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- Dodig-Crnkovic, Gordana, 1955
(författare)
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Cognition as Morphological/Morphogenetic Embodied Computation In Vivo
- 2022
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Ingår i: Entropy. - : MDPI AG. - 1099-4300. ; 24
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Tidskriftsartikel (refereegranskat)abstract
- Cognition, historically considered uniquely human capacity, has been recently found to be the ability of all living organisms, from single cells and up. This study approaches cognition from an info-computational stance, in which structures in nature are seen as information, and processes (information dynamics) are seen as computation, from the perspective of a cognizing agent. Cognition is understood as a network of concurrent morphological/morphogenetic computations unfolding as a result of self-assembly, self-organization, and autopoiesis of physical, chemical, and biological agents. The present-day human-centric view of cognition still prevailing in major encyclopedias has a variety of open problems. This article considers recent research about morphological computation, morphogenesis, agency, basal cognition, extended evolutionary synthesis, free energy principle, cognition as Bayesian learning, active inference, and related topics, offering new theoretical and practical perspectives on problems inherent to the old computationalist cognitive models which were based on abstract symbol processing, and unaware of actual physical constraints and affordances of the embodiment of cognizing agents. A better understanding of cognition is centrally important for future artificial intelligence, robotics, medicine, and related fields.
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| 2. |
- Dodig Crnkovic, Gordana, 1955
(författare)
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Morphological Computing in Cognitive Systems, Connecting Data to Intelligent Agency
- 2020
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Ingår i: Proceedings (MDPI). - Basel Switzerland : MDPI. - 2504-3900. ; 47:1
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Tidskriftsartikel (refereegranskat)abstract
- According to the currently dominant view, cognitive science is a study of mind and intelligence focused on computational models of knowledge in humans. It is described in terms of symbol manipulation over formal language. This approach is connected with a variety of unsolvable problems, as pointed out by Thagard. In this paper, I argue that the main reason for the inadequacy of the traditional view of cognition is that it detaches the body of a human as the cognizing agent from the higher-level abstract knowledge generation. It neglects the dynamical aspects of cognitive processes, emotions, consciousness, and social aspects of cognition. It is also uninterested in other cognizing agents such as other living beings or intelligent machines. Contrary to the traditional computationalism in cognitive science, the morphological computation approach offers a framework that connects low-level with high-level approaches to cognition, capable of meeting challenges listed by Thagard. To establish this connection, morphological computation generalizes the idea of computation from symbol manipulation to natural/physical computation and the idea of cognition from the exclusively human capacity to the capacity of all goal-directed adaptive self-reflective systems, living organisms as well as robots. Cognition is modeled as a layered process, where at the lowest level, systems acquire data from the environment, which in combination with the already stored data in the morphology of an agent, presents the basis for further structuring and self-organization of data into information and knowledge.
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| 3. |
- Dodig Crnkovic, Gordana, 1955, et al.
(författare)
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Recent books delineating the emergent academic filed of the Study of Information
- 2020
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Ingår i: Proceedings (MDPI). - Basel Switzerland : MDPI. - 2504-3900. ; 47:1
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Tidskriftsartikel (refereegranskat)abstract
- One of the imperative tasks of theoretical information studies is exploration of methods and techniques of presentation of information. In this article, we study the presentation of information in the following three books describing the results of the collaboration of researchers with the goal of defining the emergent filed of the Study of Information: Philosophy and Methodology of Information: The Study of Information in a Transdisciplinary Perspective (2019), Theoretical Information Studies: Information in the World (2020) and Information and Computation (2011), published by World Scientific Publishing Co. Series in Information Studies.
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| 4. |
- Hailong, Li, et al.
(författare)
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Impacts of impurities in CO2-fluids on CO2 transport process
- 2006
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Ingår i: Proceedings of the ASME Turbo Expo. - 0791842398 - 9780791842393 ; , s. 367-375
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Konferensbidrag (refereegranskat)abstract
- There are four possible transportation means that could be used to deliver CO2: motor carriers, railway carriers, water carriers, and pipeline. The impurities in CO2-fluids have significant impacts on the thermodynamic properties that will further affect the design, operation and cost of CO2 transport. This paper focuses on how impurities in CO 2-fluids affect thermodynamic properties, and how the changes of properties affect CO2 transport process. Vapor-liquid equilibrium (VLB), critical point and densities are essential thermodynamic properties for designing a CO2 transport process. Studies on these properties will be carried out for CO2-mixtures based on the combinations of the common impurities such as SO2, H2S, CH4, Ar, O2 and N2. Moreover with a real case of pipeline for CO2 transport, the impact of impurities on transport process will be demonstrated in more details.
