Search

In this paper, we design a spin model to optimize the search in complex networks using two random walkers by reducing the wasted time in revisiting nodes. A good measure of the global performance of the searching process is the Mean Cover Time (MCT), which is the time needed from the start of the searching process to the end that all sites in the network are reached by at least one walker. We use a three-state spin model to minimize the MCT for two random walkers. In the model, each site in the network is described by a three-state spin, with unvisited sites having a spin state defined by white color, and the visited sites in spin states with non-white colors (red and blue in the case of two walkers). The visit of a site by a walker changes the state of the spin. We introduce a repulsive interaction between spins to model the interactions between walkers. Numerical results using the Erdős-Rényi (ER) network, the Watts-Strogatz (WS) network and three small-world real network datasets show satisfactory results in reducing the MCT. For small-world networks, both the artificial WS network and real-world network datasets show the existence of the critical repulsion strength which minimizes the MCT. We also provide a heuristic explanation for the presence of the critical repulsion that minimizes the MCT for the WS network and its absence in the ER network. Our model provides guidance to future research on multiple random walkers over complex networks, with potential applications for efficient information spreading in social networks. © Springer International Publishing AG 2018.

The main aim of this paper is to explain why certain parts of the Swedish New Math reform failed. The secondary aim is to nuance the idea about the decline of the New Math in Sweden. The analysis is focused on governance, but also ideological, economical and sociological aspects are considered. The main sources are syllabi, official reports and textbooks. Another type of source is a database of historical textbooks in mathematics. Even though the suggested explanation to great degree concerns the Swedish context, it has a more general relevance. Previous research on New Math in other countries is mainly focused on ideological and sociological aspects of the reforms. This paper also highlights the interplay between factors related to textbooks, governance and economics. It is relevant to consider these factors in other countries as well since textbook development was a part of New Math reforms in many countries.

Europe is in a phase of vast transition regarded both from a demographic and economic-structural point of view. Studies have shown that demographic development differs a lot when comparing urban regions with more sparsely populated peripheral regions. These diverging patterns are shown to be especially strong in the northern and eastern parts of Europe where a redistribution of people contributes to a concentration process to the metropolitan or big city areas as well as to shrinkage and depopulating of rural and peripheral areas. This paper empirically addresses these differing demographic development paths by analyzing the influence of key underlying demographic factors on population change across European regions. For the stated purpose the paper applies typologies based on both economic and demographic structure and a cross-regional regression model. The economic-structural typology developed within the ESPON/EDORA-project is used to describe and analyze economic-structural factors and a typology based on demographic characteristics that classify regions as either shrinking or expanding in terms of population is used in the empirical assessment. Findings indicate that age structure is of importance with regard to population changes and there exists an east-west divide between the growing west and declining east where the declining sectors are more frequent. It is also shown that large and densely populated regions have better preconditions for growth and fewer risks for shrinking than small and sparsely populated ones., QC20190502

A personal visual lifelog can be considered to be a human memory augmentation tool and in recent years we have noticed an increased interest in the topic of lifelogging both in academic research and from industry practitioners. In this preliminary work, we explore the concept of event segmentation of visual lifelog data. Lifelog data, by its nature is continual and streams of multimodal data can easy run into thousands of wearable camera images per day, along with a significant number of other sensor sources. In this paper, we present two new approaches to event segmentation and compare them against pre-existing approaches in a user experiment with ten users. We show that our approaches based on visual concepts occurrence and image categorization perform better than the pre-existing approaches. We finalize the paper with a suggestion for next steps for the research community.

Symmetric tensor decomposition is of great importance in applications. In this paper, we design a synchronized multi-rank symmetric Tensor Decomposition alternating minimization method. In this algorithm, we start from a careful initialization for the non-convex symmetric tensor decomposition and then perform an alternating minimization algorithm. Our contributions are as follows: (1) Our method is synchronized and there is no need for a greedy algorithm to get the multi-rank tensor decomposition. (2) Initialization is an important part in our proposed method. With a careful initialization, our proposed algorithm can converge to the global minimizer of the non-convex objective function. (3) The designed alternating minimization algorithm can give a highly accurate result. In numerical results, our proposed algorithm is much better than the simple gradient descent method from the same initialization. Moreover, our results show that with eigenvectors of random projection as initialization, we can quickly get the global solution by using simple alternating minimization algorithm, though finding the global minimum of this non-convex minimization problem is NP-hard.

This paper aims at investigating the determinants of firms’ technological competencies and capabilities as defined by von Tunzelmann and Wang (Economie Appliquée 6:33–64, 2003). The analysis carried out in the paper shows that some company characteristics, such as size, being part of a group and internationalization, as well as cooperation channels significantly impact on the innovative behavior of Italian firms, in increasing both their likelihood of becoming actively innovative and their potential to economically exploit the returns from innovative activity. Moreover, also geographical location appears to be a significant relevant factor. The findings are based on firm-level data provided by the Italian Community Innovation Survey (CIS).

