2,671 research outputs found
UMSL Bulletin 2023-2024
The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp
Climate Change and Critical Agrarian Studies
Climate change is perhaps the greatest threat to humanity today and plays out as a cruel engine of myriad forms of injustice, violence and destruction. The effects of climate change from human-made emissions of greenhouse gases are devastating and accelerating; yet are uncertain and uneven both in terms of geography and socio-economic impacts. Emerging from the dynamics of capitalism since the industrial revolution — as well as industrialisation under state-led socialism — the consequences of climate change are especially profound for the countryside and its inhabitants. The book interrogates the narratives and strategies that frame climate change and examines the institutionalised responses in agrarian settings, highlighting what exclusions and inclusions result. It explores how different people — in relation to class and other co-constituted axes of social difference such as gender, race, ethnicity, age and occupation — are affected by climate change, as well as the climate adaptation and mitigation responses being implemented in rural areas. The book in turn explores how climate change – and the responses to it - affect processes of social differentiation, trajectories of accumulation and in turn agrarian politics. Finally, the book examines what strategies are required to confront climate change, and the underlying political-economic dynamics that cause it, reflecting on what this means for agrarian struggles across the world. The 26 chapters in this volume explore how the relationship between capitalism and climate change plays out in the rural world and, in particular, the way agrarian struggles connect with the huge challenge of climate change. Through a huge variety of case studies alongside more conceptual chapters, the book makes the often-missing connection between climate change and critical agrarian studies. The book argues that making the connection between climate and agrarian justice is crucial
Modern computing: Vision and challenges
Over the past six decades, the computing systems field has experienced significant transformations, profoundly impacting society with transformational developments, such as the Internet and the commodification of computing. Underpinned by technological advancements, computer systems, far from being static, have been continuously evolving and adapting to cover multifaceted societal niches. This has led to new paradigms such as cloud, fog, edge computing, and the Internet of Things (IoT), which offer fresh economic and creative opportunities. Nevertheless, this rapid change poses complex research challenges, especially in maximizing potential and enhancing functionality. As such, to maintain an economical level of performance that meets ever-tighter requirements, one must understand the drivers of new model emergence and expansion, and how contemporary challenges differ from past ones. To that end, this article investigates and assesses the factors influencing the evolution of computing systems, covering established systems and architectures as well as newer developments, such as serverless computing, quantum computing, and on-device AI on edge devices. Trends emerge when one traces technological trajectory, which includes the rapid obsolescence of frameworks due to business and technical constraints, a move towards specialized systems and models, and varying approaches to centralized and decentralized control. This comprehensive review of modern computing systems looks ahead to the future of research in the field, highlighting key challenges and emerging trends, and underscoring their importance in cost-effectively driving technological progress
Parámetros genéticos de los caracteres morfológicos lineales de la raza caprina murciano-granadina y sus relaciones con otros caracteres funcionales
Linear appraisal systems (LAS) are effective strategies for systematically collecting zoometric information from animal populations. Traditionally applied LAS in goats was developed considering the variability and scales found in highly selected breeds. Implementing LAS may reduce time, personnel, and resource needs when performing zoometric large-scale collection. Moreover, selection for zoometrics defines individuals’ productive longevity, endurance, enhanced productive abilities, and consequently, long-term profitability. As a result, traditional LAS may no longer cover the different contexts of goat breeds widespread throughout the world, and departures from normality may be indicative of the different stages of selection at which a certain population can be found. In the first study, an evaluation of the distribution and symmetry properties of twenty-eight zoometric traits was developed. After symmetry analysis was performed, the scale readjustment proposal suggested specific strategies should be implemented such