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| 5. |
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| 6. |
- Jansson, Fredrik, et al.
(författare)
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Democratic revolutions as institutional innovation diffusion : rapid adoption and survival of democracy
- 2013
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Ingår i: Technological forecasting & social change. - New York : Elsevier BV. - 0040-1625 .- 1873-5509. ; 80:8, s. 1546-1556
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Tidskriftsartikel (refereegranskat)abstract
- Recent ‘democratic revolutions’ in Islamic countries call for a re-consideration of transitions to and from democracy. Transitions to democracy have often been considered the outcome of socio-economic modernization and therefore slow and incremental processes. But as a recent study has made clear, in the last century, transitions to democracy have mainly occurred through rapid leaps rather than slow and incremental steps. Here, we therefore apply an innovation and systems perspective and consider transitions to democracy as processes of institutional, and therefore systemic, innovation adoption. We show that transitions to democracy starting before 1900 lasted for an average of 50 years and a median of 56 years, while transitions originating later took an average of 4.6 years and a median of 1.7 years. However, our results indicate that the survival time of democratic regimes is longer in cases where the transition periods have also been longer, suggesting that patience paid in previous democratizations. We identify a critical ‘consolidation-preparing’ transition period of 12 years. Our results also show that in cases where the transitions have not been made directly from autocracy to democracy, there are no main institutional paths towards democracy. Instead, democracy seems reachable from a variety of directions. This is in line with the analogy of diffusion of innovations at the nation systems level, for which assumptions are that potential adopter systems may vary in susceptibility over time. The adoption of the institutions of democracy therefore corresponds to the adoption of a new political communications standard for a nation, in this case the innovation of involving in principle all adult citizens on an equal basis.
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| 9. |
- Li, Y., et al.
(författare)
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Effects of organic composition on the anaerobic biodegradability of food waste
- 2017
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Ingår i: Bioresource Technology. - : Elsevier Ltd. - 0960-8524 .- 1873-2976. ; 243, s. 836-845
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Tidskriftsartikel (refereegranskat)abstract
- This work investigated the influence of carbohydrates, proteins and lipids on the anaerobic digestion of food waste (FW) and the relationship between the parameters characterising digestion. Increasing the concentrations of proteins and lipids, and decreasing carbohydrate content in FW, led to high buffering capacity, reduction of proteins (52.7–65.0%) and lipids (57.4–88.2%), and methane production (385–627 mLCH4/g volatile solid), while achieving a short retention time. There were no significant correlations between the reduction of organics, hydrolysis rate constant (0.25–0.66 d−1) and composition of organics. Principal Component Analysis revealed that lipid, C, and N contents as well as the C/N ratio were the principal components for digestion. In addition, methane yield, the final concentrations of total ammonia nitrogen and free ammonia nitrogen, final pH values, and the reduction of proteins and lipids could be predicted by a second-order polynomial model, in terms of the protein and lipid weight fraction.
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| 10. |
- Lu, Liu, et al.
(författare)
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High-performance formaldehyde prediction for indoor air quality assessment using time series deep learning
- 2024
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Ingår i: Building Simulation. - : TSINGHUA UNIV PRESS. - 1996-3599 .- 1996-8744.
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Tidskriftsartikel (refereegranskat)abstract
- Indoor air pollution resulting from volatile organic compounds (VOCs), especially formaldehyde, is a significant health concern needed to predict indoor formaldehyde concentration (Cf) in green intelligent building design. This study develops a thermal and wet coupling calculation model of porous fabric to account for the migration of formaldehyde molecules in indoor air and cotton, silk, and polyester fabric with heat flux in Harbin, Beijing, Xi'an, Shanghai, Guangzhou, and Kunming, China. The time-by-time indoor dry-bulb temperature (T), relative humidity (RH), and Cf, obtained from verified simulations, were collated and used as input data for the long short-term memory (LSTM) of the deep learning model that predicts indoor multivariate time series Cf from the secondary source effects of indoor fabrics (adsorption and release of formaldehyde). The trained LSTM model can be used to predict multivariate time series Cf at other emission times and locations. The LSTM-based model also predicted Cf with mean absolute percentage error (MAPE), symmetric mean absolute percentage error (SMAPE), mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE) that fell within 10%, 10%, 0.5, 0.5, and 0.8, respectively. In addition, the characteristics of the input dataset, model parameters, the prediction accuracy of different indoor fabrics, and the uncertainty of the data set are analyzed. The results show that the prediction accuracy of single data set input is higher than that of temperature and humidity input, and the prediction accuracy of LSTM is better than recurrent neural network (RNN). The method's feasibility was established, and the study provides theoretical support for guiding indoor air pollution control measures and ensuring human health and safety.
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