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The eco-city and its core environmental dimension of sustainability: green energy technologies and their integration with data-driven smart solutions

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Energy Informatics 2020年第1期3卷 1-26页

作者： Bibri, Simon Elias Department of Computer Science The Norwegian University of Science and Technology Sem Saelands veie 9 NO–7491 Trondheim Norway Department of Architecture and Planning The Norwegian University of Science and Technology Alfred Getz vei 3 Sentralbygg 1 5th floor NO–7491 Trondheim Norway

Ecological urbanism is seen today as one of the keys towards unlocking the quest for a low-carbon or fossil fuel–free society. Global and local policies promote and advocate the eco–city as the most environmentally sound model of sustainable urbanism. It is argued that the eco–city strategies and solutions are expected to deliver positive outcomes in terms of minimal demand on energy resources and thus minimal environmental impacts. Moreover, it has recently been suggested that the eco-city needs to embrace and leverage what advanced ICT has to offer, particularly with regard to sustainable energy systems, so as to improve and advance its contribution to the goals of environmental sustainability. This paper examines how the eco–city especially its core environmental dimension is practiced and justified in urban planning and development with respect to sustainable energy systems and their integration with data-driven smart technologies at the district level. To illuminate this urban phenomenon accordingly, a descriptive case study is adopted as a qualitative research methodology where the empirical basis is formed by urban planning and development documents combined with secondary data and scientific literature. To provide a theoretical foundation and produce a rationale for this study, this paper first provides a state–of–the–art review of the field of ecological urbanism in terms of its foundations, models, strategies, research issues, as well as data–driven smart technological trends. This study shows that the Eco-city District of Stockholm Royal Seaport uses green energy and data-driven smart technologies as the key strategies and solutions for achieving the environmental objectives of sustainable development in terms of lowering energy consumption and mitigating pollution. This entails conserving and decreasing the demand for energy through renewable resources (i.e., sun, wind, and water), bio–fuelled Combined Heat Power system, large-scale smart grid system, en

关键词： Sustainable development

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A Comparative Study on Deep Learning Models for Stock Price Prediction 5

A Comparative Study on Deep Learning Models for Stock Price ...

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5th Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2024

作者： He, Zhexin Zhang, Huan Por, Lip Yee Chongqing College of Architecture and Technology Chongqing401331 China Chongqing Academy of Science and Technology Chongqing401123 China Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur50603 Malaysia

ISBN: (纸本)9781643685243

With the advancement of deep learning technology, researchers have begun employing deep neural network models such as LSTM, MLP, CNN, and GRU to tackle nonlinear prediction problems in stock markets. This study harnesses these deep learning models, including LSTM, MLP, CNN, and GRU, to investigate the nonlinear forecasting of stock market price indices. The experiment selects globally representative stock indices and, through analyzing short-term, mid-term, and long-term data, discovers that the GRU model demonstrates exceptional performance in both prediction accuracy and generalization capabilities. To further enhance precision, the research constructs a filtering ensemble decision-making system based on multiple GRU models. This strategy reduces the error by at least 0.3% in medium to long-term predictions, significantly outperforming a single standalone GRU model. Consequently, the GRU-filtered ensemble decision model has been empirically proven as an effective tool for predicting stock indices, not only broadening the methods available for stock market prediction but also deepening the understanding and application of the generalization abilities of deep learning models within financial markets. © 2024 The Authors.

关键词： Long short-term memory

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Face and Facial Expression Recognition from Real World Videos 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Qiang Ji Thomas B. Moeslund Kamal Nasrollahi Gang Hua

ISBN: (数字)9783319137377

ISBN: (纸本)9783319137360

This book constitutes the thoroughly refereed conference proceedings of the International Workshop on Face and Facial Expression Recognition from Real World Videos in conjunction with the 22nd International Conference on Pattern Recognition held in Stockholm, Sweden, in August 2014. The 11 revised full papers were carefully reviewed and selected from numerous submissions and cover topics such as Face Recognition, Face Alignment, Facial Expression Recognition and Facial Images.

关键词： computer Science, general

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The emerging data–driven Smart City and its innovative applied solutions for sustainability: the cases of London and Barcelona

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Energy Informatics 2020年第1期3卷 1-42页

作者： Bibri, Simon Elias Krogstie, John Department of Computer Science The Norwegian University of Science and Technology Sem Saelands veie 9 TrondheimNO–7491 Norway Department of Architecture and Planning The Norwegian University of Science and Technology Alfred Getz vei 3 Sentralbygg 1 5th floor TrondheimNO–7491 Norway

