution of Female Roles in American Opera

  Mariah Joanna Berryman

  For many years, women in opera have been in service to their plots. They have always been present, but have either been relegated to passive roles in their own stories or actively considered societal outcasts. They were dramatically stereotyped as either air-heads or witches, mothers or daughters, love interests or foes to be conquered. And, along with the character stereotypes came typically associated vocal stereotypes. Lighter and higher voices were assigned to roles that portrayed virtue, innocence, and other general characteristics of the “feminine ideal.” Conversely, lower voices were assigned to sinful, outcast, “fallen women.” These vocal stereotypes are especially prevalent for the women condemned to the fringes of society, the othered “them” in contrast to the idealized “us.” Examination of opera plots in contrast to historical documents and artifacts through time reveals an important movement towards more accurate dramatic and musical characterization of women in American opera.

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  Gender, Mental Health, and Substance Use

  Emma Finch

  This study aimed to explore the connections between gender, age, mental health, and substance use. Data from 18,294 respondents between the ages of 12 to 17 from the 2004 National Household Survey on Drug Use were asked about their mental health and substance use. According to the results of the study, the older a respondent is the more likely they are to have higher scores on the depression scale which leads to a higher use of substances. However, after further testing, this model only explained about 5% of the variation in substance use. These results suggest that there may be other variables affecting substance use among teenagers. Further research beyond this study is necessary.

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  Genetic interaction between the axial patterning gene, dve, and Dpp signaling in the developing Drosophila eye

  Anuradha Chimata Venkatakrishnan, Neha Gogia, Katie Marie Perry, Akanksha Raj

  An interesting question in developmental biology is how any three-dimensional organ develops from a single monolayer of cells. In multicellular organisms, delineation of Antero-Posterior (AP), Dorso-Ventral (DV), and Proximo-Distal (PD) axes are crucial for organ development. Drosophila melanogaster is an ideal model organism as the genes and pathways are highly conserved between Drosophila and humans. During eye development, DV axis formation marks the first lineage restriction event, and deviation in this process results in birth defects in the eye. Previously, we identified defective proventriculus (dve) as a new dorsal eye fate selector or patterning gene. dve regulates eye development by regulating wg, a negative regulator of eye development. Apart from wg, there are several other morphogens which havean important role during eye growth and development. Dpp signaling is one such pathway important for retinal differentiation. We hypothesize that dve, a transcription factor, regulates the Decapentaplegic (Dpp) signaling pathway, which is comparable to bone morphogenetic protein (BMP) signaling in mammals, during dorsal eye development. We will investigate the role of dve in the dorsal eye andwhether dve requires Dpp signaling to specify eye and head fate to form an organ of balanced size and shape. We utilized the GAL4-UAS system to modulate Dpp signaling in the dve domain. Thus far in our research, we have found that upregulation of Dpp in the dve expression domain results in an enlarged eye phenotype, while downregulation of Dpp in the dve domain results in a small eye phenotype. We havetested retinal determination genes to explore cell specific fate and further support the genetic interaction between dve and Dpp signaling. We are currently testing their interaction using clonal strategies to understand how dve regulates dpp in the developing eye. This study may have a significant bearing on growth, signaling and patterning defects and help in understanding the etiology behind genetic birth defects in the eye.

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  Global Religion: Approaches to Climate Change and Sustainability

  Hannah Ellen Bean, Hannah Rose Kessler, Aaron D. Tilton

  We performed a literature analysis of research pertaining to how different religions approached climate change and sustainability. Our aim was to learn what different approaches, if any, world religions take to addressing climate change and sustainability. Learning what motivates action, or lack thereof, can help future leaders inspire their constituents to take positive action on climate change. We learned that different world religions have different approaches to sustainability, but usually have some sort of belief regarding environmental protection. Through our research, we learned that often, religious groups create climate action groups in order to put into action their beliefs about sustainability. The ways they approach this action is different, but climate action groups in general seem to be common amongst religious groups. Climate change is on the forefront of religious leaders' minds and there has been much more recent discussion about it and what actions we need to take than there has been in the past. As climate change becomes more of a pressing issue, it has become a focus of much religious teaching.

