Annual Research Symposium

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  Assessing Security Flaws in Modern Precision Farming Systems

  Joseph Boyd and Robert Richardson

  The increasing interconnectivity of the digital age brings new vulnerabilities for cyber criminals and nation state threat actors alike. Every day, threat actors make millions of at-tacks against a variety of systems. Though not all these attacks prove successful, they all share the same goal of manipulating or extracting data from their targets. The dawn of digitalization in the agricultural industry finds itself under the same threats. Because agriculture sits within the category of critical infrastructure, digitizing this industry should be accompanied with special concern for implementing good security practices. At a basic level, good cyber security practice includes ensuring that data remains confidential to users and processes, ensuring that data remains unmodified by unauthorized methods, and ensuring the accessibility of the data. However, no system can be made completely secure. Some form of exploitation will always exist by which proprietary data of the customer, or the manufacturer, can be leaked or abused. Thus, this paper does not ask if vulnerabilities exist on on-board precision farming equipment, but rather it asks what level of risk these exploits possess. In other words, if a vulnerability becomes exploited, what access or data does the attacker gain and does its value equal the amount of effort required to obtain it? The likely answer exposes vulnerabilities that damage the finances or reputations of individual producers and manufactures, which may provide an equal level of danger to the industry if these attacks can be scaled up against multiple targets.

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  Assessing Security Vulnerabilities in Wireless IoT Devices

  John Brumels

  This research project aims to systematically assess and analyze security vulnerabilities in accessibility technology, specifically devices related to the American Disabilities Act (ADA), such as wheelchair lifts, ADA buttons, and light switches. The project focuses on the potential risks associated with radio frequency (RF) replay attacks, a well-documented threat in IoT security. By examining the vulnerabilities and consequences of RF replay attacks in these critical areas, the research seeks to enhance the security and safety of individuals with disabilities and the broader public. The project also explores potential countermeasures and ethical considerations for responsible vulnerability disclosure, contributing to the fields of accessibility technology, IoT security, and ethical cybersecurity practices.

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  Bones et. al: Educational Human Skeletons Restoration and Investigation

  Emelye Josko and Andrew E. Sathoff

  • There has been a longstanding tradition to use real human skeletons as educational aids in classrooms {2}.
  • The interactive nature of hands-on learning often results in the degradation of these skeletal specimens, and repairs are needed to bring them back to being fully functional.
  • Drawing techniques from one of the few guides to restoring educational classroom skeletons {1} and museum approaches {2, 3, 5}, we are able to find a method that works for three human skeletons at Dakota State University.

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  Do online test proctoring services abide by standard data protections?

  Tristan Stapert and Andrew Kramer

  In the aftermath of the COVID-19 pandemic, schools adopted new software to allow for online learning. Online exam proctoring has seen rapid growth in both K-12 and higher education. The security of these suites is critical due to their extensive access. Online proctoring suites have the capabilities to assess and configure student devices, access the microphone and cam-era, and view student information in the scope of the exam. This case study investigates the security of data sent over the network using dynamic software analysis and network monitoring while using the Respondus Lockdown Browser.

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  Exploring the Antimicrobial Potential of Honey from Alfalfa (Medicago sativa) Against Both Human and Plant Pathogens

  Denyce Bravo and Andrew Santhoff

  Alfalfa (Medicago sativa) is the third most valuable crop in the United States. It produces a large amount of nectar from which honeybees and other types of bees produce a high yield of honey. It is estimated that around 416 to 1,933 pounds of nectar per acre is produced by alfalfa (Kropacova, 1963). However, even with the great antimicrobial features that honey offers, there is still limited research on the antimicrobial properties of specific types of honey, such as alfalfa honey. Topical honey application clears wounds swiftly, aiding rapid healing, even in infections resistant to typical antibiotics like methicillin-resistant Staphylococcus aureus (MRSA). Manuka honey from tea tree in Australia and New Zealand effectively combats human pathogens including Escherichia coli, Klebsiella aerogenes, Salmonella typhimurium, and Staphylococcus aureus, as well as MRSA (Mandal et al., 2011). Alfalfa honey, among others from Saudi Arabia, exhibits high antioxidant potential and significant antimicrobial activity, ranking second only to Acacia honey (Ismail et al., 2021). Honey comprises primarily of different sugars and proteins (0.5%), with variations based on bee species and flora. Hydrogen peroxide (H2O2) is the main antimicrobial agent in honey, confirmed by spectrophoto-metric assays. Other non-peroxide antimicrobial factors include low water content, low pH, phenolic compounds, and bee defensin-1 (Def-1).

