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[EN] Recent trends in waste management have initiated interest in recycled materials for sound absorption applications. The present paper studies the possibility of paper sludge to be recycled as material for sound absorption applications. Paper sludge (PS) is the water treatment waste, produced during paper production. Two different methods were studied to produce paper sludge and slaked lime composite acoustic panels for sound absorption applications at low and mid-frequencies. The sound absorption coefficient of paper sludge composite panels is measured in an impedance tube using the two-microphone method. The samples produced with different methods showed different behaviours of sound absorption. The primary method to produce showed acoustic asymmetry in the vertical direction of the samples, and it was considerably fragile as well. An improved method to produce PS composite panels was proposed in this paper. Using this method, homogenous and robust acoustic panels were obtained.

[EN] Recent trends in waste management have initiated interest in recycled materials for sound absorption applications. The present paper studies the possibility of paper sludge to be recycled as material for sound absorption applications. Paper sludge (PS) is the water treatment waste, produced during paper production. Two different methods were studied to produce paper sludge and slaked lime composite acoustic panels for sound absorption applications at low and mid-frequencies. The sound absorption coefficient of paper sludge composite panels is measured in an impedance tube using the two-microphone method. The samples produced with different methods showed different behaviours of sound absorption. The primary method to produce showed acoustic asymmetry in the vertical direction of the samples, and it was considerably fragile as well. An improved method to produce PS composite panels was proposed in this paper. Using this method, homogenous and robust acoustic panels were obtained.

Various security weaknesses have been identified in mobile ad-hoc networks (MANET). The paper focuses on MANET forensics whereby a third party can prove there was attack by collecting and analyzing evidence about it.The paper describes such a MANET forensics analysis method using a Bloomfilter., Lecture Notes in Computer Science

This paper concerns the Routh reduction procedure for Lagrangians systems with symmetry. It differs from the existing results on geometric Routh reduction in the fact that no regularity conditions on either the Lagrangian L or the momentum map JL are required apart from the momentum being a regular value of JL. The main results of this paper are: the description of a general Routh reduction procedure that preserves the Euler-Lagrange nature of the original system and the presentation of a presymplectic framework for Routh reduced systems. In addition, we provide a detailed description and interpretation of the Euler-Lagrange equa-tions for the reduced system. The proposed procedure includes Lagrangian systems with a non-positively definite kinetic energy metric., Depto. de Álgebra, Geometría y Topología, Fac. de Ciencias Matemáticas, Instituto de Matemática Interdisciplinar (IMI), TRUE, pub

Participatory design has attracted attention as a design method in recent years. Scenario or Inclusive Design is one way to make users participate in the design process. In this paper, I report on some case studies in which the visually-impaired participated in the design process. The sighted designer worked together with the visually-impaired wearing eye masks. The visually-impaired could tell designers some problems in their lives or their demand which was difficult to express in words.

In this paper we have examined the effects of scenarios from a participatory design and cross-cultural perspective. The Scenario Exchange Project was an international workshop using scenarios. The participants were university students from Japan and Taiwan. The impetus behind this project was the practical demand for designers to correctly understand different cultures and design products and services. We confirmed that scenarios are effective techniques for bolstering participatory design. Furthermore, we have recognized that we must create new methods for describing the lifestyle and cultural background of personas.

Digital innovation is challenging the traditional way of ofering fnancial services to companies; the so-called Fintech phenomenon refers to startups that use the latest technologies to ofer innovative fnancial services. Within the framework of the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA), the primary pur pose of this paper is to develop a causal-predictive analysis of the relationship between Subjective Norms, Attitudes, and Perceived Behavioral Control with the Intention to Use and Behavioral Use of the Fintech services by companies. Partial Least Squares Structural Equation Modeling methodology was used with data collected from a sur vey of 300 companies. Our fndings support the TRA and TPB models and confrm their robustness in predicting companies’ intention and use of Fintech services. Financial technology innovators must understand the processes involved in users’ adoption to design sound strategies that increase the viability of their services. Studying the ante cedents of behavioral intention to adopt Fintech services can greatly help understand the pace of adoption, allowing these players to attract and retain customers better. This study contributes to the literature by formulating and validating TPB to predict Fintech adoption, and its fndings provide useful information for banks and Fintech companies and lead to an improvement in organizational performance management in formulat ing marketing strategies.

