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Synergies between Safe Quality Food Certification and Lean Six Sigma in Analysis of Defects and Risk for Food Manufacturing
No full textPlan BThe purpose of manufacturing plants is to leverage economies of scale. A collection of raw
materials enters a building and leaves a completed commodity. A variety of products can be
produced, unique to their requirements. One requirement across the food manufacturing industry
is the consumer’s safety. A defective food product has consequences, unlike other industries’
products. Unsafe food is poisoning the well. The Safe Quality Food (SQF) Certifications hold
food manufacturers to a higher standard of safety and quality. Many of the tools deployed
through the SQF program use Lean Six Sigma tools. Whether it is reducing food safety incidents
or defects, it is different sides of the same coin. If a symbiotic relationship is formed between
SQF and Lean Six Sigma; the highest quality standards can be achieved including consumer
safety
NARRATIVE SENSE-MAKING, MEMORABLE MESSAGES, AND BROKEN HEARTS: FRIENDSHIP SUPPORT AFTER ROMANTIC TERMINATION
No full textThis project examines how individuals seek support from their friends after experiencing romantic termination, otherwise known as a breakup. Romantic breakups are a nearly universal experience with many negative repercussions including decreased physical and mental health (Kansky & Allen, 2018). To begin, this project breaks down the process of selecting friends for support after experiencing a breakup. Through applying communicated narrative sense-making theory (CNSM) and the memorable messages framework, the study explores how individuals use narratives and resonating messages during supportive conversations with friends to cope after going through a breakup. This project utilized qualitative interviews with thematic analysis to fill gaps in literature relating to seeking support from friends after breakups as well as the use of narratives and memorable messages for coping and understanding. Individuals selected friends for support based on their prior experiences, the anticipated emotional support, and the friend’s expertise. The underlying assumptions of CNSM were supported as individuals used storytelling to process, make sense of, and cope with their experiences. Building connections between narrative storytelling and supportive communication, the study additionally highlighted overlaps between CNSM and cognitive reappraisal. Finally, memorable messages were useful for reappraising the breakup in a variety of ways, and further helped support seekers get over their breakups, improving their overall well-being. This study supports CNSM, memorable messages framework and the theory of cognitive reappraisal as storytelling and memorable messages were found to facilitate new understandings of breakups. This study gives insight into support seeking and supportive interactions, expanding insight into how friends are selected for support, and how the stories they share with each other help make sense of their experiences.2025-11-3
Achieving Real Freedom: Motivating a workplace democracy reading of Rawls
No full textJohn Rawls leaves the importance of workplace democracy to the just society as an open question. Elizabeth Anderson’s Private Government argues for a workplace republicanism in the interest of extending Rawlsian relational egalitarianism into the workplace. In this paper, I contend that workplace republicanism is insufficient for these purposes. Political thinkers operating in a Rawlsian framework ought to advocate for full workplace democracy. Autonomy may be bifurcated into two constitutive elements: the personal and the collective. While Anderson’s framework provides a degree of personal autonomy to workers, I argue that collective autonomy is essential to the egalitarian project and that it is neglected in the workplace republicanism model
THE IMPACT OF MILKING FREQUENCY IN AUTOMATED MILKING STSYTEMS ON MILK PRODUCTION AND MILK REVENUE
No full textThis research investigates three novel aspects of Automatic Milking Systems (AMS) to enhance understanding of how their management influences dairy productivity and revenue. The first objective is to identify key determinants of average milk yield per cow in AMS-operated herds, focusing on biological factors (e.g., lactation number, days in milk), behavioral patterns (e.g., milking frequency), and fixed farm-specific factors that may reflect management style, facility design, or herd genetics. The second objective explores the relationship between the early establishment of high milking frequency—specifically, achieving an average of three milkings per day by day 22 of lactation—and the production and value of milk and milk components such as butterfat and protein. The third objective examines how the quantity of pellets dispensed affects milk revenue and revenue less pellet cost.
