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Evaluating Greek Government Digital Distance Learning Policies in Higher Education for the Covid-19 Period 19th

Evaluating Greek Government Digital Distance Learning Polici...

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Kyriakou, Niki Kompos, Nikolaos Loukis, Euripidis Leoutsakos, Theodoros Univ Aegean Karlovassi 83200 Samos Greece

ISBN: (纸本)9783031306938;9783031306945

The Greek government rapidly after the outbreak of the Covid-19 pandemic in order to mitigate its spread adopted for all universities a central policy of shutdown, and at the same time of continuing their educational activities through asynchronous and synchronous online teaching, based on e-learning platforms and online educational material. This study aims to evaluate these government policies, based on public policy evaluation theory, with respect to both their direct outputs, meant as educational resources (technological and human) provided to the students, as well as educational outcomes. For this purpose, evaluation data have been collected through a survey of 269 undergraduate students of the Department of information and Communication Systems Engineering of the University of Aegean. The results show that the participants in this survey were neutral to satisfied with the digital educational resources (technological and human) provided to them during the Covid-19 period. With respect to the educational outcomes the participants perceive a slightly level of understanding the online lectures in comparison with the traditional face-to-face ones, but a similar level of concentration. Finally, the extent of online participation of them in the exams of the theory and the laboratories has been large to very large.

关键词： distance learning digital learning e-learning synchronous e-learning asynchronous e-learning policy evaluation higher education university

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The Role of Responsiveness to Change in Large Onboarding Campaigns 24th

The Role of Responsiveness to Change in Large Onboarding Cam...

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24th International Conference on Agile Software Development (XP)

作者： Smite, Darja Moe, Nils Brede Blekinge Inst Technol Karlskrona Sweden SINTEF Digital Trondheim Norway

ISBN: (纸本)9783031339752;9783031339769

Onboarding is a process of organizational socialization of the new hires, that includes recruitment, orientation, training, coaching and support. While onboarding individuals into an organization is a rather straightforward task, little is known about 1) onboarding hundreds of developers and 2) doing it on a distance in outsourcing situations. Furthermore, the subject of sustainable growth with respect to organizational capabilities and culture is often overlooked. This paper reports findings from an exploratory multi-case study of two large onboarding campaigns. We collected empirical data from interviews, retrospectives, onboarding documentation and onsite visits. Based on the empirical study, onboarding hundreds of software engineers in a complex agile product development environment which lacks documentation and puts high demands on engineers' knowledge and skills is a challenging and costly endeavor. To save the costs and for practical reasons, large-scale onboarding is organized in batches with the first batch trained onsite, and the later batches trained internally. We report challenges faced in the two cases and discuss possible solutions. One core finding is that a good plan combined with the organizational agility, i.e., the responsiveness to change, together with organizational maturity determined the success of organizational scaling. The presented cases contribute to the scarce research on knowledge transfer and onboarding in a large-scale agile context.

关键词： Onboarding Scaling Training Teams Large-Scale Agile Software Engineering Empirical Case study Sustainable Organizational Growth

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Regulation-Friendly Privacy-Preserving Blockchain Based on zk-SNARK 1

引用

35th International Conference on Advanced information Systems Engineering (CAiSE)

作者： Xu, Lei Zhang, Yuewei Zhu, Liehuang Beijing Inst Technol Sch Cyberspace Sci & Technol Beijing Peoples R China

ISBN: (数字)9783031349850

ISBN: (纸本)9783031349843;9783031349850

Recently, blockchain has attracted much attention from industries, due to its good characteristics such as decentralization and tamper proofing. To ensure that sensitive transaction data are not disclosed to the public, many privacy protection methods have been proposed for blockchain, which generally conflicts with regulatory requirements. To resolve such a conflict, in this paper we propose a privacy-preserving account-based blockchain system which supports auditing on transactions. The proposed system protects the privacy of a transaction via homomorphic encryption. The validity of the transaction is guaranteed via zero-knowledge proof. Especially, details of a transaction are presented in form of ciphertexts on the public ledger, which can be decrypted by regulatory authorities. We have implemented a demo of the proposed system using the Substrate framework. Simulation results show that the system has acceptable performance.

关键词： Blockchain Privacy Preserving Regulation Compliance Homomorphic Encryption Zk-SNARK

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Efficient Deep Neural Network Training Techniques for Overfitting Avoidance 24th

Efficient Deep Neural Network Training Techniques for Overfi...