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  Graphic Design Summer Fellowship 2020

  Emily M. Cordonnier, Megan Marie Lewis

  A summer filled with uncertainty and social unrest, Megan Lewis and Emily Cordonnier researched methods of making and the creative processes. Lewis explored the intersection of form and design through clay. Using a wheel-throwing technique, she created pieces influenced by ceramic artists whose work balances at the intersection of fine art and design. Her final project was the culmination of the work she created over the tumultuous summer of 2020. Cordonnier’s research focused on paper-making techniques through experimentation and chance processes. The final book celebrates the outcomes of research and process utilizing found vinyl letters and handmade paper. Throughout their research and creative processes, both Lewis and Cordonnier researched and drew inspiration from a range of artists and designers that linked to their discipline of graphic design. In addition, research was recorded through weekly podcasts that served as a mode of dialogue about their summer research.

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  Graphs and Groups

  Chloe M. Crabb

  This is a project from the course MTH 466, Graph Theory and Combinatorics. A graph is a mathematical object that consists of two sets, a set of vertices and a set of edges. An edge joins two vertices and depicts a relationship between those vertices. Two graphs are said to be isomorphic if their vertices can be relabeled and rearranged so that the graphs have the same structure. An automorphism is an isomorphism from a graph to itself. The set of automorphisms of a graph under composition forms a group. This project will explore graphs through a lens of group theory. It will examine automorphism groups of special classes of graphs.

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  Group Trajectory Analysis in Sport Videos

  Shreenivasan Duraivelan

  Trajectory Prediction is the problem of predicting the short-term (1-3 seconds) and long-term (3-5 seconds) spatial coordinates of various agents such as cars, buses, pedestrians. In Trajectory, Prediction we use the moment of an agent’s past trajectories to predict action or course the agent is going to make in the future. In our paper, we are using trajectory prediction to predict the future location and the movement of the players and ball in a basketball game. There are several Pedestrian trajectory prediction modules which have yielded great results. But applying the same to a basketball game will not yield great results since the pedestrian trajectory modules are generalized for the huge population. We propose a model which will learn the play style and the players position/roll, which will lead to better predictions in a game. We use Transformer network to implement the trajectory prediction algorithm along with a player behavior module which will increase the accuracy of the prediction.

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  Hannah Gatlin-Artist Talk

  Hannah Ruth Gatlin

  I am a senior fine arts student, and I will be talking about the body of work that I completed. I will go in-depth on my inspirations for my work and the meanings behind it.

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  Here comes the sun: The effect of a solar panel prairie on a dragonfly and damselfly community

  Emily L. Ott

  The order Odonata that includes dragonflies and damselfies are a widespread and important insect group as predators, particularly in riparian areas. Their polarotactic capabilities provide them with an attraction to polarized light that is emitted from water which allows them to navigate their way to a water source to lay their eggs. These tendencies could also make them fall prey to an ecological trap: solar panels emit the same polarized light, potentially fooling the Odonates into laying their eggs on the panels instead of in water. The University of Dayton installed a solar array in 2018, and put a prairie underneath of this solar array to attract native insects. During the Summer and Fall months of July through October, I surveyed Odonate abundance and behavior in a prairie both underneath and outside of a solar panel array to determine if these species were using the prairie and determine if the solar panels were causing an ecological trap for this species. Odonates were most abundant in the prairie outside of the solar array, with almost no individuals seen perching underneath of the solar panels. Also, I observed no egg laying behavior on the panels. The lack of this ecological trap could be due to the inclusion of white grids on the solar panels that breaks up the polarized light and lessens the degree of attraction Odonates experience. The research shows that these native insects do use this constructed prairie, but avoid the shaded area underneath the solar array. This work has implications for how these solar arrays are installed and maintained: based on this research, I recommend using solar panels with these white grids to avoid ecological traps for polarotactic insect species.