To address these objectives, data were obtained from five Wisconsin dairy farms using AMS systems during July to December 2024, combining information from the AMS milking records with farm-specific and secondary data on milk prices, component values, and pellet costs. These data were analyzed with ordinary least squares models and a series of Random Effects Models (REMs), which were chosen over Fixed Effects Models to allow for the inclusion of both within-farm variation and between-farm differences that may influence performance.
Results show that milk yield is significantly influenced by milking frequency and days in milk, though additional milkings per day show diminishing returns. Cows that achieved an average of three milkings per day (3X) by day 22 of lactation produced about 6 pounds more milk per day from day 22 to 150—equating to a 5.4% increase in milk revenue compared to cows that did not reach this frequency. On the one farm with detailed component data, early 3X
cows also produced substantially more butterfat and protein, boosting daily milk value by approximately $1.40 per cow at the mean component price. At the herd level, a higher proportion of early 3X cows was associated with up to 11.8% more fat per day and 23.5% more protein per day. Pellet feeding was positively associated with milk production, but the revenue gains were partially offset by feed costs, especially under low milk price conditions.
These findings highlight the economic advantage of achieving high milking frequency early in lactation and the importance of balancing feed input costs against milk revenue. The study’s results offer new insights into the optimization of AMS strategies by demonstrating the production and revenue implications of early-lactation milking behavior and targeted feeding practices
Zebra Finch Relationship Stability and Stress
No full textRelationship stability is key for loving and stress-free monogamous relationships from humans to zebra finch. Consistency of affiliation can greatly influence an individual when going through a stressful event. An indicator of high stress in songbirds is a high heterophil to lymphocyte ratio in their blood. Little information is available about how socially monogamous zebra finch pairs physiologically react when separated from their partner. Two experiments collected behavioral data on the socially monogamous zebra finch. Through these experiments, the pairs were exposed to different influences of stress such as environmental and partner strain. The birds were then isolated for two hours, and their blood was taken and heterophil to lymphocyte ratio was recorded. Birds who had consistently high affiliation behavior with their partner were also recorded having higher heterophil to lymphocyte ratio after isolation. This indicates that the strength of the relationship is directly correlated with the amount of physiological stress the individual experiences when isolated from their partner
Citizen Lake Monitoring Network (CLMN) Refresher Training
No full textCitizen Lake Monitoring Network (CLMN) Refresher Trainin
Enhancing Industrial Design Education: Virtualized and Augmented Design Iteration
No full textCreative ThesisThe rapid advancement of technology has revolutionized the design landscape, necessitating the
integration of cutting-edge tools into Industrial Design education. This thesis explores the
incorporation of photogrammetry and virtual reality (VR) into Industrial Design curricula to
better prepare students for contemporary design challenges. Several technological advances have
been made, allowing for an increased use and reliance on digital tools with industrial and product
design education. This must be coupled with understanding analog techniques and the ability to
use them in tandem for the best results. Industrial Design: Photogrammetry and Virtual Reality
for Design Detailing acts as an update to current curriculum, exploring the use of
photogrammetry to scan products and prototypes three-dimensionally. Traditional methods were
used to create a number of iterative prototypes, all documented digitally. The final concept work
was in a virtual reality space, rendered digitally, and printed in full color for a presentation
prototype. These sections are presented as modules within a hybrid course targeted at students in
the 2nd or 3rd year of their Industrial and Product Design program. The hybrid nature of this
course also offers an opportunity for non-traditional markets or students. This may include
industrial design professionals of any level looking to update their skillset and apply new digital
tools to their workflow
Neurosymbolic Semantics
