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检索条件"丛书名=Lecture Notes in Networks and Systems"

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Comparative Analysis of Small Cells Efficiency Between 4G and 5G 9th

Comparative Analysis of Small Cells Efficiency Between 4G an...

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Malindzisa, Temhlanga Mashego, Theophilus Bembe, Mncedisi Univ Mpumalanga Cnr R40 & D725 Riverside ZA-1200 Mbombela South Africa

ISBN: (纸本)9789819754403;9789819754410

The fifth generation (5G) mobile network is designed to revolutionize mobile broadband technology by addressing the shortfalls of its predecessor the fourth generation (4G) mobile network, also known as the long-term evolution (LTE), with key considerations of higher data rate, improved power efficiency, low latency and better quality of service. This work analyzes the impact of small cells on the performance of LTE (4G) and 5G networks. In this paper, 4G LTE and 5G networks were simulated using Excel for simplicity and performance evaluations were carried out. The performance metrics used for the evaluations are basic system throughput and offloading. The results of the evaluations on both networks were analyzed. The results showed that 5G network performs better than 4G LTE network whether the small cell base station (SBS) is closer to the macro base station (MBS) or at the edge of the macro base station.

关键词： Hetnets Macro base station Small cells base station

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Robot Visual Servoing via Guess Filter 20th

Robot Visual Servoing via Guess Filter

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20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based systems

作者： Cossin, Tristan Strauss, Olivier Univ Montpellier LIRMM Montpellier France

ISBN: (纸本)9783031739965;9783031739972

In this paper, we propose to use an alternative to the classical Kalman filter (KF) to slave the movement of a robot manipulator to the measurements delivered by a far-infrared reflectometry sensor. This alternative, called Guess filter (GF), uses fuzzy rought set theory and possibilistic inference. It is particularly suited to measurements that are both imprecise and inaccurate. We compare the ability of GF and KF approaches to be used to control a robot on a simulated experience that favors neither approach.

关键词： Granulation Filtering Control Fuzzy inference

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Cryptanalysis and Countermeasures on Multivariate Cubic Polynomial-Based Digital Signature 3rd

Cryptanalysis and Countermeasures on Multivariate Cubic Poly...

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3rd International Conference on Network Security and Blockchain Technology

作者： Namdeo, Kuldeep Mishra, Dheerendra Srivastava, Namita Maulana Azad Natl Inst Technol Bhopal India

ISBN: (纸本)9789819780501;9789819780518

Multivariate Public Key Cryptography (MPKC) is one of the promising candidates of Post-quantum Cryptography (PQC) that ensures data security, information security, computer system security, and network security against large-scale quantum computers. Our research work in this article focuses on analyzing rank weakness in cubic cryptographic structures. The extension of the rank attack from quadratic to cubic polynomial system demonstrates the occurrence of the same rank fault as in the case of multivariate quadratic polynomial-based cryptosystems. In this paper, we present the cryptanalysis of the multivariate cubic polynomial-based digital signature algorithm, which is basically based on the big field system called Hidden Field Equation (HFE) and uses the structure of the state-of-the-art signature scheme in multivariate cryptography called Rainbow. In addition to this, we provide a countermeasure to overcome the presented attack on the MPKC digital signature.

关键词： MQ-Problem Multivariate polynomials Multivariate public key cryptography Digital signature

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WECM: An Evidential Subspace Clustering Algorithm 20th

WECM: An Evidential Subspace Clustering Algorithm

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20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based systems

作者： Van Tri Do Antoine, Violaine Koko, Jonas Univ Clermont Auvergne Clermont Auvergne INP LIMOS UMR CNRS 6158 F-63000 Clermont Ferrand France

ISBN: (纸本)9783031739965;9783031739972

This paper introduces WECM, a novel evidential and subspace clustering algorithm. It is based on the Evidential c-means, a variant of the k-means designed to produce a credal partition, allowing a better representation of the partial knowledge regarding the class membership of objects. The WECM algorithm integrates weights on features and clusters to enhance the clustering separability and interpretability. Experiments conducted on synthetic and real data show the positive effects of the weights on the clustering performances.

