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2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Airiyoshi, Ryotai Hasegawa, Mikio Ohtsuki, Tomoaki Li, Aohan Graduate School of Informatics and Engineering The University of Electro-Communications Tokyo Japan Tokyo University of Science Department of Electrical Engineering Tokyo Japan Keio University Department of Information and Computer Science Yokohama Japan

ISBN: (纸本)9798350368369

With the increase in demand for Internet of Things (IoT) applications, the number of IoT devices has drastically grown, making spectrum resources seriously insufficient. Transmission collisions and retransmissions increase power consumption. Therefore, even in long-range (LoRa) networks, selecting appropriate transmission parameters, such as channel and transmission power, is essential to improve energy efficiency. However, due to the limited computational ability and memory, traditional transmission parameter selection methods for LoRa networks are challenging to implement on LoRa devices. To solve this problem, a distributed reinforcement learning-based channel and transmission power selection method is proposed, which can be implemented on the LoRa devices to improve energy efficiency in this paper. Specifically, the channel and transmission power selection problem in LoRa networks is first mapped to the multi-armed-bandit (MAB) problem. Then, an MAB-based method is introduced to solve the formulated transmission parameter selection problem based on the acknowledgment (ACK) packet and the power consumption for data transmission of the LoRa device. The performance of the proposed method is evaluated by the constructed actual LoRa network. Experimental results show that the proposed method performs better than fixed assignment, adaptive data rate low-complexity (ADR-Lite), and e-greedy-based methods in terms of both transmission success rate and energy efficiency. © 2025 IEEE.

关键词： Reinforcement learning

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Optimizing Symbol Visibility Through Displacement 19

Optimizing Symbol Visibility Through Displacement

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19th Scandinavian Symposium on Algorithm Theory, SWAT 2024

作者： Gärtner, Bernd Kalani, Vishwas Reddy, Meghana M. Meulemans, Wouter Speckmann, Bettina Stojaković, Miloš Department of Computer Science ETH Zürich Switzerland Department of Computer Science and Engineering I.I.T. Delhi India Department of Mathematics and Computer Science TU Eindhoven Netherlands Department of Mathematics and Informatics Faculty of Sciences University of Novi Sad Serbia

ISBN: (纸本)9783959773188

In information visualization, the position of symbols often encodes associated data values. When visualizing data elements with both a numerical and a categorical dimension, positioning in the categorical axis admits some flexibility. This flexibility can be exploited to reduce symbol overlap, and thereby increase legibility. In this paper we initialize the algorithmic study of optimizing symbol legibility via a limited displacement of the symbols. Specifically, we consider unit square symbols that need to be placed at specified y-coordinates. We optimize the drawing order of the symbols as well as their x-displacement, constrained within a rectangular container, to maximize the minimum visible perimeter over all squares. If the container has width and height at most 2, there is a point that stabs all squares. In this case, we prove that a staircase layout is arbitrarily close to optimality and can be computed in O(n log n) time. If the width is at most 2, there is a vertical line that stabs all squares, and in this case, we give a 2-approximation algorithm (assuming fixed container height) that runs in O(n log n) time. As a minimum visible perimeter of 2 is always trivially achievable, we measure this approximation with respect to the visible perimeter exceeding 2. We show that, despite its simplicity, the algorithm gives asymptotically optimal results for certain instances. © Bernd Gärtner, Vishwas Kalani, Meghana M. Reddy, Wouter Meulemans, Bettina Speckmann, and Miloš Stojaković;licensed under Creative Commons License CC-BY 4.0.

