Showing papers by "University of Piraeus published in 2015"

User recruitment for mobile crowdsensing over opportunistic networks

Abstract: We look into the realization of mobile crowdsensing campaigns that draw on the opportunistic networking paradigm, as practised in delay-tolerant networks but also in the emerging device-to-device communication mode in cellular networks. In particular, we ask how mobile users can be optimally selected in order to generate the required space-time paths across the network for collecting data from a set of fixed locations. The users hold different roles in these paths, from collecting data with their sensing-enabled devices to relaying them across the network and uploading them to data collection points with Internet connectivity. We first consider scenarios with deterministic node mobility and formulate the selection of users as a minimum-cost set cover problem with a submodular objective function. We then generalize to more realistic settings with uncertainty about the user mobility. A methodology is devised for translating the statistics of individual user mobility to statistics of spacetime path formation and feeding them to the set cover problem formulation. We describe practical greedy heuristics for the resulting NP-hard problems and compute their approximation ratios. Our experimentation with real mobility datasets (a) illustrates the multiple tradeoffs between the campaign cost and duration, the bound on the hopcount of space-time paths, and the number of collection points; and (b) provides evidence that in realistic problem instances the heuristics perform much better than what their pessimistic worst-case bounds suggest.

Dual-Hop Communication Over a Satellite Relay and Shadowed Rician Channels

Abstract: A dual-hop amplify-and-forward (AF) relaying scheme over shadowed Rician fading channels is investigated. Specifically, the source and destination nodes are equipped with $N$ and $M$ antennas, respectively, whereas the relay is equipped with a single antenna. Communication via satellite relaying represents a direct application of the considered infrastructure. To this end, we study the scenario when the source and the destination are terrestrial nodes, whereas the end-to-end communication is established through an intermediate AF relay node, which is a satellite. To fully exploit the spatial diversity provided by multiple antennas, maximum ratio transmission and maximum ratio combining are implemented at the source and the destination, respectively. First, a new closed-form expression for the probability density function (pdf) of the sum of independent and identically distributed (i.i.d.) squared shadowed Rician random variables is derived by assuming integer distribution parameters. Capitalizing on the latter pdf, new closed-form results for the cumulative distribution function (cdf) and the moment function of the end-to-end signal-to-noise ratio (SNR) are obtained. Particularly, the proposed unified analysis includes the channel-state-information (CSI)-assisted and the fixed-gain AF relaying protocols. New expressions for important performance measures, namely, the outage probability, the average symbol error probability (ASEP), and the ergodic capacity of the end-to-end SNR, are presented for both AF schemes. Moreover, some useful engineering insights are manifested, such as simplified asymptotic outage performance results, the diversity order, and the impact on the number of antennas at the source and the destination.

Renewable Energy, Output, Carbon Dioxide Emissions, and Oil Prices: Evidence from South America

Abstract: This study utilizes panel cointegration techniques to estimate the long-run relationship as well as the causal dynamics between renewable energy consumption per capita, real gross domestic product (GDP) per capita, carbon dioxide emissions per capita, and real oil prices for a panel of 11 South American countries over the period 1980 to 2010. Specifically, we find the long-run elasticity estimates are positive and statistically significant with respect to real GDP per capita, carbon emissions per capita, and real oil prices. The results of the panel error correction model reveal a feedback relationship among the variables in question, indicative of the importance of renewable energy consumption in both the growth of output and the containment of carbon dioxide emissions.

Trade Credit, Bank Credit, and Flight to Quality: Evidence from French SMEs

Abstract: This paper investigates the impact of the global financial crisis on the allocation of credit to small and medium‐sized enterprises (s). Using samples of rench s from four industries, we found supp...

Ship emissions and their externalities in cruise ports

Abstract: This paper presents an estimation and analysis of ship exhaust emissions and their externalities in the popular cruise destinations of Dubrovnik (Croatia) and Kotor (Montenegro) along the eastern coast of the Adriatic Sea. To this extent, the recent record (2012–2014) of cruise ships calling at these ports is used to model and estimate the ship exhaust emission inventories and externalities within the associated bays and ports. The results indicate that cruise ship traffic produces continuously increasing air pollution in both ports over recent years. More importantly, however, the analysis of the ship operating characteristics reveals that for any given ship traffic involving specific vessels using marine fuel of a given quality, the presence of other factors (e.g. berth availability, berth accessibility etc) can also influence the ship emission levels. This is particularly evident in the case of the port of Kotor where berth space insufficiency dictates the need for ship anchorage thus leading to increased air pollution and costs of associated damage. The application and results of the aforementioned ship activity-based methodology to the ports of Dubrovnik and Kotor improves our understanding of ship emissions in cruise bays and ports, and contributes toward the implementation of port policies for the effective control of air quality in such environmentally sensitive locations.

