Institutional Repository of Academic Research University of Macedonia
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2215 research outputs found
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IoT-based health and emotion care system
No full textA "Smart Healthcare-Room" has been installed in a local network. This form of network grants controlled network access to patients and tenders huge safety of their data which have been swapped at the time cure is given and the time the patient stays in the room. In order to manage the "Data Learning" approach from all the procedures and the communication of the sensors, an "Emotion Care System" has been installed. The data will be sent through the network to the IoT framework application which will notify the medical staff for the health and emotional condition of the patient.9111211
KM tools alignment with KM processes: the case study of the Greek public sector
No full textThis paper reports an investigation into the alignment of Knowledge Management (KM) tools with KM processes under the Common Assessment Framework (CAF) implementation. An exploratory case study was conducted to address this purpose by employing literature review methods, focus groups, observation, and document analysis. From the data analysis, we found that in each KM process, both technological and non-technological KM tools were used. However, there were limitations regarding the number of public organisations and the study in the Greek context, which could be addressed with further research that enhances generalisability within different public organisations globally. In summary, the study provides: a) a novel theoretical insight in combining KM tools with KM processes in the public sector, and b) a practical "roadmap" of KM for public sector executives.21236137
Music Deep Learning: Deep Learning Methods for Music Signal Processing—A Review of the State-of-the-Art
No full textThe discipline of Deep Learning has been recognized for its strong computational tools, which have been extensively used in data and signal processing, with innumerable promising results. Among the many commercial applications of Deep Learning, Music Signal Processing has received an increasing amount of attention over the last decade. This work reviews the most recent developments of Deep Learning in Music signal processing. Two main applications that are discussed are Music Information Retrieval, which spans a plethora of applications, and Music Generation, which can fit a range of musical styles. After a review of both topics, several emerging directions are identified for future research.11170311705
SRv6‐based Time‐Sensitive Networks (TSN) with low‐overhead rerouting
No full textTime-Sensitive Networks (TSN) aims at providing a solid underpinning for the support of application connectivity demands across a wide spectrum of use cases and operational environments, such as industrial automation and automotive networks. However, handling network updates in TSN entails additional challenges, stemming from the need to perform both flow rerouting and TSN schedule reconfiguration. To address this issue, we propose a software-defined network (SDN)-based approach for low-overhead TSN network updates, exploiting segment routing over IPv6 (SRv6) for path control. To this end, we introduce the concept of TSN subgraphs in order to quickly reschedule the flows traversing the problematic area and propose a TSN-aware routing heuristic to minimize the convergence time. We further describe the control plane implementation and its integration into Mininet, which empowers us to conduct a wide range of performance tests. Our evaluation results indicate that our approach yields faster recovery and reduces significantly the number of required reconfigurations upon failures, at the expense of a small SRv6 encoding/decoding overhead.334e221
Understanding the Use of Emerging Technologies in the Public Sector: A Review of Horizon 2020 Projects
No full textThe main purpose of this article is to provide an up-to-date understanding of the utilization and deployment of emerging technologies in the public sector, as this is reflected through 19 recently funded Horizon 2020 research projects. For the needs of this study, we have adopted a well-known literature review method that enables a concept-centric analysis of the accumulated knowledge in the field under consideration, and accordingly proposed a conceptual framework that facilitates such an analysis. Through a detailed consideration of these projects and their pilot case implementations, a series of insights about recent research development and applications in the public sector are extracted and discussed. To the best of our knowledge, this is the first attempt to gain such insights from a research projects perspective, which may reveal useful information about the utilization and deployment of these technologies in real-life pilots. The findings of this study are also justified or challenged by referring to recent review articles that investigate the use of emerging technologies in the public sector.4112
Deterministic and Probabilistic P4-Enabled Lightweight In-Band Network Telemetry
