University of Piraeus

The metaverse has the potential to extend the physical world using augmented and virtual reality technologies allowing users to seamlessly interact within real and simulated environments using avatars and holograms. Virtual environments and immersive games (such as, Second Life, Fortnite, Roblox and VRChat) have been described as antecedents of the metaverse and offer some insight to the potential socio-economic impact of a fully functional persistent cross platform metaverse. Separating the hype and “meta…” rebranding from current reality is difficult, as “big tech” paints a picture of the transformative nature of the metaverse and how it will positively impact people in their work, leisure, and social interaction. The potential impact on the way we conduct business, interact with brands and others, and develop shared experiences is likely to be transformational as the distinct lines between physical and digital are likely to be somewhat blurred from current perceptions. However, although the technology and infrastructure does not yet exist to allow the development of new immersive virtual worlds at scale - one that our avatars could transcend across platforms, researchers are increasingly examining the transformative impact of the metaverse. Impacted sectors include marketing, education, healthcare as well as societal effects relating to social interaction factors from widespread adoption, and issues relating to trust, privacy, bias, disinformation, application of law as well as psychological aspects linked to addiction and impact on vulnerable people. This study examines these topics in detail by combining the informed narrative and multi-perspective approach from experts with varied disciplinary backgrounds on many aspects of the metaverse and its transformational impact. The paper concludes by proposing a future research agenda that is valuable for researchers, professionals and policy makers alike.

This work provides a systematic literature review of blockchain-based applications across multiple domains. The aim is to investigate the current state of blockchain technology and its applications and to highlight how specific characteristics of this disruptive technology can revolutionise “business-as-usual” practices. To this end, the theoretical underpinnings of numerous research papers published in high ranked scientific journals during the last decade, along with several reports from grey literature as a means of streamlining our assessment and capturing the continuously expanding blockchain domain, are included in this review. Based on a structured, systematic review and thematic content analysis of the discovered literature, we present a comprehensive classification of blockchain-enabled applications across diverse sectors such as supply chain, business, healthcare, IoT, privacy, and data management, and we establish key themes, trends and emerging areas for research. We also point to the shortcomings identified in the relevant literature, particularly limitations the blockchain technology presents and how these limitations spawn across different sectors and industries. Building on these findings, we identify various research gaps and future exploratory directions that are anticipated to be of significant value both for academics and practitioners.

The distributed nature and dynamic topology of Wireless Sensor Networks (WSNs) introduces very special requirements in routing protocols that should be met. The most important feature of a routing protocol, in order to be efficient for WSNs, is the energy consumption and the extension of the network's lifetime. During the recent years, many energy efficient routing protocols have been proposed for WSNs. In this paper, energy efficient routing protocols are classified into four main schemes: Network Structure, Communication Model, Topology Based and Reliable Routing. The routing protocols belonging to the first category can be further classified as flat or hierarchical. The routing protocols belonging to the second category can be further classified as Query-based or Coherent and non-coherent-based or Negotiation-based. The routing protocols belonging to the third category can be further classified as Location-based or Mobile Agent-based. The routing protocols belonging to the fourth category can be further classified as QoS-based or Multipath-based. Then, an analytical survey on energy efficient routing protocols for WSNs is provided. In this paper, the classification initially proposed by Al-Karaki, is expanded, in order to enhance all the proposed papers since 2004 and to better describe which issues/operations in each protocol illustrate/enhance the energy-efficiency issues.

Small and medium-sized enterprises (SMEs) are increasingly aware of the benefits of closing loops and improving resource efficiency, such as saving material costs, creating competitive advantages, and accessing new markets. At the same time, however, various barriers pose challenges to small businesses in their transition to a circular economy, namely a lack of financial resources and lack of technical skills. The aim of this paper is to increase knowledge and understanding about the barriers and enablers experienced by SMEs when implementing circular economy business models. Looking first at the barriers that prevent SMEs from realising the benefits of the circular economy, an investigation is carried out in the form of a literature review and an analysis of a sample of SME case studies that are featured on the GreenEcoNet EU-funded web platform. Several enabling factors that help SMEs adopt circular economy practices are then identified. The paper concludes that although various policy instruments are available to help SMEs incorporate circular economy principles into their business models, several barriers remain. The authors recommend that European and national policies strengthen their focus on greening consumer preferences, market value chains and company cultures, and support the recognition of SMEs’ green business models. This can be achieved through the creation of dedicated marketplaces and communities of practice, for example.

