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Blockchain-based recommender systems: Applications, challenges and future opportunities

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arXiv 2021年

作者： Himeur, Yassine Sayed, Aya Alsalemi, Abdullah Bensaali, Faycal Amira, Abbes Varlamis, Iraklis Eirinaki, Magdalini Sardianos, Christos Dimitrakopoulos, George Department of Electrical Engineering Qatar University Doha Qatar Institute of Artificial Intelligence De Montfort University Leicester United Kingdom Department of Computer Science University of Sharjah UAE Dept. of Informatics and Telematics Harokopio University of Athens Greece San Jose State University San JoseCA United States

Recommender systems have been widely used in different application domains including energy-preservation, e-commerce, healthcare, social media, etc. Such applications require the analysis and mining of massive amounts of various types of user data, including demographics, preferences, social interactions, etc. in order to develop accurate and precise recommender systems. Such datasets often include sensitive information, yet most recommender systems are focusing on the models’ accuracy and ignore issues related to security and the users’ privacy. Despite the efforts to overcome these problems using different risk reduction techniques, none of them has been completely successful in ensuring cryptographic security and protection of the users’ private information. To bridge this gap, the blockchain technology is presented as a promising strategy to promote security and privacy preservation in recommender systems, not only because of its security and privacy salient features, but also due to its resilience, adaptability, fault tolerance and trust characteristics. This paper presents a holistic review of blockchain-based recommender systems covering challenges, open issues and solutions. Accordingly, a well-designed taxonomy is introduced to describe the security and privacy challenges, overview existing frameworks and discuss their applications and benefits when using blockchain before indicating opportunities for future research. © 2021, CC BY.

关键词： Blockchain

Testing boolean functions properties

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arXiv 2021年

作者： Zhengwei, Xie Qiu, Daowen Guangya, Cai Gruska, Jozef Mateus, Paulo School of Computer Science and Engineering Sun Yat-Sen University Guangzhou510006 China Faculty of Informatics Masaryk University Brno Czech Republic Instituto de Telecomunicações Dept. de Mateḿatica Instituto Superior Técnico Av. Rovisco Pais Lisbon1049-001 Portugal

The goal in the area of functions property testing is to determine whether a given black-box Boolean function has a particular given property or is Ε-far from having that property. We investigate here several types of properties testing for Boolean functions (identity, correlations and balancedness) using the Deutsch-Jozsa algorithm (for the Deutsch-Jozsa (D-J) problem) and also the amplitude amplification technique. At first, we study here a particular testing problem: namely whether a given Boolean function f, of n variables, is identical with a given function g or is Ε-far from g, where Ε is the parameter. We present a one-sided error quantum algorithm to deal with this problem that has the query complexity O(1√Ε). Moreover, we show that our quantum algorithm is optimal. Afterwards we show that the classical randomized query complexity of this problem is Θ(1Ε). Secondly, we consider the D-J problem from the perspective of functional correlations and let C(f, g) denote the correlation of f and g. We propose an exact quantum algorithm for making distinction between |C(f, g)| = Ε and |C(f, g)| = 1 using six queries, while the classical deterministic query complexity for this problem is Θ(2n) queries. Finally, we propose a one-sided error quantum query algorithm for testing whether one Boolean function is balanced versus Ε-far balanced using O(1Ε) queries. We also prove here that our quantum algorithm for balancedness testing is optimal. At the same time, for this balancedness testing problem we present a classical randomized algorithm with query complexity of O(1/Ε2). Also this randomized algorithm is optimal. Besides, we link the problems considered here together and generalize them to the general case. Copyright © 2021, The Authors. All rights reserved.

