Ionian University
  • Corfu, Greece
Recent publications
This study presents a systematic scoping review of the literature focusing on the connections between systems thinking and green chemistry in the context of green chemistry education. The review maps extant research and, through a process of thematic synthesis, it investigates the role of systems thinking in supporting green chemistry education. The methodological search resulted in the identification of a total of 44 studies (published between 2004 and 2020) which were subsequently analyzed to establish the characteristics of existing evidence and provide answers to the research questions of the study. Specific connections between green chemistry and systems thinking were identified, together with a set of learning objectives which may been used for promoting their integration. The existence of several educational contexts and topics that take advantage of the two interrelated perspectives shows the large potential of the research field which however is still in its infancy.
In this paper, we focus on the dynamics of the spread of malicious software (malware) in multi-layer networks of various types, e.g., cyber-physical systems. Recurring malware has been one of the major challenges in modern networks, and significant research and development has been dedicated to mitigating it. The majority of relevant works has focused on networks characterized by “flat” topologies, namely topologies in which all nodes consist of a single layer, studying the dynamics of propagation of a specific threat or various types of malware over a homogeneous topology. As cyber-physical systems and multi-layer networks in general are gaining in popularity and penetration, more targeted studies are needed. In this work, we focus on the propagation dynamics of recurring malware, namely Susceptible–Infected–Susceptible (SIS type) in multi-layer topologies consisting of combinations of two different types of networks, e.g., a small-world overlaying a random geometric, or other such combinations. We utilize a stochastic modeling framework based on Markov Random Fields for analyzing the propagation dynamics of malware over such networks. Through analysis and simulation, we discover the most vulnerable and the most robust topology among the six considered combinations, as well as a result of rather practical use, namely that the denser the network, the more flexibility it provides for malware mitigation eventually.
The addition of natural components with functional properties in novel food formulations confers one of the main challenges that the modern food industry is called to face. New EU directives and the global turn to circular economy models are also pressing the agro-industrial sector to adopt cradle-to-cradle approaches for their by-products and waste streams. This review aims to present the concept of “sustainable functional compounds”, emphasizing on some main bioactive compounds that could be recovered or biotechnologically produced from renewable resources. Herein, and in view of their efficient and “greener” production and extraction, emerging technologies, together with their possible advantages or drawbacks, are presented and discussed. Μodern examples of novel, clean label food products that are composed of sustainable functional compounds are summarized. Finally, some action plans towards the establishment of sustainable food systems are suggested.
Digital marketing has now been influenced by Artificial Intelligence to such an extent that optimized algorithms are able to predict consumer behavior, make the right offers to the right customers, and even evolve along with other new technologies such as blockchain. By adding value insights through data mining techniques, chatbots are now playing a key role in digital sales. Analyzing recent articles related to machine learning and Artificial Intelligence in digital marketing, this article presents a systematic review of recent progress to the task at hand. Apart from an examination of the legal and ethical context within which these techniques develop, we also investigated at the challenges Artificial Intelligence(AI) will present in the future of digital marketing. Additional Keywords and Phrases: Digital Marketing, Artificial Intelligence, Chatbots, Emotional Intelligence
Data streams are becoming increasingly important across a wide array of fields and are generally expected to be the preferred form of big data as aggregators and smart stream analytics in general can efficiently yield stream descriptions in various levels. Among them, event detection analytics are paramount since they typically allow the identification of distinct cases of interest like the so called black swans. Reservoir sampling refers to probabilistic class of techniques for keeping representative values of a stream given limited memory capacity. In the proposed framework event detection takes place once reservoir sampling is complete by clustering its output.The rationale behind this is that repeated representative values correspond to normal stream states, whereas any outliers indicate rare yet noteworthy events. With that information a probabilistic stream state graph can be constructed in order to examine the transition dynamics between states and to evaluate the role black swans play in the overall stream stability. A major part of the descriptive power of said graph lies on its inherent geometric interpretation in addition to the algebraic one. Results from two benchmark datasets,one coming from real world and a random one, are encouraging.The proposed framework is planned to be executed in RaspberryPi as part of an IoT stack since it is sufficiently lightweight.
Purpose Cheese whey (CW) protein and lactose fractions were individually valorized in the direction of functional food development, employing a newly isolated Trametes versicolor strain from Kefalonia Island (Greece). Methods T. versicolor growth was evaluated on solid-state fermentations, using potato dextrose agar (PDA), whereas submerged fermentations were employed under static and agitated conditions, using pure lactose and CW-lactose fraction as fermentation media. Subsequently, whey protein fraction was utilized for edible films production supplemented by the freeze-dried fungal biomass. Edible films properties were further characterized concerning their thickness, water-related properties, protein composition and antioxidant capacity. Results T. versicolor presented a high growth rate (7.5 mm/day) on PDA. Submerged fermentations showed that T. versicolor assimilated lactose; however a slower consumption rate was observed in agitated cultures, compared to static cultures. The highest biomass production of 26 g/L was achieved in the CW-based medium, showing a protein content of 19.8%. Enrichment of whey protein films by T. versicolor biomass presented lower water vapor permeability and higher antioxidant capacity, compared to control films. Conclusion The development of a novel CW biorefinery scheme was shown in this study, employing medicinal mushrooms for biomass production to create added-value food products towards a zero-food waste strategy. Graphical Abstract
There is a burgeoning discussion on creating a new schema for Oral History, an Oral History Core. In this paper we present the characteristics of Oral History collections and the problems users might face when attempting to access this type of material. As a solution, we propose an integration model. From the cultural heritage milieu, we have chosen CIDOC CRM that acts as a mediating schema, while from the European audiovisual community, we have selected EBUcore ontology. By taking into consideration their strengths and their characteristics, we form a mapping methodology from EBUcore to CIDOC CRM and we present the issues that might rise. The goal of this research is to generate a model of describing Oral History interviews, in order to facilitate exchange of information between existing collection management systems of audiovisual and cultural heritage collections and to meliorate the searching experience for users.