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  Her Name is Blood: Situating Gertrude Blood Within the Flânuese, and Walking Virtually

  Lexi Ryan Marie Gallion

  Women are oftentimes forgotten in history due to the pursuit of their male colleagues. Much is the case for Lady Colin Campbell, née Gertrude Elizabeth Blood (b. 3 May 1857), as she was left behind in history. However, unlike other similar stories, Blood was subject to the thoughts and opinions of a nation when she and her husband went through the longest and nastiest - dismissed - divorce trial in UK history. After the trial, she engaged in journalistic writing, submitting over a period of time to the periodical "The World" which would eventually turn into her essays "A Woman’s Walks". Despite her popularity at the time Blood and her writing faded out of the public sphere. What this project intends to accomplish is to reintroduce Gertrude Elizabeth Blood back into society not for her scandal, but for how her work can be considered part of the Flâneur genre. As a woman born to a family capable of social climbing and then eventually a shunned member of the upper class, Blood’s work can shed unique light on the machinations of the Flâneur and the effects of class and gender. This proposed project will perform an analysis to (a) engage in understanding of the flâneur, working the flânuese into the definition of the flânuer using Blood’s writing and (b) a reintroduction of Blood as a woman worthy of analysis, and appreciation for her work as a woman who went against the grain of society.

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  Home Court Advantage In The NBA

  Zachary Andrew Lentz

  This project will use a logistic regression analysis to determine the effect of home court on the probability of winning an NBA game. The data collected is on all thirty NBA teams from the 2018-19 regular season, since this was the last normal season before Covid-19 happened. Each data point analyzed is a particular game with multiple variables for that game. The dependent variable is win, which is a binomial variable, 0 if that game is a loss and 1 if it is a win. The independent variable home is a binomial variable, 0 if the team was a away and 1 if the team was home for the game. The other independent variables are continuous: number of All-Stars for the 2018-19 season that were on the team, number of All-Stars for the 2017-18 season that were on the team, number of wins the team had in the 2017-18 season, and a variable representing head coaching experience. The head coaching experience variable is the number of wins the head coach had divided by the number of years of head coaching experience entering the 2018-19 season. Logistic regression is used to evaluate the impact of the independent variables on the probability of winning the game. The ultimate goal is to determine if there is an advantage to have the home court and crowd in an NBA regular season game.

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  Human Behavioral Analysis: Intruder Detection in Videos

  Manish Pavan Beesetti

  This research aims to develop an intruder detection system based on human behavior via front door surveillance. This is similar to the classic action recognition and scene recognition problems which are currently hot topics in the field of computer vision. To this end, we have collected YouTube videos and then annotate them as anomaly or normal labels. We then train a C3D model by considering a sequence of frames as an input. The experimental results demonstrate the effectiveness of our system.

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  Identification of ortholog and paralog-specific amino acid evolution between the Drosophila sperm specific b2 tubulin, its major tubulin paralog beta-1 and its ortholog Glossina moristans beta-2 tubulin using molecular evolutionary genetics analysis (MEGA-X)

  Kollin J. Clark

  The Drosophila spermtail tubulin b2 is a highly conserved protein. Structure/function tests find that even small changes render b2 unable to generate motile sperm. A bioinformatic approach was used to identify evolving b2 amino acids as indicators of relaxed sites, by comparing b2 to closely related homologs. After aligning Dmb1 & Dmb2 and Gbm2 & Dmb2 sequences, the analysis found 13 positions that differed in amino acid polarity, charge, or acidity characteristics that would alter its interactions within the spermtail. There are seven sites between Dmb1 and Dmb2 paralogs that have different amino acids that also have different characteristics, and nineteen sites where Dmb1 and Dmb2 have different amino acids but similar characteristics. In ortholog comparisons, there are six sites where Gmb2 had different characteristics when compared to Dmb2 and twelve sites with different amino acids that have similar characteristics. There is some segregation between the b2 paralog and ortholog in terms of which sites are evolving, 2/6 (33%) of Gb2 characteristic change sites had overlap with Dmb1 and 2/7 (28.57%) of Dmb1 characteristic change sites had overlap with Gb2. This indicates the different functions of b1 and b2 have different amino acid requirements that impact which amino acids are capable of evolving.

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  Implicit and Explicit Racial Bias: Perceptions of Racism in America

  Miranda Lynn Brooks

  This study investigated awareness of harbored implicit and explicit racial biases against the backdrop of perceived racism in America. The aim was to highlight how specific group membership and the level of willingness to self-censor affected respondents’ disclosures and perceptions of themselves and current civil movements, like Black Lives Matter. Unavoidable exposure of systemic racism and oppression in America caused the timeliness of the study, which took place in the summer of 2020.