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24th International Conference on Enterprise information Systems (ICEIS)

作者： Sabiri, Bihi EL Asri, Bouchra Rhanoui, Maryem Mohammed V Univ Rabat ENSIAS Rabat IT Ctr IMS TeamADMIR Lab Rabat Morocco Sch Informat Sci LYRICA Lab Meridian Team Rabat Morocco

ISBN: (纸本)9783031393853;9783031393860

A deep learning neural network's ultimate goal is to produce a model that does well on both the training data and the incoming data that it will use to make predictions. Overfitting is the term used to describe how successfully the prediction model created by the machine learning algorithm adapts to the training data. When a network is improperly adapted to a limited set of input data, overfitting occurs. In this scenario, the predictive model will be able to offer very strong predictions on the data in the training set, and will also capture the generalizable correlations and the noise produced by the data, but it will predict poorly on the data that it has not yet seen during his learning phase. Two methods to lessen or prevent overfitting are suggested in this publication among many others. Additionally, by examining dynamics during training, we propose a consensus classification approach that prevents overfitting, and we assess how well these two types of algorithms function in convolutional neural networks. Firstly, Early stopping makes it possible to store a model's hyper-parameters when it's appropriate. Additionally, the dropout makes learning the model more challenging. The fundamental concept behind dropout neural networks is to remove nodes to allow the network to focus on other features which reducing the model's loss rate allows for gains of up to more than 50%. This study looked into the connection between node dropout regularization and the quality of randomness in terms of preventing neural networks from becoming overfit.

关键词： Data overfitting Early stopping Dropout regularization Machine learning Neural network Deep learning

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OptiViTh: A Decision Guidance Framework and System for Design, Analysis and Optimization of Cloud-Manufactured Virtual Things 24th

OptiViTh: A Decision Guidance Framework and System for Desig...

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24th International Conference on Enterprise information Systems (ICEIS)

作者： Han, Xu Brodsky, Alexander George Mason Univ Fairfax VA 22030 USA

ISBN: (纸本)9783031393853;9783031393860

Entrepreneurs are looking for efficient and effective ways to turn their innovative ideas into marketable products. Due to the lack of accessibility, predictability and agility in the traditional idea-to-market paradigm, stiff hindrances have to be overcome, which is perceived as the manufacturing-entrepreneurship disconnect. Toward bridging this gap, we propose and develop OptiViTh - a decision guidance system to recommend Pareto-optimal instantiation and composition of virtual things - parameterized products and services that can be searched, composed and optimized within a hierarchical service network against customer requirements specs. OptiViTh is based on an extensible and reusable repository of virtual things and their artifacts, which adhere to a proposed mathematical framework. This mathematical framework formalizes the notions of (1) combined product and service designs, (2) customer-facing specifications, (3) requirements specifications, (4) virtual thing search, as a constraint satisfaction problem, (5) compositions of virtual things that are mutually consistent, Pareto-optimal against requirements specifications, and optimal against customer utility function expressed in terms of customer facing metrics, such as cost, delivery terms and desirable product characteristics. We also demonstrate OptiViTh using a case study of cloud-based bicycle production service network combined with its product design.

关键词： Markets of virtual things Decision guidance Formal framework Cloud manufacturing

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The Importance of Blockchain for Ecomobility in Smart Cities: A Systematic Literature Review 19th

The Importance of Blockchain for Ecomobility in Smart Cities...

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Dondjio, Irenee Univ Nicosia Nicosia Cyprus

ISBN: (纸本)9783031306938;9783031306945

By 2050, cities will house at least 70% of the world's population. Already, metropolitan areas are responsible for 70% of all greenhouse gas emissions caused by energy usage. The expanding population of city dwellers has presented new challenges to contemporary urban areas. Congestion and other kinds of inefficient urban movement irritate city people and reduce their quality of life. Cities are reducing carbon dioxide emissions in an attempt to prevent global warming, which necessitates innovative new modes of transportation. Smart cities are innovative problem-solving projects for difficulties that have evolved as a consequence of increasing urbanization and changing environmental circumstances. Today's cities depend largely on people's capacity to travel freely and easily in order to minimize traffic congestion, provide a high quality of life for residents and tourists, and reduce carbon emissions and environmental deterioration. Everything is dependent on an effective and sustainable transportation infrastructure. Blockchain technology is being researched for smart city applications and is used in smart mobility for ridesharing, electric charging, platoon member interactions, and vehicle communication. Although exploratory research on this issue exists, it is spread over different use-cases and applications. This research conducts a thorough analysis of the literature on the implications of blockchain for smart city mobility and transportation, as well as its potential to boost efficiency in these sectors. The goal of this article is to synthesize and summarize existing information on the issue and contribute to closing the knowledge gap by researching how blockchain technology might improve ecomobility by reducing pollution, travel time, and congestion. The results of the literature review are divided into six use-case categories.

关键词： Ecomobility Smart Mobility Blockchain Smart Cities Smart Contracts

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Digital Content Profiling Based on User Engagement Features 19th

Digital Content Profiling Based on User Engagement Features

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Misiorek, Pawel Ciesielczyk, Michal Rzycki, Bartosz Poznan Univ Tech Fac Comp & Telecommun Ul Piotrowo 2 PL-61138 Poznan Poland Deep BI Poland Warsaw Poland

ISBN: (纸本)9783031306938;9783031306945

Exploring audience engagement with digital media content may lead to many various benefits. In this paper, we study how adding engagement-based features to the article description can influence the efficiency of algorithms aimed at detecting digital media readers' propensity to buy a subscription. Based on the propensity score, the publishers can optimize a decision to display a paywall. Moreover, it is observed that more and more page views are of new or anonymous users. Consequently, the decision concerning the paywall application has to rely only on digital content features. In order to address this application scenario, we propose a novel digital content enrichment framework based on the engagement statistics of users reading a given article. We experimentally evaluate the performance of machine learning algorithms for predicting the propensity to subscribe using the dataset based on events describing the behavior of users exploring the digital news site of the large media publisher. The results of experiments demonstrate that enrichment of article profiles with user engagement features significantly improves prediction models' efficiency.