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  Flying through the air with the greatest of ease? Evaluation of glide capability in basal maniraptoran theropods

  Norah Zoller, Kierra Miller, Michael B. Habib, Hans C. Larsson, and T. Alexander Deccechi

  Pterosaurs, a lineage of Mesozoic flying archosaurs, include the largest flying animals ever known. Quetzalcoatlus nortropi a Late Cretaceous representative, had a wingspan of over 10 m and likely weighed more than 200 kg. It presents a combination of features (large head, massive wingspan, shoulder height equivalent to an extant giraYe) that has led to ecological interpretations of it as a major predator in the North American Maastrichtian Biome, perhaps second to only Tyrannosaurus rex. Here we examine the probability of that from an energetics perspective. Despite the great wingspan of Quetzalcoatlus, the body length (gleno- acetabular distance) is relatively small (~500 mm) and a volume of ~1.5 times that of an average sized human male. When factoring in lung volume this restricted the gut capacity and thus prey size. We estimate, for a 200- 250 kg adult, a maximum prey size of 5-7 kg. We then examined if this would be enough to sustain an adult Quetzalcoatlus and based on extant mammalian and avian field metabolic rates (FMR). We suggest that a daily food requirement would be around 3.5-5 kg per day using FMR. This suggests that such large creatures would be feeding on either very small prey items or could scavenge leftovers well after the larger theropods had secured their fill. In addition, take oY and flapping flight would be so extremely costly at such a large size, as demonstrated by the fact that in extant birds this value is often 20 times basal metabolic rate or greater. Given these factors (expected glide speeds on the order of 20 m/s or more, the costs of landing and launching are high, the maximum gut capacity low) we suggest that the primary ecological role was a terrestrial walking small prey specialist and/or scavenger. In the largest adults, flight would likely be minimized to extreme cases like escape or long-distance migration, with the daily locomotion primarily done terrestrially, though juveniles were likely more aerial. Given the lack of mid-sized carnivores in the environment Quetzalcoatlus likely used its size to intimidate smaller rivals such as Saurornitholestes, while feeding on similar sized prey. It was not in competition with sub adult or mature Tyrannosaurs, nor preying on all but the smallest members of the dinosaurian fauna. Thus, we suggest it played the role of a lower trophic level consumer and not an apex predator.

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  Micromouse - Maze Solving Robot

  Aiden Schramm, David Medin, and Andrew Kramer

  A Micromouse is a path-finding robot designed to traverse and map a maze to determine the shortest path possible. These robots are typically entered in annual Micromouse competitions to compete against other teams for achieving the best possible time in solving the maze in the most efficient manner.

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  Natural Language Processing: Understanding Slang and Colloquial Speech

  Beau Miller

  Within the field of Natural Language Processing, slang and colloquial language provide a unique challenge for the training and use of language models. This speech holds an odd, transient space with public consciousness, as each instance has a variable time of relevancy and popularity, amongst other factors such as their fluid definition, usage amongst certain groups, and relative lack of information and training data concerning new or evolving terms. These characteristics make it difficult for models to learn these phrases in a timely manner. This project focuses on how a NLP model could learn new additions to colloquial language in a timely and efficient manner, as well as keep up with a rapidly mutating lexicon.

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  Resonant Landscapes

  Tate Carson and Cater Gordon

  Immersive ambisonics field recordings of 13 South Dakota State Parks. Used for: interactive smartphone-based sound art exhibit and immersive soundscape compositions. Goal: by studying a park's soundscape through immersive recording, we can gain a deeper understanding and appreciation for its unique sonic characteristics.

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  Surveying for Ophidiomyces ophidiicola, the causal agent of Snake Fungal Disease in South Dakota.