In the present article we explore the Item and Process (IP) approach - frequently known as Word-Based (WB) - as a theoretical model to ontologically represent the interconnection between derivatives of Modern Greek (MG). The model puts emphasis on the word as an indivisible base unit, the template rules to which words are subsumed to form new ones and the kind of relationships they establish. After a brief MG morphological analysis and the representation of various WB formation rules we proceed to test those on the MMoOn model in order to check its ontological expressiveness. In doing so we adopt an as possible top-down approach so that templates dynamically link to their respective lexical instances. Although the model generally satisfies the IP paradigm specifications it seems deficient in dealing with MG language-specific derivational rules or directional peculiarities and not very persuasive in terms of input-output categorial change representation as well as in dealing with derivatives at lexical-to-hyper-lexical level. To tackle these issues, we propose possible solutions and present their advantages in each case.KeywordsIP morphologyWord-based morphologyMMoOnOntologiesLinguistic linked dataModern Greek derivation
The development of innovative functional products with potential health benefits, under the concept of bio-economy, is flourishing. This study undertook an evaluation of non-dairy lactobacilli Lactiplantibacillus pentosus B329 and Lactiplantibacillus plantarum 820 as “ready to use” starter cultures. Lactic acid bacteria (LAB) cultures were evaluated for their fermentation efficiency, before and after freeze-drying, using cheese whey (CW) as a fermentation substrate and subsequent immobilization on bacteria cellulose (BC) to produce a novel biocatalyst. The biocatalyst was applied in functional sour milk production and compared with free cells via the assessment of physicochemical and microbiological properties and sensory evaluation. Evidently, LAB strains exhibited high fermentative activity before and after freeze-drying. Results of a 5-month storage stability test showed that viability was 19% enhanced by immobilization on BC, supporting the concept of “ready to use” cultures for the production of fermented beverages. Likewise, sour milk produced by the BC biocatalyst presented higher organoleptic scores, compared to the free cells case, whereas immobilization on BC enhanced probiotic viability during post-fermentation storage (4 °C, 28 days). The obtained high viability (>107 log cfu/g) demonstrated the efficacy of the proposed bioprocess for the production of functional/probiotic-rich beverages. Ultimately, this work presents a consolidated scheme that includes the advantages and the cooperative effect of probiotic LAB strains combined with a functional biopolymer (BC) towards the formulation of novel functional products that coincide with the pillars of food systems sustainability.
The protection of information privacy is a timely issue, as the penetration of the Internet overwhelms every aspect of individuals’ lives. Internet users’ privacy knowledge is often low, potentially due to the lack of theoretically founded methods for awareness raising and education. To address this gap, we propose the design of privacy learning activities based on a widely accepted learning theory (i.e., constructivism) derived from the education science. Since there is no specific pedagogy that guides towards specific practices for the application of the constructivism learning theory, in this paper we discuss the principles of constructivism, and we develop a set of requirements towards this direction. We adopt these requirements in information privacy learning, and we present an indicative scenario about the way that each requirement can be adopted in an educational activity, in order to result in changes of individual’s privacy attitudes and behaviors.
Social media are widely considered as reflecting to a great extent human behavior including thoughts, emotions, as well as reactions to events. Consequently social media analysis relies heavily on examining the interaction between accounts. This work departs from this established viewpoint by treating the online activity as a result of the diffusion in a social graph of memes, namely elementary pieces of information, with hashtags being the most known ones. The groundwork for a general theory of decomposing a social graph based on hashtag trajectories is lain here. This line of reasoning stems from a functional viewpoint of the underlying social graph and is in direct analogy with the biology tenet where living organisms act as gene carriers with the latter controlling up to a part the behavior of the former. To this end hashtag diffusion properties are studied including the retweet probability, higher order distributions, and the mutation dynamics with patterns drawn from a MongoDB collection. These are evaluated on two benchmark Twitter graphs. The results are encouraging and strongly hint at the possibility of formulating a meme-based graph decomposition.
In this paper, we study the potential of using the metric of Age of Information (AoI) for enhancing delay-tolerant routing protocols. The latter have been proposed for alleviating the impact of long roundtrip time in networks operating in harsh environments, e.g., in distributed applications deployed in a desert/sparsely populated area without infrastructure, a space network, etc. Delay-tolerant routing protocols can prevent excessive packet timer expiration, but do not provide any packet delivery time guarantee. Thus, they are unsuitable for time-sensitive applications that are more intensely desired nowadays in the next generation networking applications. By incorporating AoI into the operation of delay-tolerant routing protocols, we aim at devising routing protocols that can cope with both long propagation times and challenges related to time-sensitivity in packet delivery. More specifically, in this work, we modify the operation of a well-known delay-tolerant routing protocol, namely FRESH, to make an AoI-based packet forwarding decisions, aiming at achieving specific delay guarantees regarding the end-to-end delivery time. We investigate the advantages and disadvantages of such an approach compared to the traditional FRESH protocol. This work serves as a cornerstone for successfully demonstrating the potential of exploiting AoI in delay-tolerant routing and its applications.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.
1,425 members
Ioannis Deliyannis
  • Department of Audio and Visual Arts
Andreas Floros
  • Department of Audio and Visual Arts
Panagiotis Vlamos
  • Department of Informatics
Markos Avlonitis
  • Department of Informatics
Christina Beneki
  • Department of Tourism
72, Ioannou Theotoki str., , 49132, Corfu, Greece
Head of institution
Andreas Floros