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31st International Conference on Computational Linguistics, COLING 2025

作者： Scholz, Karen Wenzel, Markus Fraunhofer Institute for Digital Medicine MEVIS Bremen Germany University of Bremen Faculty 3: Mathematics/Computer Science Germany

ISBN: (纸本)9798891761964

Clinical reports and scientific health information sources are usually written for medical experts preventing patients from understanding the main messages of these texts. Making them comprehensible for patients is important to enable patients to make informed health decisions. Metrics are required to assess readability and to evaluate text simplification methods. However, research has mainly focused on English medical texts. We collected a set of 18 statistical, part-of-speech-based, syntactic, semantic and fluency metrics from related studies and evaluate their suitability to measure readability of German medical texts. We perform multiple t-tests on technical abstracts from English and German scientific articles and related simplified summaries, respectively. While semantic and fluency metrics can be successfully transferred to German medical texts, multiple statistical, part-of-speech-based, and syntactic metrics behave differently when they are applied to German medical texts requiring careful interpretation. © 2025 Association for Computational Linguistics.

关键词： Syntactics

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Oral Cancer detection using Histopathology Images 2

Oral Cancer detection using Histopathology Images

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2nd IEEE International Conference on Advances in Information Technology, ICAIT 2024

作者： Meyyappan, M. Verma, Aniket Kaushik, Aarush Sathyapriya, L. Suresh Anand, M. Shanmugam, Selvanayaki Kolandapalayam SRM Institute of Science and Technology Kattankulathur Chennai India Department of Mathematics and Computer Science Ashland University OH United States

ISBN: (纸本)9798350383867

To increase the chances of survival for the millions of individuals impacted by oral cancer (OC), early detection of the disease is essential. More than 177,384 people died from OC in 2018, and people in the low- to middle-class demographic are primarily affected. The histological examination is the antiquated method of detecting mouth cancer. We are utilizing Deep Learning algorithms to identify OC and automate the process. This paper suggests using histopathology photos to identify OC by building CNN-based models using a transfer learning (TL) technique, then assembling the models to get the best accuracy possible. DenseNet-201, Resnet-50, and EfficientNet-B3 will be used to train the TL models using histopathology pictures. When the three models are combined, the final model has an accuracy of 93.16%, which enables the model to be used in real time and is useful for categorizing images of OC. © 2024 IEEE.

关键词： Lung cancer

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INFERENCE PROCESSES IN THE AUTOMATIC COMMUNICATION SYSTEM FOR AUTONOMOUS VESSELS

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Archives of Transport 2023年第4期68卷 117-135页

作者： Pańka, Anna Wolejsza, Piotr Institute of Mathematics Physics and Chemistry Maritime University of Szczecin Szczecin Poland Faculty of Computer Science and Telecommunication Maritime University of Szczecin Szczecin Poland

The era of autonomous ships has already begun in maritime transport. The 30-year forecast for the development of marine technologies predicts many autonomous vessels at sea. This will necessitate radical implementation of new intelligent maritime navigation systems. One of the intelligent systems that has to be implemented is a collision avoidance system. The inference process is a key element of autonomous manoeuvres. These authors propose an inference process that enables exchange of information, intentions and expectations between autonomous vessels and gives them an opportunity to negotiate a safe manoeuvre satisfying all the parties concerned. The model of inference in the communication process has been presented. Methods and algorithms for information exchange and negotiation have been developed. These models were implemented and tested under various conditions. The results of case studies indicate that it is possible to effectively communicate and negotiate used the developed method. To demonstrate the effectiveness of the presented approach over 30 random simulations have been carried out. After successful laboratory tests, over 100 scenarios were executed in quasi-real conditions and fully operational conditions. Tests were carried out in the center of the Foundation for the Safety of Navigation and Environmental Protection on Lake Silm in Ilawa, Poland. In the framework of project AVAL (Autonomous Vessel with an Air Look) POIR.04.01.04-00-0025-16, 82 random scenarios involving four vessels were performed and 60 random scenarios with two vessels. In 2020 tests were carried out in real conditions on the ferries Wolin and m/f Gryf. The communication and negotiation system presented in the article has been designed and developed specially for maritime navigation purposes. The authors believe that the presented solution can be one of various solutions implemented in autonomous shipping in the near future. © 2023 Warsaw University of Technology. All rights reser