The increasing need for mobility has brought about significant changes in transportation infrastructures. Inefficiencies cause enormous losses of time, decrease in the level of safety for both vehicles and pedestrians, high pollution, degradation of quality of life, and huge waste of nonrenewable fossil energy.The scope of this article is to introduce novel functionality for providing knowledge to vehicles, thus jointly managing traffic and safety. This will be achieved through the design of the proposed functionality, which, at a high level, will comprise (1) sensor networks formed by vehicles of a certain vicinity that exchange traffic-related information, (2) cognitive management functionality placed inside the vehicles for inferring knowledge and experience, and (3) cognitive management functionality in the overall transportation infrastructure. The goal of the aforementioned three main components shall be to issue directives to the drivers and the overall transportation infrastructure valuable in context handling.

Abstract The initial hype and fanfare from the Meta Platforms view of how the metaverse could be brought to life has evolved into an ongoing discussion of not only the metaverse's impact on users and organizations but also the societal and cultural implications of widespread usage. The potential of consumer interaction with brands within the metaverse has engendered significant debate within the marketing‐focused discourse on the key challenges and transformative opportunities for marketers. Drawing on insights from expert contributors, this study examines the marketing implications of the hypothetical widespread adoption of the metaverse. We identify new research directions and propose a new framework offering valuable contributions for academia, practice, and policy makers. Our future research agenda culminates in a checklist for researchers which clarifies how the metaverse can be beneficial to digital marketing and advertising, branding, services, value creation, and consumer wellbeing.

BACKGROUND: Ovarian cancer continues to have a poor prognosis with the majority of women diagnosed with advanced disease. Therefore, we undertook the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) to determine if population screening can reduce deaths due to the disease. We report on ovarian cancer mortality after long-term follow-up in UKCTOCS. METHODS: In this randomised controlled trial, postmenopausal women aged 50-74 years were recruited from 13 centres in National Health Service trusts in England, Wales, and Northern Ireland. Exclusion criteria were bilateral oophorectomy, previous ovarian or active non-ovarian malignancy, or increased familial ovarian cancer risk. The trial management system confirmed eligibility and randomly allocated participants in blocks of 32 using computer generated random numbers to annual multimodal screening (MMS), annual transvaginal ultrasound screening (USS), or no screening, in a 1:1:2 ratio. Follow-up was through national registries. The primary outcome was death due to ovarian or tubal cancer (WHO 2014 criteria) by June 30, 2020. Analyses were by intention to screen, comparing MMS and USS separately with no screening using the versatile test. Investigators and participants were aware of screening type, whereas the outcomes review committee were masked to randomisation group. This study is registered with ISRCTN, 22488978, and ClinicalTrials.gov, NCT00058032. FINDINGS: Between April 17, 2001, and Sept 29, 2005, of 1 243 282 women invited, 202 638 were recruited and randomly assigned, and 202 562 were included in the analysis: 50 625 (25·0%) in the MMS group, 50 623 (25·0%) in the USS group, and 101 314 (50·0%) in the no screening group. At a median follow-up of 16·3 years (IQR 15·1-17·3), 2055 women were diagnosed with tubal or ovarian cancer: 522 (1·0%) of 50 625 in the MMS group, 517 (1·0%) of 50 623 in the USS group, and 1016 (1·0%) of 101 314 in the no screening group. Compared with no screening, there was a 47·2% (95% CI 19·7 to 81·1) increase in stage I and 24·5% (-41·8 to -2·0) decrease in stage IV disease incidence in the MMS group. Overall the incidence of stage I or II disease was 39·2% (95% CI 16·1 to 66·9) higher in the MMS group than in the no screening group, whereas the incidence of stage III or IV disease was 10·2% (-21·3 to 2·4) lower. 1206 women died of the disease: 296 (0·6%) of 50 625 in the MMS group, 291 (0·6%) of 50 623 in the USS group, and 619 (0·6%) of 101 314 in the no screening group. No significant reduction in ovarian and tubal cancer deaths was observed in the MMS (p=0·58) or USS (p=0·36) groups compared with the no screening group. INTERPRETATION: The reduction in stage III or IV disease incidence in the MMS group was not sufficient to translate into lives saved, illustrating the importance of specifying cancer mortality as the primary outcome in screening trials. Given that screening did not significantly reduce ovarian and tubal cancer deaths, general population screening cannot be recommended. FUNDING: National Institute for Health Research, Cancer Research UK, and The Eve Appeal.

