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International Conference on Frontiers in Computing and Systems, COMSYS 2020

作者： Ray, Soujanya Chatterjee, Kingshuk Majumdar, Ritaji Ganguly, Debayan Department of Computer Science and Engineering Netaji Subhash Engineering College Kolkata India Department of Computer Science Government College of Engineering and Ceramic Technology Kolkata India Advanced Computing and Microelectronics Unit Indian Statistical Institute Kolkata India Department of Computer Science Government College of Engineering and Leather Technology Kolkata India

ISBN: (纸本)9789811578335

Social network science and social interaction science is an interesting and steadily growing field of research in current time. Social network influences the lives of millions, and therefore the propagation of influence in such a network deserves study. In this paper, we have studied voting in a Watts-Strogatz small-world network for two parties. In our model, each node has an initial bias towards one of the parties (or can be neutral) and are influenced by their neighbours to vote for a particular party. We show via simulation that (i) for linear of logarithmic voting function, the small-scale variation is minimum, but the majority of the nodes tend to align towards one of the parties in the long term, (ii) for periodic voting function, the small-scale variations are sharp and oscillating, but in the long term the number of voters in each party roughly remains the same, (iii) the degree of the graph does not seem to have a strong influence on the result, and (iv) networks with higher small-world probability tend to resist the alignment of voters towards a particular party for a longer time as compared to networks with lower small-world probability. This majority voting model seems to efficiently capture the potential behaviour of voters on small-world network over a campaigning period. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Small-world networks

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A finite sufficient set of conditions for catalytic majorization

arXiv

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arXiv 2025年

作者： Elkouss, David Maity, Ananda G. Nema, Aditya Strelchuk, Sergii Networked Quantum Devices Unit Okinawa Institute of Science and Technology Graduate University Okinawa Onna-son904-0495 Japan Institute of Quantum Information RWTH Aachen Germany Department of Computer Science University of Oxford United Kingdom

The majorization relation has found numerous applications in mathematics, quantum information and resource theory, and quantum thermodynamics, where it describes the allowable transitions between two physical states. In many cases, when state vector x does not majorize state vector y, it is nevertheless possible to find a catalyst – another vector z such that x z majorizes y z. Determining the feasibility of such catalytic transformation typically involves checking an infinite set of inequalities. Here, we derive a finite sufficient set of inequalities that imply catalysis. Extending this framework to thermodynamics, we also establish a finite set of sufficient conditions for catalytic state transformations under thermal operations. For novel examples, we provide a software toolbox implementing these conditions. © 2025, CC BY-NC-ND.

关键词： Z transforms

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Amplitude-Based Sequential Optimization of Energy Harvesting with Reconfigurable Intelligent Surfaces

Amplitude-Based Sequential Optimization of Energy Harvesting...

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Asilomar Conference on Signals, Systems & computers

作者： Morteza Tavana Meysam Masoudi Emil Björnson School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Ericsson Global AI Accelerator (GAIA) unit Sweden

Reconfigurable Intelligent Surfaces (RISs) have gained immense popularity in recent years because of their ability to improve wireless coverage and their flexibility to adapt to the changes in a wireless environment. These advantages are due to RISs' ability to control and manipulate radio frequency (RF) wave propagation. RISs may be deployed in inaccessible locations where it is difficult or expensive to connect to the power grid. Energy harvesting (EH) can enable the RIS to self-sustain its operations without relying on external power sources. In this paper, we consider the problem of energy harvesting for RISs in the absence of coordination with the ambient RF source. We consider both direct and indirect EH scenarios and show that the same mathematical model applies to them. We propose a sequential phase-alignment algorithm that maximizes the received power based on only power measurements. We prove the convergence of the proposed algorithm to the optimal value under specific circumstances. Our simulation results show that the proposed algorithm converges to the optimal solution in a few iterations and outperforms the random phase update method in terms of the number of required measurements.