No full textIn-band network telemetry (INT), empowered by programmable dataplanes such as P4, comprises a viable approach to network monitoring and telemetry analysis. However, P4-INT as well as other existing frameworks for INT yield a substantial transmission overhead, which grows linearly with the number of hops and the number of telemetry values. To address this issue, we present a deterministic and a probabilistic technique for lightweight INT, termed as DLINT and PLINT, respectively. In particular, DLINT exercises per-flow aggregation by spreading the telemetry values across the packets of a flow. DLINT relies on switch coordination through the use of per-flow telemetry states, maintained within P4 switches. Furthermore, DLINT utilizes Bloom Filters (BF) in order to compress the state lookup tables within P4 switches. On the other hand, PLINT employs a probabilistic approach based on reservoir sampling. PLINT essentially empowers every INT node to insert telemetry values with equal probability within each packet. Our evaluation results corroborate that both proposed techniques alleviate the transmission overhead of P4-INT, while maintaining a high degree of monitoring accuracy. In addition, we perform a comparative evaluation between DLINT and PLINT. DLINT is more effective in conveying path traces to the telemetry server, whereas PLINT detects more promptly path updates exploiting its more efficient INT header space utilization.4909492
Optimal decision making, using interval uncertainty techniques, of a production-inventory model under warranty-linked demand and carbon tax regulations
No full textThe concepts of generalized Hukuhara difference and interval differential equation play important role in the theory of interval uncertainty. These concepts have many applications in different branches of research, viz. optimization, information theory, inventory control and others. The goal of this work is to study an application of Hukuhara difference and interval differential equation in inventory management. In this paper, an inventory model for imperfect production process under warranty-dependent demand and carbon tax regulatory mechanism, is presented with the help of Hukuhara difference and interval differential equation. Also, using the interval arithmetic, the generalized Hukuhara difference, and the existence and uniqueness theorem of interval differential equation, the corresponding average profit function of this model is obtained. In order to maximize the average profit, a center-radius optimization technique is proposed. Some numerical examples are considered and solved by using different variant of quantum-behaved particle swarm optimization algorithms.272903292
Founder or employee? The effect of social factors and the role of entrepreneurship education
No full textCareer intentions of students are extremely important and they are affected by the particular social context, such as cultures, communities, universities in which they are embedded. The exposure to entrepreneurship education may also have moderating effects on the different social antecedents of career intentions. We draw data from a large sample and use logistic regression and marginal effects to highlight the importance of the socio-cultural environment to the intention to become a founder instead of an employee in the near and distant future. We show that the effect of entrepreneurship education is not the same in every social context. While entrepreneurship research up to now has mainly focused on individual level determinants of career choices, we highlight the importance of the social environment. Policy makers should consider the characteristics of the different levels of the social environment before designing policies to reinforce the intention to become a founder.155, Part A11342
Information Systems Strategy and Innovation: Analyzing Perceptions Using Multiple Criteria Decision Analysis
No full textThe current challenging environment may cause difficulties in the financial dimension of firms and particularly for small-medium-sized enterprises (SMEs), which may lead to the lack of administrative, technical, and human capabilities which, in effect, may constrain the capacity to deal with the crisis. In light of technological advances, scholars and practitioners have concluded that the greatest obstacle to the adoption of innovative technologies is the lack of information systems (IS) strategy. IS strategy is a critical dimension of innovation and competitive advantage for SMEs. IS strategy includes multiple conflicting objectives and the use of multiple criteria decision analysis (MCDA) is to support better decision making. SMEs need a guide for effective decision making in the information technology (IT) field and decision-making processes that are based on MCDA methods increase innovation and entrepreneurship. Thus, this article aims to investigate the effect of the use of IS strategic planning on IT executives' satisfaction using MCDA. All data are obtained in 294 Greek SMEs from IS executives. The results of this article could enable managers to understand how IS strategy supports the development of innovative technologies that incorporate opportunities to enhance business development and innovation.7051977198
Exploring the Impact of Supermarket Store Layout and Atmospheric Elements on Consumer Behavior: A Field Research Study in Greece
No full textThe highly competitive retail industry pushes retailers to seek strategies like creating atmospheric in-store experiences to boost consumer satisfaction and encourage return visits. Store atmosphere and layout design influence consumer decision-making, perception, and satisfaction. Factors such as building design, customer patterns, merchandise mix, and proximity requirements impact consumer perception and store layout.
This article investigates the effect of supermarket chains’ layouts on consumer behavior, focusing on atmospheric elements. A Greek field study involving 205 participants assessed perceptions and attitudes toward supermarket layouts and design elements. Results suggest that retail environment characteristics impact emotional reactions, which in turn influence impulse buying behavior.
Emphasizing the importance of a superior customer experience throughout the purchasing process, the study identifies key atmospheric elements affecting consumer behavior in supermarkets. The article concludes by discussing implications for retail marketers and suggesting future research directions.6213115