  Adam Peak, Brandon Daniels, and Andrew E. Sathoff

  For the past decade there has been an emerging disease plaguing wild snakes across the Eastern United States and Europe. In 2006, researchers started investigating the decline of Timber rattlesnake populations in New Hampshire. They discovered a fungal infection killing off the young to mid-juvenal snakes, thus know as Snake Fungal Disease or Ophidiomycosis. In 2011, San Deigo State University, identified the pathogen that causes infection, the fungus Ophidiomyces ophiodiicola. O. ophiodiicola has now affected 30 different snakes from six families within at least 20 different states since it’s discovery. This study pertains to determining the prevalence of Snake Fungal Disease within South Dakota.

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  Terror from the Skies?: Investigating the energetics and feeding ecology of one of the largest pterosaurs: Quetzalcoatlus northropi

  Kierra Miller and T. Alexander Deccechi

  Our goal is to assess the gut capacity and energetics requirements for Q. northropi in order to understand the role that it played when living.

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  The Impact of Family Business Ownership and Involvement on Entrepreneurial Self-Identification

  Ephrata Yared Feyissa and Robert Girtz

  In this study I analyze the impact that family business ownership has on the tendency of individuals to identify as being entrepreneurial. Drawing data from the 1979 cohort of the National Longitudinal Survey of Youth, I use two-sample t-tests and logistic regression models to explore the relationship between personal entrepreneurial aspirations and having come from an environment involving a family business. As part of this analysis, I control for several demographic factors, such as cognition, gender, and ethnicity. The outcomes from this research highlight the importance of family business as a key factor in fostering entrepreneurial mindsets, suggesting that the experiences and cultural context provided by family-owned enterprises are instrumental in encouraging future generations of entrepreneurship.

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  Assessing Commercial Biological Control Agents for Activity Against Alfalfa Root Rotting Pathogens

  Travis R. Rebstock, Conner L. Tordsen, Brandon Daniels, Oleksandra Rachynska, and Andrew E. Sathoff

  Alfalfa is the fourth most valuable crop in the United States and is widely grown as feed for livestock due to its high protein content. According to the USDA 2021 Crop Production Summary, the United States planted 1,646,000 acres of newly seeded alfalfa, and alfalfa seedlings are highly susceptible to disease. Pathogens such as Aphanomyces euteiches and Pythium sp. have devastating effects on newly seeded alfalfa stands causing seed rot, reduced root development, and diminished stand establishment. Current management strategies for these diseases are fungicidal seed treatments and planting of disease resistant alfalfa varieties. To expand upon these management strategies, we investigated commercial biological control (biocontrol) treatments. Isolates of both A. euteiches and Pythium sp. were tested against commercial biocontrol agents with active ingredients such as: Streptomyces actinobacterium K61 (Mycostop), Bocillus amyloliquefociens D747 (Southern Ag), Streptomyces lydicus WYEC 108 (Actinovate), Bacillus subtilis QST 713 (Minuet/Serenade), Trichoderma osperellum ICCO12 and Trichoderma gamsii ICCO80 (Tenet), and Trichoderma harzianum Rifai KRL-AG2 (RootShield). Biocontrol activity against A. euteiches and Pythium sp. was evaluated in growth chamber assays using a susceptible alfalfa variety, Saranac. Treatment effectiveness against A. euteiches was assessed by rating seedling roots using the NAAIC Standard Test rating scale of 1-5, with a score > 2 indicating susceptibility. Seedlings in pots inoculated with Pythium sp. were counted after 5 days to calculate percent germination. Biological controls with the active ingredient, B. amyloliquefaciens D747 have antagonistic effects against Pythium sp. increasing percent germination of alfalfa by 21-70% depending on the pathogen isolate. S. sctinobacterium K61 (Mycostop) had high activity against A. euteiches. Several biological control agents demonstrated activity against both A. euteiches and Pythium sp., providing an additional management strategy against these root rotting pathogens.

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  Do AI-Generated Political Advertisements Create Positive or Negative Responses from Voters?