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Distributing graph states with a photon-weaving quantum server

arXiv

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arXiv 2025年

作者： Bhatti, Daniel Goodenough, Kenneth Networked Quantum Devices Unit Okinawa Institute of Science and Technology Graduate University Okinawa Japan College of Information and Computer Sciences University of Massachusetts Amherst AmherstMA01003 United States

One of the key aims of quantum networks is the efficient distribution of multipartite entangled states among end users. While various architectures have been proposed, each comes with distinct advantages and limitations. Many designs depend on long-lived quantum memories and deterministic gates, which, while powerful, introduce considerable cost and technical challenges. Experimentally cheaper alternatives that circumvent these constraints are often limited to specific types of entanglement and a specific number of users. Here, we present an experiment-friendly quantum server that relies only on linear optical elements, offering a flexible approach to multipartite entanglement distribution. Our so-called photon-weaving quantum server can generate and distribute one of several locally nonequivalent graph states, including Greenberger-Horne-Zeilinger (GHZ) states, as well as path, cycle, and caterpillar graph states. This is achieved through two distinct fusion protocols, i.e., multiphoton graph-state fusion (graph-state weaving) and multiphoton GHZ-state fusion (GHZ-state weaving), and can readily be implemented. Copyright © 2025, The Authors. All rights reserved.

关键词： Quantum entanglement

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A Netnographic-Based Semantic Analysis of Tweet Contents for Stress Management

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computers, Materials & Continua 2022年第1期70卷 1845-1856页

作者： Jari Jussila Eman Alkhammash Norah Saleh Alghamdi Prashanth Madhala Mohammad Ayoub Khan HAMK Smart Research Unit Häme University of Applied SciencesHämeenlinna13100Finland Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia College of Computer and Information Sciences Princess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Faculty of Management and Business Tampere UniversityTampere33720Finland College of Computing and Information Technologies University of BishaBisha67714Saudi Arabia

Social media platforms provide new value for markets and research *** article explores the use of social media data to enhance customer value *** case study involves a company that develops wearable Internet of Things(IoT)devices and services for stress *** and semantic annotation for recognizing and categorizing the context of tweets are conducted to gain a better understanding of users’stress management *** aim is to analyze the tweets about stress management practices and to identify the context from the ***,we map the tweets on pleasure and arousal to elicit customer *** analyzed a case study of a marketing strategy on the Twitter *** in the marketing campaign shared photos and texts about their stress management *** learning techniques were used to evaluate and estimate the emotions and contexts of the tweets posted by the campaign *** computational semantic analysis of the tweets was compared to the text analysis of the *** content analysis of only tweet images resulted in 96%accuracy in detecting tweet context,while that of the textual content of tweets yielded an accuracy of 91%.Semantic tagging by Ontotext was able to detect correct tweet context with an accuracy of 50%.

关键词： Social media stress semantic analysis Twitter context recognition

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Rough Fermatean fuzzy decision-based approach for modelling IDS classifiers in the federated learning of IoMT applications

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Neural Computing and Applications 2023年第30期35卷 22531-22549页

作者： Albahri, O.S. Al-Samarraay, Mohammed S. AlSattar, H.A. Alamoodi, A.H. Zaidan, A.A. Albahri, A.S. Zaidan, B.B. Jasim, Ali Najm Computer Techniques Engineering Department Mazaya University College Thi-Qar Nassiriya12733 Iraq Faculty of Computing and Meta-Technology Universiti Pendidikan Sultan Idris Perak Tanjong Malim35900 Malaysia Department of Business Administration College of Administrative Science The University of Mashreq Baghdad10021 Iraq SP Jain School of Global Management Lidcombe SydneyNSW2141 Australia Iraqi Commission for Computers and Informatics Baghdad10022 Iraq Future Technology Research Center College of Future National Yunlin University of Science and Technology 123 University Road Section 3 Yunlin Douliou64002 Taiwan Foundation of Alshuhda Baghdad Iraq MEU Research Unit Middle East University Amman Jordan