In this paper, we design a spin model to optimize the search in complex networks using two random walkers by reducing the wasted time in revisiting nodes. A good measure of the global performance of the searching process is the Mean Cover Time (MCT), which is the time needed from the start of the searching process to the end that all sites in the network are reached by at least one walker. We use a three-state spin model to minimize the MCT for two random walkers. In the model, each site in the network is described by a three-state spin, with unvisited sites having a spin state defined by white color, and the visited sites in spin states with non-white colors (red and blue in the case of two walkers). The visit of a site by a walker changes the state of the spin. We introduce a repulsive interaction between spins to model the interactions between walkers. Numerical results using the Erdős-Rényi (ER) network, the Watts-Strogatz (WS) network and three small-world real network datasets show satisfactory results in reducing the MCT. For small-world networks, both the artificial WS network and real-world network datasets show the existence of the critical repulsion strength which minimizes the MCT. We also provide a heuristic explanation for the presence of the critical repulsion that minimizes the MCT for the WS network and its absence in the ER network. Our model provides guidance to future research on multiple random walkers over complex networks, with potential applications for efficient information spreading in social networks. © Springer International Publishing AG 2018.

In this paper, we consider the a priori traveling salesman problem (TSP) in the scenario model. In this problem, we are given a list of subsets of the vertices, called scenarios, along with a probability for each scenario. Given a tour on all vertices, the resulting tour for a given scenario is obtained by restricting the solution to the vertices of the scenario. The goal is to find a tour on all vertices that minimizes the expected length of the resulting restricted tour. We show that this problem is already NP-hard and APX-hard when all scenarios have size four. On the positive side, we show that there exists a constant-factor approximation algorithm in three restricted cases: if the number of scenarios is fixed, if the number of missing vertices per scenario is bounded by a constant, and if the scenarios are nested. Finally, we discuss an elegant relation with an a priori minimum spanning tree problem.

Numerous scholars study how to design evidence-based interventions that can improve the lives of individuals, in a way that also brings social benefits. However, within the behavioral sciences in general, and the persuasive technology field specifically, scholars rarely focus-on, or report the negative outcomes of behavior change interventions, and possibly fewer report a special type of negative outcome, a backfire. This paper has been authored to start a wider discussion within the scientific community on intervention backfiring. Within this paper, we provide tools to aid academics in the study of persuasive backfiring, present a taxonomy of backfiring causes, and provide an analytical framework containing the intention-outcome and likelihood-severity matrices. To increase knowledge on how to mitigate the negative impact of intervention backfiring, we discuss research and practitioner implications.

The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency., SOCRATES

The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency., SOCRATES

The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency., SOCRATES

New smart cities, i.e. technology enabled cities is an ambitious project currently in India. However, the focus should be on rejuvenating the existing dying cities from the plethora of problems they are facing and make them sustainable. In lieu of this, the paper attempts to uncover the environmental disaster of air pollution engulfing the royal Nawabi city of Lucknow which is experiencing a new stage of urbanization and is expanding to its fullest by engulfing the rural fringes. Hasty urbanization poses grave challenge to the environment, which is emerging as an important apprehension and has become a major subject of concern. In this spurious process of expansion, it is attracting negativity which in turn is hampering its own quality. Due to excessive discharge of pollutants like oxides of nitrogen, carbon monoxide, sulphur dioxide, particulate matter, and lead emitted from vehicles, the quality of air is deteriorating. The increased traffic has resulted in increased emission of gaseous pollutants and particulate matter which has enough potential for deterioration of environmental sustainability of any ecosystem and human health too (Nagendra et al. 2004). The quality of air that we are breathing is rapidly changing. Managing the urban environment is becoming an overwhelming dilemma as the city is experiencing critical environmental degradation and is having solemn setback in sustaining human life. Though attempts are being made to curb this problem, huge efforts are still awaited. This paper provides a close view concerning the blow of environment pollution in the perspective of air pollution and problems faced by the citizens.

The exponential increase in population and unplanned growth over the years have created enormous pressure on the availability of land and infrastructure with the result that most cities and towns are severely stressed in terms of available infrastructure and delivery of basic services. Through this paper, an attempt has been made to bring into light the problems and prospects incurred in the way of development in Guwahati City of Assam. Cities and towns play a vital role in the country's socioeconomic growth, its transformation and change. Guwahati is recognized to be the most critical city in the North East India. The city has a well-developed connectivity with the rest of the country and acts as the gateway to the entire Northeastern India. Hence, the development of the city is not only critical to the state of Assam but also to the entire North East. This paper mainly deals with the issues and challenges related with environmental and also socioeconomic aspects recognized by government, non-government agencies and local people, those standing as barriers in the development of Guwahati city as a smart city identified on the basis of the study conducted on different areas using descriptive survey method and observation method.

