Institutional Repository of Academic Research University of Macedonia
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Fake News Incidents through the Lens of the DCAM Disinformation Blueprint
No full textThe emergence of the Internet and web technologies has magnified the occurrence of disinformation events and the dissemination of online fake news items. Fake news is a phenomenon where fake news stories are created and propagated online. Such events occur with ever increasing frequency, they reach a wide audience, and they can have serious real-life consequences. As a result, disinformation events are raising critical public interest concerns as in many cases online news stories of fake and disturbing events have been perceived as being truthful. However, even at a conceptual level, there is not a comprehensive approach to what constitutes fake news with regard to the further classification of individual occurrences and the detection/mitigation of actions. This work identifies the emergent properties and entities involved in fake news incidents and constructs a disinformation blueprint (DCAM-DB) based on cybercrime incident architecture. To construct the DCAM-DB in an articulate manner, the authors present an overview of the properties and entities involved in fake news and disinformation events based on the relevant literature and identify the most prevalent challenges. This work aspires to enable system implementations towards the detection, classification, assessment, and mitigation of disinformation events and to provide a foundation for further quantitative and longitudinal research on detection strategies.13730
Fast Training Set Size Reduction Using Simple Space Partitioning Algorithms
No full textThe Reduction by Space Partitioning (RSP3) algorithm is a well-known data reduction technique. It summarizes the training data and generates representative prototypes. Its goal is to reduce the computational cost of an instance-based classifier without penalty in accuracy. The algorithm keeps on dividing the initial training data into subsets until all of them become homogeneous, i.e., they contain instances of the same class. To divide a non-homogeneous subset, the algorithm computes its two furthest instances and assigns all instances to their closest furthest instance. This is a very expensive computational task, since all distances among the instances of a non-homogeneous subset must be calculated. Moreover, noise in the training data leads to a large number of small homogeneous subsets, many of which have only one instance. These instances are probably noise, but the algorithm mistakenly generates prototypes for these subsets. This paper proposes simple and fast variations of RSP3 that avoid the computationally costly partitioning tasks and remove the noisy training instances. The experimental study conducted on sixteen datasets and the corresponding statistical tests show that the proposed variations of the algorithm are much faster and achieve higher reduction rates than the conventional RSP3 without negatively affecting the accuracy.131257
Health Outcomes, Income and Income Inequality: Revisiting the Empirical Relationship
No full textIn this paper we revisit the relationship between health outcomes, income, and income inequality by applying alternative panel methodologies to a dataset of high-income countries spanning the time period 1980–2017. In this direction, we adopt alternative methodological frameworks in order to provide a) meaningful results by taking into account standard errors that alleviate problems of cross-sectional (spatial) and temporal dependence, and b) insights into the underlying relationships at several points of the conditional distribution of the health outcomes dependent variables. The evidence strongly supports the significant role that income plays in determining health outcomes. The findings relating to income inequality and nonlinear terms are more fragmented in that their significance and sign-direction depend on the functional form and the respective quantiles of the distribution the relationships are evaluated.0
Higher Education Students’ Training Toward Inclusion; Virtual Reality Introduces Socially Assistive Robots Technologies for Digital Inclusion
No full textInclusion is a system that embraces difference as the norm. It is possible to accomplish successful inclusion in situations that support and encourage social contact, such as the interventions using Socially Assistive Robots (SAR).The proven, through research, the ability of SAR to promote interventions for the inclusion of children with autism spectrum disorders (ASD), leads to the need for specialized education of university students in pedagogical or special education departments, to get acquainted with robots and their utilization methods for the inclusion of children.However, getting acquainted with SAR is not always easy as the variety of proposed robots is significant. In addition, it is pretty demanding work to design and develop software for the wide variety of SARs’ educational applications and organize hands-on training. For this reason, in an Erasmus+ program, virtual reality (VR) technology was proposed and utilized to present robots and introduce analytical methods for their implementation on how to use SAR through detailed scenarios, such as the detailed description of the outlined ARRoW (Assisting Relations Robotic Workfellow) method.This chapter will initially present the ASD aspects, inclusive techniques, and why SAR is a powerful tool to deliver inclusive interventions to the ASD population, subsequently will analyze the design and implementation of a VR training scenario that utilizes the ARRoW method and the SAR Daisy toward inclusion. Then we discuss the implementation aspects of the training activities and Higher Education (HE) students’ participation.227237Inclusive Digital Educatio
Improving Mobile Game Performance with Basic Optimization Techniques in Unity
No full textCreating video games can be a very complex process, which requires taking into account various hardware and software limitations. This process is even more complex for mobile games, which are limited to the resources that their platforms (mobile devices) offer in comparison to game consoles and personal computers. This restriction makes performance one of the top critical requirements, meaning that a videogame should be designed and developed more carefully. In order to reduce the resources that a game uses, there are optimization techniques that can be applied in different stages of the development. For the purposes of this article, we designed and developed a simple shooter videogame, intended for Android mobile devices. The game was developed with the Unity game engine and most of the models were designed with the 3D computer graphics software Blender. Two versions of the game were developed in order to study the differences in performance: one version that applies basic optimization techniques, such as low poly count for the models and the object pooling algorithm for the enemy’s spawn; and one where the aforementioned optimizations were not used. Even though the game is not large in scale, the optimized version achieves a better user experience and needs less resources in order to run smoothly. This means that in larger and more complex video games these optimizations could have a bigger impact on the performance of the final product. To measure how the techniques affected the two versions of the game, the values of frames per second, batches and triangles/polygons were taken under consideration and used as metrics for game performance in terms of CPU usage, rendering (GPU usage) and memory usage.3220122
