Future Internet

3 pages, 156 KiB

Open AccessEditorial

Multimedia Quality of Experience (QoE): Current Status and Future Direction

by Chaminda Hewage and Erhan Ekmekcioglu

Future Internet 2020, 12(7), 121; https://doi.org/10.3390/fi12070121 - 20 Jul 2020

Cited by 8 | Viewed by 3063

Quality of Experience (QoE) is becoming an important factor of User-Centred Design (UCD). The deployment of pure technical measures such as Quality of Service (QoS) parameters to assess the quality of multimedia applications is phasing out due to the failure of those methods [...] Read more.

Quality of Experience (QoE) is becoming an important factor of User-Centred Design (UCD). The deployment of pure technical measures such as Quality of Service (QoS) parameters to assess the quality of multimedia applications is phasing out due to the failure of those methods to quantify true user satisfaction. Though significant research results and several deployments have occurred and been realized over the last few years, focusing on QoE-based multimedia technologies, several issues both of theoretical and practical importance remain open. Accordingly, the papers of this Special Issue are significant contribution samples within the general ecosystem highlighted above, ranging from QoE in the capture, processing and consumption of next-generation multimedia applications. In particular, a total of five excellent articles have been accepted, following a rigorous review process, which address many of the aforementioned challenges and beyond. Full article

(This article belongs to the Special Issue Multimedia Quality of Experience (QoE): Current Status and Future Direction)

23 pages, 4241 KiB

Open AccessArticle

A Decoding-Complexity and Rate-Controlled Video-Coding Algorithm for HEVC

by Thanuja Mallikarachchi, Dumidu Talagala, Hemantha Kodikara Arachchi, Chaminda Hewage and Anil Fernando

Future Internet 2020, 12(7), 120; https://doi.org/10.3390/fi12070120 - 16 Jul 2020

Cited by 11 | Viewed by 2816

Abstract

Video playback on mobile consumer electronic (CE) devices is plagued by fluctuations in the network bandwidth and by limitations in processing and energy availability at the individual devices. Seen as a potential solution, the state-of-the-art adaptive streaming mechanisms address the first aspect, yet [...] Read more.

Video playback on mobile consumer electronic (CE) devices is plagued by fluctuations in the network bandwidth and by limitations in processing and energy availability at the individual devices. Seen as a potential solution, the state-of-the-art adaptive streaming mechanisms address the first aspect, yet the efficient control of the decoding-complexity and the energy use when decoding the video remain unaddressed. The quality of experience (QoE) of the end-users’ experiences, however, depends on the capability to adapt the bit streams to both these constraints (i.e., network bandwidth and device’s energy availability). As a solution, this paper proposes an encoding framework that is capable of generating video bit streams with arbitrary bit rates and decoding-complexity levels using a decoding-complexity–rate–distortion model. The proposed algorithm allocates rate and decoding-complexity levels across frames and coding tree units (CTUs) and adaptively derives the CTU-level coding parameters to achieve their imposed targets with minimal distortion. The experimental results reveal that the proposed algorithm can achieve the target bit rate and the decoding-complexity with 0.4% and 1.78% average errors, respectively, for multiple bit rate and decoding-complexity levels. The proposed algorithm also demonstrates a stable frame-wise rate and decoding-complexity control capability when achieving a decoding-complexity reduction of 10.11 (%/dB). The resultant decoding-complexity reduction translates into an overall energy-consumption reduction of up to 10.52 (%/dB) for a 1 dB peak signal-to-noise ratio (PSNR) quality loss compared to the HM 16.0 encoded bit streams. Full article

(This article belongs to the Special Issue Multimedia Quality of Experience (QoE): Current Status and Future Direction)

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24 pages, 5611 KiB

Open AccessArticle

Intrusion Detection for in-Vehicle Communication Networks: An Unsupervised Kohonen SOM Approach

by Vita Santa Barletta, Danilo Caivano, Antonella Nannavecchia and Michele Scalera

Future Internet 2020, 12(7), 119; https://doi.org/10.3390/fi12070119 - 14 Jul 2020

Cited by 51 | Viewed by 4360

Abstract

The diffusion of embedded and portable communication devices on modern vehicles entails new security risks since in-vehicle communication protocols are still insecure and vulnerable to attacks. Increasing interest is being given to the implementation of automotive cybersecurity systems. In this work we propose [...] Read more.