The chapter summarizes the detailed discussions about the Smart city concept and its perspective with reference to India, presented in various chapters in the book. The book is an encapsulation of case studies from different cities of India based on multifaceted issues, potentials and challenges. The research papers suggest the optimal management of technology and infrastructure to achieve future goals. It also suggests integrating the complex economic and social structures of cities for sustainable growth and development. The book has four sections namely smart cities development potential and challenges; environment, energy, disaster management and sustainable development; role of ICT, remote sensing and geographical information system and multifarious management for smart cities covering diverse nature of papers catering the issues of smart city understanding, design, planning, execution, technology and governance.

Tinsukia is an important flourishing urban centre in Assam. It is selected among the 100 Smart Cities of India in 2014. As a commercial and trade hub, it has a large Railway junction, an ongoing Plastic Park project and several corporate offices. It has also been dealing in tea, coal, crude oil and petroleum products, plywood, etc., supplied from the hinterlands. Its location is near the major oil and coal fields of Upper Brahmaputra valley and many tourist places are also located in its vicinity. This paper is based on mainly secondary data—maps, documents and other information from offices of Government and non Government organisations. The findings suggest that public–private partnership (PPP) and digitisation in infrastructure, trade and commerce and transportation and storage should be welcomed to initiate the Smart City process in Tinsukia. In order to sustain the future city, ‘green economy’ practices in manufacturing, trade and transportation are vital. Moreover, its location near the Indo-Myanmar international boundary and the opening of the historic Stilwell Road shall be a great impetus to financial sustainability and also to implement the Look East Policy. This paper emphasises on the economic potentiality of Tinsukia which will aid the Smart City process. It also dwells on the challenges and vision of a smart public transport system within the city.

Urbanization is one of the key indicators of the process of socio-economic development. Health plays a vital role in human life. It is also one of the most important factors of development. Despite the tremendous effort of the government towards ensuring equality of healthcare opportunities, inequality still prevails. The present paper aims at examining the close relationship with urbanization and healthcare facilities and health status in Western Uttar Pradesh. The data for the analysis have been obtained from the secondary sources. This paper suggests that enhancement of healthcare facilities shall reduce the disparities in health status rather than urbanization in Western Uttar Pradesh.

In the present knowledge and information age, Indian towns are expanding rapidly in spatial and demographic terms. Moreover, spatial information are not correlated with the complex urban integrated problems, as data generated at various levels for urban planning remains uncoordinated and redundant to support decision-making and leading to poor urban governance. Hence, there is an urgent need to create common platform so as to address problems and issues in the right perspective to assist cities in coping with economic realities and, thereby, produce high-quality responsive environment and demonstrate successful urban solutions. Thus, in order to address these issues in a holistic manner, the Ministry of Urban Development has launched the National Urban Information System (NUIS) Scheme. The implementation of the NUIS Scheme would ultimately lead to e-Governance. In this context, the present paper is an attempt to address the various challenges like enhancing organizational capacity; cooperation between various stakeholders, accessibility of data, capacity building; and standardization of data format for the implementation of the Urban Information and Knowledge Management (UIKM) system in India. To establish the Digital Urban Information System in India is not simply a challenge but a mission to foster the mind of town planners and urban managers to tackle the real world problems only after analyzing the virtual world situations. Moreover, this paper also discusses that how establishment of effective efficient information system will pave the way for development of smart cities in India.

Household behavior is a very important factor in sustainable urbanization of a city. No policy can succeed if it is not implemented at the household level. This paper is concerned with the relationships between urbanization and residential water consumption, taking as a case study five areas–-Bhugaon, Warje-Malwadi, Kothrud, Kasba Peth, and Pashan–-in Pune Municipal Corporation. The paper investigates the influence of various factors like income, education, and location of households and other behavioral factors on water consumption using correlations and other statistical methods. The data are derived from a sample of sixty households in each of five areas of Pune city located in different directions of the city. Results show that factors like income, housing type, members per household, and the presence of outdoor uses like a garden and swimming pool, lifestyle and consumer behavior toward conservation practices play a significant role in explaining variations in water consumption. Areas with higher consumption show higher water usage. Therefore, behavior and awareness is linked to income and education. Similarly, what practices do the households take with respect to saving water? As a measure, water pricing and metering of water connections could be effective but it needs the companionship of awareness regarding water use. It is concluded that, along with prices and incomes, further research is needed on other demographic and housing variables in order to obtain a more comprehensive understanding of the determinants of domestic water consumption and relating it with implementation of public policies related to sustainability.

This paper reviews the concept of accessibility and strongly focuses on urban transport accessibility factors. Accessibility refers to people's ability to reach goods, services and activities, which is the ultimate goal of most transport activity. Accessibility can be evaluated from various perspectives, including a particular group, mode, location or activity. This paper will also focus on accessibility of urban transport at city and regional level to give an overview of accessibility factors. Jodhpur has been taken as case study. The city is spread over an area of about 78.60 km2. As per 2011 census, the population of Jodhpur city is 11.38 lakh with growth rate of 3.3% per annum, respectively. Jodhpur district is well connected by road, railway and airway. Major issues regarding road infrastructure, traffic, public transport, bus terminals, non-motorized facilities, parking have been taken into consideration. Transport parameters such as affordability, availability, accessibility, acceptability are mainly adopted. Thus, this paper emphasizes on following factor to make city more accessible with well-connected surroundings and the transport network must be planned efficiently.