关键词： Containers

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Enhancing Software Cost Estimation Using Feature Selection and Machine Learning Techniques

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computers, Materials & Continua 2024年第12期81卷 4603-4624页

作者： Fizza Mansoor Muhammad Affan Alim Muhammad Taha Jilani Muhammad Monsoor Alam Mazliham Mohd Su’ud Department of Software Engineering FAST-National University of Computer&Emerging SciencesKarachi75030Pakistan Faculty of Engineering Science and Technology IQRA UniversityKarachi72500Pakistan Department of Computer Science Bahria UnivesityKarachi74800Pakistan Faculty of Computing Riphah International UniversityIslamabad44600Pakistan Faculty of Computing and Informatics Multimedia University(MMU)Cyberjaya63100SelangorMalaysia

Software cost estimation is a crucial aspect of software project management,significantly impacting productivity and *** research investigates the impact of various feature selection techniques on software cost estimation accuracy using the CoCoMo NASA dataset,which comprises data from 93 unique software projects with 24 *** applying multiple machine learning algorithms alongside three feature selection methods,this study aims to reduce data redundancy and enhance model *** findings reveal that the principal component analysis(PCA)-based feature selection technique achieved the highest performance,underscoring the importance of optimal feature selection in improving software cost estimation *** is demonstrated that our proposed method outperforms the existing method while achieving the highest precision,accuracy,and recall rates.

关键词： Machine learning software cost estimation PCA hyper parameter feature selection

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Maritime radar odometry inspired by visual odometry 26

Maritime radar odometry inspired by visual odometry

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26th International Conference on Information Fusion, FUSION 2023

作者： Flemmen, Henrik D. Mester, Rudolf Stahl, Annette Bryne, Torleiv H. Brekke, Edmund Førland Norwegian University of Science and Technology Department of Engineering Cybernetics Norway Norwegian University of Science and Technology Department of Informatics and Computer Science Norway

ISBN: (纸本)9798890344854

Future autonomous ships will need several redundant positioning systems to navigate reliably. Global Navigation Satellite Systems are highly accurate but they are susceptible to disruptions and intentional jamming. Maritime radars have long range and are robust against bad weather and darkness, but the use for ownship motion estimation has received relatively little attention in the research field. In this work, we present a radar odometry estimation method inspired by advances in visual odometry and simultaneous localization and mapping. The method works on raw radar data in a coastal environment and combines the Kanade-Lucas-Tomashi tracker with a factor graph back-end. We test it on data from a large ship with a maritime radar with a range of 19 km. We find that it is robust with only a small drift and no erroneous jumps in the estimate. © 2023 International Society of Information Fusion.

关键词： Motion estimation

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Assisting Neurosurgeons: Advancing Brain Tumor Surgery with Smartphone Augmented Reality Navigation

Assisting Neurosurgeons: Advancing Brain Tumor Surgery with ...

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2024 International Conference on Innovation and Intelligence for informatics, Computing, and Technologies, 3ICT 2024

作者： Java, Muhammad Iskandar Hidayati, Shintami Chusnul Sarno, Riyanarto Anistyasari, Yeni Ali, Khurshed Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia Department of Informatics Engineering Universitas Negeri Surabaya Surabaya Indonesia Department of Computer Science Sukkur IBA University Sukkur Pakistan

ISBN: (纸本)9798331533137

Integrating Augmented Reality (AR) into neurosurgical procedures has shown substantial promise in enhancing surgical precision and educational outcomes, building upon previous applications primarily focused on simple visualization tasks. This study extends the current scope by using smartphone-based AR navigation systems tailored to assist neurosurgeons performing brain tumor surgery. Unlike prior efforts, our research developed and validated an AR system that superimposes precise virtual representations of critical anatomical structures, such as the skull and brain, onto a 3D-printed patient model. These models are rendered in transparent materials that improve the visibility and understanding of intricate internal structures, facilitating more intuitive surgical planning and training. Our findings demonstrate that while AR significantly enhances the visualization of anatomical details and the alignment of virtual to physical models, its effectiveness depends on the viewing angle and facial feature distinctiveness, achieving the highest accuracy in frontal views. These results underscore improvements over traditional AR systems, which often struggle with accurate depth perception and spatial orientation, and highlight the challenges of broad integration. ©2024 IEEE.

关键词： Smartphones

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Scenario-Based Cross-Site Request Forgery (CSRF) Attack Simulation 6

Scenario-Based Cross-Site Request Forgery (CSRF) Attack Simu...

