9,879 research outputs found
Southern Adventist University Undergraduate Catalog 2022-2023
Southern Adventist University\u27s undergraduate catalog for the academic year 2022-2023.https://knowledge.e.southern.edu/undergrad_catalog/1121/thumbnail.jp
2023-2024 Boise State University Undergraduate Catalog
This catalog is primarily for and directed at students. However, it serves many audiences, such as high school counselors, academic advisors, and the public. In this catalog you will find an overview of Boise State University and information on admission, registration, grades, tuition and fees, financial aid, housing, student services, and other important policies and procedures. However, most of this catalog is devoted to describing the various programs and courses offered at Boise State
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Can I Get a Witness?—Living While Black Death is Trending
It is not uncommon for graphic scenes of violence and death to infiltrate our timelinesfrom retweets, reposts, and shares. I often question how much control do we really have over the images that enter our feed? In what ways are we affected and influenced by these images? How do we relate to these images and video clips that are played and replayed before us? In what ways are these images evoking or are related to past scenes of racist violence? In what ways are these racially violent moments captured in photos and videos and shared online speaking to a Black consciousness?
This project comparatively researches and examines the relationship between past modes and methods of Black trauma curation in the past, to contemporary modes of dissemination on social media in order to argue that contemporary uses of spaces such as Instagram, Facebook, and Twitter serve as an extension of previous scrapbooking methods. By comparing The Emmet Till Generation and their curation of trauma via scrapbooks which were used to galvanize social movements, and impact organizing efforts of the youth, The Trayvon Generation today uses social media in a similar fashion; to bear witness, to organize, and to curate digital memorials for the dead. Witnessing is further extended and complicated on digital platforms, providing an abundance of visual evidence that has proven to be vital in leading tp prosecutions and arrests of violent state officials, and perpetrators of extrajudicial violence.
These live or recorded moments of witnessing are used not only as evidence, but to inform the public. However, we have always known that it’s always happening somewhere, even if we aren’t around to witness it. With that said, what are the effects of having the duty, and the responsibility to bear witness? Paying particular attention to Black youth, this project examines their presence and usage of social media spaces. By analyzing young Black people’s use of social media platforms in relation to Darnella Frazier’s strategic use Facebook, this project examines how Black youth and witnessing is currently driving a cultural shift in entertainment media that highlights witnessing death as a significant milestone for Black youth that marks the transition between childhood and adulthood. It is also impacting entertainment media that is not marketed towards Black people, further highlighting Black witnessing of racialized violence at the intersection of technology as both a contemporary and future issue through its inclusion in contemporary media.Witnessing for Black people is framed as being both necessary and traumatic.
This project concludes with an in depth examination of speculative media to reveal the implications of both the present and the future intersections of race relations, state violence and technology. Through analyses of interviews, image circulation and dissemination, magazine articles, social media platforms, visual and speculative media, this dissertation works to address and attempts to answer the aforementioned questions
Conceptualising the multifaceted nature of urban road congestion
Urban road congestion is not a new phenomenon and remains an outstanding problem that continues to impact people around the world. Road congestion costs the European Union an estimated 1-2% of GDP each year and is responsible for 27% of deadly C02 emissions. In addition, it can cause life-threatening delays in the emergency services response time.
Road congestion has a multifaceted nature and lacks a clear and explicit definition. This makes the problem of tackling it very subjective, time and context dependent. There have been several approaches to both modelling and predicting road congestion. From a physical perspective, road congestion has been modelled using speed, capacity, velocity, and journey time; relatively road congestion has been classified using terms such as non-recurrent and recurrent congestion which tend to be relative to each stakeholder; conceptual models such as the bathtub, traffic flow, and origin to the destination have been used to ascertain the impact of road congestion on a city scale.
This research presented tackles the problem of defining what is meant by congestion within an urban road network through defining a conceptual model that captures the semantics of road traffic congestion and its causes. The model is validated through the construction of a real-world dataset and the development of a visual tool which can be used to identify and alleviate congestion. The final stage of the project uses both the model and the dataset to investigate and implement a series of fuzzy systems to classify three types of congestion (non-recurrent, recurrent, and semi-recurrent). The fuzzy system results are then validated against human methods of classifying congestion.
The main contributions of this thesis to world knowledge can be summarised as follows: The design and development of a novel universal Urban Road Congestion Conceptual (URCC) model. The URCC model is broken down into two main components: Analogical conceptualisation which builds upon the famous ‘bathtub’ model and will integrate with other analogies to create ‘a raindrop hitting a leaf inside the bathtub with ever changing water temperatures’. The second component is an ontological approach to modelling congestion thus providing a better understanding for decision-makers through providing a formal and explicit explanation for concepts within the domain of urban road congestion. Another contribution is the development of a real-world spatiotemporal quasi-real-time big data dataset known as the Manchester Urban Congestion Data (MUCD) dataset which was used to validate the URCC. A visualisation graphical user interface called TIM (Transport Incident Manager) was developed with stakeholders TfGM (Transport for Greater Manchester). TIM has the ability to fill the void left by the clear lack of visualisation tools that are capable of visualising real-world big data datasets, such as the MUCD and models of urban road congestion. The final contribution to knowledge is the design and development of two fuzzy decision-making systems which are not only capable of predicting urban road congestion on a link but the type of congestion occurring on a network of links. Using a fuzzy decision-making system allows for explainable and interpretable decisions, and also provided useful and meaningful qualitative context back to the relevant TfGM stakeholders. The non-optimised multi-classification fuzzy system had slightly worst accuracy than the J48 decision tree algorithm, however, the fuzzy system is easier to interpret and provides meaningful context compared to the J48 algorithm due to only requiring 12 rules compared to the 1184 learned rules in the J48 decision tree. Furthermore, once the fuzzy system has been optimised (future work) it is likely to have similar if not better performance than the J48 decision tree
A Design Science Research Approach to Smart and Collaborative Urban Supply Networks
Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness.