A Survey of TDMA Scheduling Schemes in Wireless Multihop Networks

Abstract: One of the major problems in wireless multihop networks is the scheduling of transmissions in a fair and efficient manner Time Division Multiple Access (TDMA) seems to be one of the dominant solutions to achieve this goal since it is a simple scheme and can prolong the devices’ lifetime by allowing them to transmit only a portion of the time during conversation For that reason, several TDMA scheduling algorithms may be found in the literature The scope of this article is to classify the existing TDMA scheduling algorithms based on several factors, such as the entity that is scheduled, the network topology information that is needed to produce or maintain the schedule, and the entity or entities that perform the computation that produces and maintains the schedules, and to discuss the advantages and disadvantages of each category

Incremental learning of event definitions with Inductive Logic Programming

Abstract: Event recognition systems rely on knowledge bases of event definitions to infer occurrences of events in time. Using a logical framework for representing and reasoning about events offers direct connections to machine learning, via Inductive Logic Programming (ILP), thus allowing to avoid the tedious and error-prone task of manual knowledge construction. However, learning temporal logical formalisms, which are typically utilized by logic-based event recognition systems is a challenging task, which most ILP systems cannot fully undertake. In addition, event-based data is usually massive and collected at different times and under various circumstances. Ideally, systems that learn from temporal data should be able to operate in an incremental mode, that is, revise prior constructed knowledge in the face of new evidence. In this work we present an incremental method for learning and revising event-based knowledge, in the form of Event Calculus programs. The proposed algorithm relies on abductive---inductive learning and comprises a scalable clause refinement methodology, based on a compressive summarization of clause coverage in a stream of examples. We present an empirical evaluation of our approach on real and synthetic data from activity recognition and city transport applications.

A proactive decision making framework for condition-based maintenance

Abstract: – The purpose of this paper is to perform an extensive literature review in the area of decision making for condition-based maintenance (CBM) and identify possibilities for proactive online recommendations by considering real-time sensor data. Based on these, the paper aims at proposing a framework for proactive decision making in the context of CBM. , – Starting with the manufacturing challenges and the main principles of maintenance, the paper reviews the main frameworks and concepts regarding CBM that have been proposed in the literature. Moreover, the terms of e-maintenance, proactivity and decision making are analysed and their potential relevance to CBM is identified. Then, an extensive literature review of methods and techniques for the various steps of CBM is provided, especially for prognosis and decision support. Based on these, limitations and gaps are identified and a framework for proactive decision making in the context of CBM is proposed. , – In the proposed framework for proactive decision making, the CBM concept is enriched in the sense that it is structured into two components: the information space and the decision space. Moreover, it is extended in a way that decision space is further analyzed according to the types of recommendations that can be provided. Moreover, possible inputs and outputs of each step are identified. , – The paper provides a framework for CBM representing the steps that need to be followed for proactive recommendations as well as the types of recommendations that can be given. The framework can be used by maintenance management of a company in order to conduct CBM by utilizing real-time sensor data depending on the type of decision required. , – The results of the work presented in this paper form the basis for the development and implementation of proactive Decision Support System (DSS) in the context of maintenance.

Competitive advantage: the known unknown concept

Abstract: Purpose – The purpose of this paper is to investigate empirically managers’ awareness regarding the concept of competitive advantage, the most taken-for-granted concept in the field of strategic management. Design/methodology/approach – Managers’ awareness regarding the concept of competitive advantage was explored by applying a cross-sectional, self-administered, e-mail survey. Findings – The results of quantitative and qualitative data analyses provide empirical evidence that senior managers, who are heavily involved in the strategic management process of their firms, seem to confuse the concept of competitive advantage with the concept of sources of competitive advantage, especially those pertaining to resource-based theory. Research limitations/implications – The findings establish the hypothesis that senior managers are not aware of the concept of competitive advantage. At the same time, future researchers are encouraged to continue testing the above hypothesis. Practical implications – The findings ...