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6th International Symposium on Advanced Electrical and Communication Technologies, ISAECT 2024

作者： Saleh, Taj Malkawi, Malek Elgammal, Ziad Calayir, Arzu Kilitci Alhajj, Reda Department of Computer Engineering Istanbul Medipol University Istanbul Turkey Department of Computer Engineering Marmara University Istanbul Turkey Department of Computer Science University of Calgary Alberta Canada Department of Heath Informatics University of Southern Denmark Odense Denmark

ISBN: (纸本)9798331529987

In the dynamic realm of technology, where new advancements consistently transform our online interactions, maintaining the security of web apps is crucial. This study explores the area of web security by investigating Cross-Site Request Forgery (CSRF) vulnerabilities in great detail. We untangle the complexities of CSRF attacks and highlight their possible risks and implications by using advanced simulations in a controlled environment. To carefully and correctly mimic CSRF attacks, the process entails creating a legitimate web application along with a malicious counterpart. The study carefully assesses the effectiveness of custom headers, SameSite cookie characteristics, and anti-CSRF tokens as defense strategies. In addition to its technological focus, the research emphasizes participant involvement's ethical implications and stresses the significance of user safety. The results provide practical advice for developers and security experts to strengthen web apps in addition to furthering our theoretical understanding of CSRF issues. We show why there is a need for strong security measures to be put in place as soon as possible, acknowledge the ever-changing nature of cyber threats, and call for ongoing research to keep ahead of the curve in terms of protecting digital ecosystems. In conclusion, this study is an invaluable tool for understanding and resolving the urgent problems caused by CSRF vulnerabilities, demonstrating its importance in strengthening the security framework of our globalized digital society. © 2024 IEEE.

关键词： Economic and social effects

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Solving Secluded Path Problem by Heuristics and Local Search

Solving Secluded Path Problem by Heuristics and Local Search

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2024 Cognitive Models and Artificial Intelligence Conference, AICCONF 2024

作者： Acikalin, Utku Umur Caskurlu, Bugra Abul, Osman Department of Computer Engineering TOBB University of Economics and Technology Ankara Turkey Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798400716928

Wireless Sensor Networks (WSNs) play a crucial role in various domains, from commercial to military, enabling precise monitoring of environmental and other conditions. However, the transmission of sensitive data in WSNs poses security challenges, particularly concerning eavesdropping attacks. While cryptographic methods offer protection, they often incur high energy costs, making them impractical for battery-powered WSNs. Our problem formulation, based on graph theory, reduces to the Secluded Paths problem for which no polynomial solution yet to known. Motivated by the challenge of reducing the eavesdropping risk through intelligent routing, we propose a scalable optimization approach using heuristics and local search techniques. We present a solution framework, followed by an experimental evaluation to demonstrate its efficacy. This paper contributes to the advancement of secure and efficient data transmission in WSNs. © 2024 ACM.

关键词： Sensitive data

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Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

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computers, Materials & Continua 2024年第8期80卷 2301-2330页

作者： Uddagiri Sirisha Parvathaneni Naga Srinivasu Panguluri Padmavathi Seongki Kim Aruna Pavate Jana Shafi Muhammad Fazal Ijaz Department of Computer Science and Engineering Prasad V Potluri Siddhartha Institute of TechnologyVijayawada520007India Amrita School of Computing Amrita Vishwa VidyapeethamAmaravatiAndhra Pradesh522503India Department of Tele informatics Engineering Federal University of CearáFortaleza60455-970Brazil Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramGunturAndhra Pradesh522302India Department of Computer Engineering Chosun UniversityGwangju61452Republic of Korea School of CSIT Symbiosis Skills and Professional UniversityPune412101India Department of Computer Engineering and Information College of Engineering inWadi AlddawasirPrince Sattam bin Abdulaziz UniversityWadi Alddawasir11991Saudi Arabia School of IT and Engineering Melbourne Institute of TechnologyMelbourne3000Australia

Fetal health care is vital in ensuring the health of pregnant women and the *** check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential *** know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,***,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during *** researchers have proposed various methods for classifying the status of fetus *** processing of CTG data is time-consuming and ***,automated tools should be used to classify fetal *** study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal *** strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also *** study easily provides valuable interpretations for healthcare professionals in the decision-making process.