The diffusion of embedded and portable communication devices on modern vehicles entails new security risks since in-vehicle communication protocols are still insecure and vulnerable to attacks. Increasing interest is being given to the implementation of automotive cybersecurity systems. In this work we propose an efficient and high-performing intrusion detection system based on an unsupervised Kohonen Self-Organizing Map (SOM) network, to identify attack messages sent on a Controller Area Network (CAN) bus. The SOM network found a wide range of applications in intrusion detection because of its features of high detection rate, short training time, and high versatility. We propose to extend the SOM network to intrusion detection on in-vehicle CAN buses. Many hybrid approaches were proposed to combine the SOM network with other clustering methods, such as the k-means algorithm, in order to improve the accuracy of the model. We introduced a novel distance-based procedure to integrate the SOM network with the K-means algorithm and compared it with the traditional procedure. The models were tested on a car hacking dataset concerning traffic data messages sent on a CAN bus, characterized by a large volume of traffic with a low number of features and highly imbalanced data distribution. The experimentation showed that the proposed method greatly improved detection accuracy over the traditional approach. Full article

(This article belongs to the Special Issue Vehicular Networks and Mobility as Service)

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20 pages, 412 KiB

Open AccessArticle

Collaborative Facilitation and Collaborative Inhibition in Virtual Environments

by Andrea Guazzini, Elisa Guidi, Cristina Cecchini and Eiko Yoneki

Future Internet 2020, 12(7), 118; https://doi.org/10.3390/fi12070118 - 13 Jul 2020

Cited by 7 | Viewed by 3646

Abstract

Worldwide, organizations and small and medium-sized enterprises have already disruptively changed in many ways their physiological inner mechanisms, because of information and communication technologies (ICT) revolution. Nevertheless, the still ongoing COVID-19 worldwide emergency definitely promoted a wide adoption of teleworking modalities for many [...] Read more.

Worldwide, organizations and small and medium-sized enterprises have already disruptively changed in many ways their physiological inner mechanisms, because of information and communication technologies (ICT) revolution. Nevertheless, the still ongoing COVID-19 worldwide emergency definitely promoted a wide adoption of teleworking modalities for many people around the world, making it more relevant than before to understand the real impact of virtual environments (VEs) on teamwork dynamics. From a psychological point of view, a critical question about teleworking modalities is how the social and cognitive dynamics of collaborative facilitation and collaborative inhibition would affect teamwork within VEs. This study analyzed the impact of a virtual environment (VE) on the recall of individuals and members of nominal and collaborative groups. The research assessed costs and benefits for collaborative retrieval by testing the effect of experimental conditions, stimulus materials, group size, experimental conditions order, anxiety state, personality traits, gender group composition and social interactions. A total of 144 participants were engaged in a virtual Deese-Roediger-McDermott (DRM) classical paradigm, which involved remembering word lists across two successive sessions, in one of four protocols: I-individual/nominal,

I I

-nominal/individual,

I I I

-nominal/collaborative,

I V

-collaborative/nominal. Results suggested, in general, a reduced collaborative inhibition effect in the collaborative condition than the nominal and individual condition. A combined effect between experimental condition and difficulty of the task appears to explain the presence of collaborative inhibition or facilitation. Nominal groups appeared to enhance the collaborative groups’ performance when virtual nominal groups come before collaborative groups. Variables such as personality traits, gender and social interactions may have a contribution to collaborative retrieval. In conclusion, this study indicated how VEs could maintain those peculiar social dynamics characterizing the participants’ engagement in a task, both working together and individually, and could affect their intrinsic motivation as well as performances. These results could be exploited in order to design brand new and evidenced-based practices, to improve teleworking procedures and workers well-being, as well as teleworking teamwork effectiveness. Full article

(This article belongs to the Special Issue Selected Papers from the INSCI2019: Internet Science 2019)

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4 pages, 163 KiB

Open AccessEditorial

Innovative Topologies and Algorithms for Neural Networks

by Salvatore Graziani and Maria Gabriella Xibilia

Future Internet 2020, 12(7), 117; https://doi.org/10.3390/fi12070117 - 11 Jul 2020

Cited by 3 | Viewed by 2476

Abstract

The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved the state of the art in many applications, such as computer vision, [...] Read more.