The Circular Economy: Barriers and Opportunities for SMEs

Abstract: The ‘circular economy’ is gaining momentum as a concept in both academic and policy circles, while circular business models have been linked to significant economic benefits. This paper identifies key barriers and enablers to adopting circular economy business practices, using input from a literature review, discussions held in the context of the GreenEcoNet project and an analysis of two SME circular business models. Main policy messages

Fuzzy Logic for Adaptive Instruction in an E-learning Environment for Computer Programming

Abstract: In this paper, a novel approach to web-based education that performs individualized instruction on the domain of programming languages is presented. This approach is fully implemented and evaluated in an educational application module, called fuzzy knowledge state definer (FuzKSD). In particular, FuzKSD performs user modeling by dynamically identifying and updating a student's knowledge level of all the concepts of the domain knowledge. The operation of FuzKSD is based on fuzzy cognitive maps (FCMs) that are used to represent the dependences among the domain concepts. FuzKSD uses fuzzy sets to represent a student's knowledge level as a subset of the domain knowledge. Thus, it combines fuzzy theory with the overlay model. Moreover, it employs a novel inference mechanism that dynamically updates user stereotypes using fuzzy sets. It should be noted that the overlay model and stereotypes constitute two widely used methods for user modeling. However, they have not been combined with fuzzy sets thus far in the literature. The gain from this novel combination is significant as a student level of knowledge is represented in a more realistic way by automatically modeling the learning or forgetting process of a student with respect to the FCMs and thus the system can provide individualized adaptive advice. The application of this approach is not limited to adaptive instruction. It can also be used in other systems with changeable user states, such as e-shops, where consumers' preferences change over time and affect one another. Therefore, the particular module constitutes a novel generic fuzzy tool, which offers dynamic adaptation to users' needs and preferences of adaptive systems.

Ultra Dense Networks: The New Wireless Frontier for Enabling 5G Access

Abstract: The extreme traffic load that future wireless networks are expected to accommodate requires a re-thinking of the system design. Initial estimations indicate that, different from the evolutionary path of previous cellular generations that was based on spectral efficiency improvements, the most substantial amount of future system performance gains will be obtained by means of network infrastructure densification. By increasing the density of operator-deployed infrastructure elements, along with incorporation of user-deployed access nodes and mobile user devices acting as "infrastructure prosumers", it is expected that having one or more access nodes exclusively dedicated to each user will become feasible, introducing the ultra dense network (UDN) paradigm. Although it is clear that UDNs are able to take advantage of the significant benefits provided by proximal transmissions and increased spatial reuse of system resources, at the same time, large node density and irregular deployment introduce new challenges, mainly due to the interference environment characteristics that are vastly different from previous cellular deployments. This article attempts to provide insights on fundamental issues related to UDN deployment, such as determining the infrastructure density required to support given traffic load requirements and the benefits of network-wise coordination, demonstrating the potential of UDNs for 5G wireless networks.

Privacy-Preserving Indoor Localization on Smartphones

Abstract: Indoor Positioning Systems (IPS) have recently received considerable attention, mainly because GPS is unavailable in indoor spaces and consumes considerable energy On the other hand, predominant Smartphone OS localization subsystems currently rely on server-side localization processes, allowing the service provider to know the location of a user at all times In this paper, we propose an innovative algorithm for protecting users from location tracking by the localization service, without hindering the provisioning of fine-grained location updates on a continuous basis Our proposed Temporal Vector Map (TVM) algorithm, allows a user to accurately localize by exploiting a $k$ -Anonymity Bloom (kAB) filter and a bestNeighbors generator of camouflaged localization requests, both of which are shown to be resilient to a variety of privacy attacks We have evaluated our framework using a real prototype developed in Android and Hadoop HBase as well as realistic Wi-Fi traces scaling-up to several GBs Our analytical evaluation and experimental study reveal that TVM is not vulnerable to attacks that traditionally compromise k-anonymity protection and indicate that TVM can offer fine-grained localization in approximately four orders of magnitude less energy and number of messages than competitive approaches

The Baquara2 knowledge-based framework for semantic enrichment and analysis of movement data

Abstract: The analysis of movements frequently requires more than just spatio-temporal data. Thus, despite recent progresses in trajectory handling, there is still a gap between movement data and formal semantics. This gap hinders movement analyses benefiting from available knowledge, with well-defined and widely agreed semantics. This article describes the Baquara2 framework to help narrow this gap by exploiting knowledge bases to semantically enrich and analyze movement data. It provides an ontological model for structuring and abstracting movement data in a multilevel hierarchy of progressively detailed movement segments that generalize concepts such as trajectories, stops, and moves. Baquara2 also includes a general customizable process to annotate movement data with concepts and objects described in ontologies and Linked Open Data (LOD) collections. The resulting semantic annotations enable queries for movement analyses based on application and domain specific knowledge. The proposed framework has been used in experiments to semantically enrich movement data collected from social media with geo-referenced LOD. The obtained results enable powerful queries that illustrate Baquara2 capabilities.

