5,734 research outputs found

    Urban Renewal as Violence: Documenting the Erasure of Wooster Square

    Get PDF
    In American urban development, a defining period known as the urban renewal era took place in the decades after the Second World War. Many cities in the United States experienced a new interest in addressing urban decay; laws such as the 1949 Housing Act facilitated the movement. Municipalities had the capability to demolish areas that they labelled as ‘slums’ or ‘blighted’ in order to build new, attractive urban fabric and infrastructure. Although perhaps rooted in an optimistic and utopian vision of the future city, urban renewal projects had significant flaws—namely that the areas targeted for demolition disproportionately belonged to marginalized communities. In New Haven, Connecticut, the historic neighbourhood of Wooster Square was subject to an urban renewal scheme that included both rehabilitation of existing buildings, and complete redevelopment. Further, a new Interstate highway was situated through the centre of the neighbourhood, designed to sever Wooster Square into two distinct areas. This thesis explores the motivations and impact of Wooster Square’s renewal, both on the urban fabric itself, as well as on the neighbourhood’s Italian, immigrant and working class community. Through a series of ten illustrations that draw knowledge from archival sources such as photographs and oral histories, the thesis visualizes Wooster Square before and after renewal. In doing so, the thesis documents the destructive nature of the urban renewal approach and the violence that it inflicted on one of New Haven’s most marginalized groups

    Delivering low carbon energy service demands: A UK case study: An examination of Local Authority level energy consumption and the potential for a disaggregated approach to energy demand reduction

    Get PDF
    Alongside decarbonising energy supply and greenhouse gas removal, energy demand reduction is expected to contribute significantly towards the achievement of the UK’s long-term climate goals. Many emission scenarios include ambitious improvements in energy efficiency, however, relying largely upon energy efficiency to deliver the level of energy demand reduction required for a 1.5°C future is considered a high risk strategy for demand-side mitigation. The thesis has highlighted the role that local authorities can assume in the demand-side transition, through subsidiarity, and framed analysis around the concept of energy service demands. Using this broader framing of energy demand reduction, the current direct and embodied energy demand associated with delivering Great Britain’s household energy service demands was modelled. Four universal energy demand reduction strategies which considered consumption-based policy options for energy demand reduction were also modelled, and capacity index scores for each local authority were calculated to assess whether universal energy demand reduction strategies would be equitable, and effective at reducing Great Britain’s level of energy consumption in line with the levels required for a 1.5°C future. This project found that energy service demands vary across Great Britain, driven primarily by heating and personal transport energy service demands, with households in London having the lowest energy service demands per capita across the majority of energy service categories. The energy demand reduction strategies demonstrate that energy consumption associated with household energy service demands can be significantly reduced while maintaining service levels and therefore not compromising wellbeing, however reduced service levels, and their associated energy demand reduction, need to be considered if Great Britain’s energy consumption is to be reduced to levels which align with estimates of the energy demand reduction required for a 1.5°C future. Finally, assessing the energy service demand and energy demand reduction results in the context of the capacity index scores showed that universal approaches to energy demand reduction which do not consider local context would not lead to an equitable demand-side transition, and that subsidiarity must play a larger role in energy demand reduction going forward

    The Trinity Reporter, Winter 2023

    Get PDF
    Alumni magazine for Trinity College, Hartford, CThttps://digitalrepository.trincoll.edu/reporter/2181/thumbnail.jp

    Sounding Chinese: Tracing the Voice of Early 20th Century to Present day Transnational Chinese

    Full text link
    Accent, that is differences heard in pronunciations, specifically the speech sound that identifies Chineseness is the departure point for this research into the construction of the identity of transnational Chinese. This question also frames pronounce, Meddling English, Oh Canada! and the six volumes of a project The Phrase Book of Migrant Sounds. The genesis of The Phrase Books of Migrant Sounds lies in phrase books written in the late-19th and early-20th centuries for migrants to North America. Of great interest is not only the fact that English phrases were translated into languages spoken in the southern parts of China (for example Toisanese and Cantonese) but that English words and phrases were transcribed using their corresponding pronunciations. These phrase books helped them articulate words of a language they had not heard before, the unfamiliar sounds made familiar, the alien brought closer to home. The research employs knowledge from an array of disciplines—cultural studies, sociolinguistics and anthropology to name a few—as well as archived sound recordings of late-19th century and contemporary transnational Chinese to map a sound history of transnational Chinese. It considers the experiences of those who call multiple places ‘home’ to challenge the singularity of transnational Chinese identity and to suggest that, rather than being monolithic, transnational Chinese identity is pluricentric and multiphonic. The thesis affords a link between one’s sense of identities, however changing though they are, with political, cultural and social experiences. My practice-based research Sounding Chinese: Tracing the Voice of Early 20th to 21st Century Transnational Chinese looks at how transnationals—those who call more than one place home and who modify the way they speak accordingly— conceptualize themselves