In search for the most preferred solution in value efficiency analysis
No full textChoosing the Most Preferred Solution (MPS), namely a real or artificial Decision Making Unit (DMU) reflecting the decision maker’s preferences over the desirable structure of inputs and outputs, is of particular importance in Value Efficiency Analysis (VEA). In this paper, we review various MPS choices used in the VEA literature and propose some new, which rely respectively on the relative position of frontier DMUs, the Most Productive Scale Size (MPSS), the Average Production Unit (APU), and common vectors of weights. The suggested MPS choices reflect overall organizational goals such as the pursuit of scale economies and the maximization of structural efficiency, or the need to assess DMUs against common standards because of limited control over the resources allocated to them or autonomy in setting their own priorities. The potential implications of using different MPSs in VEA are illustrated by providing comparative empirical results using a dataset of 526 Greek cotton farms.582-320322
Job demands-resources model, transformational leadership and organizational performance: a multilevel study
No full textPurpose – The purpose of this paper is to integrate an extended by personal resources job demands-resources (JD-R) model in the relationship between transformational leadership and organizational performance. It is argued that responsive, supportive and developmental leader’s style will reduce employee’s levels of burnout and increase their levels of work engagement, and ultimately will increase organizational performance expressed by productivity, growth and creativity.Design/methodology/approach – The hypotheses were tested among a national sample of 1011 employees in 107 Greek public and private organizations operating within an environment of economic and financial crises. The operational model was tested using a multilevel structural equation modeling.Findings – It appeared that job demands and work burnout, and job resources and work engagement, serially and fully mediated the relationship between transformational leadership and organizational performance. Further, it is found that personal resources negatively and fully mediate the relationship between job resources and work burnout and positively and partially mediate the relationship between job resources and work engagement.Research limitations/implications – Data was collected using a cross-sectional design, not allowing therefore dynamic causal inferences.Practical implications – Considering that the transformational leadership style reduces employee’s levels of burnout and increases their levels of work engagement, and accordingly it improves organizational performance, organizations are well advised to encourage this leadership style.Social implications – Transformational leadership by balancing job demands and job resources could have a positive impact on employee well-being.Originality/value – The study, using multilevel testing, demonstrates that the extended JD-R model can be integrated into the transformational leadership – organizational performance relationship.7172704272
Mobile Telepresence Robots in Education: Strengths, Opportunities, Weaknesses, and Challenges
No full textA mobile telepresence robot (MTR) is a semi-autonomous robot whose movement and interaction with its surrounding environment is controlled by a person from a distance. In education, MTR enable learners or educators to virtually participate in a class from a distance. TRinE: Telepresence Robots in Education is an EU project that aims at providing an interactive toolkit to support educators, learners, and others in order to integrate MTR in education. During January and February 2022, project’s partners conducted a qualitative study to collect the experiences and views of educators, learners, and other stakeholders (i.e., administrators, technical support staff, librarians) regarding the use of MTR in education across Austria, Germany, Greece, France, Iceland, Malta, and USA. A total of 19 persons were interviewed and 66 persons participated in 12 focus groups discussions. The findings describe interviewees’ experiences with MTR in education as well as the views of interviewees and focus groups’ participants with regard to pros, cons, and recommendations of using MTR in education. These findings may help educational policy makers, educational institutes officials, educators, and others to efficiently integrate MTR in education.13450573579Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoptio
Postnatal Neurogenesis Beyond Rodents: the Groundbreaking Research of Joseph Altman and Gopal Das
No full textAn integral component of neural ontogeny and plasticity is the ongoing generation of new neurons from precursor cells throughout the lifespan in virtually all animals with a nervous system. In mammals, postnatal neurogenesis has been documented in the cerebellum, olfactory bulb, hippocampus, striatum, substantia nigra, hypothalamus, and amygdala. Germinal centers of new neuron production in the adult brain have been identified in the neuroepithelium of the subventricular zone and the dentate gyrus. One of the earliest lines of evidence gathered came from studies on the production of cerebellar microneurons in the external germinal layer of rodents and carnivores in the 1960s and 1970s. The undeniable pioneer of that research was the insightful developmental neurobiologist Joseph Altman (1925-2016). This Cerebellar Classic is devoted to the groundbreaking work of Altman and his graduate student and, subsequently, fellow faculty member, Gopal Das (1933-1991), on postnatal neurogenesis using tritiated thymidine autoradiography to tag newly formed neurons in the cerebellum of cats. Perseverant to their ideas and patiently working in West Lafayette (Indiana), they were the founders of two fields that brought about paradigm shifts and led to an explosive growth in brain research: adult neurogenesis and neural tissue transplantation.2111
Software-Defined Reconfigurable Intelligent Surfaces: From Theory to End-to-End Implementation
No full textProgrammable wireless environments (PWEs) utilize internetworked intelligent metasurfaces to transform wireless propagation into a software-controlled resource. In this article, the interplay is explored between the user devices, the metasurfaces, and the PWE control system from the theory to the end-to-end implementation. This article first discusses the metasurface hardware and software, covering the complete workflow from the user device initialization to its final service via the PWE. Furthermore, to be compatible with the 5G and 6G wireless systems, the software-defined networking (SDN) paradigm is extended to achieve scalable internetworking and central control in PWE deployments with multiple metasurfaces and multihop communication. Subsequently, the set of SDN foundations is exploited in order to abstract the physics behind PWEs and a theoretical framework is established to describe and manipulate them in an algorithmic form. This can lead to smart radio environments that are readily accessible from various engineering disciplines, facilitating their integration into existing networks, wireless systems, and applications. This article is concluded by outlining strategies for the optimal placement of metasurfaces within a PWE-controlled space, open challenges in PWE security, specialized SDN integration issues, and theoretical problems toward the graph-driven modeling of PWEs.11091466149