973 resultados para Socio-technical
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This paper reflects the changing notion of the Virtual University and its realization. We introduce an approach from the Sociology of Science and Technology (STS) which analyses the construction of the “student as a user” as seen through the “eyes of designers”. We ask how social relations are built into technological artefacts. In showing how socio-technical developments transcend sometimes contradict and various notions of “the student” we discuss difficulties and chances of bridging the gap between designers of e-learning-artefacts and its assumed addresses. (DIPF/Orig.)
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With global markets and global competition, pressures are placed on manufacturing organizations to compress order fulfillment times, meet delivery commitments consistently and also maintain efficiency in operations to address cost issues. This chapter argues for a process perspective on planning, scheduling and control that integrates organizational planning structures, information systems as well as human decision makers. The chapter begins with a reconsideration of the gap between theory and practice, in particular for classical scheduling theory and hierarchical production planning and control. A number of the key studies of industrial practice are then described and their implications noted. A recent model of scheduling practice derived from a detailed study of real businesses is described. Socio-technical concepts are then introduced and their implications for the design and management of planning, scheduling and control systems are discussed. The implications of adopting a process perspective are noted along with insights from knowledge management. An overview is presented of a methodology for the (re-)design of planning, scheduling and control systems that integrates organizational, system and human perspectives. The most important messages from the chapter are then summarized.
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Doutoramento em Estudos de Desenvolvimento
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This thesis studies how commercial practice is developing with artificial intelligence (AI) technologies and discusses some normative concepts in EU consumer law. The author analyses the phenomenon of 'algorithmic business', which defines the increasing use of data-driven AI in marketing organisations for the optimisation of a range of consumer-related tasks. The phenomenon is orienting business-consumer relations towards some general trends that influence power and behaviors of consumers. These developments are not taking place in a legal vacuum, but against the background of a normative system aimed at maintaining fairness and balance in market transactions. The author assesses current developments in commercial practices in the context of EU consumer law, which is specifically aimed at regulating commercial practices. The analysis is critical by design and without neglecting concrete practices tries to look at the big picture. The thesis consists of nine chapters divided in three thematic parts. The first part discusses the deployment of AI in marketing organisations, a brief history, the technical foundations, and their modes of integration in business organisations. In the second part, a selected number of socio-technical developments in commercial practice are analysed. The following are addressed: the monitoring and analysis of consumers’ behaviour based on data; the personalisation of commercial offers and customer experience; the use of information on consumers’ psychology and emotions, the mediation through marketing conversational applications. The third part assesses these developments in the context of EU consumer law and of the broader policy debate concerning consumer protection in the algorithmic society. In particular, two normative concepts underlying the EU fairness standard are analysed: manipulation, as a substantive regulatory standard that limits commercial behaviours in order to protect consumers’ informed and free choices and vulnerability, as a concept of social policy that portrays people who are more exposed to marketing practices.
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Social interactions have been the focus of social science research for a century, but their study has recently been revolutionized by novel data sources and by methods from computer science, network science, and complex systems science. The study of social interactions is crucial for understanding complex societal behaviours. Social interactions are naturally represented as networks, which have emerged as a unifying mathematical language to understand structural and dynamical aspects of socio-technical systems. Networks are, however, highly dimensional objects, especially when considering the scales of real-world systems and the need to model the temporal dimension. Hence the study of empirical data from social systems is challenging both from a conceptual and a computational standpoint. A possible approach to tackling such a challenge is to use dimensionality reduction techniques that represent network entities in a low-dimensional feature space, preserving some desired properties of the original data. Low-dimensional vector space representations, also known as network embeddings, have been extensively studied, also as a way to feed network data to machine learning algorithms. Network embeddings were initially developed for static networks and then extended to incorporate temporal network data. We focus on dimensionality reduction techniques for time-resolved social interaction data modelled as temporal networks. We introduce a novel embedding technique that models the temporal and structural similarities of events rather than nodes. Using empirical data on social interactions, we show that this representation captures information relevant for the study of dynamical processes unfolding over the network, such as epidemic spreading. We then turn to another large-scale dataset on social interactions: a popular Web-based crowdfunding platform. We show that tensor-based representations of the data and dimensionality reduction techniques such as tensor factorization allow us to uncover the structural and temporal aspects of the system and to relate them to geographic and temporal activity patterns.