The Paris Agreement aims to limit global mean temperature rise this century to well below 2 °C above pre-industrial levels. This target has wide-ranging implications for Europe and its cities, which are the source of substantial greenhouse gas emissions. This paper reports the state of local planning for climate change by collecting and analysing information about local climate mitigation and adaptation plans across 885 urban areas of the EU-28. A typology and framework for analysis was developed that classifies local climate plans in terms of their alignment with spatial (local, national and international) and other climate related policies. Out of eight types of local climate plans identified in total we document three types of stand-alone local climate plans classified as type A1 (autonomously produced plans), A2 (plans produced to comply with national regulations) or A3 (plans developed for international climate networks). There is wide variation among countries in the prevalence of local climate plans, with generally more plans developed by central and northern European cities. Approximately 66% of EU cities have a type A1, A2, or A3 mitigation plan, 26% an adaptation plan, and 17% a joint adaptation and mitigation plan, while about 33% lack any form of stand-alone local climate plan (i.e. what we classify as A1, A2, A3 plans). Mitigation plans are more numerous than adaptation plans, but planning for mitigation does not always precede planning for adaptation. Our analysis reveals that city size, national legislation, and international networks can influence the development of local climate plans. We found that size does matter as about 80% of the cities with above 500,000 inhabitants have a comprehensive and stand-alone mitigation and/or an adaptation plan (A1). Cities in four countries with national climate legislation (A2), i.e. Denmark, France, Slovakia and the United Kingdom, are nearly twice as likely to produce local mitigation plans, and five times more likely to produce local adaptation plans, compared to cities in countries without such legislation. A1 and A2 mitigation plans are particularly numerous in Denmark, Poland, Germany, and Finland; while A1 and A2 adaptation plans are prevalent in Denmark, Finland, UK and France. The integration of adaptation and mitigation is country-specific and can mainly be observed in two countries where local climate plans are compulsory, i.e. France and the UK. Finally, local climate plans produced for international climate networks (A3) are mostly found in the many countries where autonomous (type A1) plans are less common. This is the most comprehensive analysis of local climate planning to date. The findings are of international importance as they will inform and support decision-making towards climate planning and policy development at national, EU and global level being based on the most comprehensive and up-to-date knowledge of local climate planning available to date.

Abstract In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart‐type control charts, multivariate CUSUM control charts and multivariate EWMA control charts. In addition, we review unique procedures for the construction of multivariate control charts, based on multivariate statistical techniques such as principal components analysis (PCA) and partial least squares (PLS). Finally, we describe the most significant methods for the interpretation of an out‐of‐control signal. Copyright © 2006 John Wiley & Sons, Ltd.

The new era of mobile health ushered in by the wide adoption of ubiquitous computing and mobile communications has brought opportunities for governments and companies to rethink their concept of healthcare. Simultaneously, the worldwide urbanization process represents a formidable challenge and attracts attention toward cities that are expected to gather higher populations and provide citizens with services in an efficient and human manner. These two trends have led to the appearance of mobile health and smart cities. In this article we introduce the new concept of smart health, which is the context-aware complement of mobile health within smart cities. We provide an overview of the main fields of knowledge that are involved in the process of building this new concept. Additionally, we discuss the main challenges and opportunities that s-Health would imply and provide a common ground for further research.

Focus on movement data has increased as a consequence of the larger availability of such data due to current GPS, GSM, RFID, and sensors techniques. In parallel, interest in movement has shifted from raw movement data analysis to more application-oriented ways of analyzing segments of movement suitable for the specific purposes of the application. This trend has promoted semantically rich trajectories, rather than raw movement, as the core object of interest in mobility studies. This survey provides the definitions of the basic concepts about mobility data, an analysis of the issues in mobility data management, and a survey of the approaches and techniques for: (i) constructing trajectories from movement tracks, (ii) enriching trajectories with semantic information to enable the desired interpretations of movements, and (iii) using data mining to analyze semantic trajectories and extract knowledge about their characteristics, in particular the behavioral patterns of the moving objects. Last but not least, the article surveys the new privacy issues that arise due to the semantic aspects of trajectories.