  Grace Schofield

  Artificial intelligence (AI) is advancing at breakneck speeds, and it’s more important than ever that voters understand AI’s implications on the United States’ political landscape. Political campaigns can synthesize political advertisements using genera-tive AI, fabricating images and videos alike. The public often has difficulty distinguishing these advertisements from their genuine, non-AI counterparts—and deepfake technology improves exponentially, causing the public to struggle even more in identifying AI-generated advertisements.

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  Functional analysis of differentially expressed genes in alfalfa (Medicago sativa) inoculated with Aphanomyces euteiches race 1 and race 2

  Jay Alexander, Deborah A. Samac, and Andrew E. Sathoff

  Aphanomyces root rot caused by Aphanomyces euteiches is one of the most destructive diseases of alfalfa. Resistant cultivars have been developed that exhibit race-specific resistance. Transcript profiling was done to gain a better understanding of the compatible and incompatible interactions. Three-day-old seedlings of the check cultivars WAPH-1 (resistant to race 1 strains) and WAPH-5 ( resistant to race 1 and race 2 strains) were inoculated with MF-1 (race 1) and MER-4 (race 2) and RNA extracted 24 h post-inoculation, with three biological replicates. RNAseq using an illumina HiSeq 2500 to obtain 125 bp paired-end reads was carried out with >10.5 million reads/sample. Differentially expressed genes (DEGs) were identified after sequence trimming and quality control. The incompatible interaction in WAPH-1 and WAPH-5 to MF-1 contained the most unique up-regulated DEGs, 637 and 217, respectively. The incompatible response of WAPH-5 to MF-1 and MER-4 appears to be similar with 258 common up-regulated DEGs and only 59 unique DEGs in response to MER-4. Functional annotation of the DEGs was performed using the Blast2GO tool. The unique DEGs of the incompatible interactions were primarily placed into four categories in the Gene Ontology term Biological Processes: 'defense response,' 'response to stress,' 'organic substance catabolic process,' and 'protein phosphorylation'. These results increase understanding of the A. euteiches and alfalfa molecular interaction for development of cultivars with increased resistant to Aphanomyces root rot.

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  Aphanomyces root rot of alfalfa disease survey in Eastern South Dakota establishes widespread pathogen distribution

  Jennifer M. Giles, Conner L. Tordsen, and Andrew E. Sathoff

  Aphanomyces euteiches causes Aphanomyces root rot (ARR) and damping-off in alfalfa (Medicago sativa), along with root rotting in many other legumes. According to the United States Department of Agriculture 2020 Crop Production Summary, South Dakota plants the most acres of alfalfa in the United States but is the sixth highest state in production. Identification of A. euteiches has been confirmed in several states surrounding South Dakota providing the need for detection in state since ARR management centers on planting resistant alfalfa cultivars.

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  Assessing Commercial Biological Control Agents for Activity Against South Dakota Alfalfa Pathogens

  Conner L. Tordsen and Andrew E. Sathoff

  Alfalfa is the third most valuable crop in the United States and is commonly grown in South Dakota. It is used as a protein-rich feed for livestock, a cover crop that protects against soil erosion, and a natural fertilizer because of its ability to fix nitrogen in the soil. According to the USDA 2021 Crop Production Summary, South Dakota ranks third in the US for newly seeded acres, and alfalfa seedlings are highly susceptible to disease. Oomycete pathogens are arguably the most economically important pathogens causing negative effects on alfalfa field establishment and yield. These root rotting pathogens (Aphanomyces euteiches and Pythium spp.) can cause seed rot, reduce root development, and diminish stand establishment. Oomycete pathogens that inhabit the soil can remain present and pathogenic as oospores for many years regardless of soil conditions. Seed rot is a major issue, forcing growers to spend a substantial amount of money to replant stands. Recent research tested the management strategy of using fungicidal treatment to inhibit these pathogens. These chemical treatments were unsuccessful against many of these pathogens in field studies (Smith, 2014). In this study, alfalfa root rotting pathogen isolates from South Dakota fields and the USDA were evaluated for sensitivity to biological control treatments. A biological control is the addition of a natural microbial predator to a inhibit the growth of a pathogen or pest. This research will identify additional management strategies for South Dakota alfalfa diseases and provide growers with the information necessary to make educated decisions to increase yields and maximize their profits.