No full textHumans exhibit distinct yet complementary cognitive capacities for logical and relational reasoning, foundational to understanding language processing and meaning representation. These capacities find mathematical expression in two prominent computational frameworks: formal semantics, which maps expressions to truth values through logical structures; distributional semantics, which represents meaning through contextual relationships in vector spaces. This research establishes well-defined mathematical compatibilities between these philosophies of language by constructing structural correspondences. These correspondences: (1) preserve core semantic relationships; (2) respect compositionality and logical dependencies; (3) allow for embeddings of intensional structures (e.g., modality and tense) into continuous representations. Consequently, a reconciliation emerges between `meaning as reference' and `meaning as use' while retaining computational tractability. Five fundamental results follow: (1) a delineation and classification of mathematical linguistics as distinct from yet complementary to compututational linguistics, itself distinct yet complementary to natural language processing; (2) a categorical framework organizing extensional and intensional models under a cohesive theoretical structure, such that semantic representation and processing remain modular and order-independent; (3) proofs of structure-preserving homomorphisms between formal and distributional semantics, demonstrating compatibility between symbolic and sub-symbolic approaches while maintaining compositionality and logical dependencies, subject to certain limitations; (4) a generalized vector logic compatible with compositionality that respects the representation of logical operators within distributional spaces; (5) a generalized grounding problem and proposed heuristic for identifying grounding problems, with which we show that neurosymbolic semantics is, indeed, grounded. These results show that logical and relational reasoning, though distinct cognitive processes, are mathematically compatible, albeit at the cost of linearity. This research establishes a linguistically grounded and cognitively plausible foundation for investigating reasoning and semantic representation in human and machine language processing, framed as a possible solution to the symbol grounding problem in neurosymbolic artificial intelligence
THE RIGHT THING TO DO IF IT WERE POSSIBLE: THE TIRA DE SANTA CATARINA IXTEPEJI OF OAXACA, MEXICO AND VALUATIONS OF THE AUTHENTIC AND REAL IN THE AGE OF DIGITAL REPATRIATION
No full textThe Tira de Santa Catarina Ixtepeji is a post-conquest Indigenous Zapotec codex housed at the University of Wisconsin—Milwaukee’s (UWM) American Geographic Society Library (AGSL). The Tira is a Mexican pictographic manuscript that traces the ruling lineages of the Zapotec community of Santa Catarina Ixtepeji in the Sierra Juárez Region of Oaxaca that legitimized claims to land ownership and autonomy during the Spanish colonial period of Mexico. Utilizing Igor Kopytoff’s “cultural biography of things” methodology, this thesis traces the Tira across its existence from its creation in 1691, the Mexican Revolution (1911), sale to the American Geographic Society (1917), and rediscovery in the early 2010s to examine how ideas of authenticity, originality, and copies are produced in practice. Following the growing body of literature examining the colonial legacies of archival cataloging practices, I argue that the accessioning, cataloging, care, digitization, and digital repatriation of the Tira are not neutral acts. Instead, they are examples of individuals materializing through practice the presumed objective data of human history, that is, in practice, contextualized interpretation
Improving the Predictability of Heavy Precipitation Events during the Nowcast Period using Convolutional Neural Networks
No full textAccurate short-term forecasting of heavy rainfall remains a challenge in operational meteorology. This study develops a convolutional neural network (CNN) trained on Multi-Radar/Multi-Sensor (MRMS) data to predict the probability of exceeding 12.5 mm/hr and 25.0 mm/hr rainfall thresholds across the southeastern United States within a 1.5–3.5 hour window. The CNN utilized variables including shear, precipitation rate, reflectivity, and vertically integrated liquid. Validation against 2022 data showed moderate skill for the 12.5 mm/hr model, with a Probability of Detection of 0.568, False Alarm Ratio of 0.630, and Critical Success Index of 0.289. Case studies highlighted strong performance during organized convective events, often with performance scores exceeding operational numerical weather models, but noted challenges in disorganized setups. Model limitations were attributed partly to training data imbalance, favoring null events. Results suggest CNNs can provide useful probabilistic guidance for operational forecasting, though further improvements in data balance and feature selection are recommended