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Correlation-based wireless sensor networks performance: the compressed sensing paradigm
No full textIn this paper, the performance of Wireless Sensor Networks (WSNs) operating for environmental monitoring is investigated. The performance metrics considered are normalized reconstruction error and energy estimation error. The temporal, spatial and spatiotemporal correlations are separately considered for the above metrics. The independent case and correlated cases for dense measurement cases along with the Compressed Sensing (CS) compressibility rule by selecting a subset of measurements for metric evaluation are thoroughly examined with extensive simulations and technical interpretations. Finally, applications of the proposed scheme are formulated in terms of topology and routing in fifth generation sensor networks and Internet of Things (IoT) deployment scenarios.25296598
CYBELE: On the Convergence of HPC, Big Data Services, and AI Technologies
No full textInefficiency in planting, harvesting, water use, meat consumption, as well as uncertainty about weather, pests, consumer demand, and other intangibles contribute to lower production, advanced costs, and greater need for products of higher quality and quantity. Precision agriculture (PA) and precision livestock farming (PLF) are introduced to assist in optimizing agricultural and livestock production while minimizing the wastes and costs. In this chapter, CYBELE is introduced, a platform aspiring to ensure that the stakeholders involved in the PA and PLF value chain (research and academia, SMEs, entrepreneurs, etc.) are granted unmediated access to a vast amount of very large-scale and distributed datasets. Additionally, by leveraging the convergence of big data, artificial intelligence, and high-performance computing infrastructures, CYBELE facilitates these stakeholders to generate value and extract insights out of the data through advanced data exploration, aggregation, processing, training, analysis, and visualization services.240254HPC, Big Data, and AI Convergence Towards Exascal
Development and initial validation of a scale for the situational recognition of the basic psychological needs
No full textCentered on the Basic Psychological Needs Theory, recent theoretical underpinnings were used and initial empirical processes were initiated to conceptualize, develop and validate a new questionnaire about how teachers shape instructional goals. In a first exploratory study, 188 university graduates and 211 in-service teachers from both the general and special education domains were recruited to recognize the basic psychological needs of an adolescent with physical and mild cognitive disability presented in a short video vignette. In the second confirmatory study, the sample consisted of 239 in-service teachers. According to the results, the new instrument demonstrated acceptable psychometric qualities. For instance, the goodness-of-fit indices CFI and NNFI were both good (1.00) in the confirmatory factor analysis. In both studies, the recognition of the basic psychological needs was involved in a series of statistically significant correlations with participants’ intrinsic life goals (R ≥ .34), state empathy (R ≥ .38) and intrinsic instructional goals (R ≥ .51). This preliminary research suggested that participants integrated the new concept in their intrinsic motivational style. Overall, the results highlight the importance of recognizing the basic psychological needs by including this construct both in research and practice.81e0878
Digital Twin Intelligent System for Industrial Internet of Things-based Big Data Management and Analysis in Cloud Environments
No full textThis work initially surveys and illustrates the multiple open challenges in the field of industrial IoT-based Big Data management and analysis in Cloud environments. Challenges arise from fields of Machine Learning in the Cloud infrastructures, A.I. techniques of Big Data Analytics in the Cloud environments, and Federated Learning Cloud systems try to be clarified. Additionally, Reinforcement Learning is a novel technique that allows large data centers such as Cloud data centers to affect a more energy-efficient resource allocation. Moreover, we propose an architecture that tries to combine the features offered by several Cloud Providers to emerge and achieve an Energy-Efficient industrial IoT-based Big Data Management Framework (EEIBDM) established outside of every user, in Cloud. IoT data could be integrated with techniques such as Reinforcement and Federated Learning to achieve a Digital Twin scenario, for the virtual representation of industrial IoT-based Big Data of machines and rooms temperatures. Furthermore, we propose an algorithm for delivering the energy consumption of the infrastructure through the evaluation of the EEIBDM framework. Finally, some future directions as an expansion of our research are illustrated.4427929
Discoverability of OER: The Case of Language OER
No full textOne of the obstacles that prevent the widespread adoption of Open Educa-tional Resources (OER) is the difficulty to find appropriate OER for specif-ic educational objectives. This paper investigates this discoverability prob-lem by searching for OER in eleven well-known Repositories of OER (ROER). The search for "Language Game" and "Italian Language" OER was used as a case study. The search found very few useful language OER in these ROER. Also, it revealed a number of obstacles in finding appropriate OER such as absence of a uniform structure of ROER, absence of a uniform OER metadata description, inaccurate, obsolete, and missing metadata de-scriptions of OER, obsolete OER, not really open and free educational re-sources, and more. Finally, the paper makes suggestions for improving both ROER and OER description.2495566Ludic, Co-design and Tools Supporting Smart Learning Ecosystems and Smart Educatio
Employee high-performance work systems-experience attributions of well-being and exploitation: a multilevel study of Greek workplaces
No full textPurpose – This paper aims to theoretically propose and empirically test a research framework that investigates the relationship between high-performance work systems (HPWS) and organizational performance through the serially mediating mechanisms of employee HPWS-experience attributions of well-being and exploitation, attitudes, and behaviors. Design/methodology/approach – Multilevel structural equation modeling through Mplus was applied to a sample of 1,112 employees working at 158 Greek organizations. Findings – The modeling’s findings indicate that the serially mediating mechanism of employee HPWS-experience attributions of well-being, attitudes, and behaviors improves organizational performance. Meanwhile, the serially mediating mechanism of employee HPWS-experience attributions of exploitation, attitudes, and behaviors was found to weaken organizational performance. Practical implications – This study shows that, to improve employees’ well-being and weaken employee exploitation through employees’ HPWS-experience attributions, senior and line managers should gain competencies and communication skills through training and development programs, successfully communicating HPWS messages to employees. Originality/value – This study may be the first study to elucidate the serially mediating mechanisms of employees’ well-being and exploitation through employees’ HPWS-experience attributions, attitudes, and behaviors in the relationship between HPWS and organizational performance.4451030104