The big data revolution is heralding an era where instrumentation, datafication, and computation are increasingly pervading the very fabric of cities. Big data technologies have become essential to the functioning of cities. Consequently, urban processes and practices are becoming highly responsive to a form of data-driven urbanism that is the key mode of production for smart cities. Such form is increasingly being directed towards tackling the challenges of sustainability in the light of the escalating urbanization trend. This paper investigates how the emerging data-driven smart city is being practiced and justified in terms of the development and implementation of its innovative applied solutions for sustainability. To illuminate this new urban phenomenon, a descriptive case study is adopted as a qualitative research methodology to examine and compare London and Barcelona as the leading data-driven smart cities in Europe. This study shows that these cities have a high level of the development of applied data-driven technologies, but they slightly differ in the level of the implementation of such technologies in different city systems and domains with respect to sustainability areas. They also moderately differ in the degree of their readiness as to the availability and development level of the competences and infrastructure needed to generate, transmit, process, and analyze large masses of data to extract useful knowledge for enhanced decision making and deep insights pertaining to urban operational functioning, management, and planning in relation to sustainability. London takes the lead as regards the ICT infrastructure and data sources, whereas Barcelona has the best practices in the data-oriented competences, notably horizontal information platforms, operations centers, dashboards, training programs and educational institutes, innovation labs, research centers, and strategic planning offices. This research enhances the scholarly community’s current understand

关键词： Sustainable development

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Advances in Computational Intelligence 1

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丛书名： Lecture Notes in computer Science

1000年

作者： Ignacio Rojas Gonzalo Joya Joan Cabestany

ISBN: (数字)9783642386824

ISBN: (纸本)9783642386817

This two-volume set LNCS 7902 and 7903 constitutes the refereed proceedings of the 12th International Work-Conference on Artificial Neural Networks, IWANN 2013, held in Puerto de la Cruz, Tenerife, Spain, in June 2013. The 116 revised papers were carefully reviewed and selected from numerous submissions for presentation in two volumes. The papers explore sections on mathematical and theoretical methods in computational intelligence, neurocomputational formulations, learning and adaptation emulation of cognitive functions, bio-inspired systems and neuro-engineering, advanced topics in computational intelligence and applications.

关键词： Computational Biology/Bioinformatics Pattern Recognition Artificial Intelligence Data Mining and Knowledge Discovery Models and Principles Bioinformatics

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INSEE: An interconnection network simulation and evaluation environment

INSEE: An interconnection network simulation and evaluation ...

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11th International Euro-Par Conference, Euro-Par 2005

作者： Perez, Fco. Javier Ridruejo Miguel-Alonso, José University of the Basque Country Department of Computer Architecture and Technology P.O. Box 649 20080 San Sebastian Spain

In this paper we introduce INSEE, an environment to help in the design of interconnection networks for parallel computing systems. It contains two main modules: a system to generate traffic (TrGen) and a lightweight functional simulator (FSIN). Additionally, external tools can be integrated into the environment. Examples are SICOSYS (a sophisticated network simulator that provides accurate timing information) and SIMICS (a complete, detailed computer simulator). This environment has been used to conduct some studies of interest in the design of interconnection networks, such as the effect of head-of-line blocking in the injection queues of the network routers, the effects of the injection interface in network performance, and the characteristics of topologies with skewed wraparound links. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Interconnection networks

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Energy-consumption prediction of genetic programming algorithms using a fuzzy rule-based system 18

Energy-consumption prediction of genetic programming algorit...

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2018 Genetic and Evolutionary Computation Conference, GECCO 2018

作者： Chávez, F. Fdez De Vega, F. Díaz, J. García, J.A. Rodriguez, F.J. Castillo, P.A. Centro Universitario de Mérida Universidad de Extremadura Spain Department of Architecture and Computer Technology University of Granada Spain

ISBN: (纸本)9781450357647

Energy awareness has gained momentum over the last decade in the software industry, as well as in environmentally concious society. Thus, algorithm designers and programmers are paying increasing attention this issue, particularly when handheld devices are considered, given their battery-consuming characteristics. When we focus on Evolutionary Algorithms, few works have attempted to study the relationship between the main features of the algorithm, the problem to be solved and the underlying hardware where it runs. This work presents a preliminary analysis and modeling of energy consumption of EAs. We try to predict it by means of a fuzzy rule-based system, so that different devices are considered as well as a number of problems and Genetic Programming parameters. Experimental results performed show that the proposed model can predict energy consumption with very low error values. © 2018 Copyright held by the owner/author(s).

关键词： Genetic programming

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Sub-nanosecond synchronization accuracy for time-sensitive applications on industrial networks 30

Sub-nanosecond synchronization accuracy for time-sensitive a...