Probabilistic Event Calculus for Event Recognition

Abstract: Symbolic event recognition systems have been successfully applied to a variety of application domains, extracting useful information in the form of events, allowing experts or other systems to monitor and respond when significant events are recognised. In a typical event recognition application, however, these systems often have to deal with a significant amount of uncertainty. In this article, we address the issue of uncertainty in logic-based event recognition by extending the Event Calculus with probabilistic reasoning. Markov logic networks are a natural candidate for our logic-based formalism. However, the temporal semantics of the Event Calculus introduce a number of challenges for the proposed model. We show how and under what assumptions we can overcome these problems. Additionally, we study how probabilistic modelling changes the behaviour of the formalism, affecting its key property—the inertia of fluents. Furthermore, we demonstrate the advantages of the probabilistic Event Calculus through examples and experiments in the domain of activity recognition, using a publicly available dataset for video surveillance.

Hands-On Experiences in Deploying Cost-Effective Ambient-Assisted Living Systems

Abstract: Older adults’ preferences to remain independent in their own homes along with the high costs of nursing home care have motivated the development of Ambient Assisted Living (AAL) technologies which aim at improving the safety, health conditions and wellness of the elderly. This paper reports hands-on experiences in designing, implementing and operating UbiCare, an AAL based prototype system for elderly home care monitoring. The monitoring is based on the recording of environmental parameters like temperature and light intensity as well as micro-level incidents which allows one to infer daily activities like moving, sitting, sleeping, usage of electrical appliances and plumbing components. The prototype is built upon inexpensive, off-the-shelf hardware (e.g., various sensors, Arduino microcontrollers, ZigBee-compatible wireless communication modules) and license-free software, thereby ensuring low system deployment costs. The network comprises nodes placed in a house’s main rooms or mounted on furniture, one wearable node, one actuator node and a centralized processing element (coordinator). Upon detecting significant deviations from the ordinary activity patterns of individuals and/or sudden falls, the system issues automated alarms which may be forwarded to authorized caregivers via a variety of communication channels. Furthermore, measured environmental parameters and activity incidents may be monitored through standard web interfaces.

Design and management of vehicle-sharing systems: a survey of algorithmic approaches

Abstract: Vehicle (bike or car) sharing represents an emerging transportation scheme which may comprise an important link in the green mobility chain of smart city environments. This chapter offers a comprehensive review of algorithmic approaches for the design and management of vehicle-sharing systems. Our focus is on one-way vehicle-sharing systems (wherein customers are allowed to pick-up a vehicle at any location and return it to any other station) which best suit typical urban journey requirements. Along this line, we present methods dealing with the so-called asymmetric demand–offer problem (ie, the unbalanced offer and demand of vehicles) typically experienced in one-way sharing systems which severely affects their economic viability as it implies that considerable human (and financial) resources should be engaged in relocating vehicles to satisfy customer demand. The chapter covers all planning aspects that affect the effectiveness and viability of vehicle-sharing systems: the actual system design (eg, number and location of vehicle station facilities, vehicle fleet size, vehicles distribution among stations); customer incentivisation schemes to motivate customer-based distribution of bicycles/cars (such schemes offer meaningful incentives to users so as to leave their vehicle to a station different to that originally intended and satisfy future user demand); cost-effective solutions to schedule operator-based repositioning of bicycles/cars (by employees explicitly enrolled in vehicle relocation) based on the current and future (predicted) demand patterns (operator-based and customer-based relocation may be thought as complementary methods to achieve the intended distribution of vehicles among stations).

EMU and the Process of European Integration: Southern Europe’s Economic Challenges and the Need for Revisiting EMU’s Institutional Framework

Abstract: The EU has been experiencing over the last few years an unprecedented crisis that really touches on its core characteristics and values. The EMU project was structured on political foundations and expectations, bearing, however, immense socio-economic impact. The main aims of this paper is to identify the main driving forces that influence the future development of the Economic and Monetary Union and to examine the present situation that the EU faces, the priorities of the ECB and the challenges that EU’s Southern member-states face.