Digital innovation is challenging the traditional way of ofering fnancial services to companies; the so-called Fintech phenomenon refers to startups that use the latest technologies to ofer innovative fnancial services. Within the framework of the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA), the primary pur pose of this paper is to develop a causal-predictive analysis of the relationship between Subjective Norms, Attitudes, and Perceived Behavioral Control with the Intention to Use and Behavioral Use of the Fintech services by companies. Partial Least Squares Structural Equation Modeling methodology was used with data collected from a sur vey of 300 companies. Our fndings support the TRA and TPB models and confrm their robustness in predicting companies’ intention and use of Fintech services. Financial technology innovators must understand the processes involved in users’ adoption to design sound strategies that increase the viability of their services. Studying the ante cedents of behavioral intention to adopt Fintech services can greatly help understand the pace of adoption, allowing these players to attract and retain customers better. This study contributes to the literature by formulating and validating TPB to predict Fintech adoption, and its fndings provide useful information for banks and Fintech companies and lead to an improvement in organizational performance management in formulat ing marketing strategies.

Digital innovation is challenging the traditional way of ofering fnancial services to companies; the so-called Fintech phenomenon refers to startups that use the latest technologies to ofer innovative fnancial services. Within the framework of the Theory of Planned Behavior (TPB) and the Theory of Reasoned Action (TRA), the primary pur pose of this paper is to develop a causal-predictive analysis of the relationship between Subjective Norms, Attitudes, and Perceived Behavioral Control with the Intention to Use and Behavioral Use of the Fintech services by companies. Partial Least Squares Structural Equation Modeling methodology was used with data collected from a sur vey of 300 companies. Our fndings support the TRA and TPB models and confrm their robustness in predicting companies’ intention and use of Fintech services. Financial technology innovators must understand the processes involved in users’ adoption to design sound strategies that increase the viability of their services. Studying the ante cedents of behavioral intention to adopt Fintech services can greatly help understand the pace of adoption, allowing these players to attract and retain customers better. This study contributes to the literature by formulating and validating TPB to predict Fintech adoption, and its fndings provide useful information for banks and Fintech companies and lead to an improvement in organizational performance management in formulat ing marketing strategies.

© 2002 Springer-Verlag London Limited. Part of the work has been performed under project CICYT TAP94-0832-C02-01. The constructive recommendations provided by the reviewers are also gratefully acknowledged., The key step in stereovision is image matching. This is carried out on the basis of selecting features, edge points, edge segments, regions, corners, etc. Once the features have been selected, a set of attributes (properties) for matching is chosen. This is a key issue in stereovision matching. This paper presents an approach for attribute selection in stereovision matching tasks based on a Probabilistic Neural Network, which allows the computation of a mean vector and a covariance matrix from which the relative importance of attributes for matching and the attribute interdependence can be derived. This is possible because the matching problem focuses on a pattern classification problem. The performance of the method is verified with a set of stereovision images and the results contrasted with a classical attribute selection method and also with the relevance concept., CICYT, Sección Deptal. de Arquitectura de Computadores y Automática (Físicas), Fac. de Ciencias Físicas, TRUE, pub

Since Arrow's main theorem showed the impossibility of a rational procedure in group decision making, many variations in restrictions and objectives have been introduced in order to find out the limits of such a negative result. But so far all those results are often presented as a proof of the great expected difficulties we always shall find pursuing a joint group decision from different individual opinions, if we pursue rational and ethical procedures. In this paper we shall review some of the alternative approaches fuzzy sets theory allows, showing among other things that the main assumption of Arrow's model, not being made explicit in his famous theorem, was its underlying binary logic (a crisp definition is implied in preferences, consistency, liberty, equality, consensus and every concept or piece of information). Moreover, we shall also point out that focusing the problem on the choice issue can be also misleading, at least when dealing with human behaviour., Depto. de Estadística e Investigación Operativa, Fac. de Ciencias Matemáticas, TRUE, pub