关键词： Boolean functions

Assessing responsible innovation training

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Journal of Responsible Technology 2023年 16卷

作者： Stahl, Bernd Carsten Aicardi, Christine Brooks, Laurence Craigon, Peter J. Cunden, Mayen Burton, Saheli Datta Heaver, Martin De Saille, Stevienna De Dolby, Serena Dowthwaite, Liz Eke, Damian Hughes, Stephen Keene, Paul Kuh, Vivienne Portillo, Virginia Shanley, Danielle Smallman, Melanie Smith, Michael Stilgoe, Jack Ulnicane, Inga Wagner, Christian Webb, Helena School of Computer Science University of Nottingham United Kingdom Dept. of Informatics and School of Biomedical Engineering & Imaging Sciences King's College London United Kingdom Information School University of Sheffield Sheffield United Kingdom Horizon Digital Economy Research School of Computer Science University of Nottingham United Kingdom Independent Researcher Dept of Science and Technology Studies University College London United Kingdom ORBIT RRI limited Leicester United Kingdom Dept of Sociological Studies University of Sheffield Sheffield United Kingdom Centre for Computing and Social Responsibility De Montfort University Leicester United Kingdom School of Chemistry University of Bristol United Kingdom Department of Philosophy Faculty of Arts and Social Sciences Maastricht University Netherlands Biodiversity and Conservation Science Department of Biodiversity Conservation and Attractions Wildlife Research Centre Western Australia De Montfort University United Kingdom Lab for Uncertainty in Data and Decision Making (LUCID) School of Computer Science University of Nottingham United Kingdom

There is broad agreement that one important aspect of responsible innovation (RI) is to provide training on its principles and practices to current and future researchers and innovators, notably including doctoral students. Much less agreement can be observed concerning the question of what this training should consist of, how it should be delivered and how it could be assessed. The increasing institutional embedding of RI leads to calls for the alignment of RI training with training in other subjects. One can therefore observe a push towards the official assessment of RI training, for example in the recent call for proposals for centres for doctoral training by UK Research and Innovation. This editorial article takes its point of departure from the recognition that the RI community will need to react to the call for assessment of RI training. It provides an overview of the background and open questions around RI training and assessment as a background of examples of RI training assessment at doctoral level. There is unlikely to be one right way of assessing RI training across institutions and disciplines, but we expect that the examples provided in this article can help RI scholars and practitioners orient their training and its assessment in ways that are academically viable as well as supportive of the overall aims of RI. © 2023

关键词： Assessment Doctoral training Education Responsible innovation

Quantifying the quality of indoor maps 4

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Quantifying the quality of indoor maps

4th ISPRS Geospatial Week 2019

作者： Assali, M. Pipelidis, G. Podolskiy, V. Iwaszczuk, D. Heinen, L. Gerndt, M. Dept. of Computer Architecture and Parallel Systems Dept. of Informatics Technical University of Munich Munich Germany Software and Systems Engineering Research Group Dept. of Informatics Technical University of Munich Munich Germany Remote Sensing and Image Analysis Group Dept. of Civil and Environmental Engineering Science Technische Universität Darmstadt Germany BMW Group IT Munich Germany

Indoor maps are required for multiple applications, such as, navigation, building maintenance and robotics. One of common methods for map generation is laser scanning. In such maps, not only geometry of the map is of interest, but also its quality. This study aims at developing methods for real-time generation of indoor maps using features extracted from pointclouds obtained by a robot with their simultaneous quality assessment. We investigate, how this quality can be quantified for feature-based maps. First, we introduce a method for modeling 2D maps into 3D models that enable their usage for localization. Second, we review and evaluate a number of algorithms that can enable us to address features in a map. Hence, we enable the generation of objects from a pointcloud that has been sensed. Finally, we study several aspects of the map quality and we formalize them into metrics that can be applied to quantify their quality. © Authors 2019.