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  Managing South Dakota Alfalfa Diseases with Commercial Biological Control Agents

  Travis R. Rebstock, Conner L. Tordsen, Brandon Daniels, Oleksandra Rachynska, and Andrew E. Sathoff

  Alfalfa is the fourth most valuable crop in the United States and is widely grown as feed for livestock due to its high protein content. In 2021, South Dakota harvested 1,320,000 acres of alfalfa and has some of the most acres growing in the United States. Alfalfa seedlings are highly susceptible to disease, which reduces field establishment and yield. Oomycete pathogens, Aphanomyces euteiches and Pythium sp., have devastating effects on newly seeded alfalfa fields causing seed rot and reduced root development. Current management strategies are fungicidal seed coatings and planting disease resistant alfalfa varieties. To create more of an Integrated management strategy, we investigated numerous commercial, organic biological control (biocontrol) treatments, which had previously shown to be effective against oomycetes but have not been tested against alfalfa pathogens. South Dakota and USDA isolates of both A. euteiches and Pythium sp. were evaluated against biocontrols with active ingredients such as: Streptomyces octinobacterium K61 (Mycostop), Bacillus amyloliquefaciens D747 (Southern Ag), Streptomyces lydicus WYEC 108 (Actinovate), and Bacillus subtilis QST 713 (Serenade). Biocontrol activity against A. euteiches and Pythium sp. was evaluated in growth chamber assays using seed of a susceptible alfalfa variety, Saranac. Treatment effectiveness against A. euteiches was assessed by rating seedling roots after 29 days using a standardized rating scale. Seedlings inoculated with Pythium sp. were evaluated after 5 days to calculate percent germination. Biocontrols with the active ingredient, B. amyloliquefaciens D747 have antagonistic effects against Pythium sp. increasing percent germination by up to 71%. 5. octlnobacterium K61 had high activity against several isolates of A. euteiches. Various biological control agents demonstrated activity against alfalfa pathogens, which provides growers with an additional management strategy to protect their fields. In Fall 2022, we plan on testing A. euteiches and Pythium sp. isolates against biocontrol treatments that use fungal antagonists.

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  Quantitative Real-Time PCR Identification of Soybean Pathogens in Eastern South Dakota Soil

  Brandon Daniels, Oleksandra Rachynska, Travis R. Rebstock, Conner L. Tordsen, and Andrew E. Sathoff

  According to the 2021 State Agricultural Overview, South Dakota (SD) planted 5,450,000 acres of soybeans in 2021, and 5.8% of potential soybean production was lost due to diseases. Revealing prevalent soilborne soybean pathogens throughout the state and utilizing the proper management strategies could increase SD soybean yields. With the relatively recent (2014) first report of soybean sudden death syndrome (SDS) in SD and confirmation of SDS in three more counties in 2017, we utilized quantitative real time polymerase chain reaction (qPCR) assays to detect pathogens that cause SDS and other soilborne soybean pathogens using DNA extracted from the soil. qPCR-based diagnostics eficiently and specifically test for pathogens with high sensitivity. The soil was sampled from six fields under commercial soybean production in Deuel County and Brookings County. The collected soil was dried at 55°C for two days, and three DNA extractions were done for each field sampled. qPCR assays were performed on a Bio Rad CFX Opus 96 Real-Time PCR system for several soybean pathogens such as Fusarium virguliforme, Fusariunm brasiliense, Phytophthora sojae, Phytophthora sansomeana, and Phiolophora gregata. qPCR reactions were run in triplicate, with three technical replicates on each biological replicate per field assessed. The presence of P. gregata was detected in three out of the six fields evaluated, while F. virguliforme, F. brasiliense, P. sojae, and P. sansomeana were not detected. Our primary objective was to develop distinct qPCR protocols on samples of DNA extracted directly from the soil for a more extensive SD soilborne soybean pathogen survey in Fall 2022 and Summer 2023. Providing SD soybean growers with accurate, timely information about pathogens detected in their soil should allow them to take proper management strategies and increase their yields.