关键词： Collision avoidance

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HS–WOA–MANET: a hybrid meta-heuristic approach-based multi-objective constraints for energy efficient routing protocol in mobile ad hoc networks

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Journal of Reliable Intelligent Environments 2024年第2期10卷 151-176页

作者： Goswami, Subhrananda Mondal, Sukumar Johardar, Subhankar Das, Chandan Bikash Research Centre of Natural and Applied Sciences Department of Computer Science Raja Narendra Lal Khan Women’s College Affiliated to Vidyasagar University Midnapore India Department of Mathematics Raja Narendra Lal Khan Women’s College Midnapore India Department of Computer Science Haldia Institute of Technology Haldia India Department of Mathematics Tamralipta Mahavidyalaya Tamluk India

A self-organizing, reconfigurable, and structure-less wireless network that provides intended communications without any radio infrastructure is called the mobile ad hoc network (MANETs). It is generally utilized in special outside occasions, locations, military surgeries, and natural disasters. In MANET, providing security is the primary issue because of the adoption of network structures. Moreover, the modifications in dynamic topologies expose the strike selection, such as routing, eavesdropping, and alteration of several programs. If MANET has several privacy and security issues, then it may surpass the quality of services (QoS). Hence, the security in MANET is guaranteed by using intrusion tracking approaches. This intrusion tracking system regulates the MANET in recognizing some other violation weaknesses. High protections are provided by detecting intrusions from the entire network, which includes attacks that are beyond the network layer. The nodes are not merely altered by the power collapse in the system, but it is also capable of transferring the packets in the network, which depends on the total system life. An effective routing protocol is designed to select the optimal paths for enhancing navigation in MANETs. Moreover, the terms secure routing and energy efficiency are critical problems when changing the network topology and limiting resources with this kind of network. A hybridized optimization-aided routing strategy is offered in this research work to provide an energy-efficient routing protocol. At the initial stage, the experimentation is conducted based on the sensor nodes in MANET. Since the existing models are ineffective in achieving high energy efficiency, the new routing protocol is developed by proposing the hybrid optimization algorithm. Accordingly, the suggested work is regarded for optimizing the shortest path in the routing model by using the Hybrid Sailfish Optimizer and Whale Optimization Algorithm (HS-WOA). To validate the network e

关键词： Mobile ad hoc networks

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Blockchain-based secure and transparent election and vote counting mechanism using secret sharing scheme

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 14009-14027页

作者： Chouhan, Vikas Arora, Anshul Department of Computer Science and Engineering Indian Institute of Technology Roorkee Roorkee India Department of Applied Mathematics Delhi Technological University Delhi India

Privacy and transparency in vote counting are the most prevalent concerns these days due to the involvement of untrusted authorities in the counting process. As a result, the counting process faces significant privacy, trust, and transparency hurdles. Hence, there is a need for an efficient and trusted mechanism to resolve such problems. Blockchain technology has the potential to bring transparency and trust in several applications. Therefore, in this work, we explore blockchain technology in conjunction with a secure partitioning scheme to promote transparency, trust, and privacy between users and participating authorities in a decentralized platform. This paper presents a chaincode-based implementation of our proposed secure and verifiable vote counting mechanism that enables trust and fairness over a decentralized platform. Multiple authorities participate in the vote counting process in a trusted manner to cooperate and coordinate in a decision process over a decentralized platform. Our research exhibits that blockchain technology can eliminate the trust gaps and increase transparency and fairness in the election and vote counting procedure. We register user votes in the blockchain platform based on the secret sharing mechanism to enable fairness and openness between counting authorities. Each vote is recorded into the distributed ledger to support openness and verifiability in our mechanism. The ledger is accessible to every registered user as per the permissioned blockchain policy. We created many authorities in the blockchain network and deployed multiple smart contracts on the Hyperledger platform to analyze the feasibility of our strategy. The performance results are obtained and reported using the Hyperledger Caliper benchmark tool. The results demonstrate that the proposed chaincode-based solution achieves the highest throughput at 200–400 tps for fetching and removing contracts. We achieve the optimal latency of 18.09 s for the vote distribution contract