Urbanization is a global multidimensional process that is manifest through rapidly changing human population densities and changing land use/cover. A significant facet of Indian urbanization has been greater concentration of population in metropolitan cities, especially in the recent years. Delhi is one of the fastest growing cities in the country. The population pressure is immense on the urban ecosystem to provide basic facilities to its residents. The rapid migration toward Delhi has changed the land use/land cover (LULC) status of the capital city. The analysis revealed that substantial growth of built-up areas in NCT of Delhi over the study period resulted significant decrease in the area of water bodies, cultivated land, vegetation, and wetlands. Rapid urban expansion through infilling of surrounding areas and clearing of vegetation resulted in a wide range of environmental impacts including habitat quality. This paper describes the process of urbanization and land use changes in the urban ecosystems of the National Capital Territory (NCT) of Delhi and analyzes its impact on Ecosystem Services (ES). Two types of land use change are considered from natural to urban and from agricultural to urban. This paper has evaluates the LULC changes and urban expansion in NCT, Delhi and highlights the major impact of rapid urbanization and population growth on the LULC changes which needs immediate attention. This paper has emphasis on the urban planning to be applied such that more consideration is toward the conservation and management of natural land use classes which will increase the quality of life in an urban environment with sustainable development approaches.

The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency., SOCRATES

In this paper we present the AmuS database of about three hours worth of data related to amused speech recorded from two males and one female subjects and contains data in two languages French and English. We review previous work on smiled speech and speech-laughs. We describe acoustic analysis on part of our database, and a perception test comparing speech-laughs with smiled and neutral speech. We show the efficiency of the data in AmuS for synthesis of amused speech by training HMM-based models for neutral and smiled speech for each voice and comparing them using an on-line CMOS test., QC 20200313

In this paper we present the AmuS database of about three hours worth of data related to amused speech recorded from two males and one female subjects and contains data in two languages French and English. We review previous work on smiled speech and speech-laughs. We describe acoustic analysis on part of our database, and a perception test comparing speech-laughs with smiled and neutral speech. We show the efficiency of the data in AmuS for synthesis of amused speech by training HMM-based models for neutral and smiled speech for each voice and comparing them using an on-line CMOS test., QC 20200313

The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency., SOCRATES

In this paper we present the AmuS database of about three hours worth of data related to amused speech recorded from two males and one female subjects and contains data in two languages French and English. We review previous work on smiled speech and speech-laughs. We describe acoustic analysis on part of our database, and a perception test comparing speech-laughs with smiled and neutral speech. We show the efficiency of the data in AmuS for synthesis of amused speech by training HMM-based models for neutral and smiled speech for each voice and comparing them using an on-line CMOS test., QC 20200313

In this paper we present the AmuS database of about three hours worth of data related to amused speech recorded from two males and one female subjects and contains data in two languages French and English. We review previous work on smiled speech and speech-laughs. We describe acoustic analysis on part of our database, and a perception test comparing speech-laughs with smiled and neutral speech. We show the efficiency of the data in AmuS for synthesis of amused speech by training HMM-based models for neutral and smiled speech for each voice and comparing them using an on-line CMOS test., QC 20200313

The aim of the study presented in this paper is to develop a quantitative evaluation tool of the sense of safety and security for robots in eldercare. By investigating the literature on measurement of safety and security in human-robot interaction, we propose new evaluation tools. These tools are semantic differential scale questionnaires. In experimental validation, we used the Pepper robot, programmed in the way to exhibit social behaviors, and constructed four experimental conditions varying the degree of the robot’s non-verbal behaviors from no gestures at all to full head and hand movements. The experimental results suggest that both questionnaires (for the sense of safety and the sense of security) have good internal consistency., SOCRATES

In this paper we present the AmuS database of about three hours worth of data related to amused speech recorded from two males and one female subjects and contains data in two languages French and English. We review previous work on smiled speech and speech-laughs. We describe acoustic analysis on part of our database, and a perception test comparing speech-laughs with smiled and neutral speech. We show the efficiency of the data in AmuS for synthesis of amused speech by training HMM-based models for neutral and smiled speech for each voice and comparing them using an on-line CMOS test., QC 20200313

Numerous scholars study how to design evidence-based interventions that can improve the lives of individuals, in a way that also brings social benefits. However, within the behavioral sciences in general, and the persuasive technology field specifically, scholars rarely focus-on, or report the negative outcomes of behavior change interventions, and possibly fewer report a special type of negative outcome, a backfire. This paper has been authored to start a wider discussion within the scientific community on intervention backfiring. Within this paper, we provide tools to aid academics in the study of persuasive backfiring, present a taxonomy of backfiring causes, and provide an analytical framework containing the intention-outcome and likelihood-severity matrices. To increase knowledge on how to mitigate the negative impact of intervention backfiring, we discuss research and practitioner implications.