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This thesis offers an exploration of impact and social investments for agricultural development projects in Sub-Saharan Africa. It does so through the case of SustAgric-Africa (SAA), a social enterprise that aims to lift smallholder farmers out of poverty through the promotion of sustainable farming and operates with capital provided by a variety of investors who are committed to pairing financial returns with social and environmental outcomes. The thesis sets off to answer the following research questions: What is the moral dimension that emerges in finance with the establishment of environmental and social criteria? What kind of arrangements do social and impact investments give origin to? Is it possible to talk about a ‘spirit of the gift’ in such arrangements? What happens when abstract and globalizing ideas around ‘impact’ hit the ground? Drawing from the STS and Actor-Network Theory, I look at the formation engendered by social and impact investments in terms of a socio-technical arrangement, and look at the movements of “objects” between the main actors in terms of circuits. In these processes ideas about ‘value’ and ‘values’ articulate in complex ways in the interplay of gift, debt and credit in the relationships among the three main categories of involved actors: investors, SAA, and the farmers. In the case of SAA, I contend that the ways abstract and globalising ideas about ‘impact’ hit the ground produce uncertain results and contribute to the reproduction of inequalities and unequal wealth distribution and accumulation, deepening ongoing processes of financialization. However, my ethnography also reveals how actors depicted as beneficiaries of impact and social policies and resources, far from being passive recipients of policies and resources, actually question and appropriate them, potentially unsettling the whole arrangement and the moral and ethical claims underpinning it.
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The advent of Bitcoin suggested a disintermediated economy in which Internet users can take part directly. The conceptual disruption brought about by this Internet of Money (IoM) mirrors the cross-industry impacts of blockchain and distributed ledger technologies (DLTs). While related instances of non-centralisation thwart regulatory efforts to establish accountability, in the financial domain further challenges arise from the presence in the IoM of two seemingly opposing traits: anonymity and transparency. Indeed, DLTs are often described as architecturally transparent, but the perceived level of anonymity of cryptocurrency transfers fuels fears of illicit exploitation. This is a primary concern for the framework to prevent money laundering and the financing of terrorism and proliferation (AML/CFT/CPF), and a top priority both globally and at the EU level. Nevertheless, the anonymous and transparent features of the IoM are far from clear-cut, and the same is true for its levels of disintermediation and non-centralisation. Almost fifteen years after the first Bitcoin transaction, the IoM today comprises a diverse set of socio-technical ecosystems. Building on an analysis of their phenomenology, this dissertation shows how there is more to their traits of anonymity and transparency than it may seem, and how these features range across a spectrum of combinations and degrees. In this context, trade-offs can be evaluated by referring to techno-legal benchmarks, established through socio-technical assessments grounded on teleological interpretation. Against this backdrop, this work provides framework-level recommendations for the EU to respond to the twofold nature of the IoM legitimately and effectively. The methodology cherishes the mutual interaction between regulation and technology when drafting regulation whose compliance can be eased by design. This approach mitigates the risk of overfitting in a fast-changing environment, while acknowledging specificities in compliance with the risk-based approach that sits at the core of the AML/CFT/CPF regime.
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The abundance of visual data and the push for robust AI are driving the need for automated visual sensemaking. Computer Vision (CV) faces growing demand for models that can discern not only what images "represent," but also what they "evoke." This is a demand for tools mimicking human perception at a high semantic level, categorizing images based on concepts like freedom, danger, or safety. However, automating this process is challenging due to entropy, scarcity, subjectivity, and ethical considerations. These challenges not only impact performance but also underscore the critical need for interoperability. This dissertation focuses on abstract concept-based (AC) image classification, guided by three technical principles: situated grounding, performance enhancement, and interpretability. We introduce ART-stract, a novel dataset of cultural images annotated with ACs, serving as the foundation for a series of experiments across four key domains: assessing the effectiveness of the end-to-end DL paradigm, exploring cognitive-inspired semantic intermediaries, incorporating cultural and commonsense aspects, and neuro-symbolic integration of sensory-perceptual data with cognitive-based knowledge. Our results demonstrate that integrating CV approaches with semantic technologies yields methods that surpass the current state of the art in AC image classification, outperforming the end-to-end deep vision paradigm. The results emphasize the role semantic technologies can play in developing both effective and interpretable systems, through the capturing, situating, and reasoning over knowledge related to visual data. Furthermore, this dissertation explores the complex interplay between technical and socio-technical factors. By merging technical expertise with an understanding of human and societal aspects, we advocate for responsible labeling and training practices in visual media. These insights and techniques not only advance efforts in CV and explainable artificial intelligence but also propel us toward an era of AI development that harmonizes technical prowess with deep awareness of its human and societal implications.