关键词： Smart contract

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VTAN: A Novel Video Transformer Attention-Based Network for Dynamic Sign Language Recognition

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computers, Materials & Continua 2025年第2期82卷 2793-2812页

作者： Ziyang Deng Weidong Min Qing Han Mengxue Liu Longfei Li School of Mathematics and Computer Science Nanchang UniversityNanchang330031China Institute of Metaverse Nanchang UniversityNanchang330031China Jiangxi Provincial Key Laboratory of Virtual Reality Nanchang UniversityNanchang330031China

Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dynamic sign language requires identifying keyframes that best represent the signs, and missing these keyframes reduces accuracy. Secondly, some methods do not focus enough on hand regions, which are small within the overall frame, leading to information loss. To address these challenges, we propose a novel Video Transformer Attention-based Network (VTAN) for dynamic sign language recognition. Our approach prioritizes informative frames and hand regions effectively. To tackle the first issue, we designed a keyframe extraction module enhanced by a convolutional autoencoder, which focuses on selecting information-rich frames and eliminating redundant ones from the video sequences. For the second issue, we developed a soft attention-based transformer module that emphasizes extracting features from hand regions, ensuring that the network pays more attention to hand information within sequences. This dual-focus approach improves effective dynamic sign language recognition by addressing the key challenges of identifying critical frames and emphasizing hand regions. Experimental results on two public benchmark datasets demonstrate the effectiveness of our network, outperforming most of the typical methods in sign language recognition tasks.

关键词： Dynamic sign language recognition transformer soft attention attention-based visual feature aggregation

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Energy-based model order reduction for linear stochastic Galerkin systems of second order

Energy-based model order reduction for linear stochastic Gal...

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93rd Annual Meeting of the International Association of Applied mathematics and Mechanics, GAMM 2023

作者： Pulch, Roland Institute of Mathematics and Computer Science University of Greifswald Greifswald Germany

We consider a second-order linear system of ordinary differential equations (ODEs) including random variables. A stochastic Galerkin method yields a larger deterministic linear system of ODEs. We apply a model order reduction (MOR) of this high-dimensional linear dynamical system, where its internal energy represents a quadratic quantity of interest. We investigate the properties of this MOR with respect to stability, passivity and energy dissipation. Numerical results are shown for a system modelling a mass-spring-damper configuration. © 2023 The Authors. Proceedings in Applied mathematics & Mechanics published by Wiley-VCH GmbH.

关键词： Stochastic systems

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Approximation Algorithms and Lower Bounds for Graph Burning 26

Approximation Algorithms and Lower Bounds for Graph Burning

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26th International Conference on Approximation Algorithms for Combinatorial Optimization Problems, APPROX 2023 and the 27th International Conference on Randomization and Computation, RANDOM 2023

作者： Lieskovský, Matej Sgall, Jiří Feldmann, Andreas Emil Faculty of Mathematics and Physics Computer Science Institute of Charles University Prague Czech Republic Department of Computer Science University of Sheffield United Kingdom