In order to ensure sustainable development of our cities, we all have to do our part. There is a growing awareness about environmental problems, and citizens want to be informed and find the information about the environment relevant for all, not just for those who are making decisions. Many communities want to have a role in making their cities attractive and livable. However, the public cannot always easily perceive the causes of environmental problems-e.g., neighborhood or city-level energy consumption, air and water pollution, or noise levels. Making such information easily accessible and understandable to all is the challenge this paper addresses. This paper argues for the use of public buildings and local landmarks as a means for communicating information about the quality of the environment by employing their existing illumination systems as a medium for transferring and disseminating the respective information. Instead of using one color or randomly changing colors (as is a case employed on many public buildings nowadays), the proposal this paper advocates for is to connect the light color to the corresponding environmental parameter, and, in this way, convey the information. For instance, if CO2 is taken as a relevant parameter, when the emissions go above a certain level, the building could glow red. The intensity of color or a choice of color corresponds to the parameter that is measured. This is an informative, non-invasive, simple, and inexpensive solution that can help in raising awareness about the environmental problems and, at the same time, make the public informed. The information presented in this way is easy to understand, it is visible to a large number of people and " glanceable". Furthermore, it could support the involvement of a community in coping with the environmental issues by spurring a bottom-up action and making the community one step closer to the ideal of making their cities sustainable and resilient. The approach in developing this

Background: The paper investigates the use of Healthcare Tax Credits (HTCs) in Italy through the analysis of a panel data which provides information on individual income tax from 2008 to 2014. Disparities emerging in the use of HTCs between Northern and Southern regions require to be analyzed. Objective: The aim of the paper consists in investigating the socioeconomic determinants in the use of Healthcare Tax Credits in Italy. Methods: A fixed effects Ordinary Least Square model is run to examine the impact of selected socioeconomic variables on regional per capita HTCs, with a particular focus on the role of education. Results: Findings corroborate the regressive traits of HTCs supported by literature and provide highlights on the role of education in explaining HTCs’ distribution among Italian regions. Conclusion: Public money is reimbursed to regions where people are on average richer and better educated. More equitable objectives could be reached by allocating the same resources in the provision of services covered by the NHS.

The success of a digitally developed architecture project requires a new vision of collaboration and design practices and the adaptation of the current ones. The recent innovative tools and media extend the design capabilities, and foster the proposal of complex architectural solutions. This paper aims to evaluate the existing interactive synchronous collaboration technologies and solutions. The evaluation must reveal their potential advantages and future uses for professionals and education in the architecture, engineering, and construction (AEC) industry are assessed. Furthermore, suggestions are made on how to improve the current synchronous collaboration practices in decision-making sessions. Such suggestions consider the complexity of 3D-based project and the multidisciplinary of a project team. The paper introduces a summary of the current digital AEC practices and identifies digital synchronous collaboration requirements for an efficient decision-making session through observation and evaluation of several collaborative session experiments.

This paper evaluates the behavior of the Microsoft Azure G5 cloud instance type over multiple Data Centers. The purpose is to identify if there are major differences between them and to help the users choose the best option for their needs. Our results show that there are differences in the network level for the same instance type in different locations and inside the same location at different times. The network performance causes interference in the applications level, as we could verify in our results., This research received funding from the EU H2020 Programme and from MCTI/RNP-Brazil under the HPC4E project, grant agreement no. 689772. Experiments presented in this paper were carried out using the Grid'5000 testbed, supported by a scientific interest group hosted by Inria and including CNRS, RENATER and several Universities as well as other organizations (see https://www.grid5000.fr). Additional funding was provided by CAPES and Microsoft., Peer Reviewed, Postprint (author's final draft)

Since the latest review about solitary localized waves in muscovite, called quodons, (F.M. Russell in Quodons in Mica. Springer, Cham, pp. 475–559, 2015a [1], F.M. Russell in Quodons in Mica. Springer, Cham, pp. 3–33, 2015b [2]) there have been many developments, specially from the point of view of experiments, published in several journals. The breakthrough hypothesis that was advanced in that review that dark tracks were produced by positive electrical charge moving in a localized wave, either transported by swift particles or by nonlinear localized waves, has been confirmed by experiments in muscovite and other silicates. In this paper we review the experimental results, some already published and some new, specially the phenomenon of charge transport without an electric field, called hyperconductivity. We also consider alternative explanations as phase transitions for other tracks. We also attempt to describe numerical simulations that have confirmed the order of magnitude of quodons energy and calculations underway to determine more properties of electron and hole transport by quodons.