The introduction of new topologies and training procedures to deep neural networks has solicited a renewed interest in the field of neural computation. The use of deep structures has significantly improved the state of the art in many applications, such as computer vision, speech and text processing, medical applications, and IoT (Internet of Things). The probability of a successful outcome from a neural network is linked to selection of an appropriate network architecture and training algorithm. Accordingly, much of the recent research on neural networks is devoted to the study and proposal of novel architectures, including solutions tailored to specific problems. The papers of this Special Issue make significant contributions to the above-mentioned fields by merging theoretical aspects and relevant applications. Twelve papers are collected in the issue, addressing many relevant aspects of the topic. Full article

(This article belongs to the Special Issue Innovative Topologies and Algorithms for Neural Networks)

3 pages, 188 KiB

Open AccessEditorial

5G-V2X Communications and Networking for Connected and Autonomous Vehicles

by Antonella Molinaro, Claudia Campolo, Jérôme Härri, Christian Esteve Rothenberg and Alexey Vinel

Future Internet 2020, 12(7), 116; https://doi.org/10.3390/fi12070116 - 08 Jul 2020

Cited by 2 | Viewed by 3617

Abstract

In the last decade, there has been a surge in interest in connected and automated vehicles (CAVs) and related enabling technologies in the fields of communication, automation, computing, sensing, and positioning [...] Full article

(This article belongs to the Special Issue 5G-V2X Communications and Networking for Connected and Autonomous Vehicles)

11 pages, 1890 KiB

Open AccessArticle

Science Cafés, Science Shops and the Lockdown Experience in Florence and Rome

by Giovanna Pacini, Cinzia Belmonte and Franco Bagnoli

Future Internet 2020, 12(7), 115; https://doi.org/10.3390/fi12070115 - 08 Jul 2020

Cited by 1 | Viewed by 2800

Abstract

The lockdown was crucial to stop the COVID-19 pandemic in Italy, but it affected many aspects of social life, among which traditional live science cafés. Moreover, citizens and experts asked for a direct contact, not relying on mass-media communication. In this paper, we [...] Read more.

The lockdown was crucial to stop the COVID-19 pandemic in Italy, but it affected many aspects of social life, among which traditional live science cafés. Moreover, citizens and experts asked for a direct contact, not relying on mass-media communication. In this paper, we describe how the Florence and Rome science cafés, contacted by citizens and experts, either directly or through the Florence science shop, responded to these needs by organizing online versions of traditional face-to-face events, experiencing high levels of participation. The science café methodology was also requested by a high school that needed to conclude an engagement experience with students and their families. We also report the results of a survey about the satisfaction of this new methodology with respect to the old one. Full article

(This article belongs to the Special Issue Selected Papers from the INSCI2019: Internet Science 2019)

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17 pages, 3851 KiB

Open AccessArticle

An IoT-Based Framework for Smart Water Supply Systems Management

by Rosiberto Gonçalves, Jesse J. M. Soares and Ricardo M. F. Lima

Future Internet 2020, 12(7), 114; https://doi.org/10.3390/fi12070114 - 07 Jul 2020

Cited by 27 | Viewed by 6980

Abstract

The world’s population growth and climate changes increase the demand for high-quality water. This fact forces humankind to create new water management strategies. Smart cities have successfully applied the Internet of Things (IoT) technology in many sectors. Moreover, Complex Event Processing (CEP) can [...] Read more.

The world’s population growth and climate changes increase the demand for high-quality water. This fact forces humankind to create new water management strategies. Smart cities have successfully applied the Internet of Things (IoT) technology in many sectors. Moreover, Complex Event Processing (CEP) can analyze and process large data sets produced by IoT sensors in real-time. Traditional business processes are too rigid in expressing the dynamic behavior of water supply systems. Every execution path must be explicitly specified. On the other hand, declarative business processes allow execution paths that are not prohibited by the rules, providing more flexibility for water supply managers. This paper joins together IoT, CEP, and declarative processes to create a powerful, efficient, and flexible architecture (REFlex Water) to manage water supply systems. To the knowledge of the authors, REFlex Water is the first solution to combine these technologies in the context of water supply systems. The paper describes the REFlex Water architecture and demonstrates its application to a real water system from a Brazilian municipality. Results are promising, and the managers from the Brazilian water company are expanding the use of REFlex Water to other sectors of their water supply system. Full article

(This article belongs to the Special Issue Internet of Things for Smart City Applications)

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22 pages, 557 KiB

Open AccessReview

An Updated Survey of Efficient Hardware Architectures for Accelerating Deep Convolutional Neural Networks

by Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Muhammad Shafique, Guido Masera and Maurizio Martina

Future Internet 2020, 12(7), 113; https://doi.org/10.3390/fi12070113 - 07 Jul 2020

Cited by 104 | Viewed by 12524

Abstract

Deep Neural Networks (DNNs) are nowadays a common practice in most of the Artificial Intelligence (AI) applications. Their ability to go beyond human precision has made these networks a milestone in the history of AI. However, while on the one hand they present [...] Read more.