Entrepreneurial strategies and family firm culture in the Arab world: a systematic literature review
No full textPurposeFamily businesses are value-based enterprises, contributing significantly to wealth creation. Although extensive research is conducted on family businesses, there is no study investigating how the cultural traits in the Arab world affect the organizational culture of family businesses. This paper discusses how the cultural characteristics in the Arab world shape family enterprises and explores how the Arab world's organizational culture enables family firms to establish competitive advantage underpinned by founder centrality, the concept of family, and business principles spanning many generations.Design/methodology/approachA thorough search of the extant literature was done in Scopus, Web of Science, EBSCO, and ScienceDirect using a combination of keywords such as Arab culture, family businesses, family firm culture, organizational culture, cultural traits, management strategies, and entrepreneurial strategies. Selected articles were classified according to their content, reviewed, and analyzed.FindingsThis study makes a few critical contributions about the nature, and the origins of organizational culture in family firms, entailing the founder's centrality and stewardship theory. Specifically, family firms in the examined region appear to have a stronger firm culture compared to non-family businesses. Also, organizational culture affects family businesses considering the firm-level outcomes, such as hereditary transition success, family inertia, etc.Originality/valueThis paper adds to the existing theoretical knowledge and underlines the cultural traits and family firm culture in the Arab world. A framework is presented, offering practical recommendations to managers of family firms striving to advance their competitiveness.297994101
Experimenting with an SDN-Based NDN Deployment over Wireless Mesh Networks
No full textInternet of Things (IoT) evolution calls for stringent communication demands, including low delay and reliability. At the same time, wireless mesh technology is used to extend the communication range of IoT deployments, in a multi-hop manner. However, Wireless Mesh Networks (WMNs) are facing link failures due to unstable topologies, resulting in unsatisfied IoT requirements. Named-Data Networking (NDN) can enhance WMNs to meet such IoT requirements, thanks to the content naming scheme and in-network caching, but necessitates adaptability to the challenging conditions of WMNs.In this work, we argue that Software-Defined Networking (SDN) is an ideal solution to fill this gap and introduce an integrated SDN-NDN deployment over WMNs involving: (i) global view of the network in real-time; (ii) centralized decision making; and (iii) dynamic NDN adaptation to network changes. The proposed system is deployed and evaluated over the wiLab.1 Fed4FIRE+ test-bed. The proof-of-concept results validate that the centralized control of SDN effectively supports the NDN operation in unstable topologies with frequent dynamic changes, such as the WMNs.16IEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS
Exploring the Quality of Dynamic Open Government Data for Developing Data Intelligence Applications: The Case of Attica Traffic Data
No full textDynamic data (including environmental, traffic, and sensor generated data) were, recently, recognised as an important part of the Open Government Data (OGD) movement. These data are of vital importance in the development of data intelligence applications. For example, various business applications exploit traffic data to predict, e.g., traffic demand and an estimated time of arrival. However, this type of data is inherently vulnerable to data quality errors produced by, e.g., failures of sensors and network faults. The objective of this paper is to explore the quality of Dynamic Open Government Data for the development of data intelligence applications. Towards this end, we study a single case about the traffic data provided by the official Greek OGD portal. The portal involves the use of an Application Programming Interface (API), which is essential for the effective dissemination of dynamic data. Our research approach involves the exploration and the evaluation of the provided data with regards to missing values and anomalies. We anticipate that this paper will contribute to the identification of organisational and technical challenges that hamper the effective dissemination of dynamic OGD.10210
Factors Predicting Surgical Effort Using Explainable Artificial Intelligence in Advanced Stage Epithelial Ovarian Cancer
No full text(1) Background: Surgical cytoreduction for epithelial ovarian cancer (EOC) is a complex procedure. Encompassed within the performance skills to achieve surgical precision, intra-operative surgical decision-making remains a core feature. The use of eXplainable Artificial Intelligence (XAI) could potentially interpret the influence of human factors on the surgical effort for the cytoreductive outcome in question; (2) Methods: The retrospective cohort study evaluated 560 consecutive EOC patients who underwent cytoreductive surgery between January 2014 and December 2019 in a single public institution. The eXtreme Gradient Boosting (XGBoost) and Deep Neural Network (DNN) algorithms were employed to develop the predictive model, including patient- and operation-specific features, and novel features reflecting human factors in surgical heuristics. The precision, recall, F1 score, and area under curve (AUC) were compared between both training algorithms. The SHapley Additive exPlanations (SHAP) framework was used to provide global and local explainability for the predictive model; (3) Results: A surgical complexity score (SCS) cut-off value of five was calculated using a Receiver Operator Characteristic (ROC) curve, above which the probability of incomplete cytoreduction was more likely (area under the curve [AUC] = 0.644; 95% confidence interval [CI] = 0.598-0.69; sensitivity and specificity 34.1%, 86.5%, respectively; p = 0.000). The XGBoost outperformed the DNN assessment for the prediction of the above threshold surgical effort outcome (AUC = 0.77; 95% [CI] 0.69-0.85; p 4, and a Peritoneal Carcinomatosis Index >7, in a surgical environment with the optimization of infrastructural support. (4) Conclusions: Using XAI, we explain how intra-operative decisions may consider human factors during EOC cytoreduction alongside factual knowledge, to maximize the magnitude of the selected trade-off in effort. XAI techniques are critical for a better understanding of Artificial Intelligence frameworks, and to enhance their incorporation in medical applications.1414344