The term metaverse is described as the next iteration of the Internet. Metaverse is a virtual platform that uses extended reality technologies, i.e. augmented reality, virtual reality, mixed reality, 3D graphics, and other emerging technologies to allow real-time interactions and experiences in ways that are not possible in the physical world. Companies have begun to notice the impact of the metaverse and how it may help maximize profits. The purpose of this paper is to offer perspectives on several important areas, i.e. marketing, tourism, manufacturing, operations management, education, the retailing industry, banking services, healthcare, and human resource management that are likely to be impacted by the adoption and use of a metaverse. Each includes an overview, opportunities, challenges, and a potential research agenda.

Jamming represents the most serious security threat in the field of wireless sensor networks (WSNs), as it can easily put out of order even WSNs that utilize strong highlayer security mechanisms, simply because it is often ignored in the initial WSN design. The objective of this article is to provide a general overview of the critical issue of jamming in WSNs and cover all the relevant work, providing the interested researcher pointers for open research issues in this field. We provide a brief overview of the communication protocols typically used in WSN deployments and highlight the characteristics of contemporary WSNs, that make them susceptible to jamming attacks, along with the various types of jamming which can be exercised against WSNs. Common jamming techniques and an overview of various types of jammers are reviewed and typical countermeasures against jamming are also analyzed. The key ideas of existing security mechanisms against jamming attacks in WSNs are presented and open research issues, with respect to the defense against jamming attacks are highlighted.

In this paper we present two deep-learning systems that competed at SemEval-2017 Task 4 "Sentiment Analysis in Twitter". We participated in all subtasks for English tweets, involving message-level and topic-based sentiment polarity classification and quantification. We use Long Short-Term Memory (LSTM) networks augmented with two kinds of attention mechanisms, on top of word embeddings pre-trained on a big collection of Twitter messages. Also, we present a text processing tool suitable for social network messages, which performs tokenization, word normalization, segmentation and spell correction. Moreover, our approach uses no hand-crafted features or sentiment lexicons. We ranked 1 st (tie) in Subtask A, and achieved very competitive results in the rest of the Subtasks. Both the word embeddings and our text processing tool 1 are available to the research community.

Business analytics aims to enable organizations to make quicker, better, and more intelligent decisions with the aim to create business value. To date, the major focus in the academic and industrial realms is on descriptive and predictive analytics. Nevertheless, prescriptive analytics, which seeks to find the best course of action for the future, has been increasingly gathering the research interest. Prescriptive analytics is often considered as the next step towards increasing data analytics maturity and leading to optimized decision making ahead of time for business performance improvement. This paper investigates the existing literature pertaining to prescriptive analytics and prominent methods for its implementation, provides clarity on the research field of prescriptive analytics, synthesizes the literature review in order to identify the existing research challenges, and outlines directions for future research.

This paper discusses the use of Augmented Reality (AR) applications for the needs of tourism. It describes the technology's evolution from pilot applications into commercial mobile applications. We address the technical aspects of mobile AR application development, emphasizing the technologies that render the delivery of augmented reality content possible and experientially superior. We examine the state of the art, providing an analysis concerning the development and the objectives of each application. Acknowledging the various technological limitations hindering AR's substantial end-user adoption, the paper proposes a model for developing AR mobile applications for the field of tourism, aiming to release AR's full potential within the field.

As the deployment of Internet of Things (IoT) is experiencing an exponential growth, it is no surprise that many recent cyber attacks are IoT-enabled: the attacker initially exploits some vulnerable IoT technology as a first step toward compromising a critical system that is connected, in some way, with the IoT. For some sectors, like industry, smart grids, transportation, and medical services, the significance of such attacks is obvious, since IoT technologies are part of critical back-end systems. However, in sectors where IoT is usually at the end-user side, like smart homes, such attacks can be underestimated, since not all possible attack paths are examined. In this paper, we survey IoT-enabled cyber attacks, found in all application domains since 2010. For each sector, we emphasize on the latest, verified IoT-enabled attacks, based on known real-world incidents and published proof-of-concept attacks. We methodologically analyze representative attacks that demonstrate direct, indirect, and subliminal attack paths against critical targets. Our goal is threefold: 1) to assess IoT-enabled cyber attacks in a risk-like approach, in order to demonstrate their current threat landscape; 2) to identify hidden and subliminal IoT-enabled attack paths against critical infrastructures and services; and 3) to examine mitigation strategies for all application domains.