Intrusion detection systems (IDSs) are commonly employed to mitigate network security threats in various fields, including federated learning applications within the Internet of Medical Things (IoMT). However, IDSs face challenges owing to the sheer volume of network traffic, high-dimensional datasets and the necessity for real-time detection. Although machine learning integration assists IDSs in overcoming these challenges, modelling difficulties persist due to varied evaluation criteria and levels of conflict and importance. Multi-criteria decision-making (MCDM) solutions have been utilised in IoMT and IDS, yet they fall short in capturing the subjective judgements of experts and rely on normalisation approaches, which can impact results. This study seeks to address these issues through the integration of robust MCDM methodologies, namely fuzzy-weighted zero-inconsistency (FWZIC) and fuzzy decision by opinion score method (FDOSM). Utilising rough Fermatean fuzzy sets (RFFSs), this integration produces precise solutions with reduced uncertainty. Our methodology involves adopting a decision matrix for IDS classifiers based on integrated evaluation criteria, followed by deriving new formulations and developments for RFFSs-based FDOSM and FWZIC for the modelling and weighting of criteria, respectively. Evaluations using datasets involving 125,973 records and 41 features across 17 evaluation criteria revealed that accuracy–security and training time–performance weights yielded the highest scores, whereas false negative rate–security and CPU time–performance criteria received the lowest weights. The random forest emerged as the optimal IDS classifier. Systematic modelling, sensitivity analysis and comparative studies confirmed the robustness of our results. © 2023, Crown.

关键词： Integration

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The Sustainability Component of the Brand and the Purchase Intention of Gen Z: State of the Art

The Sustainability Component of the Brand and the Purchase I...

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International Conference on Marketing and Technologies, ICMarkTech 2023

作者： Coutinho, Evelina Maria Oliveira Au-Yong-Oliveira, Manuel Department of Economics Management Industrial Engineering and Tourism Campus Universitário de Santiago University of Aveiro Aveiro3810-193 Portugal Research Unit On Governance Competitiveness and Public Policies Campus Universitário de Santiago University of Aveiro Aveiro3810-193 Portugal INESC TEC-Institute for Systems and Computer Engineering Technology and Science Porto4200-465 Portugal

ISBN: (纸本)9789819736973

In recent decades, the concept of sustainability has taken on a key role in the agendas of political decision-makers, businesses, and society. Brands have incorporated attributes associated with the concept of sustainability, making it essential to understand how these attributes are perceived and how they influence purchasing decisions. Young consumers tend to be well informed about social and environmental aspects and are more sensitive than previous generations to environmental issues. Although Gen Z’s purchasing intentions are influenced by the sustainable practices of organizations, their preferences are not fully understood. Recent studies have shown that the sustainability component associated with the brand influences Gen Z’s purchase intentions, and that social and economic aspects are at the root of this, emphasizing the importance of corporate social responsibility and transparent brand communication in terms of sustainability. Understanding how the sustainability component of brands influences the purchasing decisions of young consumers is fundamental for defining future branding strategies. The aim of this paper is to describe the state of the art of the relationship between the sustainability component of the brand and the purchase intention of Gen Z, based on the literature. The topic has not yet been widely studied, so it leaves clues for future development. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Sustainable development goals

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Securing Data in an Internet of Things Network Using Blockchain technology: Smart Home Case

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SN computer science 2022年第2期3卷 167页

作者： Tchagna Kouanou, Aurelle Tchito Tchapga, Christian Sone Ekonde, Michael Monthe, Valery Mezatio, Brice Anicet Manga, Josépha Simo, Gael R. Muhozam, Yves Department of Computer Engineering College of Technology University of Buea Buea Cameroon Department of Training Research Development and Innovation InchTech’s Solutions Yaoundé Cameroon Department of Electrical and Electronic Engineering College of Technology University of Buea Buea Cameroon Department of Computer Science Faculty of Sciences University of Yaoundé 1 Yaoundé Cameroon Research Unit Condensed Matter Electronics and Signal Processing Department of Physics Faculty of Science University of Dschang PO Box 67 Dschang Cameroon

Every day, innovative technologies emerge (5G networks, quantum computing) or change to existing technologies (big data, deep learning, blockchain, etc.). These technologies are expected to play an essential role on the Internet of Things (IoT) systems and applications. The IoT architecture generates substantial amounts of diverse types of data at extremely high speeds. All these generated data need to be secure. Scalable and secure data sharing is essential for all technological domains. Taking into consideration of blockchain technology today in data security, we can also think about a method to secure IoT data based on blockchain. In this paper, we proposed a blockchain method to secure data in an IoT architecture. We used EOS Blockchain for its scalability, flexibility and native enhanced throughput. Architecture in a concept of a smart home using blockchain is proposed. We combine Arduino, Raspberry Pi and sensors to create an IoT ecosystem for a smart home. Data are collected and stored in EOS blockchain for better security and integrity. We use Raspberry Pi as a client to get data in our developed blockchain. The real implementation is performed and the obtained results show us that we can send more than 500 data per second in our EOS blockchain. We discuss our results and saw that our blockchain method outperformed those in related works in terms of the number of data stored per millisecond in blockchain and the scalability. The proposed EOS blockchain pipeline for securing Smart Home data is provided at the end of this paper. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2022.