    New Approach for Market Intelligence Using Artificial and Computational Intelligence

    Get PDF
    Small and medium sized retailers are central to the private sector and a vital contributor to economic growth, but often they face enormous challenges in unleashing their full potential. Financial pitfalls, lack of adequate access to markets, and difficulties in exploiting technology have prevented them from achieving optimal productivity. Market Intelligence (MI) is the knowledge extracted from numerous internal and external data sources, aimed at providing a holistic view of the state of the market and influence marketing related decision-making processes in real-time. A related, burgeoning phenomenon and crucial topic in the field of marketing is Artificial Intelligence (AI) that entails fundamental changes to the skillssets marketers require. A vast amount of knowledge is stored in retailers’ point-of-sales databases. The format of this data often makes the knowledge they store hard to access and identify. As a powerful AI technique, Association Rules Mining helps to identify frequently associated patterns stored in large databases to predict customers’ shopping journeys. Consequently, the method has emerged as the key driver of cross-selling and upselling in the retail industry. At the core of this approach is the Market Basket Analysis that captures knowledge from heterogeneous customer shopping patterns and examines the effects of marketing initiatives. Apriori, that enumerates frequent itemsets purchased together (as market baskets), is the central algorithm in the analysis process. Problems occur, as Apriori lacks computational speed and has weaknesses in providing intelligent decision support. With the growth of simultaneous database scans, the computation cost increases and results in dramatically decreasing performance. Moreover, there are shortages in decision support, especially in the methods of finding rarely occurring events and identifying the brand trending popularity before it peaks. As the objective of this research is to find intelligent ways to assist small and medium sized retailers grow with MI strategy, we demonstrate the effects of AI, with algorithms in data preprocessing, market segmentation, and finding market trends. We show with a sales database of a small, local retailer how our Åbo algorithm increases mining performance and intelligence, as well as how it helps to extract valuable marketing insights to assess demand dynamics and product popularity trends. We also show how this results in commercial advantage and tangible return on investment. Additionally, an enhanced normal distribution method assists data pre-processing and helps to explore different types of potential anomalies.Små och medelstora detaljhandlare är centrala aktörer i den privata sektorn och bidrar starkt till den ekonomiska tillväxten, men de möter ofta enorma utmaningar i att uppnå sin fulla potential. Finansiella svårigheter, brist på marknadstillträde och svårigheter att utnyttja teknologi har ofta hindrat dem från att nå optimal produktivitet. Marknadsintelligens (MI) består av kunskap som samlats in från olika interna externa källor av data och som syftar till att erbjuda en helhetssyn av marknadsläget samt möjliggöra beslutsfattande i realtid. Ett relaterat och växande fenomen, samt ett viktigt tema inom marknadsföring är artificiell intelligens (AI) som ställer nya krav på marknadsförarnas färdigheter. Enorma mängder kunskap finns sparade i databaser av transaktioner samlade från detaljhandlarnas försäljningsplatser. Ändå är formatet på dessa data ofta sådant att det inte är lätt att tillgå och utnyttja kunskapen. Som AI-verktyg erbjuder affinitetsanalys en effektiv teknik för att identifiera upprepade mönster som statistiska associationer i data lagrade i stora försäljningsdatabaser. De hittade mönstren kan sedan utnyttjas som regler som förutser kundernas köpbeteende. I detaljhandel har affinitetsanalys blivit en nyckelfaktor bakom kors- och uppförsäljning. Som den centrala metoden i denna process fungerar marknadskorgsanalys som fångar upp kunskap från de heterogena köpbeteendena i data och hjälper till att utreda hur effektiva marknadsföringsplaner är. Apriori, som räknar upp de vanligt förekommande produktkombinationerna som köps tillsammans (marknadskorgen), är den centrala algoritmen i analysprocessen. Trots detta har Apriori brister som algoritm gällande låg beräkningshastighet och svag intelligens. När antalet parallella databassökningar stiger, ökar också beräkningskostnaden, vilket har negativa effekter på prestanda. Dessutom finns det brister i beslutstödet, speciellt gällande metoder att hitta sällan förekommande produktkombinationer, och i att identifiera ökande popularitet av varumärken från trenddata och utnyttja det innan det når sin höjdpunkt. Eftersom målet för denna forskning är att hjälpa små och medelstora detaljhandlare att växa med hjälp av MI-strategier, demonstreras effekter av AI med hjälp av algoritmer i förberedelsen av data, marknadssegmentering och trendanalys. Med hjälp av försäljningsdata från en liten, lokal detaljhandlare visar vi hur Åbo-algoritmen ökar prestanda och intelligens i datautvinningsprocessen och hjälper till att avslöja värdefulla insikter för marknadsföring, framför allt gällande dynamiken i efterfrågan och trender i populariteten av produkterna. Ytterligare visas hur detta resulterar i kommersiella fördelar och konkret avkastning på investering. Dessutom hjälper den utvidgade normalfördelningsmetoden i förberedelsen av data och med att hitta olika slags anomalier