as scale reduction of lower or upper levels, determination of a setup moment to evaluate and collect information from young (up to 2 years) and adult bucks (over 2 years), the addition of upper categories in males due to upper values in the scale being incorrectly clustered together. Thus, the particular analysis of each variable permits determining specific strategies for each trait and serve as a model for other breeds, either selected or in terms of selection. The aim of the second study was to propose a method to optimize and validate LAS in opposition to traditional measuring protocols routinely implemented in Murciano-Granadina goats. The data sample consisted of 41323 LAS and traditional measuring records, belonging to 22727 herdbook registered primipara does, 17111 multipara does, and 1485 bucks. Each record comprised information on 17 linear traits for primipara and multipara does, and 10 traits for bucks. All zoometric parameters were scored on a 9-points scale. Cronbach’s alpha values suggested a high internal consistency of the optimized variable panel. Model fit, variability explanation power, and predictive power (MSE, AIC/AICc, and BIC, respectively) suggested a model comprising zoometric LAS scores performed better than traditional zoometry. Optimization procedures result in reduced models able to capture variability for dairy-related zoometric traits without noticeable detrimental effects on model validity properties. The third study aimed to perform a particular analysis of each variable that permits determining specific strategies for each trait and serves as a model for other breeds. Among the strategies proposed are the reduction/readjustment of the levels in the scale as it happens for limb-related traits, the extension of the scale as it occurs in the stature of males, or the subdivision of the scale used in males into two categories, bucks younger than two years and bucks of two years old and older. Murciano- Granadina goat breed has drifted towards better dairy-linked conformation traits but without losing the grounds of the zoometric basis which confers it with enhanced adaptability to the environment. Hence, such strategies can help to achieve a better understanding of the momentum of selection for dairy-linked zoometric traits in Murciano-Granadina population and their future evolution to enhance the profitability and efficiency of breeding plans. The objective of the fourth study was to evaluate the progress of heritabilities of the traits comprising the linear appraisal system in the Murciano-Granadina breed during the complete decade from December 2011 to December 2021. The estimated values for heritability were obtained from multivariate analyzes using the BLUP methodology and MTDFREML software. For 2021 heritabilities, a simple animal model was applied to records collected from 22727 primiparous goats and 17111 multiparous goats belonging to 85 herds. The model included the linear and quadratic and linear components of the covariates age and days in milk, respectively. The fixed effects considered in the model were herd, reproductive status, calving month, and herd/year interaction. The animal was considered as a random effect. The variables studied included five characteristics related to structure and capacity, two traits related to dairy structure, six related to the mammary system, and three related to legs and feet. The heritabilities for structure and capacity characters progressed from 0.22 to 0.28 including non-convergent variables in June 2012 to values between 0.10 and 0.41 with all variables converging in June 2021. Heritabilities for dairy structure progressed from 0.18 with nonconvergent variables in 2011 to 0.17 to 0.25 in 2021. Heritabilities for mammary system traits progressed from 0.12 to 0, 27 with non-convergent variables in 2012 to between 0.10 and 0.41 in 2021. For legs and feet, heritabilities progressed from 0.16 to 0.17 with non-convergent variables to 0.09 a 0.22. Genetic progress is not only evident in heritability values, but there has been a notable reduction in the standard error of heritabilities from 0.1000 (0.080-0.120) to 0.000 (0.000-0.001) from 2011 to 2021. These results provide evidence of the enhancement in the effectiveness and precision of the linear qualification system applied during the past decade and its successful integration into the breeding program of the Murciano- Granadina breed. The fifth study estimates genetic and phenotypic parameters for zoometric/LAS traits in Murciano-Granadina goats, estimate genetic and phenotypic correlations among all traits, and to determine whether major area selection would be appropriate or if adaptability strategies may need to be followed. Heritability estimates for the zoometric/LAS traits were low to high, ranging from 0.09 to 0.43 and the accuracy of estimation has improved after decades rendering standard errors negligible. Scale inversion of specific traits may need to be performed