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  Influence of Prairie Restoration on Hemiptera Composition

  Claire Townsend Brewer, Stephanie Kay Gunter

  Ohio has historically hosted a patchwork of tallgrass prairies, which provide habitat for native species and prevent erosion. As these vulnerable habitats have declined in the last 200 years due to increased human land use, restoration efforts have increased, and it is important to evaluate their success. The Hemiptera (true bugs) are an abundant and varied order of insects including leafhoppers, aphids, cicadas, stink bugs, and more. They play important roles in grassland ecosystems, feeding on plant sap and providing prey to predators. Previous research has found that Hemiptera respond in their abundance and composition to grassland restorations, age of restoration, and size and isolation of habitat. This study investigates the effects of these variables on the abundance and composition of Hemiptera within 13 Ohio prairies in order to answer 4 questions regarding prairie restoration: 1- Do older constructed prairies resemble remnant prairies in Hemiptera abundance, diversity, and composition more than they resemble newer constructed prairies? 2- Does the size of a prairie fragment affect the abundance, diversity, and composition of Hemiptera? 3- Does the distance of a prairie to an agricultural field affect the abundance, diversity, and composition of Hemiptera? 4- Are there particular morphospecies that indicate particular prairie types? Insect samples were taken via sweep net from 13 prairies (7 restored and 6 remnant) in 4 southwestern Ohio counties in summer 2019, and were sorted to order. I then sorted the Hemiptera to family and morphospecies. I will use analysis of variance, correlations, linear regression, and NMDS to determine the effect of prairie type (remnant, old constructed, new constructed), fragment size, and distance to agriculture on Hemiptera abundance, diversity, and composition. I will also perform an Indicator Species analysis to determine if any morphospecies indicate any particular prairie type.

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  Investigating the Effects of a p53 Mutation on Glioma Progression and Therapy Resistance in Drosophila

  Kaitlyn M. Alleman

  Gliomas, which are brain tumors that arise from glial cells, are some of the most aggressive and lethal types of tumors. These brain tumors are difficult to treat because not enough information regarding the mutations present in these tumors exists. This project studies effects of a p53 mutation on Drosophila glioma progression and then will test to see if this results in resistance to current chemotherapy. Drosophila are used as model organisms to mimic these processes. The current genetic crosses that have been created will be studied, and an effective p53 knockdown will be made. In essence, this will effectively mimic a human brain tumor so the treatments tested and the data collected from this model can be applied to the current understanding of human gliomas. In addition to studying just the p53 mutation, PI3K and oncogenic Ras signaling will be coactivated. This will lead to an even more accurate glioma model because multiple mutations, such as the ones added are present in human tumors as well. These genetic crosses will be treated with Tyrosine Kinase Inhibitors, which are currently used to treat brain cancer patients in order to find out whether or not this mutation plays a role in resistance to current therapy. The main goal of this endeavor is to investigate the numerous defects occurring at the cellular and biochemical level in gliomas, which will give insight into why these types of tumors are so difficult to treat. Data gathered from this project will lead to further inquiry into the role of p53 mutations in gliomas and hopefully, to better outcomes for those affected by this type of cancer. Here, we present the data gathered from this project thus far.

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  Is it the ‘Most Magical Place on Earth’ for Interns? A Cost-Benefit Analysis of the Disney College Program and its Emotional Labor