Deep Neural Networks (DNNs) are nowadays a common practice in most of the Artificial Intelligence (AI) applications. Their ability to go beyond human precision has made these networks a milestone in the history of AI. However, while on the one hand they present cutting edge performance, on the other hand they require enormous computing power. For this reason, numerous optimization techniques at the hardware and software level, and specialized architectures, have been developed to process these models with high performance and power/energy efficiency without affecting their accuracy. In the past, multiple surveys have been reported to provide an overview of different architectures and optimization techniques for efficient execution of Deep Learning (DL) algorithms. This work aims at providing an up-to-date survey, especially covering the prominent works from the last 3 years of the hardware architectures research for DNNs. In this paper, the reader will first understand what a hardware accelerator is, and what are its main components, followed by the latest techniques in the field of dataflow, reconfigurability, variable bit-width, and sparsity. Full article

(This article belongs to the Collection Featured Reviews of Future Internet Research)

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28 pages, 1939 KiB

Open AccessArticle

A Study on Design Requirement Development and Satisfaction for Future Virtual World Systems

by Bingqing Shen, Weiming Tan, Jingzhi Guo, Hongming Cai, Bin Wang and Shuaihe Zhuo

Future Internet 2020, 12(7), 112; https://doi.org/10.3390/fi12070112 - 06 Jul 2020

Cited by 14 | Viewed by 5028

Abstract

Virtual worlds have become global platforms connecting millions of people and containing various technologies. For example, No Man’s Sky (nomanssky.com), a cross-platform virtual world, can dynamically and automatically generate content with the progress of user adventure. AltspaceVR (altvr.com) is a social virtual reality [...] Read more.

Virtual worlds have become global platforms connecting millions of people and containing various technologies. For example, No Man’s Sky (nomanssky.com), a cross-platform virtual world, can dynamically and automatically generate content with the progress of user adventure. AltspaceVR (altvr.com) is a social virtual reality platform supporting motion capture through Microsoft’s Kinect, eye tracking, and mixed reality extension. The changes in industrial investment, market revenue, user population, and consumption drive the evolution of virtual-world-related technologies (e.g., computing infrastructure and interaction devices), which turns into new design requirements and thus results in the requirement satisfaction problem in virtual world system architecture design. In this paper, we first study the new or evolving features of virtual worlds and emerging requirements of system development through market/industry trend analysis, including infrastructure mobility, content diversity, function interconnectivity, immersive environment, and intelligent agents. Based on the trend analysis, we propose a new design requirement space. We, then, discuss the requirement satisfaction of existing system architectures and highlight their limitations through a literature review. The feature-based requirement satisfaction comparison of existing system architectures sheds some light on the future virtual world system development to match the changing trends of the user market. At the end of this study, a new architecture from an ongoing research, called Virtual Net, is discussed, which can provide higher resource sufficiency, computing reliability, content persistency, and service credibility. Full article

(This article belongs to the Special Issue VR, AR, and 3-D User Interfaces for Measurement and Control)

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27 pages, 26378 KiB

Open AccessArticle

Human Psychophysiological Activity Estimation Based on Smartphone Camera and Wearable Electronics

by Alexey Kashevnik, Mikhail Kruglov, Igor Lashkov, Nikolay Teslya, Polina Mikhailova, Evgeny Ripachev, Vladislav Malutin, Nikita Saveliev and Igor Ryabchikov

Future Internet 2020, 12(7), 111; https://doi.org/10.3390/fi12070111 - 01 Jul 2020

Cited by 7 | Viewed by 4500

Abstract

This paper presents a study related to human psychophysiological activity estimation based on a smartphone camera and sensors. In recent years, awareness of the human body, as well as human mental states, has become more and more popular. Yoga and meditation practices have [...] Read more.