Organisations can be complex entities, performing heterogeneous processing on large volumes of diverse personal data, potentially using outsourced partners or subsidiaries in distributed geographical locations and jurisdictions. Many organisations appoint a Data Protection Officer (DPO) to assist them with their demonstration of compliance with the GDPR Principle of Accountability. The challenge for the DPO is to monitor these complex processing activities and to advise and inform the organisation with regard to the organisations demonstration of compliance with the Principle of Accountability. A review of GDPR compliance software solutions shows that organisations are being greatly challenged in meeting compliance obligations as set out under the GDPR, despite the myriad of software tools available to them. Many organisations continue to take a manual and informal approach to GDPR compliance. Our analysis shows significant gaps on the part of GDPR tools in their ability to demonstrate compliance in that they lack interoperability features, and they are not supported by published methodologies or evidence to support their validity or even utility. In contrast, RegTech has brought great success to financial compliance, using technological solutions to facilitate compliance with, and the monitoring of regulatory requirements. A review of the State of the Art identified the four success features of a RegTech system to be, strong data governance, automation through technology, interoperability of systems and a proactive regulatory framework. This paper outlines a set of requirements for GDPR compliance tools based on the RegTech experience and evaluate how these success features could be applied to improve GDPR compliance. A proof of concept prototype GDPR compliance tool was explored using the four success factors of RegTech, in which RegTech best practice was applied to regulator based self-assessment checklist to establish if the demonstration of GDPR compliance coul

The Video Browser Showdown (VBS) is an annual competition in which each participant prepares an interactive video retrieval system and partakes in a live comparative evaluation at the annual MMMConference. In this paper, we introduce Eolas, which is a prototype video/image retrieval system incorporating a novel virtual reality (VR)interface. For VBS’21, Eolas represented each keyframe of the collection by an embedded feature in a latent vector space, into which a query would also be projected to facilitate retrieval within a VR environment. A user could then explore the space and perform one of a number of filter operations to traverse the space and locate the correct result.

The Video Browser Showdown (VBS) is an annual competition in which each participant prepares an interactive video retrieval system and partakes in a live comparative evaluation at the annual MMMConference. In this paper, we introduce Eolas, which is a prototype video/image retrieval system incorporating a novel virtual reality (VR)interface. For VBS’21, Eolas represented each keyframe of the collection by an embedded feature in a latent vector space, into which a query would also be projected to facilitate retrieval within a VR environment. A user could then explore the space and perform one of a number of filter operations to traverse the space and locate the correct result.

The Video Browser Showdown (VBS) is an annual competition in which each participant prepares an interactive video retrieval system and partakes in a live comparative evaluation at the annual MMMConference. In this paper, we introduce Eolas, which is a prototype video/image retrieval system incorporating a novel virtual reality (VR)interface. For VBS’21, Eolas represented each keyframe of the collection by an embedded feature in a latent vector space, into which a query would also be projected to facilitate retrieval within a VR environment. A user could then explore the space and perform one of a number of filter operations to traverse the space and locate the correct result.

Organisations can be complex entities, performing heterogeneous processing on large volumes of diverse personal data, potentially using outsourced partners or subsidiaries in distributed geographical locations and jurisdictions. Many organisations appoint a Data Protection Officer (DPO) to assist them with their demonstration of compliance with the GDPR Principle of Accountability. The challenge for the DPO is to monitor these complex processing activities and to advise and inform the organisation with regard to the organisations demonstration of compliance with the Principle of Accountability. A review of GDPR compliance software solutions shows that organisations are being greatly challenged in meeting compliance obligations as set out under the GDPR, despite the myriad of software tools available to them. Many organisations continue to take a manual and informal approach to GDPR compliance. Our analysis shows significant gaps on the part of GDPR tools in their ability to demonstrate compliance in that they lack interoperability features, and they are not supported by published methodologies or evidence to support their validity or even utility. In contrast, RegTech has brought great success to financial compliance, using technological solutions to facilitate compliance with, and the monitoring of regulatory requirements. A review of the State of the Art identified the four success features of a RegTech system to be, strong data governance, automation through technology, interoperability of systems and a proactive regulatory framework. This paper outlines a set of requirements for GDPR compliance tools based on the RegTech experience and evaluate how these success features could be applied to improve GDPR compliance. A proof of concept prototype GDPR compliance tool was explored using the four success factors of RegTech, in which RegTech best practice was applied to regulator based self-assessment checklist to establish if the demonstration of GDPR compliance coul