before major areas selection strategies are implemented. Genetic and phenotypic correlations suggest that negative selection against thicker bones and higher rear insertion heights, indirectly results in the optimization of selection practices in the rest of the traits, especially of those in the structure and capacity and mammary system major areas. The integration and implementation of the strategies proposed within Murciano-Granadina breeding program maximize selection opportunities and the sustainable international competitiveness of the Murciano- Granadina goat in the dairy goat breed panorama. The objective of the sixth study was to develop a discriminant canonical analysis (DCA) tool that permits outlining the role of the individual haplotypes of each component of the casein complex (αS1, β, αS2, and κ-casein) on zoometrics/linear appraisal breeding values. The relationship of the predicted breeding value for 17 zoometric/Linear appraisal traits and αS1, β, αS2, and κ-casein genes haplotypic sequences was assessed. Results suggest that, although a lack of significant differences (P>0.05) was reported across the predictive breeding values of zoometric/linear appraisal traits for αS1, αS2 and κ casein, significant differences were found for β Casein (P0,05) en los valores de cría predichos de los rasgos de zoometría/calificación lineal para la αS1, αS2 y κ-caseína, se encontraron diferencias significativas para la β-caseína (P<0,05), respectivamente. La presencia de secuencias haplotípicas de β-caseína GAGACCCC, GGAACCCC, GGAACCTC, GGAATCTC, GGGACCCC, GGGATCTC y GGGGCCCC, vinculadas a combinaciones diferenciales de mayores cantidades de leche de mayor calidad en términos de su composición, también puede estar relacionada con una mayor valoración zoométrica/lineal de la predicción de los valores de cría. La selección debe realizarse con cuidado, dado que la consideración de animales aparentemente deseables que presentan la secuencia haplotípica GGGATCCC en el gen de la β- caseína, debido a sus valores genéticos predichos positivos para ciertos rasgos de zoometría/calificación lineal, como la altura de la inserción trasera, la calidad ósea , la inserción anterior, la profundidad de ubre, la vista lateral de patas traseras y la vista trasera de patas traseras pueden conducir a una selección indirecta frente al resto de rasgos de zoometría/calificación lineal y a su vez conducir a una selección ineficiente hacia un tipo morfotipo lechero óptimo en cabras Murciano-Granadina. Por el contrario, la consideración de animales que presentan la secuencia haplotípica GGAACCCC implica también considerar animales que aumentan el potencial genético para todos los rasgos de zoometría/calificación lineal, haciéndolos así recomendables como reproductores. La información derivada de los presentes análisis mejorará la selección de individuos reproductores que busquen un tipo lechero bastante deseable, a través de la determinación de las secuencias haplotípicas que presentan en el locus β-caseína. Todos estos estudios persiguen la obtención de un conocimiento más profundo de los caracteres morfológicos lineales de la raza caprina Murciano-Granadina y sus relaciones con otras características funcionales. Esto sienta las bases para estrategias de normalización y mejora de la capacidad productiva y el morfotipo lechero de la cabra Murciano-Granadina y ayudará a alcanzar su consolidación competitiva en el panorama caprino lechero internacional
UMSL Bulletin 2022-2023
The 2022-2023 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1087/thumbnail.jp
Adaptive Data-driven Optimization using Transfer Learning for Resilient, Energy-efficient, Resource-aware, and Secure Network Slicing in 5G-Advanced and 6G Wireless Systems
Title from PDF of title page, viewed January 31, 2023Dissertation advisor: Cory BeardVitaIncludes bibliographical references (pages 134-141)Dissertation (Ph.D)--Department of Computer Science and Electrical Engineering. University of Missouri--Kansas City, 20225G–Advanced is the next step in the evolution of the fifth–generation (5G) technology. It will introduce a new level of expanded capabilities beyond connections and enables a broader range of advanced applications and use cases. 5G–Advanced will support modern applications with greater mobility and high dependability. Artificial intelligence and Machine Learning will enhance network performance with spectral efficiency and energy savings enhancements.
This research established a framework to optimally control and manage an appropriate selection of network slices for incoming requests from diverse applications and services in Beyond 5G networks. The developed DeepSlice model is used to optimize the network and individual slice load efficiency across isolated slices and manage slice lifecycle in case of failure. The DeepSlice framework can predict the unknown connections by utilizing the learning from a developed deep-learning neural network model.