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30th European Frequency and Time Forum, EFTF 2016

作者： Gutiérrez-Rivas, José Luis Prados, César Díaz, Javier Department of Computer Architecture and Technology University of Granada Granada Spain GSI Helmholtz Centre for Heavy Ion Research Darmstadt Germany

ISBN: (纸本)9781509007202

White Rabbit (WR) is a technology born at CERN able to provide sub-nanosecond accuracy for time and frequency transfer using standard PTP and Synchronous Ethernet (SyncE). WR was designed to be the main time provider system for scientific infrastructures such as particle accelerators and colliders. This contribution proposes a change of approach for the WR PTP distribution to become a timing solution with strong focus on engineering frameworks, such as Smart Grid. This approach includes a new design following IEC 61850, where new developments make possible for WR devices to work as Transparent Clocks (TCs) instead of Boundary clocks (BCs) as in the case today. This maximizes the interoperability with other industrial devices and, at the same time, the utilization of TCs offers better synchronization results since PTP messages include the entire network delay considering all TCs as a unique fiber. Using TCs for time and data propagation also opens the doors to high-availability and fault tolerance features for mission-critical and time-sensitive applications. It supports the development of redundancy protocols, such as HSR or PRP to guarantee the delivery and reception of critical services such as timing and substation events (GOOSE, GSSE, SMV). Finally, P2P approach offers a better synchronization mechanism to avoid synchronization loss of middle nodes and also supports the development of redundancy protocols to make possible the migration of WR to industrial networks. © 2016 IEEE.

关键词： Synchronization

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A novel model for data-driven smart sustainable cities of the future: the institutional transformations required for balancing and advancing the three goals of sustainability

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Energy Informatics 2021年第1期4卷 1-37页

作者： Bibri, Simon Elias Department of Computer Science The Norwegian University of Science and Technology Sem Saelands veie 9 TrondheimNO 7491 Norway Department of Architecture and Planning The Norwegian University of Science and Technology Alfred Getz vei 3 Sentralbygg 1 5th floor TrondheimNO 7491 Norway

In recent years, it has become increasingly feasible to achieve important improvements of sustainability by integrating sustainable urbanism with smart urbanism thanks to the proven role and synergic potential of data-driven technologies. Indeed, the processes and practices of both of these approaches to urban planning and development are becoming highly responsive to a form of data-driven urbanism, giving rise to a new phenomenon known as "data-driven smart sustainable urbanism." Underlying this emerging approach is the idea of combining and integrating the strengths of sustainable cities and smart cities and harnessing the synergies of their strategies and solutions in ways that enable sustainable cities to optimize, enhance, and maintain their performance on the basis of the innovative data-driven technologies offered by smart cities. These strengths and synergies can be clearly demonstrated by combining the advantages of sustainable urbanism and smart urbanism. To enable such combination, major institutional transformations are required in terms of enhanced and new practices and competences. Based on case study research, this paper identifies, distills, and enumerates the key benefits, potentials, and opportunities of sustainable cities and smart cities with respect to the three dimensions of sustainability, as well as the key institutional transformations needed to support the balancing of these dimensions and to enable the introduction of data-driven technology and the adoption of applied data-driven solutions in city operational management and development planning. This paper is an integral part of a futures study that aims to analyze, investigate, and develop a novel model for data-driven smart sustainable cities of the future. I argue that the emerging data-driven technologies for sustainability as innovative niches are reconfiguring the socio-technical landscape of institutions, as well as providing insights to policymakers into pathways for strengthening

关键词： Sustainable development

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Environmentally data-driven smart sustainable cities: applied innovative solutions for energy efficiency, pollution reduction, and urban metabolism

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Energy Informatics 2020年第1期3卷 1-59页

The IoT and big data technologies have become essential to the functioning of both smart cities and sustainable cities, and thus, urban operational functioning and planning are becoming highly responsive to a form of data-driven urbanism. This offers the prospect of building models of smart sustainable cities functioning in real time from routinely sensed data. This in turn allows to monitor, understand, analyze, and plan such cities to improve their energy efficiency and environmental health in real time thanks to new urban intelligence functions as an advanced form of decision support. However, prior studies tend to deal largely with data-driven technologies and solutions in the realm of smart cities, mostly in relation to economic and social aspects, leaving important questions involving the underlying substantive and synergistic effects on environmental sustainability barely explored to date. These issues also apply to sustainable cities, especially eco-cities. Therefore, this paper investigates the potential and role of data-driven smart solutions in improving and advancing environmental sustainability in the context of smart cities as well as sustainable cities, under what can be labeled "environmentally data-driven smart sustainable cities." To illuminate this emerging urban phenomenon, a descriptive/illustrative case study is adopted as a qualitative research methodology§ to examine and compare Stockholm and Barcelona as the ecologically and technologically leading cities in Europe respectively. The results show that smart grids, smart meters, smart buildings, smart environmental monitoring, and smart urban metabolism are the main data-driven smart solutions applied for improving and advancing environmental sustainability in both eco-cities and smart cities. There is a clear synergy between such solutions in terms of their interaction or cooperation to produce combined effects greater than the sum of their separate effects—with respect to the environment. Th

关键词： Energy efficiency

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