  Jacqueline R. Russo

  Any internship for college students demands work and it may appear straightforward to gauge this in terms of energy, time, and the value of the costs associated with the job. How do we understand the full cost, whether physical and emotional, of certain internships, especially at a renowned location such as Walt Disney World? The Disney College Program (DCP) is a semester-long internship for college students and expects its interns to be “on stage” and perform tasks for the entertainment value of guests. To understand the physical and emotional impacts of the DCP, this study utilizes a cost-benefit analysis and applies the concepts of emotional labor, emotional management, and emotional regulation to this internship experience. Specifically, this research asks, “What kinds of emotional labor and regulation do DCP interns give to their job and do they interpret this experience to be worth the costs?” Through snowball sampling, participants were accessed via Facebook groups and includes those who participated in the DCP at Walt Disney World Resort from the years 2012-2019. Exploring the intersections of costs, benefits, and emotional labor, the results of this research show that there are many demands and pressures DCP interns experience. With many lifestyle, personal, academic, and career-oriented adjustments to make to participate in the DCP, interns often experienced stress, emotional dissonance, burnout, alienation, and little room for emotional flexibility. Interns can also gain customer service skills, develop relationships, and a sense of accomplishment from their involvement in the DCP. From these findings, it can be concluded that interns often utilize deep acting in order to reduce the cost of emotional labor applied to tasks, remaining “on stage” during work hours, and managing personal emotions.

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  Is Mental Health Declining? University of Dayton Students in a Pandemic

  Coleen Marie Coffey

  This research asks how the COVID-19 pandemic has affected the mental health of college students at the University of Dayton. Mental health on college campuses can be strenuous as students deal with the anxieties of living independently, classwork, as well as finding their career path. With a combination of these existing stressors and now a pandemic, students at the University of Dayton endure social isolation and a lack of in-person classes. The purpose of this study is to identify the reasons, if any, that have caused a decline in students’ mental health. The study was conducted through an online survey which was sent out via email and messages to students and professors who were asked to forward it to their students. Utilizing the organizations and clubs that I am in I received fifty-eight responses. The survey included Likert scale and open ended questions. Major findings were that many students feel as though their mental health has been ignored when it comes to their schoolwork, and they feel that their mental health has gotten worse since the pandemic. Numerous students explain that they do their best to be around their friends and other people as well as focusing on physical exercise to help with their mental health. Despite a smaller response from first-year students, the study was able to determine that 68% of students are moderately concerned about caring for their mental health. I conclude that there needs to be an increase of access and availability for mental health support from the university so that students can seek the help that they need.

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  Isolating Antibiotic Producing Pseudomonas From Soil

  Caroline Rose Wattles

  The Tiny Earth Network works to address the decreasing amount of effective antibiotics by testing soil bacteria for antibiotic production. Antibiotics are used in medicine to treat bacterial infections by killing or slowing the growth of bacteria. A threat to the common treatment is antibiotic resistance which has resulted in a health crisis. To combat this, new antibiotics need to be discovered and through the Tiny Earth Initiative bacteria from soil samples are being used as a source. The isolated soil bacteria was tested for antibiotic production against clinical pathogens such as E. coli and S. epidermidis. Laboratory methods such as gram staining, biochemical testing, and 16s rRNA gene sequencing were used to identify the isolated soil bacteria. An organic extract was also prepared from the isolate using ethyl acetate for extraction and methanol as a solvent to confirm the antimicrobial activity and to check for potential toxicity. The methanol solution of the extract was plated onto a water agar plate. Chia seeds were sprinkled onto the plate and left to grow. Chia seed growth indicated the antibiotic extract was not toxic to Eukaryotic organisms while no growth indicated toxicity. Discovery of antibiotic producing bacteria will help the ongoing battle against antibiotic resistance and its effect on bacterial infection treatment options.

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  Isolation and Characterization of Soil Bacteria Having Antibacterial Activity

  Brenna Marie Reilly

  Antibiotic resistance in bacteria against a single or multiple drugs is a burning issue worldwide. According to the 2019 Antibiotic/Antimicrobial Resistance (AR) threats report of the Centers for Disease Control and Prevention (CDC), more than 2.8 million antibiotic-resistance infections occur in the U.S. each year, and more than 35,000 people die as a result. Therefore, the current study was carried out to isolate and characterize soil bacteria having a new compound with antibacterial activity. Soil samples were collected from GPS coordinates of 39.73594418442152, -81.17545763942566 at a depth of 7.62cm. The weather was 16 Fahrenheit, even though the soil was hard, the deeper I dug the soil became moist and soil was collected and placed in a sterile test tube. The appearance of the soil was a dark brown. Individual bacteria from soil were separated and isolated using serial dilution techniques. Bacterial media such as Reasoners 2A Agar and Todd Hewitt were used for bacterial isolation. Six different bacterial isolates based on colony morphology, were screened for antibacterial efficacy against close relative bacteria to ESKAPE pathogens, such as B. subtilis and E. coli. Out of six, one bacterial isolate showed antibacterial activity against B. subtilis. Bacteria which showed the antibacterial activity against B. subtilis was characterized as gram-negative bacillus. Biochemical testing showed that bacteria was motile (by Sulfide Indole Motility), gelatinase positive (by gelatin Agar), non-lactose, sucrose and glucose fermenter (by triple Sugar Iron Agar) and citrate positive (examined by Simmons Citrate Agar). 16S ribosomal gene sequencing result is awaited. Organic extract of this bacteria furthered the antibacterial activity against B. subtilis on Todd Hewitt agar, while awaiting a test for toxicity to chia seeds. In future, organic extract from this bacteria will be characterized for structure of this active compound.