    Smart contract and web DApp for traceability in the olive oil production chain

    Get PDF
    Mestrado em Engenharia Informática na Escola Superior de Tecnologia e Gestão do Instituto Politécnico de Viana do CasteloNowadays, as people become more health-conscious, adopting a healthy and balanced diet has become increasingly important for a better quality of life. A good diet not only helps to prevent and fight diseases, but also contributes to overall well-being. At the same time, consumers are concerned about climate change and the sustainability of the planet. Consequently, consumers are paying more attention to the food they consume, seeking products that offer nutritional value and sustainability rather than just brand recognition. Portugal is one of the largest olive oil producers in the world, and olive oil is a fundamental component of the Mediterranean diet. The nutritional value of olive oil is directly linked to every stage of the product's value chain, from cultivation to consumption. To ensure that consumers have access to reliable and accurate information about the quality of the olive oil they purchase, it is important to establish traceability in the production chain. By doing so, consumer confidence can be consolidated. This study focuses on traceability in the olive oil production chain, as well as social and environmental sustainability indicators and quality indicators. The goal is to create a solution that utilizes Blockchain technology and Smart Contracts to enable more reliable and transparent information about olive oil production and quality to be easily accessible to consumers. This case study is important because it highlights the need for greater transparency in the food production chain, as well as the benefits of utilizing new technologies like Blockchain to improve transparency and trace ability. It also demonstrates the significance of sustainability in the production of food products, and how it can impact both the environment and consumer health.Hoje em dia, à medida que as pessoas se tornam mais conscientes sobre a saúde, a adopção de uma dieta saudável e equilibrada tornou-se cada vez mais importante para uma melhor qualidade de vida. Uma boa dieta não só ajuda a prevenir e combater doenças, como também contribui para o bem-estar geral. Consequentemente, os consumidores estão a prestar mais atenção aos alimentos que consomem, procurando produtos que ofereçam valor nutricional e sustentabilidade e não apenas o reconhecimento da marca. Portugal é um dos maiores produtores de azeite do mundo, e o azeite é uma componente fundamental da dieta mediterranica O valor nutricional do azeite está directamente ligado a todas as fases da cadeia de valor do produto, desde o cultivo até ao consumo. Para garantir que os consumidores tenham acesso a informação fiável e precisa sobre a qual- idade do azeite que adquirem, é importante estabelecer a rastreabilidade na cadeia de produção. Ao fazê-lo, a confiança dos consumidores pode ser consolidada. Este estudo centra-se na rastreabilidade na cadeia de produção do azeite, bem como nos indicadores de sustentabilidade social e ambiental e nos indicadores de qualidade. O objectivo é criar uma solução que utilize a tecnologia Blockchain e Smart Contracts para permitir que informações mais fiáveis e transparentes sobre a produção e qualidade do azeite sejam facilmente acessíveis aos consumidores Este caso de estudo é importante porque sublinha a necessidade de maior transparência na cadeia da valor da produção alimentar, bem como os benefícios de utilizar novas tecnologias como a Blockchain para melhorar a transparência e a rastreabilidade. Também demonstra a importância da sustentabilidade na produção de produtos alimentares, e como pode ter impacto tanto no ambiente como na saúde dos consumidores
    corecore