A critical component of autonomous driving in urban environment is the vehicle’s ability to interact safely and intelligently with the human drivers and on-road pedestrians. This requires identifying the human intentions in real time based on a limited observation history and reacting accordingly. In the context of pedestrian avoidance, traditional approaches like proximity based reactive avoidance, or taking the most likely behavior of the pedestrian into account, often fail to generate a safe and successful avoidance strategy. This is mainly because they fail to take into account the human intention and the inherent uncertainty resulting in identifying such intentions from direct observations. This work formulates the on-road pedestrian avoidance problem as an instance of the Intention-Aware Motion Planning (IAMP) problem, where the human intention uncertainty is incorporated in a principled manner into the planning framework. Assuming a set of all possible pedestrian intentions in the environment, IAMPs generate a Mixed Observable Markov Decision Process (MOMDP), (a factored variant of Partially Obervable Markov Decision Process (POMDP)) with the human intentions being the unobserved variables. Solving the resulting MOMDP generates a robust pedestrian avoidance policy. In spite of the criticism of POMDPs to be computationally intractable in general, we show that with proper state factorization and latest sampling based approaches the policy can be executed online on a real vehicle on road. We demonstrate this by running the algorithm on a real pedestrian crossing in the NUS campus successfully handling the intentions for multiple pedestrians, even when they are jaywalking. In this paper, we present results in simulation to show the improved performance of the proposed approach over existing methods. Additionally, we present results validating experimentally the assumptions made in formulating the intention aware pedestrian avoidance problem. This work presents a

Sydney is Australia’s largest and most cosmopolitan global city and the fourth greatest immigrant city in the world today. Immigrant entrepreneurs have been a part of Sydney’s long immigration history. This paper explores the complex and uneven contemporary dynamics of immigrant entrepreneurship in Sydney through the lens of Korean, Muslim, and recently arrived refugee entrepreneurs. First-generation Korean immigrant entrepreneurs in the Sydney restaurant industry cluster in the Sydney CBD and key suburbs of Korean immigrant settlement. Their story permits an understanding of the neighborhood impact of immigrant entrepreneurship and the contradictions underlying the emerging suburban ethnic precincts—Koreatown in this instance—in cosmopolitan neighborhoods. The experience of Muslim immigrant entrepreneurs in Sydney explores the role of religion is Sydney’s immigrant entrepreneurship landscape. Refugee entrepreneurs face greater barriers to entrepreneurship than other immigrants but have the highest rate of entrepreneurship of all immigrants. The explanation for this apparent paradox, and in understanding the dynamics of immigrant entrepreneurship in Sydney overall, lies in the importance of looking at immigrant (and refugee) agency and their determination to make a better life for themselves and their family in Australia and rejecting a deficit approach to immigrant entrepreneurship.

Physical memory capacity has increased owing to large-scale integration. In addition, memory footprints have increased in size, as multiple programs are executed on a single computer. Many operating systems manage physical memory by paging a 4 KB page. Therefore, the number of entries in the virtual address translation table for virtual to physical increases along with the size of the memory footprints. This cause a decrease in the translation lookaside buffer (TLB) hit ratio, resulting in the performance degradation of the application. To address this problem, we propose the implementation of physical memory management with two page sizes: 4 KB and 4 MB. This allows us to expand range of addresses to be translated by a single TLB entry, thereby improving the TLB hit rate. This paper describes the design and implementation of the physical memory management mechanism that manages physical memory using two page sizes on The ENduring operating system for Distributed EnviRonment (Tender OS). Our results showed that when the page size is 4 MB, the processing time of the memory allocation can be reduced by as much as approximately 99.7%, and the processing time for process creation can be reduced by as much as approximately 51%, and the processing time of the memory operation could be reduced by as much as 91.9%.

Network interface cards (NICs) are fundamental components of modern high-speed networked systems, supporting multi-100 Gbps speeds and increasing programmability. Offloading computation from a server’s CPU to a NIC frees a substantial amount of the server’s CPU resources, making NICs key to offer competitive cloud services. Therefore, understanding the performance benefits and limitations of offloading a networking application to a NIC is of paramount importance. In this paper, we measure the performance of four different NICs from one of the largest NIC vendors worldwide, supporting 100 Gbps and 200 Gbps. We show that while today’s NICs can easily support multi-hundred-gigabit throughputs, performing frequent update operations of a NIC’s packet classifier—as network address translators (NATs) and load balancers would do for each incoming connection—results in a dramatic throughput reduction of up to 70 Gbps or complete denial of service. Our conclusion is that all tested NICs cannot support high-speed networking applications that require keeping track of a large number of frequently arriving incoming connections. Furthermore, we show a variety of counter-intuitive performance artefacts including the performance impact of using multiple tables to classify flows of packets.

Since the latest review about solitary localized waves in muscovite, called quodons, (F.M. Russell in Quodons in Mica. Springer, Cham, pp. 475–559, 2015a [1], F.M. Russell in Quodons in Mica. Springer, Cham, pp. 3–33, 2015b [2]) there have been many developments, specially from the point of view of experiments, published in several journals. The breakthrough hypothesis that was advanced in that review that dark tracks were produced by positive electrical charge moving in a localized wave, either transported by swift particles or by nonlinear localized waves, has been confirmed by experiments in muscovite and other silicates. In this paper we review the experimental results, some already published and some new, specially the phenomenon of charge transport without an electric field, called hyperconductivity. We also consider alternative explanations as phase transitions for other tracks. We also attempt to describe numerical simulations that have confirmed the order of magnitude of quodons energy and calculations underway to determine more properties of electron and hole transport by quodons.