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  Kill Probability in Volleyball

  Maura C. Collins

  This project aims to predict the probability of a kill on left-side and right-side attacks in volleyball. Specifically, it looks at the type of attack, which accounts for it being either a left-side vs a right-side attack and whether it was a fast tempo or a slower tempo set, the grade of the pass for this play, and whether this attack was on a first-ball play or in the transition of a rally. A logistic regression model was used to To look at the relationship of these variables. Using the p-value, it was found that attack type and whether it was a first-ball or transition play were the significant variables for this model.

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  Leonardo de Pisa and Interesting Results of the Fibonacci numbers

  Megan Elizabeth Schaner

  Leonardo de Pisa, better known as Fibonacci, is an Italian mathematician who is responsible for numerous mathematical notions and ideas. The most notable are the use of the Hindu-Arabic numerals in modern society and the famous Fibonacci sequence. These ideas were published in his two books Liber Abaci and Liber Quadratorum published in the early 13th century. The Fibonacci numbers are a set of numbers that make up a recursive sequence where a term is constructed by the sum of the two terms that immediately precede it. There are numerous identities and interesting facts revolving around the Fibonacci numbers such as the approximation of the famous Golden ratio, the sum of the even and odd indices of the Fibonacci numbers, and how consecutive Fibonacci numbers are relatively prime. This presentation will focus on how the fact that the greatest common divisor of two Fibonacci numbers is also a Fibonacci number helps to establish that a Fibonacci number divides another Fibonacci number if and only if the corresponding index of the divisor divides the corresponding index of the dividend.

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  Lesion Synthesis Algorithm and Multi-Scale U-Net for Lung and Lesion Segmentation

  Dhaval Dilip Kadia

  Artificial Intelligence (AI) is growing exponentially with novel computational architectures and their cognitive capabilities. AI helps solve complex problems in medical imaging. Lung segmentation is essential since it processes the volumetric information of the lungs, removes the unnecessary areas of the scan, and segments the actual area of the lungs in CT scan. This research focuses on deep learning applications to segment lungs and further develop a novel algorithm to make them robust. Supervised learning requires data to train a deep neural network. The deep learning model, such as U-Net, outperforms other network architectures for biomedical image segmentation. We propose a deep neural network based on U-Net for the lung and lung lesion segmentation tasks. The proposed model integrates convolution into the sophisticated Multiscale Recurrent Residual Neural Network based on U-Net. Both deep neural network (DNN) and availability of diverse annotated data make the given deep learning based solution robust and generalized for practical use. Even if having sophisticated DNN, scarcity of annotated data challenges the expected outcomes. Robust segmentation of COVID-19 infected lungs requires rich labeled data. Accurate pixel-level annotation tasks to generate such data are time-consuming, and that delays data preparation. We propose a novel algorithm to generate lesion-like artificial patterns, and U-Net based deep neural network for robust lung segmentation further helps segment COVID-19 lung infection. The pattern generation algorithm generates 2D and 3D patterns to create an enormous amount of synthetic data. This algorithm and DNN give accurate lung segmentation results for highly infected lungs and provides infection segmentation. This research applies to the preprocessing stages of different applications of deep learning, medical imaging, and data annotation. The proposed work helps the deep neural network to generalize on a given domain to accomplish robust segmentation results in the absence of exact data.