关键词： Robots

EUROPA - A ROS-based Open Platform for Educational Robotics

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EUROPA - A ROS-based Open Platform for Educational Robotics

IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems

作者： Georgios Karalekas Stavros Vologiannidis John Kalomiros Dept. of Computer Informatics and Telecommunications Engineering International Hellenic University

ISBN: (纸本)9781728140704

Introducing robotics to young students is becoming very important for modern education of all levels. This paper presents EUROPA, an educational robot, which was developed as a handy, low-cost and extensible platform of high capabilities, suitable to bring robotics to secondary school students and beyond. It is designed as a system of easily accessible hardware and open software that can be incorporated in STEM classes of all levels in the Greek education system. The proposed robot incorporates Robot Operating System (ROS) and is based on Python which is already taught in Greek modula on informatics, similarly to other countries worldwide. We present in detail the hardware and software architecture of our robot and define its advantages among similar state-of-the-art educational robots. EUROPA platform was introduced to a class of secondary school students with robotic experience in Lego Mindstorms, and was assessed with very positive results.

关键词： Educational robotics ROS STEM Stems Stemming Scanning transmission electron microscopy ROS1 gene EUROPA robotics Secondary Schools Open Software Robot Pythonidae Software architecture Platform

Revenue maximization approaches in iaas clouds: Research challenges and opportunities

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arXiv 2020年

作者： Badshah, Afzal Ghani, Anwar Daud, Ali Chronopoulos, Anthony Theodore Jalal, Ateeqa Department of Computer Science International Islamic University Islamabad Pakistan Department of Computer Science University of Texas San AntonioTX78249 United States Faculty Dept Computer Engineering and Informatics University of Patras Rio26500 Greece Department of Computer Science University of Science and Technology Bannu Bannu Pakistan

Revenue generation is the main concern of any business, particularly in the cloud, where there is no direct interaction between the provider and the consumer. Cloud computing is an emerging core for today's businesses, however, Its complications (e.g, installation and migration) with traditional markets are the main challenges. It earns more but needs exemplary performance and marketing skills. In recent years, cloud computing has become a successful paradigm for providing desktop services. It is expected that more than 331 billion will be invested by 2023, likewise, 51 billion devices are expected to be connected to the cloud. Infrastructure as a Service (IaaS) provides physical resources (e.g, computing, memory, storage and network) as VM instances. In this article, the main revenue factors are categorized as SLA and penalty management, resource scalability, customer satisfaction and management, resource utilization and provision, cost and price management, and advertising and auction. These parameters are investigated in detail and new dynamics for researchers in the field of the cloud are discovered. Copyright © 2020, The Authors. All rights reserved.

关键词： Commerce

COMPARISON OF OPTIMAL POWER FLOW FORMULATIONS IN ACTIVE DISTRIBUTION GRIDS

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COMPARISON OF OPTIMAL POWER FLOW FORMULATIONS IN ACTIVE DIST...

The 12th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion (MEDPOWER 2020)

作者： C. Mylonas S. Karagiannopoulos P. Aristidou D. Shchetinin G. Hug Power Systems Laboratory ETH Zurich 8092 Zurich Switzerland Dept. of Electrical Engineering Computer Engineering & Informatics Cyprus University of Technology 3036 Limassol Cyprus ABB Corporate Research Center 5405 Baden Switzerland

Active Distribution Networks (DNs) are expected to host an increasing number of Distributed Generators (DGs) and other Distributed Energy Resources (DERs), offering new flexible sources and enabling the provision of ancillary services to system operators. Centralized DER controls that use Optimal Power Flow (OPF) methods necessitate tractable and scalable computational tools that can handle large DNs with satisfactory performance. In this paper, we compare an iterative OPF method against the standard exact AC OPF calculations in terms of the computational effort and solution quality. Furthermore, we highlight the suitability of the selected formulation to offer voltage support (VS) as an ancillary service to the transmission network. The results are demonstrated using a combination of a medium and low voltage grid, and show that tractable OPF formulations can unlock financial business cases for DNs that can actively participate in VS schemes.