This paper presents a study related to human psychophysiological activity estimation based on a smartphone camera and sensors. In recent years, awareness of the human body, as well as human mental states, has become more and more popular. Yoga and meditation practices have moved from the east to Europe, the USA, Russia, and other countries, and there are a lot of people who are interested in them. However, recently, people have tried the practice but would prefer an objective assessment. We propose to apply the modern methods of computer vision, pattern recognition, competence management, and dynamic motivation to estimate the quality of the meditation process and provide the users with objective information about their practice. We propose an approach that covers the possibility of recognizing pictures of humans from a smartphone and utilizes wearable electronics to measure the user’s heart rate and motions. We propose a model that allows building meditation estimation scores based on these parameters. Moreover, we propose a meditation expert network through which users can find the coach that is most appropriate for him/her. Finally, we propose the dynamic motivation model, which encourages people to perform the practice every day. Full article

(This article belongs to the Special Issue Recent Advances of Machine Learning Techniques on Smartphones)

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17 pages, 540 KiB

Open AccessArticle

Investigating the Relationship between Personality and Technology Acceptance with a Focus on the Smartphone from a Gender Perspective: Results of an Exploratory Survey Study

by Cornelia Sindermann, René Riedl and Christian Montag

Future Internet 2020, 12(7), 110; https://doi.org/10.3390/fi12070110 - 30 Jun 2020

Cited by 11 | Viewed by 4205

Abstract

Prior research found that user personality significantly affects technology acceptance perceptions and decisions. Yet, evidence on the moderating influence of user gender on the relationship between personality and technology acceptance is barely existent despite theoretical consideration. Considering this research gap, the present study [...] Read more.

Prior research found that user personality significantly affects technology acceptance perceptions and decisions. Yet, evidence on the moderating influence of user gender on the relationship between personality and technology acceptance is barely existent despite theoretical consideration. Considering this research gap, the present study reports the results of a survey in which we examined the relationships between personality and technology acceptance from a gender perspective. This study draws upon a sample of N = 686 participants (n = 209 men, n = 477 women) and applied the HEXACO Personality Inventory—Revised along with established technology acceptance measures. The major result of this study is that we do not find significant influence of user gender on the relationship between personality and technology acceptance, except for one aspect of personality, namely altruism. We found a negative association between altruism and intention to use the smartphone in men, but a positive association in women. Consistent with this finding, we also found the same association pattern for altruism and predicted usage: a negative one in men and a positive one in women. Implications for research and practice are discussed, along with limitations of the present study and possible avenues for future research. Full article

(This article belongs to the Special Issue Selected Papers from the INSCI2019: Internet Science 2019)

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14 pages, 5204 KiB

Open AccessArticle

Employing a Chatbot for News Dissemination during Crisis: Design, Implementation and Evaluation

by Theodora A. Maniou and Andreas Veglis

Future Internet 2020, 12(7), 109; https://doi.org/10.3390/fi12070109 - 30 Jun 2020

Cited by 37 | Viewed by 8140

Abstract

The use of chatbots in news media platforms, although relatively recent, offers many advantages to journalists and media professionals and, at the same time, facilitates users’ interaction with useful and timely information. This study shows the usability of a news chatbot during a [...] Read more.

The use of chatbots in news media platforms, although relatively recent, offers many advantages to journalists and media professionals and, at the same time, facilitates users’ interaction with useful and timely information. This study shows the usability of a news chatbot during a crisis situation, employing the 2020 COVID-19 pandemic as a case study. The basic targets of the research are to design and implement a chatbot in a news media platform with a two-fold aim in regard to evaluation: first, the technical effort of creating a functional and robust news chatbot in a crisis situation both from the AI perspective and interoperability with other platforms, which constitutes the novelty of the approach; and second, users’ perception regarding the appropriation of this news chatbot as an alternative means of accessing existing information during a crisis situation. The chatbot designed was evaluated in terms of effectively fulfilling the social responsibility function of crisis reporting, to deliver timely and accurate information on the COVID-19 pandemic to a wide audience. In this light, this study shows the advantages of implementing chatbots in news platforms during a crisis situation, when the audience’s needs for timely and accurate information rapidly increase. Full article

(This article belongs to the Special Issue Data Science and Knowledge Discovery)

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Future Internet, Volume 12, Issue 7 (July 2020) – 13 articles

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