Deep neural networks are fragile as they are easily fooled by inputs with deliberate perturbations, which are key concerns in image security issues. Given a trained neural network, we are always curious about whether the neural network has learned the concept that we’d like it to learn. We want to know whether there might be some vulnerabilities of the neural network that could be exploited by hackers. It could be useful if there is a tool that can be used by non-experts to test a trained neural network and try to find its vulnerabilities. In this paper, we introduce a tool named AdverseGen for generating adversarial examples to a trained deep neural network using the black-box approach, i.e., without using any information about the neural network architecture and its gradient information. Our tool provides customized adversarial attacks for both non-professional users and developers. It can be invoked by a graphical user interface or command line mode to launch adversarial attacks. Moreover, this tool supports different attack goals (targeted, non-targeted) and different distance metrics.

Predicting air quality is increasingly important for protecting people’s daily health and helping government decision-making. The multistep air quality prediction largely depends on the correlations of air quality-related factors. How to model the correlations among factors is a big challenge. In this paper, we propose a cross-correlation gaining framework (C2 -Guard) consisting of a temporal correlation module, factor correlation module, and cross gaining module for air quality (mainly PM2.5) prediction. Specifically, the temporal correlation module is used to extract the temporal dependence of air pollutant time series to gain their distributed representation. In the factor correlation module, a novel convolution and recalibration block is designed for air quality factor correlations extraction to gain their distributed representation in the factor dimension. In the cross gaining module, a joint-representation block is proposed to learn the cross-correlations between time and factor dimensions. Finally, extensive experiments are conducted on two real-world air quality datasets. The results demonstrate that our C2 -Guard outperforms the state-of-the-art methods of air pollutants prediction in terms of RMSE and MAE.

Public Private Partnership (PPP) is an approach adopted to expand the economic value of infrastructure outputs. Many researchers have explored the application of PPP to improve the efficiency of infrastructure delivery. Although interests in reviewing general trends and diverse topics of the PPP literature have increased over the years, there is a lack of a systematic review of the PPP literature from urban infrastructure projects in China. The purpose of this study is to analyze the research status and possible future studies from the viewpoint of urban infrastructure projects in China under public private partnership. The review is conducted by searching related papers from the leading construction management journals, then classifying them into distinct type of urban infrastructure projects applied with PPP in China to facilitate further discussion on significant research topics. The findings show that education and urban development, attracting uneven attention from researchers, meanwhile transportation, water supply finding as the key factor driving the urban infrastructure projects under PPP in China. The outcomes of this study reveal Urban infrastructure under public private partnership still facing some challenges such regional corruption, risk factors and short-term uncertainty, which will be the future research trends.

The identification of protein-protein interaction (PPI) is one of the most important tasks to understand the biological functions and disease mechanisms. Although numerous databases of biological interactions have been published in debt to advanced high-throughput technology, the study of inter-species protein-protein interactions, especially between human and bacterium pathogens, remains an active yet challenging topic to harness computational models tackling the complex analysis and prediction tasks. In this paper, we comprehensively revisit the prediction task of human-bacterium protein-protein interactions (HB-PPI), which is a first ever endeavour to report an empirical evaluation in learning and predicting HB-PPI based on machine learning models. Firstly, we summarise the literature review of human-bacterium interaction (HBI) study, meanwhile a vast number of databases published in the last decades are carefully examined. Secondly, a broader and deeper experimental framework is designed for HB-PPI prediction task, which explores a variety of feature representation algorithms and different computational models to learn from the curated HB-PPI dataset and perform predictions. Furthermore, a bidirectional LSTM-based model is proposed for the prediction task, which demonstrates a more effective performance in comparison with the others. Finally, opportunities for improving the performance and robustness of machine learning models for HP-PPI prediction are also discussed, laying a foundation for future work.

Emotion classification is one of the most important tasks of natural language processing (NLP). It focuses on identifying each kind of emotion expressed in text. However, most of the existing models are based on deep learning methods, which often suffer from long training time, difficulties in convergence and theoretical analysis. To solve the above problems, we propose a method for emotion classification of text based on bidirectional encoder representation from transformers (BERT) and broad learning system (BLS) in this paper. The texts are input into BERT pre-trained model to obtain context-related word embeddings and all word vectors are averaged to obtain sentence embedding. The feature nodes and enhancement nodes of BLS are used to extract the linear and nonlinear features of text, and three cascading structures of BLS are designed to transform input data to improve the ability of text feature extraction. The two groups of features are fused and input into the output layer to obtain the probability distribution of each kind of emotion, so as to achieve emotion classification. Extensive experiments are conducted on datasets from SemEval-2019 Task 3 and SMP2020-EWECT, and the experimental results show that our proposed method can better reduce the training time and improve the classification performance than that of the baseline methods.