Supervised classification in remote sensing is a very complex problem and involves steps of different nature, including a serious data preprocessing. The final objective can be stated in terms of a classification of isolated pixels between classes, which can be either previously known or not (for example, different land uses), but with no particular shape nither well defined borders. Hence, a fuzzy approach seems natural in order to capture the structure of the image. In this paper we stress that some useful tools for a fuzzy classification can be derived from fuzzy coloring procedures, to be extended in a second stage to the complete non visible spectrum. In fact, the image is considered here as a fuzzy graph defined on the set of pixels, taking advantage of fuzzy numbers in order to summarize information. A fuzzy model is then presented, to be considered as a decision making aid tool. In this way we generalize the classical definition of fuzzy partition due to Ruspini, allowing in addition a first evaluation of the quality of the classification in this way obtained, in terms of three basic indexes (measuring covering, relevance and overlapping of our family of classes)., Universidad Complutense, University of California, Depto. de Estadística e Investigación Operativa, Fac. de Ciencias Matemáticas, TRUE, pub

Mitigation activities, whether at the personal level relating to lifestyle or on the professional level, especially in the agriculture sector, are widely encouraged by scientists and policymakers. This research empirically analyses the association between agricultural experts’ perceptions about climate change and their intention to implement climate change mitigation. Based on survey data, individuals’ reported intention to implement personal and professional mitigation behavior is explained using a conceptual model. The structural equation modeling results suggest that the new ecological paradigm (NEP), institutional trust, and risk salience indirectly influence climate change mitigation intentions. The findings indicate that risk perception, personal efficacy, responsibility, belief in climate change occurring, and low psychological distance trigger a significantly greater intention to support personal and professional mitigation behaviors. However, the research framework is much stronger at predicting the intention to mitigate climate change in professional affairs compared to personal activities. The findings suggest that hypothetical distance factors only have a moderating effect on the relationship between higher climate change environmental values, institutional trust, risk salience, and mitigation intention. This paper analytically explores the regulating role of risk perception, hypothetical distance, personal efficacy, and responsibility between institutional trust, risk salience, and the NEP as independent concepts and intention to personal and professional mitigation behaviors as dependent variables. The findings of the study have important implications for encouraging personal and professional mitigation behaviors.

Mitigation activities, whether at the personal level relating to lifestyle or on the professional level, especially in the agriculture sector, are widely encouraged by scientists and policymakers. This research empirically analyses the association between agricultural experts’ perceptions about climate change and their intention to implement climate change mitigation. Based on survey data, individuals’ reported intention to implement personal and professional mitigation behavior is explained using a conceptual model. The structural equation modeling results suggest that the new ecological paradigm (NEP), institutional trust, and risk salience indirectly influence climate change mitigation intentions. The findings indicate that risk perception, personal efficacy, responsibility, belief in climate change occurring, and low psychological distance trigger a significantly greater intention to support personal and professional mitigation behaviors. However, the research framework is much stronger at predicting the intention to mitigate climate change in professional affairs compared to personal activities. The findings suggest that hypothetical distance factors only have a moderating effect on the relationship between higher climate change environmental values, institutional trust, risk salience, and mitigation intention. This paper analytically explores the regulating role of risk perception, hypothetical distance, personal efficacy, and responsibility between institutional trust, risk salience, and the NEP as independent concepts and intention to personal and professional mitigation behaviors as dependent variables. The findings of the study have important implications for encouraging personal and professional mitigation behaviors.

In this paper, we describe a novel approach to the prediction of human blood glucose levels by analysing rich biometric human contextual data from a pioneering lifelog dataset. Numerous prediction models (RF, SVM, XGBoost and Elastic-Net) along with different combinations of input attributes are compared. An efficient ensemble method of stacking of multiple combination of prediction models was also implemented as our contribution. It was found that XGBoost outperformed three other models and that a stacking ensemble method further improved the performance.

In this paper, we describe a novel approach to the prediction of human blood glucose levels by analysing rich biometric human contextual data from a pioneering lifelog dataset. Numerous prediction models (RF, SVM, XGBoost and Elastic-Net) along with different combinations of input attributes are compared. An efficient ensemble method of stacking of multiple combination of prediction models was also implemented as our contribution. It was found that XGBoost outperformed three other models and that a stacking ensemble method further improved the performance.