关键词： Architecture Blockchain Data security IoT Smart home

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Anomaly Handwritten Text Detection for Automatic Descriptive Answer Evaluation 11

Anomaly Handwritten Text Detection for Automatic Descriptive...

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11th International Conference on Computing and Pattern Recognition, ICCPR 2022

作者： Chatterjee, Nilanjana Shivakumara, Palaiahnaakote Pal, Umapada Lu, Tong Lu, Yue Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia National Key Lab for Novel Software Technology Nanjing University Nanjing China Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai China

ISBN: (纸本)9781450397056

Although there are advanced technologies for character recognition, automatic descriptive answer evaluation is an open challenge for the document image analysis community due to large diversified handwritten text and answers to the question. This paper presents a novel method for detecting anomaly handwritten text in the responses written by the students to the questions. The method is proposed based on the fact that when the students are confident in answering questions, the students usually write answers legibly and neatly while they are not confident, they write sloppy writing which may not be easy for the reader to understand. To detect such anomaly handwritten text, we explore a new combination of Fourier transform and deep learning model for detecting edges. This result preserves the structure of handwritten text. For extracting features for classification of anomaly text and normal text, the proposed method studies the behavior of writing style, especially the variation at ascenders and descenders. Therefore, the proposed work draws principal axis which is invariant to rotation, scaling and some extent to distortion for the edge images. With respect to principal axis, the proposed method draws medial axis using uppermost and lowermost points. The distance between the medial axis and principal axis points are considered as feature vector. Further, the feature vector is passed to Artificial Neural Network for classification of anomaly text. The proposed method is evaluated by testing on our own dataset, standard dataset of gender identification (IAM) and handwritten forgery detection dataset (ACPR 2019). The results on different datasets show that the proposed work outperforms the existing methods. © 2022 ACM.

关键词： Students

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Subjective Logic Encodings

arXiv

引用

arXiv 2025年

作者： Vasilakes, Jake Zerva, Chrysoula Ananiadou, Sophia Department of Computer Science University of Sheffield United Kingdom Instituto de Telecomunicaçoes ELLIS Unit Lisbon Instituto Superior Tecnico Universidade de Lisboa Portugal National Centre for Text Mining Department of Computer Science The University of Manchester Artificial Intelligence Research Center National Institute of Advanced Industrial Science and Technology United Kingdom

Many existing approaches for learning from labeled data assume the existence of gold-standard labels. According to these approaches, inter-annotator disagreement is seen as noise to be removed, either through refinement of annotation guidelines, label adjudication, or label filtering. However, annotator disagreement can rarely be totally eradicated, especially on more subjective tasks such as sentiment analysis or hate speech detection where disagreement is natural. Therefore, a new approach to learning from labeled data, called data perspectivism, seeks to leverage inter-annotator disagreement to learn models that stay true to the inherent uncertainty of the task by treating annotations as opinions of the annotators, rather than gold-standard facts. Despite this conceptual grounding, existing methods under data perspectivism are limited to using disagreement as the sole source of annotation uncertainty. To expand the possibilities of data perspectivism, we introduce Subjective Logic Encodings (SLEs), a flexible framework for constructing classification targets that explicitly encodes annotations as opinions of the annotators. Based on Subjective Logic Theory, SLEs encode labels as Dirichlet distributions and provide principled methods for encoding and aggregating various types of annotation uncertainty —annotator confidence, reliability, and disagreement— into the targets. We show that SLEs are a generalization of other types of label encodings as well as how to estimate models to predict SLEs using a distribution matching objective. We make our code publicly available at https://***/jvasilakes/SLEncodings. © 2025, CC BY.

关键词： Encoding (symbols)

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