关键词： Digital content scoring Behavioural profiles for articles Subscription for digital content Streaming data processing Big Data

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An Educational Metaverse Experiment: The First On-Chain and In-Metaverse Academic Course 19th

An Educational Metaverse Experiment: The First On-Chain and ...

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19th European, Mediterranean, and Middle Eastern Conference (EMCIS)

作者： Themistocleous, Marinos Christodoulou, Klitos Katelaris, Leonidas Univ Nicosia Nicosia Cyprus

ISBN: (纸本)9783031306938;9783031306945

The Metaverse is not a new concept;nor its use for educational purpose. Despite its considerable attention and recent popularity, largely due to Facebook's strategic bet, educators have been experimenting with such an environment for a while. Still though, educational activities that are delivered over a Metaverse environment require further exploration to fully understand their full potential, opportunities, and challenges, since such activities differ from traditional on-campus or e-learning education. Nowadays, the area of on-chain education in the Metaverse remains unexplored. In this paper, we are presenting the findings from our attempt to deliver the first of its kind on-chain and in the Metaverse course delivered by the University of Nicosia (UNIC). The course was offered in Fall 2022 as a Massive Open Online Course (MOOC) and was attended by 22,500 students. The paper reports interesting observations from this experiment highlighting lessons learned and open issues for further research. The findings reveal that a Metaverse-like environment that is structured for offering educational experiences to potential learners is likely to disrupt existing educational paradigms and academic practices. We are at a stage where significant amount of research and development is required to further understand and explore the opportunities for the application of a "meta" environment for education.

关键词： Metaverse on-chain education MOOC experiment

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Detecting Surprising Situations in Event Data

Detecting Surprising Situations in Event Data

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4th International Conference on Process Mining (ICPM)

作者： Kohlschmidt, Christian Qafari, Mahnaz Sadat van der Aalst, Wil M. P. Rhein Westfal TH Aachen Proc & Data Sci Chair PADS Aachen Germany

ISBN: (纸本)9783031278143;9783031278150

Process mining is a set of techniques that are used by organizations to understand and improve their operational processes. The first essential step in designing any process reengineering procedure is to find process improvement opportunities. In existing work, it is usually assumed that the set of problematic process instances in which an undesirable outcome occurs is known prior or is easily detectable. So the process enhancement procedure involves finding the root causes and the treatments for the problem in those process instances. For example, the set of problematic instances is considered as those with outlier values or with values smaller/bigger than a given threshold in one of the process features. However, on various occasions, using this approach, many process enhancement opportunities, not captured by these problematic process instances, are missed. To overcome this issue, we formulate finding the process enhancement areas as a context-sensitive anomaly/outlier detection problem. We define a process enhancement area as a set of situations (process instances or prefixes of process instances) where the process performance is surprising. We aim to characterize those situations where process performance is significantly different from what was expected considering its performance in similar situations. To evaluate the validity and relevance of the proposed approach, we have implemented and evaluated it on a real-life event log.

关键词： Process mining Process enhancement Context-sensitive outlier detection Surprising instances

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An Empirical Study About the Instability and Uncertainty of Non-functional Requirements 24th

An Empirical Study About the Instability and Uncertainty of ...

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24th International Conference on Agile Software Development (XP)

作者： Viviani, Luiz Guerra, Eduardo Melegati, Jorge Wang, Xiaofeng Inst Technol Res Sao Paulo Brazil Free Univ Bozen Bolzano Bolzano Italy

ISBN: (纸本)9783031339752;9783031339769

Managing non-functional requirements (NFRs) has been a challenge in software development for many years. These requirements are typically used to make important architectural decisions early in the project, which can be problematic if they are uncertain or unstable. When this uncertainty is not considered when designing the software architecture, changes are often costly and sometimes even unfeasible. Some empirical studies on the subject have already been carried out, but few have focused on the perspective of professionals with extensive experience on the changes and uncertainties of NFRs. This work aims to expand the understanding about the management, clarity and validation of NFRs to fill this gap in the literature. To achieve this goal, a survey was carried out with professionals to find out how NFRs were managed and validated. For the research design, instead of generic questions, the questionnaire focused on some specific types of NFRs to induce participants to recall and report concrete situations. As a result, 40 valid responses were obtained, most from professionals with more than 10 years of experience. The results reveal that a significant number of NFRs were defined after the delivery of software increments (more than 30%) and that revision and change occurred in about a third of the NFRs. Hence, this study presents evidence that NFRs, as the functional ones, can also be uncertain and change frequently, requiring agile approaches and techniques to evolve the software architecture to consider this uncertainty.

关键词： empirical study Non-functional requirements quality attributes requirements engineering software evolution software maintenance

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