关键词： distributed power generation distribution networks load flow power grids iterative methods centralised control

Microwave Frequency Fiber Interferometry in Submarine Deployed Telecommunication Cables

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arXiv 2025年

作者： Bogris, A. Simos, C. Simos, I. Wang, Y. Fichtner, A. Deligiannidis, S. Melis, N.S. Mesaritakis, C. Department of Informatics and Computer Engineering University of West Attica Aghiou Spiridonos Egaleo12243 Greece Dept. of Physics University of Thessaly Lamia35100 Greece Department of Electrical and Electronics Engineering University of West Attica Egaleo12244 Greece Department of Earth and Planetary Sciences ETH Zurich Zurich Switzerland National Observatory of Athens Institute of Geodynamics Athens Greece Department of Biomedical Engineering University of West Attica Aghiou Spiridonos Egaleo12243 Greece

We operated a microwave frequency fiber interferometer in a telecommunication cable in the Ionian Sea, Greece, for two months. The capability of detecting undersea micro earthquakes (magnitude~1.5), tides and ocean wa... 详细信息

关键词： Interferometry

Automated Diagnosis of Cardiovascular Diseases from Cardiac Magnetic Resonance Imaging Using Deep Learning Models: A Review

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arXiv 2022年

作者： Jafari, Mahboobeh Shoeibi, Afshin Khodatars, Marjane Ghassemi, Navid Moridian, Parisa Delfan, Niloufar Alizadehsani, Roohallah Khosravi, Abbas Ling, Sai Ho Zhang, Yu-Dong Wang, Shui-Hua Gorriz, Juan M. Rokny, Hamid Alinejad Acharya, U. Rajendra Internship in BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia Data Science and Computational Intelligence Institute University of Granada Spain Department of Medical Engineering Mashhad Branch Islamic Azad University Mashhad Iran Faculty of Computer Engineering Dept. of Artificial Intelligence Engineering K. N. Toosi University of Technology Tehran Iran Deakin University VIC3217 Australia Australia School of Computing and Mathematical Sciences University of Leicester Leicester United Kingdom Department of Psychiatry University of Cambridge United Kingdom BioMedical Machine Learning Lab The Graduate School of Biomedical Engineering UNSW Sydney SydneyNSW2052 Australia UNSW Data Science Hub The University of New South Wales SydneyNSW2052 Australia Research Centre Macquarie University Sydney2109 Australia Ngee Ann Polytechnic Singapore599489 Singapore Dept. of Biomedical Informatics and Medical Engineering Asia University Taichung Taiwan Dept. of Biomedical Engineering School of Science and Technology Singapore University of Social Sciences Singapore

In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality globally. CVDs appear with minor symptoms and progressively get worse. The majority of people experience symptoms such as exhaustion, shortness of breath, ankle swelling, fluid retention, and other symptoms when starting CVD. Coronary artery disease (CAD), arrhythmia, cardiomyopathy, congenital heart defect (CHD), mitral regurgitation, and angina are the most common CVDs. Clinical methods such as blood tests, electrocardiography (ECG) signals, and medical imaging are the most effective methods used for the detection of CVDs. Among the diagnostic methods, cardiac magnetic resonance imaging (CMR) is increasingly used to diagnose, monitor the disease, plan treatment and predict CVDs. Coupled with all the advantages of CMR data, CVDs diagnosis is challenging for physicians due to many slices of data, low contrast, etc. To address these issues, deep learning (DL) techniques have been employed to the diagnosis of CVDs using CMR data, and much research is currently being conducted in this field. This review provides an overview of the studies performed in CVDs detection using CMR images and DL techniques. The introduction section examined CVDs types, diagnostic methods, and the most important medical imaging techniques. In the following, investigations to detect CVDs using CMR images and the most significant DL methods are presented. Another section discussed the challenges in diagnosing CVDs from CMR data. Next, the discussion section discusses the results of this review, and future work in CVDs diagnosis from CMR images and DL techniques are outlined. The most important findings of this study are presented in the conclusion section. © 2022, CC BY-NC-ND.

关键词： Electrocardiography