In this paper, we describe a novel approach to the prediction of human blood glucose levels by analysing rich biometric human contextual data from a pioneering lifelog dataset. Numerous prediction models (RF, SVM, XGBoost and Elastic-Net) along with different combinations of input attributes are compared. An efficient ensemble method of stacking of multiple combination of prediction models was also implemented as our contribution. It was found that XGBoost outperformed three other models and that a stacking ensemble method further improved the performance.

India has committed to reducing the emissions intensity of GDP by 33-35% from the 2005 level by 2030 in alignment with objectives of the Paris Agreement. This will require a significant reduction in greenhouse gas (GHG) emissions from the food and land-use sector. In this paper, we construct three potential pathways for India to achieve its emissions target by 2050 involving moderate ambitions of mitigation action (BAU), moderate ambitions combined with achieving healthy diets (BAU + NIN), and high levels of mitigation action inclusive of healthy diets (SUSTAINABLE). Using an integrated accounting tool, the FABLE Calculator, that harmonizes various socioeconomic and biophysical data, we project these pathways under the conditions of cross-country balanced trade flows. Results from the projections show that the demand for cereals will increase by 2050, leading to increased GHG emissions under BAU. Under the SUSTAINABLE pathways, GHG emissions will decrease over the same period due to reduced demand for cereals, whereas significant crop productivity and harvest intensity gains would lead to increased crop production. The exercise reveals the indispensability of healthy diets, improved crop, and livestock productivity, and net-zero deforestation in achieving India's mid-century emission targets from the agriculture sector.

India has committed to reducing the emissions intensity of GDP by 33-35% from the 2005 level by 2030 in alignment with objectives of the Paris Agreement. This will require a significant reduction in greenhouse gas (GHG) emissions from the food and land-use sector. In this paper, we construct three potential pathways for India to achieve its emissions target by 2050 involving moderate ambitions of mitigation action (BAU), moderate ambitions combined with achieving healthy diets (BAU + NIN), and high levels of mitigation action inclusive of healthy diets (SUSTAINABLE). Using an integrated accounting tool, the FABLE Calculator, that harmonizes various socioeconomic and biophysical data, we project these pathways under the conditions of cross-country balanced trade flows. Results from the projections show that the demand for cereals will increase by 2050, leading to increased GHG emissions under BAU. Under the SUSTAINABLE pathways, GHG emissions will decrease over the same period due to reduced demand for cereals, whereas significant crop productivity and harvest intensity gains would lead to increased crop production. The exercise reveals the indispensability of healthy diets, improved crop, and livestock productivity, and net-zero deforestation in achieving India's mid-century emission targets from the agriculture sector.

The KM3NeT research infrastructure is under construction in the Mediterranean Sea. KM3NeT will study atmospheric and astrophysical neutrinos with two multi-purpose neutrino detectors, ARCA and ORCA, primarily aimed at GeV–PeV neutrinos. Thanks to the multi-photomultiplier tube design of the digital optical modules, KM3NeT is capable of detecting the neutrino burst from a Galactic or near-Galactic core-collapse supernova. This potential is already exploitable with the first detection units deployed in the sea. This paper describes the real-time implementation of the supernova neutrino search, operating on the two KM3NeT detectors since the first months of 2019. A quasi-online astronomy analysis is introduced to study the time profile of the detected neutrinos for especially significant events. The mechanism of generation and distribution of alerts, as well as the integration into the SNEWS and SNEWS 2.0 global alert systems are described. The approach for the follow-up of external alerts with a search for a neutrino excess in the archival data is defined. Finally, an overview of the current detector capabilities and a report after the first two years of operation are given, Postprint (published version)

As ongoing research efforts contribute to elucidating the consequences of climate change as well as adaptation and mitigation options, aligning the current research knowledge with stakeholder opinions and perceptions remains critical for adopting effective climate change policies. This paper utilizes an interactive survey to (1) address the aforementioned gap in studies involving three groups of stakeholders and opinion makers and (2) perform a comparative primary study of the climate change assumptions, risk perceptions, policy preferences, observations, and knowledge of Czech farmers, governmental policy-makers and researchers. This study shows that the stakeholder groups agree that the climate is clearly changing, attribute this change mostly to man-made causes and expect the negative effects to either prevail or be unevenly geographically distributed. The large majority of all three groups consider unmitigated climate change a major threat even by 2050 and agree that preparing in advance is the best sectoral strategy. Importantly, while investment in adaptation measures is considered the most efficient tool for accelerating the implementation of adaptation measures, the CAP and EU rules (as valid in 2016) are believed to hinder such measures. The results of this study have ramifications for the wider region of Central Europe.