The research also addresses threats to the performance, availability, and robustness of B5G networks by proactively preventing and resolving threats. The study proposed a Secure5G framework for authentication, authorization, trust, and control for a network slicing architecture in 5G systems. The developed model prevents the 5G infrastructure from Distributed Denial of Service by analyzing incoming connections and learning from the developed model. The research demonstrates the preventive measure against volume attacks, flooding attacks, and masking (spoofing) attacks. This research builds the framework towards the zero trust objective (never trust, always verify, and verify continuously) that improves resilience.
Another fundamental difficulty for wireless network systems is providing a desirable user experience in various network conditions, such as those with varying network loads and bandwidth fluctuations. Mobile Network Operators have long battled unforeseen network traffic events. This research proposed ADAPTIVE6G to tackle the network load estimation problem using knowledge-inspired Transfer Learning by utilizing radio network Key Performance Indicators from network slices to understand and learn network load estimation problems. These algorithms enable Mobile Network Operators to optimally coordinate their computational tasks in stochastic and time-varying network states.
Energy efficiency is another significant KPI in tracking the sustainability of network slicing. Increasing traffic demands in 5G dramatically increase the energy consumption of mobile networks. This increase is unsustainable in terms of dollar cost and environmental impact. This research proposed an innovative ECO6G model to attain sustainability and energy efficiency. Research findings suggested that the developed model can reduce network energy costs without negatively impacting performance or end customer experience against the classical Machine Learning and Statistical driven models. The proposed model is validated against the industry-standardized energy efficiency definition, and operational expenditure savings are derived, showing significant cost savings to MNOs.Introduction -- A deep neural network framework towards a resilient, efficient, and secure network slicing in Beyond 5G Networks -- Adaptive resource management techniques for network slicing in Beyond 5G networks using transfer learning -- Energy and cost analysis for network slicing deployment in Beyond 5G networks -- Conclusion and future scop
Quality of experience and access network traffic management of HTTP adaptive video streaming
The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.Die Doktorarbeit beschäftigt sich mit Quality of Experience (QoE) – der subjektiv empfundenen Dienstgüte – von adaptivem HTTP Videostreaming (HAS) und mit Verkehrsmanagement, das in Zugangsnetzwerken eingesetzt werden kann, um die QoE des adaptiven Videostreamings zu verbessern. Zuerst wurde der Einfluss von Adaptionsparameters und der Zeit pro Qualitätsstufe auf die QoE von adaptivem Videostreaming mittels subjektiver Crowdsourcingstudien untersucht. Die Ergebnisse wurden benutzt, um die QoE-optimale Adaptionsstrategie für gegebene Videos und Netzwerkbedingungen zu berechnen. Dies ermöglicht Dienstanbietern von Videostreaming verbesserte Adaptionsstrategien für adaptives Videostreaming zu entwerfen und zu benchmarken. Weiterhin untersuchte die Arbeit Konzepte zum Überwachen von QoE von Videostreaming in der Applikation und im Netzwerk, die von Netzwerkbetreibern im Kreislauf des QoE-bewussten Verkehrsmanagements eingesetzt werden können. Außerdem wurde eine analytische und simulative Leistungsbewertung von QoE-bewusstem Verkehrsmanagement auf einer Engpassverbindung durchgeführt. Schließlich untersuchte diese Arbeit sozialbewusstes Verkehrsmanagement für adaptives Videostreaming mittels WLAN Offloading, also dem Auslagern von mobilen Videoflüssen über WLAN Netzwerke. Es wurde ein Modell für die Verteilung von öffentlichen WLAN Zugangspunkte und eine Plattform für sozialbewusstes Verkehrsmanagement auf privaten, häuslichen WLAN Routern vorgestellt. Abschließend untersuchte eine simulative Leistungsbewertung den Einfluss von WLAN Offloading auf die QoE und den Energieverbrauch von mobilem adaptivem Videostreaming
- …