关键词： evidential c-means subspace clustering weights belief function theory

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Sentiment Impact on Fake News Detection: A Preliminary Study 20th

Sentiment Impact on Fake News Detection: A Preliminary Study

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20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based systems

作者： Lomasto, Luigi Aurucci, Raffaele Brandi, Yuri Gajewski, Lukasz Lettieri, Nicola Malandrino, Delfina Zaccagnino, Rocco Univ Salerno Dept Comp Sci Fisciano Italy Natl Inst Publ Policy Anal INAPP Rome Italy

ISBN: (纸本)9783031739965;9783031739972

The information disorder phenomenon represents one of the main challenges for the current society, that researchers of a huge variety of scientific areas are trying to solve. To date, the majority of the studies carried out in this context are focused on Machine Learning-based Fake News detectors trained on textual data. Despite the numerous attempts available in the literature and the promising results of such models, unfortunately, the expectations are not truly met considering their use in real-world scenarios. The main limitations are directly related to the nature of the phenomenon since the model trained on past events can't understand and classify novel contents and breaking news. In the current work, we study if sentiment discrepancy between news and its associated evidence can determine the possible presence of fake content. In fact checking activities, the evidence are inferred claims or information used to accept or reject shared news [2]. To do that we have conducted a preliminary study in which the outcome is a metric called Negativity Score. This metric can be used as a feature in Fake News detection models and automated fact-checking activities. For completeness, we have also provided a framework that uses the proposed metric. The results of preliminary experiments highlight the possibility of exploiting sentiment aspects in addition to more common and well-known approaches.

关键词： Information Disorder Fake News Automated Fact-Checking Sentiment Analysis Natural Language Processing

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Clustering Performance of an Evolutionary K-Means Algorithm 9th

Clustering Performance of an Evolutionary K-Means Algorithm

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9th International Congress on Information and Communication Technology (ICICT)

作者： Nigro, Libero Cicirelli, Franco Pupo, Francesco Univ Calabria DIMES I-87036 Arcavacata Di Rende Italy Natl Res Council Italy Inst High Performance Comp & Networking ICAR CNR I-87036 Arcavacata Di Rende Italy

ISBN: (纸本)9789819750344;9789819750351

This paper continues research aimed at improving the performance accuracy of an evolutionary K-Means algorithm named Population-Based K-Means (PBKM). The PBKM design tries to overcome some limitations of basic K-Means behavior by two steps. In the first step, a population is built with a certain number of centroid candidates, some of which naturally located close to ground truth centroids. In the second step, the population candidate centroids are systematically recombined to achieve a careful clustering solution. Both steps depend on the use of Repeated K-Means together with careful seeding. The paper's contribution paper consists in developing a new seeding method in the crucial first step of population set-up. Each candidate solution is determined by randomly splitting the dataset into a certain number of segments, clustering each segment by careful seeding, and merging the clusters of the various segments through a pairwise-nearest-neighbor (PNN) strategy. The paper demonstrates the clustering performance of the new PBKM by several simulation experiments carried out on synthetic and real-world datasets.

关键词： Unsupervised clustering K-Means Seeding methods Evolutionary clustering Merging clusters by pairwise-nearest neighbor Benchmark datasets Real-world datasets Java

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Designing a Novel Fuzzy Association Rule Mining Algorithm for Federated Environments 20th

Designing a Novel Fuzzy Association Rule Mining Algorithm fo...

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20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based systems

作者： Fernandez-Basso, Carlos Ruiz, M. Dolores Martin-Bautista, Maria J. Univ Granada Res Ctr Informat & Communicat Technol CITIC UGR Granada 18014 Spain UCL Div Psychol & Language Sci Causal Cognit Lab London England Univ Granada Dept Comp Sci & Artificial Intelligence Granada 18014 Spain

ISBN: (纸本)9783031739965;9783031739972

This paper introduces a novel fuzzy association rule mining algorithm explicitly developed for federated environments. With exponential growth in datasets and increasing data privacy concerns, solutions such as federated learning have become at the forefront of secure and efficient data analysis. However, efficiently finding meaningful and relevant patterns in data across decentralized databases remains challenging. To address this, we propose integrating fuzzy logic with association rule mining in a federated setting. The ability of fuzzy logic to handle uncertainty and nuance in data combined with the distributed data mining process of federated systems, creates an efficient, secure, and powerful tool for pattern discovery. Our proposed algorithm respects data privacy and effectively manages communication overhead, an innate challenge in federated systems. Experimental results demonstrate the efficacy of the proposed algorithm. The system has significant implications for the healthcare sector, where data volume and privacy concerns are paramount.