Toward the fifth generation (5G) of wireless/mobile broadband, numerous devices and networks will be interconnected and traffic demand will constantly rise. Heterogeneity will also be a feature that is expected to characterize the emerging wireless world, as mixed usage of cells of diverse sizes and access points with different characteristics and technologies in an operating environment are necessary. Wireless networks pose specific requirements that need to be fulfilled. In this respect, approaches for introducing intelligence will be investigated by the research community. Intelligence shall provide energy- and cost-efficient solutions at which a certain application/service/quality provision is achieved. Particularly, the introduction of intelligence in heterogeneous network deployments and the cloud radio-access network (RAN) is investigated. Finally, elaboration on emerging enabling technologies for applying intelligence will focus on the recent concepts of software-defined networking (SDN) and network function virtualization (NFV). This article provided an overview for delivering intelligence toward the 5G of wireless/mobile broadband by taking into account the complex context of operation and essential requirements such as QoE, energy efficiency, cost efficiency, and resource efficiency.

Deep-sea ecosystems represent the largest biome of the global biosphere, but knowledge of their biodiversity is still scant. The Mediterranean basin has been proposed as a hot spot of terrestrial and coastal marine biodiversity but has been supposed to be impoverished of deep-sea species richness. We summarized all available information on benthic biodiversity (Prokaryotes, Foraminifera, Meiofauna, Macrofauna, and Megafauna) in different deep-sea ecosystems of the Mediterranean Sea (200 to more than 4,000 m depth), including open slopes, deep basins, canyons, cold seeps, seamounts, deep-water corals and deep-hypersaline anoxic basins and analyzed overall longitudinal and bathymetric patterns. We show that in contrast to what was expected from the sharp decrease in organic carbon fluxes and reduced faunal abundance, the deep-sea biodiversity of both the eastern and the western basins of the Mediterranean Sea is similarly high. All of the biodiversity components, except Bacteria and Archaea, displayed a decreasing pattern with increasing water depth, but to a different extent for each component. Unlike patterns observed for faunal abundance, highest negative values of the slopes of the biodiversity patterns were observed for Meiofauna, followed by Macrofauna and Megafauna. Comparison of the biodiversity associated with open slopes, deep basins, canyons, and deep-water corals showed that the deep basins were the least diverse. Rarefaction curves allowed us to estimate the expected number of species for each benthic component in different bathymetric ranges. A large fraction of exclusive species was associated with each specific habitat or ecosystem. Thus, each deep-sea ecosystem contributes significantly to overall biodiversity. From theoretical extrapolations we estimate that the overall deep-sea Mediterranean biodiversity (excluding prokaryotes) reaches approximately 2805 species of which about 66% is still undiscovered. Among the biotic components investigated (Prokaryotes excluded), most of the unknown species are within the phylum Nematoda, followed by Foraminifera, but an important fraction of macrofaunal and megafaunal species also remains unknown. Data reported here provide new insights into the patterns of biodiversity in the deep-sea Mediterranean and new clues for future investigations aimed at identifying the factors controlling and threatening deep-sea biodiversity.

The Internet of Things (IoT) is expected to substantially support sustainable development of future smart cities. This article identifies the main issues that may prevent IoT from playing this crucial role, such as the heterogeneity among connected objects and the unreliable nature of associated services. To solve these issues, a cognitive management framework for IoT is proposed, in which dynamically changing real-world objects are represented in a virtualized environment, and where cognition and proximity are used to select the most relevant objects for the purpose of an application in an intelligent and autonomic way. Part of the framework is instantiated in terms of building blocks and demonstrated through a smart city scenario that horizontally spans several application domains. This preliminary proof of concept reveals the high potential that self-reconfigurable IoT can achieve in the context of smart cities.