Efficient Portfolio Construction with the Use of Multiobjective Evolutionary Algorithms: Best Practices and Performance Metrics

Abstract: This paper provides a systematic study of the technologies and algorithms associated with the implementation of multiobjective evolutionary algorithms (MOEAs) for the solution of the portfolio opti...

Herding, anti-herding behaviour in metal commodities futures: a novel portfolio-based approach

Abstract: The purpose of this article is twofold. Motivated by the heated debate on the financialization of commodities, we examine the existence of herding behaviour in metal commodities futures. In order to identify any time-dependent properties reflected in time-varying parameters, we employ the overlapping rolling window regression technique. The empirical evidence confirms a time-varying anti-herding behaviour before the global financial crisis and the absence of herding or anti-herding behaviour during the crisis. Next we attempt to formally establish the link between the documented anti-herding behaviour and portfolio management with the use of dynamic conditional correlations via the DCC-GARCH family multivariate modelling. After specifying the correlations, an in-sample recursive dynamic Markowitz portfolio is constructed and monitored. By doing so, we attribute the anti-herding behaviour to different portfolio positioning and rebalancing. On the other hand, in the absence of herding or anti-herding behavi...

Bank resolution financing in the banking union

Abstract: In early 2012, the Spanish state came under strong market pressure due to its engagement in round after round of large-scale bank bailouts. The country’s joint sovereignbank crisis shed new light on the nature of the euro area’s crisis. European decision-makers were forced to openly recognize the non-fiscal – that is, the banking and monetary – causes of sovereign distress and to accept the need for drastic policy solutions. The policy shift soon took concrete form with the launch of the Banking Union project in June 2012. The principal intention was to break the bank-sovereign link and to relieve the euro area’s weaker economies from the almost impossible burden of having to finance bank bailouts out of national fiscal resources. The mutualization of bailout costs through a common ‘fiscal backstop’ was, in other words, the key objective of the Banking Union as originally conceived. Subsequent policy choices, however, have marked a relaxation, if not partial abandonment, of this objective. The policy approach eventually adopted with regard to resolution financing in the context of the Banking Union’s Single Resolution Mechanism (SRM) is based on the burden-sharing norms of the Bank Recovery and Resolution Directive (BRRD), the instrument harmonizing bank resolution regimes across the EU. This guarantees the legal consistency of resolution frameworks within and outside the euro area. It is less certain, whether the chosen approach can insulate national state finances from the costs of bank bailouts and/or ensure the full equalization of the financial conditions for bank resolution everywhere in the euro area. The sufficiency of the planned common financial instruments is a particular concern.

Economic evaluation of pharmacogenomic-guided warfarin treatment for elderly Croatian atrial fibrillation patients with ischemic stroke.

Abstract: Background & methods: Economic evaluation in genomic medicine is an emerging discipline to assess the cost–effectiveness of genome-guided treatment. Here, we developed a pharmaco-economic model to assess whether pharmacogenomic (PGx)-guided warfarin treatment of elderly ischemic stroke patients with atrial fibrillation in Croatia is cost effective compared with non-PGx therapy. The time horizon of the model was set at 1 year. Results: Our primary analysis indicates that 97.07% (95% CI: 94.08–99.34%) of patients belonging to the PGx-guided group have not had any major complications, compared with the control group (89.12%; 95% CI: 84.00–93.87%, p < 0.05). The total cost per patient was estimated at €538.7 (95% CI: €526.3–551.2) for the PGx-guided group versus €219.7 (95% CI: €137.9–304.2) for the control group. In terms of quality-adjusted life-years (QALYs) gained, total QALYs was estimated at 0.954 (95% CI: 0.943–0.964) and 0.944 (95% CI: 0.931–0.956) for the PGx-guided and the control groups, respective...

Performance of CA-CFAR detectors in nonhomogeneous positive alpha-stable clutter

Abstract: This paper studies the performance of a cell-averaging constant false alarm rate (CA-CFAR) receiver that operates in a nonhomogeneous clutter environment with impulsive, heavy-tailed statistics. The clutter distribution is modeled by a positive alpha-stable distribution, which is described by the characteristic exponent α, where 0 < α <1. Analytical expressions for the false alarm and detection probabilities are derived for arbitrary values of α assuming a nonhomogeneous clutter background. The analytical results are validated with computer simulation.