关键词： Association rules federated learning data mining privacy preserving

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Deep Learning-Based Diagnosis of Leukemia in Africa: Case of Acute Lymphoblastic and Acute Myeloid Leukemia in Senegal 9th

Deep Learning-Based Diagnosis of Leukemia in Africa: Case of...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Diagne, Therese Daba Siga Ba, Mandicou Sall, Abibatou Toure, Fadel Fall, Ibrahima Diagne, Khadija Diouf, Assane Sene, Ibrahima Ngom, Charles Abdoulaye Diop, Idy Bah, Alassane Cheikh Anta Diop Univ Dakar UCAD Res Inst Dev IRD Unit Math Modeling & Comp Sci Complex Syst UMMISC Polytech Higher Sch ESP Dakar Senegal Univ Quebec Trois Rivieres Dept Math & Comp Sci Trois Rivieres PQ Canada Dalal Jamm Natl Hosp Ctr Hematol Dept Dakar Senegal

ISBN: (纸本)9789819754403;9789819754410

Early and accurate diagnosis of leukemia in Africa, particularly for children, remains a major public health challenge. In the current paper, we propose an application of deep learning (DL) and computer vision approaches in order to improve the diagnosis of acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). We rely on two models, namely ViT and YOLOv8, that have been trained, evaluated on public open dataset (C-NMC dataset [1]) and designed for identifying acute lymphoblastic leukemia cell from microscopic images of immature blood cells. The results of this experimental evaluation reveal that YOLOv8 gives better performance in the context of limited data and resources. We then selected YOLOv8 pre-trained models and adopted a transfer learning approach on augmented data we collected from the Senegalese context of the Dalal Jamm Hospital. The results obtained present a precision of 96.6%, a recall of 92.9%, and an mAP50 of 98.6%. These encouraging performances demonstrate the ability of YOLOv8 to accurately identify ALL and AML cells.

关键词： Deep learning Computer vision Cancer blood cells Lymphoblasts Myeloblasts ViT YOLOv8 Data augmentation Transfer learning

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Behavioral Dynamic Portfolio Selection via Epsilon-Contaminations 20th

Behavioral Dynamic Portfolio Selection via Epsilon-Contamina...

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20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based systems

作者： Cinfrignini, Andrea Petturiti, Davide Vantaggi, Barbara Sapienza Univ Rome Dept MEMOTEF Rome Italy Univ Perugia Dept Econ Perugia Italy

ISBN: (纸本)9783031739965;9783031739972

We consider a dynamic portfolio selection problem in a finite horizon binomial market model, composed of a non-dividend-paying risky stock and a risk-free bond. We assume that the investor's behavior distinguishes between gains and losses, as in the classical cumulative prospect theory (CPT). This is achieved by considering preferences that are represented by a CPT-like functional, depending on an S-shaped utility function. At the same time, we model investor's beliefs on gains and losses through two different epsilon-contaminations of the "real-world" probability measure. We formulate the portfolio selection problem in terms of the final wealth and reduce it to an iterative search problem over the set of optimal solutions of a family of non-linear optimization problems.

关键词： Behavioral investor S-shaped utility function Epsilon-contamination Dynamic portfolio selection

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Smart Solar Energy Management System Using Wi-Fi Wireless Communication 9th

Smart Solar Energy Management System Using Wi-Fi Wireless Co...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Zaeri, Hassan Saleh, Fatma Zaeri, Naser Kuwait Univ Dept Elect Engn POB 5969 Safat 13060 Kuwait Arab Open Univ Fac Comp Studies POB 830 Kuwait Kuwait

ISBN: (纸本)9789819750344;9789819750351

Most of the current solar energy systems use fixed solar panels that are oriented toward one direction. In this paper, we present the initial stages of an ongoing project that considers absorbing maximum solar energy by tracking the sun's direction. This will maximize the produced electricity and enhance system efficiency. The proposed architecture consists of hardware and software aimed at sensing maximum illumination based on a photovoltaic panel controlled by a servomotor. This solar tracking system is remotely managed by a wireless communication system based on Wi-Fi technology. This is accomplished by two user interfaces that offer different parameter readings and various statistical analyses. The obtained results are encouraging and promising and furnish a platform for future applications in the field of solar energy generation.

关键词： Smart system Solar energy Wireless communication Wi-Fi

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