The next generation of water Cherenkov neutrino telescopes in the Mediterranean Sea are under construction offshore France (KM3NeT/ORCA) and Sicily (KM3NeT/ARCA). The KM3NeT/ORCA detector features an energy detection threshold which allows to collect atmospheric neutrinos to study flavour oscillation. This paper reports the KM3NeT/ORCA sensitivity to this phenomenon. The event reconstruction, selection and classification are described. The sensitivity to determine the neutrino mass ordering was evaluated and found to be 4.4s if the true ordering is normal and 2.3s if inverted, after 3 years of data taking. The precision to measure ¿m2 32 and ¿23 were also estimated and found to be 85.10-6 eV2 and ( +1.9 -3.1)¿ for normal neutrino mass ordering and, 75.10-6 eV2 and ( +2.0 -7.0)¿ for inverted ordering. Finally, a unitarity test of the leptonic mixing matrix by measuring the rate of tau neutrinos is described. Three years of data taking were found to be sufficient to exclude ¿t event rate variations larger than 20% at 3s level., Peer Reviewed, Postprint (published version)

As ongoing research efforts contribute to elucidating the consequences of climate change as well as adaptation and mitigation options, aligning the current research knowledge with stakeholder opinions and perceptions remains critical for adopting effective climate change policies. This paper utilizes an interactive survey to (1) address the aforementioned gap in studies involving three groups of stakeholders and opinion makers and (2) perform a comparative primary study of the climate change assumptions, risk perceptions, policy preferences, observations, and knowledge of Czech farmers, governmental policy-makers and researchers. This study shows that the stakeholder groups agree that the climate is clearly changing, attribute this change mostly to man-made causes and expect the negative effects to either prevail or be unevenly geographically distributed. The large majority of all three groups consider unmitigated climate change a major threat even by 2050 and agree that preparing in advance is the best sectoral strategy. Importantly, while investment in adaptation measures is considered the most efficient tool for accelerating the implementation of adaptation measures, the CAP and EU rules (as valid in 2016) are believed to hinder such measures. The results of this study have ramifications for the wider region of Central Europe.

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This study attempts to capture the problems discovered on a field trip and to clarify user requirements with the participation of the user. With Mobile AP II, a platform for gathering user information and communication, user and designer can discuss issues so that user requirements can be specified from the context of the situation. In addition, we use narrative factors based on user experience and activity to make modeling scenarios easy to organize. In this study, we discovered how helpful it is to share information and to communicate via Mobile AP II, and that scenarios could be built using narrative factors to analyze the context of information systematically.

We aim to explore a potentially valuable tool for scenario writing, focusing on the collection of user experiences organized around photos. We have developed a tool, Mobile AP II, to produce a comprehensive context classification based on a sample scenario to demonstrate how the context of photos and their relationships can be integrated to assist with scenario-based design. An efficient scenario-building technique for concept development and design leads to a simple user-modeling framework whereby the Mobile AP II system can learn to display query results based on photo relationships provided by the designer. The resulting retrieval, browsing and visualization can adapt to the user’s selection of content, context and preferences in style and interactive navigation. Our purpose is to develop rich and flexible methods and concepts that can incorporate users’ descriptions and their current and potential use of a scenario into the very design reasoning about such a system.

Generally, RFID systems consist of RFID tag, RFID reader, and back-end database. We are facing privacy and security problems and challenges in the RFID system. The privacy and security problems arise from RFID tag limitation such as small memory and low computing power. Due to such the limitation, data transmission between RFID tags and RFID readers are unencrypted, in addition RFID tags provide no tamper resistance. That is, RFID tags and RFID readers communicate with each other in insecure wirelesschannel., IEEE International Conference on Cybernetics and Intelligent Systems (CIS 2007)

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