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Sökning: hsv:(SAMHÄLLSVETENSKAP) > Chalmers tekniska högskola > Teknik

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  • Gren, Åsa, et al. (författare)
  • How smart is smart growth? : Examining the environmental validation behind city compaction
  • 2019
  • Ingår i: Ambio. - : Springer Netherlands. - 0044-7447 .- 1654-7209. ; 48:6, s. 580-589
  • Forskningsöversikt (refereegranskat)abstract
    • Smart growth (SG) is widely adopted by planners and policy makers as an environmentally friendly way of building cities. In this paper, we analyze the environmental validity of the SG-approach based on a review of the scientific literature. We found a lack of proof of environmental gains, in combination with a great inconsistency in the measurements of different SG attributes. We found that a surprisingly limited number of studies have actually examined the environmental rationales behind SG, with 34% of those studies displaying negative environmental outcomes of SG. Based on the insights from the review, we propose that research within this context must first be founded in more advanced and consistent knowledge of geographic and spatial analyses. Second, it needs to a greater degree be based on a system's understanding of urban processes. Third, it needs to aim at making cities more resilient, e.g., against climate-change effects.
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  • Kurdve, Martin, et al. (författare)
  • Can Social Sustainability Values be Incorporated in a Product Service System for Temporary Public Building Modules?
  • 2017
  • Ingår i: Procedia CIRP. - : Elsevier. - 2212-8271. ; 64, s. 193-198
  • Tidskriftsartikel (refereegranskat)abstract
    • The temporary constructions industry has cost efficiency and sustainability challenges that may require new innovative business models as well as product and processes. This paperaims to discuss how social sustainability services can be included in product service system (PSS)by investigating a case where employment is offered in distributed temporary building module manufacturing in the PSS context. The case has been evaluated against PSS literature. Recent reviews and literature on inclusion of social sustainability and PSS for buildings were used. It is concluded that the current concept fits basic definitions of PSS although it is not typical. The social value of employment is difficult to evaluate and inclusion in PSS needs further research. Design practice could be used to further develop the services in the studied concept. © 2017 The Authors.
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  • Mocholí Montañés, Rubén, 1990 (författare)
  • Emissions reduction and flexible operation of energy-intensive industrial processes and power plants
  • 2019
  • Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
    • Every year, the German Federal Ministry of Education and Research (BMBF) hosts the prestigious ”Green Talents – International Forum for High Potentials in Sustainable Development” to promote the international exchange of innovative green ideas. The award, under the patronage of Minister Anja Karliczek, honours young researchers each year. The winners come from numerous countries and scientific disciplines and are recognised for their outstanding achievements in making our societies more sustainable. Selected by a jury of German experts, the award winners are granted unique access to the country’s research community
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  • Femenias, Paula, 1966, et al. (författare)
  • Från omfattande till varsam renovering
  • 2019
  • Ingår i: Hållbar renovering ur ett helhetsperspektiv: En antologi från forskningsmiljön SIRen. - 9789188722652 ; , s. 47-54
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)
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  • Boyraz Baykas, Pinar, 1981 (författare)
  • Semantic Analysis of Driver Behavior by Data Fusion
  • 2020
  • Ingår i: Vehicles, Drivers, and Safety, Edited by: Huseyin Abut, Kazuya Takeda, Gerhard Schmidt and John H.L. Hansen, (Intelligent Vehicles and Transportation, 2). - 9783110666472
  • Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
    • Behavioral signal processing and data-fusion have been two important components of the analytical toolbox that is used to understand driver behavior and implement advanced driver assistance systems (ADAS). The recent need for quantitative analysis of driver behavior is now driven by a new revelation that incorporating human-like behavior and control strategies in the autonomous vehicles can increase their safety and acceptability in a mixed-fleet traffic environment. In addition to that, the overall safety and efficiency of the driver-vehicle system in a conditional or partial automation (Level 2–4) can be leveraged if the perception, cognition, and action capabilities of driver are enhanced based on driving-task or traffic-scenario. Motivated by this new interest, this work attempts to define a highlevel semantic analysis framework incorporating eye-motion, road-scene, and vehicle dynamics data. The study aims to identify general trends or patterns in driver behavior, especially concerning focus of attention (FoA), based on two categories: traffic scenario and complexity. To perform semantic analysis, open database from DR(eye)VE Project is used. First, the road-scene video and vehicle dynamics data are used together to obtain a complexity measure in addition to automatic recognition of the traffic-scenario. Next, the raw eye-movement data is processed to obtain gaze distribution maps and metrics. Then, a support vector machine (SVM) is trained using gaze metrics to infer the complexity level or the traffic-scenario. To obtain better separation between two classes (i.e., low vs high complexity or urban vs highway scenarios), the SVM is trained using Bayesian optimization. The results showed that based on the gaze distribution, it is possible to distinguish between urban and highway scenarios (85% accuracy), while this distinction between complexity levels can be even stronger (98% accuracy). The framework can be used as a high-level analysis and inference tool to discover behavioral characteristics of drivers and their relation to FoA patterns.
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  • Mathern, Alexandre, 1986, et al. (författare)
  • Sustainability-driven structural design using artificial intelligence
  • 2019
  • Ingår i: 20th Congress of IABSE, New York City 2019: The Evolving Metropolis - Report. ; , s. 1058-1065
  • Konferensbidrag (refereegranskat)abstract
    • The construction industry is responsible for a large share of the global environmental impact. The need for addressing sustainability and increased competition calls for the development of innovative design methods that include sustainability in a transparent way. The aim of this work is to propose a framework to use machine learning and artificial intelligence (AI) for structural design optimization based on sustainability and buildability criteria. AI opens up new possibilities to optimize and assess structures early in the planning and design stages. In that way, it is possible to decrease the negative and enhance the positive environmental, economic and social impacts and create a more time‐ and cost‐effective design process. The work is meant to serve as a first step toward the development of AI‐based methods in the construction industry, which can bring digitalization in the construction industry to a new level and create new services and business models.
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