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  Identification and Characterization of Pythium Species Isolated From Commercial Alfalfa Fields in South Dakota

  Oleksandra Rachynska, Travis R. Rebstock, Conner L. Tordsen, Jennifer M. Giles, and Andrew E. Sathoff

  Alfalfa (Medicago sativo) seeds are often planted when environmental conditions are optimal for Pythium seed rot and damping-off, which is caused by various different Pythium species. Pythium seed rot can devastate alfalfa stands requiring them to be completely replanted. South Dakota plants the second most acres of alfalfa in the United States, and surveys describing Pythium spp. causing disease on alfalfa in the state were lacking. In this study, putative Pythium isolates were baited from soil samples collected in eastern South Dakota using the rolled-towel technique. Pure cultures were obtained, and Pythium spp. were identified using ITS and cox1 sequences. The Pythium isolates were assessed for pathogenicity on alfalfa using a culture plate method. P. sylvaticum was the most frequently isolated alfalfa pathogen. Several commercial fungicides were evaluated against Pythium spp. using agar plate-based assays. CruiserMaxx (mefenoxam, fludioxonil, thiamethoxam) demonstrated strong activity against Pythium isolates. This study establishes the presence of a diverse array of Pythium spp. that are alfalfa pathogens in South Dakota, and the fungicide sensitivity tests provide growers with localized information to select effective fungicide treatments. Increased grower awareness to Pythium diseases of alfalfa may lead to better disease management and increased alfalfa yields in South Dakota.ds

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  Isolation and Characterization of Pythium spp. from South Dakota soils under commerical alfalfa production

  Jennifer M. Giles and Andrew E. Sathoff

  Alfalfa is a significant crop in South Dakota that provides many different benefits for its growers. South Dakota plants the most acres of alfalfa in the United States. It is used as a protein-rich feed for livestock, a cover crop that protects against soil erosion, and a natural fertilizer because of its ability to fix nitrogen in the soil. However, alfalfa seedlings are susceptible to many diseases. Pythium root and seed rot is one disease known to have devastating effects on alfalfa field establishment and yield. Pythium species are oomycete pathogens that inhabit the soil and remain present and pathogenic as oospores. Pythium diseases of alfalfa cause reduced root systems, plant size, length, and growth rate. Pythium management is centered on fungicidal seed treatments. There have been recent reports of Pythium spp. infecting alfalfa across the world in places like Sudan and China, but current research in South Dakota is needed. In our research, we isolated Pythium spp. from Lake County South Dakota soils under commercial alfalfa production. We also characterized these isolates with a DNA sequencing analysis and evaluated the isolates for fungicide sensitivity. This summer, we will conduct a statewide Pythium disease survey and assess the collected isolates for fungicide sensitivity and pathogenicity towards various commercial lines of alfalfa. This research will provide growers with the information necessary to make educated decisions in order to increase yields and maximize their profits.

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  Feature Extraction and Analysis of Binaries for Classification

  Micah Flack

  The research project, Feature Extraction and, Analysis of Binaries for Classification, provides an in-depth examination of the features shared by unlabeled binary samples, for classification into the categories of benign or malicious software using several different methods. Because of the time it takes to manually analyze or reverse engineer binaries to determine their function, the ability to gather features and then instantly classify samples without explicitly programming the solution is incredibly valuable. It is possible to use an online service; however, this is not always viable depending on the sensitivity of the binary. With Python3 and the Pefile library, we can gather the necessary features to begin choosing different classifier models from the Scikit-learn library for machine learning. This all addresses the issue of local automated classification, and we present several different classifier models, datasets and methods that allow for the classification of unknown binaries with a high degree of accuracy for predicting malware and benignware.

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  Accessing the Impact of IT Budgets on Hospital Performance: A Panel Data Analysis

  Giridhar Reddy Bojja, and Jun Liu

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  A Stream of Consciousness

  Truman Weyand

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  Bust-A-Binary: Active Attribution and Analysis of Malware Campaigns

  Micah Flack, Nathan Kramer, Zayn Snyder, Ezra Chona, Matthew Steckelberg, and Bramwell Brizendine