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Includes bibliography
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Incluye Bibliografía
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This study aims at assessing the socio-economic and environmental effects of different societal and human development scenarios and climate change in the water-scarce southern and eastern Mediterranean. The study develops a two-stage modelling methodology that includes an econometric analysis for the southern and eastern Mediterranean region as a whole and a detailed, integrated socioecological assessment focusing on Jordan, Syria and Morocco. The results show that water resources will be under increasing stress in future years. In spite of country differences, a future path of sustainable development is possible in the region. Water withdrawals could decrease, preserving renewable water resources and reversing the negative effects on agricultural production and rural society. This, however, requires a combination across the region of technical, managerial, economic, social and institutional changes that together foster a substantive structural change. A balanced implementation of water supply-enhancing and demand-management measures along with improved governance are key to attaining a cost-effective sustainable future in which economic growth, a population increase and trade expansion are compatible with the conservation of water resources.
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This report aims to identify, explain and detail the links and interactions in southern and eastern Mediterranean countries (SEMCs) between energy supply and demand and socio-economic development, as well as the potential role of energy supply and demand policies on both. Another related aim is to identify and analyse, in a quantitative and qualitative way, the changing role of energy (both demand and supply) in southern Mediterranean economies, focusing on its positive and negative impact on socio-economic development. This report investigates in particular: o The most important channels through which resource wealth can contribute to or hamper economic and social development in the analysed region; o Mechanisms and channels of relations between energy supply and demand policies and economic and social development. The burdens of energy subsidies and ‘oil syndrome’ are of particular relevance for the region. An integrated socio-economic development and energy policy scenario approach showing the potential benefits and synergies within countries and the region is developed in the final part of the report.
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The historiography dedicated to tourism has emphasised how some socio-economic evolutions such as urbanisation, mechanisation of transport or the advent of leisure time in society have supported pleasure trips and therefore the development of the hotel industry. On the contrary, the research has too often neglected or at least minimised the impact of the hotel sector on a region's development. This contribution seeks to fill this gap by analysing the Geneva Lake region, one of the most important birthplaces of the European tourism. In this space not much touched by the first industrial revolution, the hotel business has in fact played the role of an economic motor, stimulating investment and employment. This dynamism provoked a domino effect on several other sectors of the economy (industry, bulding sector, banking). To please their customers, the hoteliers have not only given impulses on housing modernisation, but also to the revitalisation of transport, energy and communication networks. The necessity to remain on the state-of-the-art of technical issues, with the concern of competitiveness, has called forth an acceleration of the technology transfer and stimulated the constitution of technical know-how.
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This paper describes certain findings of intonation and intensity study of emotive speech with the minimal use of signal processing algorithms. This study was based on six basic emotions and the neutral, elicited from 1660 English utterances obtained from the speech recordings of six Indian women. The correctness of the emotional content was verified through perceptual listening tests. Marked similarity was noted among pitch contours of like-worded, positive valence emotions, though no such similarity was observed among the four negative valence emotional expressions. The intensity patterns were also studied. The results of the study were validated using arbitrary television recordings for four emotions. The findings are useful to technical researchers, social psychologists and to the common man interested in the dynamics of vocal expression of emotions
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The present study examines the level of pure technical and scale efficiencies of cassava production system including its sub-processes (that is production and processing stages) of 278 cassava farmers/processors from three regions of Delta State, Nigeria by applying Two-Stage Data Envelopment Analysis (DEA) approach. Results reveal that pure technical efficiency (PTE) is significantly lower at the production stage 0.41 vs 0.55 for the processing stage, but scale efficiency (SE) is high at both stages (0.84 and 0.87), implying that productivity can be improved substantially by reallocation of resources and adjusting operation size. The socio-economic determinants exert differential impacts on PTE and SE at each stage. Overall, education, experience and main occupation as farmer significantly improve SE while subsistence pressure reduces it. Extension contact significantly improves SE at the processing stage but reduces PTE and SE overall. Inverse size-PTE and size-SE relationships exist in cassava production system. In other words, large/medium farms are technically and scale inefficient. Gender gap exists in performance. Male farmers are technically efficient at processing stage but scale inefficient overall. Farmers in northern region are technically efficient. Investments in education, extension services and infrastructure are suggested as policy options to improve the cassava sector in Nigeria.