A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense.
Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice
Differentiable and Transportable Structure Learning
Directed acyclic graphs (DAGs) encode a lot of information about a particular
distribution in their structure. However, compute required to infer these
structures is typically super-exponential in the number of variables, as
inference requires a sweep of a combinatorially large space of potential
structures. That is, until recent advances made it possible to search this
space using a differentiable metric, drastically reducing search time. While
this technique -- named NOTEARS -- is widely considered a seminal work in
DAG-discovery, it concedes an important property in favour of
differentiability: transportability. To be transportable, the structures
discovered on one dataset must apply to another dataset from the same domain.
We introduce D-Struct which recovers transportability in the discovered
structures through a novel architecture and loss function while remaining fully
differentiable. Because D-Struct remains differentiable, our method can be
easily adopted in existing differentiable architectures, as was previously done
with NOTEARS. In our experiments, we empirically validate D-Struct with respect
to edge accuracy and structural Hamming distance in a variety of settings.Comment: Accepted at the International Conference on Machine Learning (ICML)
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Ant-Balanced multiple traveling salesmen: ACO-BmTSP
A new algorithm based on the ant colony optimization (ACO) method for the multiple traveling salesman problem (mTSP) is presented and defined as ACO-BmTSP. This paper addresses the problem of solving the mTSP while considering several salesmen and keeping both the total travel cost at the minimum and the tours balanced. Eleven different problems with several variants were analyzed to validate the method. The 20 variants considered three to twenty salesmen regarding 11 to 783 cities. The results were compared with best-known solutions (BKSs) in the literature. Computational experiments showed that a total of eight final results were better than those of the BKSs, and the others were quite promising, showing that with few adaptations, it will be possible to obtain better results than those of the BKSs. Although the ACO metaheuristic does not guarantee that the best solution will be found, it is essential in problems with non-deterministic polynomial time complexity resolution or when used as an initial bound solution in an integer programming formulation. Computational experiments on a wide range of benchmark problems within an acceptable time limit showed that compared with four existing algorithms, the proposed algorithm presented better results for several problems than the other algorithms did.info:eu-repo/semantics/publishedVersio
DIN Spec 91345 RAMI 4.0 compliant data pipelining: An approach to support data understanding and data acquisition in smart manufacturing environments
Today, data scientists in the manufacturing domain are confronted with a set of challenges associated to data acquisition as well as data processing including the extraction of valuable in-formation to support both, the work of the manufacturing equipment as well as the manufacturing processes behind it.
One essential aspect related to data acquisition is the pipelining, including various commu-nication standards, protocols and technologies to save and transfer heterogenous data. These circumstances make it hard to understand, find, access and extract data from the sources depend-ing on use cases and applications.
In order to support this data pipelining process, this thesis proposes the use of the semantic model. The selected semantic model should be able to describe smart manufacturing assets them-selves as well as to access their data along their life-cycle.
As a matter of fact, there are many research contributions in smart manufacturing, which already came out with reference architectures or standards for semantic-based meta data descrip-tion or asset classification. This research builds upon these outcomes and introduces a novel se-mantic model-based data pipelining approach using as a basis the Reference Architecture Model for Industry 4.0 (RAMI 4.0).Hoje em dia, os cientistas de dados no domÃnio da manufatura são confrontados com várias normas, protocolos e tecnologias de comunicação para gravar, processar e transferir vários tipos de dados. Estas circunstâncias tornam difÃcil compreender, encontrar, aceder e extrair dados necessários para aplicações dependentes de casos de utilização, desde os equipamentos aos respectivos processos de manufatura.
Um aspecto essencial poderia ser um processo de canalisação de dados incluindo vários normas de comunicação, protocolos e tecnologias para gravar e transferir dados. Uma solução para suporte deste processo, proposto por esta tese, é a aplicação de um modelo semântico que descreva os próprios recursos de manufactura inteligente e o acesso aos seus dados ao longo do seu ciclo de vida.
Muitas das contribuições de investigação em manufatura inteligente já produziram arquitecturas de referência como a RAMI 4.0 ou normas para a descrição semântica de meta dados ou classificação de recursos. Esta investigação baseia-se nestas fontes externas e introduz um novo modelo semântico baseado no Modelo de Arquitectura de Referência para Indústria 4.0 (RAMI 4.0), em conformidade com a abordagem de canalisação de dados no domÃnio da produção inteligente como caso exemplar de utilização para permitir uma fácil exploração, compreensão, descoberta, selecção e extracção de dados
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