ISBN: (纸本)9783959772969

Graph Burning models information spreading in a given graph as a process such that in each step one node is infected (informed) and also the infection spreads to all neighbors of previously infected nodes. Formally, given a graph G = (V, E), possibly with edge lengths, the burning number b(G) is the minimum number g such that there exist nodes v0, . . ., vg−1 ∈ V satisfying the property that for each u ∈ V there exists i ∈ {0, . . ., g − 1} so that the distance between u and vi is at most i. We present a randomized 2.314-approximation algorithm for computing the burning number of a general graph, even with arbitrary edge lengths. We complement this by an approximation lower bound of 2 for the case of equal length edges, and a lower bound of 4/3 for the case when edges are restricted to have length 1. This improves on the previous 3-approximation algorithm and an APX-hardness result. © 2023 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Approximation algorithms

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Enhancing Accuracy with Recursive Feature Selection Using Multiple Machine Learning and Deep Learning Techniques on NSL-KDD Dataset 1

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2nd International Conference on Advances in Data-driven Computing and Intelligent Systems, ADCIS 2023

作者： Mohanty, Subrat Kumar, Satendra Agarwal, Mayank Department of Mathematics Indian Institute of Technology Patna India Department of Computer Science and Engineering Indian Institute of Technology Patna India

ISBN: (数字)9789819995189

ISBN: (纸本)9789819995172

The world has moved toward digital revolution and more and more services are now being available online. This has presented significant challenges in ensuring the availability, integrity, and confidentiality of networks. Therefore, the implementation of intrusion detection systems (IDS) that actively monitor network activity and dynamically analyze incoming traffic has become essential. In modern computer networks, IDS play a critical role in identifying and alerting administrators of any malicious activities that could threaten data *** research aims to evaluate machine learning (ML) and deep learning (DL) techniques for intrusion detection using the NSL-KDD dataset. While having many features may seem advantageous, it doesn’t always lead to improved performance on large datasets. Reducing and picking just the right set of features may improve both speed and accuracy. This is why a method called recursive feature elimination (RFE) is utilized to select the most relevant features for the NSL-KDD dataset. In order to test the efficacy of ML and DL methods in IDS, we have undertaken a comprehensive experiment. Specifically, we tested the effectiveness of several algorithms, including CNN, RNN, LSTM, GB, CART, and CatBoost. Our study involved evaluating the performance of various algorithms and comparing them, and the detection accuracy [lowest-highest] for all the attacks are as follows: DoS [98.79–99.81%], Probe [96.34–99.64%], R2L [96.15–98.66%], U2R [79.98–99.73%]. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Intrusion detection

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Multi-frame Depth Estimation for Autonomous Driving Using Motion Masking and Self-supervised Learning 1

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2nd International Conference on Intelligent Computing Systems and Applications, ICICSA 2023

作者： Singh, Om Biswas, Anupam Paul, Rajdeep Department of Mathematics National Institute of Technology Silchar India Department of Computer Science and Engineering National Institute of Technology Silchar India

ISBN: (数字)9789819754120

ISBN: (纸本)9789819754113

Fisheye cameras are often employed in automatic driving for 360∘ near-field sensing around the car. This paper suggests a multi-task visual perception network using rectified fisheye photographs and motion masking to assist the vehicle in detecting its surroundings. However, strong nonlinear distortions constitute a trade-off and necessitate more complex algorithms. Dense-depth supervision in practice has shown promise and may be able to address the problem, even though it can be difficult to offer accurate methods for self-supervised learning. The supervision signal from the neighbouring frames is used to train self-supervised depth estimation networks to forecast scene depth. Additionally, the information between the consecutive frames consists of moving objects which has relative motion between them with respect to the motion of the camera which will produce bias and must be tackled with motion masking annotations before feeding to the network. Also, for further ablation study, the proposed system is trained with the unstructured environments of roads that most developing countries have. Thus, we used AdasInd dataset along with WoodScape and Kitti dataset. Further, to measure the accuracy of the output from the depth pixel, a novel measure relative pixel depth alignment (RPDA) is proposed. Most monocular networks do not make use of this additional signal, ignoring crucial information that can enhance expected depth. Therefore, we propose multi-frame depth estimation from fisheye images using self-supervised learning, a dense adaptive depth estimation method that makes use of the sequential data accessible during test time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Pixels

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