关键词： Fetal health cardiotocography data deep learning dynamic multi-layer perceptron feature engineering

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Advanced brain tumor segmentation using DeepLabV3Plus with Xception encoder on a multi-class MR image dataset

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Multimedia Tools and Applications 2025年 1-22页

作者： Saifullah, Shoffan Dreżewski, Rafal Yudhana, Anton Faculty of Computer Science AGH University of Krakow Krakow30-059 Poland Department of Informatics Universitas Pembangunan Nasional Veteran Yogyakarta Yogyakarta55281 Indonesia Department of Electrical Engineering Universitas Ahmad Dahlan Yogyakarta55191 Indonesia

Accurate segmentation of brain tumors from Magnetic Resonance Imaging (MRI) scans presents notable challenges. This particularly in differentiating tumors from surrounding tissues with similar intensity. This study utilizes the DeepLabV3Plus model with an Xception encoder to address these challenges. We evaluated the model on a dataset of 3064 MR images, which included meningioma, glioma, and pituitary tumors. The model achieved high segmentation performance, with an accuracy of 0.9991, Dice Similarity Coefficient (DSC) of 0.9529, and Jaccard Index (JI) of 0.9133. It also demonstrated substantial boundary precision, recording an Average Symmetric Surface Distance (ASSD) of 0.84 mm and a Hausdorff Distance (HD) of 2.3 mm. These metrics surpass those of existing state-of-the-art models. While the model performed well with well-defined tumor boundaries, it faced challenges segmenting tumors with ambiuous edges. These findings suggest significant potential for enhancing diagnostic accuracy in neuro-oncology. Future work will focus on enhancing the model’s sensitivity to subtle tumor features and expanding the dataset to include a broader range of tumor characteristics. Additionally, incorporating multimodal imaging data could further improve segmentation precision. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Magnetic resonance imaging

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DocFlow: A Visual Analytics System for Question-Based Document Retrieval and Categorization

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IEEE Transactions on Visualization and computer Graphics 2024年第2期30卷 1533-1548页

作者： Qiu, Rui Tu, Yamei Wang, Yu-Shuen Yen, Po-Yin Shen, Han-Wei The Ohio State University Department of Computer Science and Engineering ColumbusOH43210-1132 United States National Yang Ming Chiao Tung University Department of Computer Science HsinChu300 Taiwan Washington University School of Medicine Institute for Informatics St. LouisMO63110 United States

A systematic review (SR) is essential with up-to-date research evidence to support clinical decisions and practices. However, the growing literature volume makes it challenging for SR reviewers and clinicians to discover useful information efficiently. Many human-in-the-loop information retrieval approaches (HIR) have been proposed to rank documents semantically similar to users' queries and provide interactive visualizations to facilitate document retrieval. Given that the queries are mainly composed of keywords and keyphrases retrieving documents that are semantically similar to a query does not necessarily respond to the clinician's need. Clinicians still have to review many documents to find the solution. The problem motivates us to develop a visual analytics system, DocFlow, to facilitate information-seeking. One of the features of our DocFlow is accepting natural language questions. The detailed description enables retrieving documents that can answer users' questions. Additionally, clinicians often categorize documents based on their backgrounds and with different purposes (e.g., populations, treatments). Since the criteria are unknown and cannot be pre-defined in advance, existing methods can only achieve categorization by considering the entire information in documents. In contrast, by locating answers in each document, our DocFlow can intelligently categorize documents based on users' questions. The second feature of our DocFlow is a flexible interface where users can arrange a sequence of questions to customize their rules for document retrieval and categorization. The two features of this visual analytics system support a flexible information-seeking process. The case studies and the feedback from domain experts demonstrate the usefulness and effectiveness of our DocFlow. © 1995-2012 IEEE.

关键词： Information retrieval

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