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4th International Conference on Ubiquitous Computing and Intelligent Information Systems, ICUIS 2024

作者： Bhavana, J. Hameed, Thushara Maruthakutti, Maheswari Sivaraman, R. Vijayanand, Sellamuthu Palanisamy Jegajothi, B. Sr University Department of Cs & Ai India College of Engineering and Technology University of Technology and Applied Sciences Nizwa Oman Dwaraka Doss Goverdhan Doss Vaishnav College Department of Mathematics Arumbakkam Tamil Nadu Chennai600 106 India Government of Engineering Department of Computer Science and Engineering Erode India Srs Tech Solutions Chennai India

ISBN: (纸本)9798331529635

Deep learning algorithms have made considerable strides in recent years, and these advancements have the potential to significantly improve multi-organ segmentation in three-dimensional biomedical images. This would result in improved diagnostic accuracy and efficiency in medical imaging. DA-TransUNet is an innovative architecture that successfully combines information on several scales and enhances feature extraction by utilizing the DA-Block encoder and the Convolutional Block Attention Module (CBAM). The assessed propsoed model using a variety of datasets, one of which being the LiTS dataset. Finally, were able to achieve a Dice coefficient of 92.56% and a Hausdorff Distance (HD95) of 28.09 mm for liver images. DA-TransUNet surpasses existing state-of-the-art segmentation models across a variety of medical imaging datasets, as demonstrated by the results of the experiments, which reveal considerable increases in accuracy and robustness. The discoveries that have obtained contribute to the advancement of automated segmentation approaches in medical imaging, which in turn facilitates increased diagnostic capabilities. © 2024 IEEE.

关键词： Image segmentation

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On an impulsive faecal-oral model in a moving infected environment

arXiv

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arXiv 2024年

作者： Zhou, Qi Lin, Zhigui Pedersen, Michael School of Mathematical Science Yangzhou University Yangzhou225002 China Department of Applied Mathematics and Computer Science Technical University of Denmark LyngbyDK 2800 Denmark

This paper develops an impulsive faecal-oral model with free boundary to in order to understand how the exposure to a periodic disinfection and expansion of the infected region together influences the spread of faecal-oral diseases. We first check that this impulsive model has a unique globally nonnegative classical solution. The principal eigenvalues of the corresponding periodic eigenvalue problem at the initial position and infinity are defined as λ∆1 (h0) and λ∆1 (∞), respectively. They both depend on the impulse intensity 1 - G′(0) and expansion capacities µ1 and µ2. The possible long time dynamical behaviours of the model are next explored in terms of λ∆1 (h0) and λ∆1 (∞): if λ∆1 (∞) ≥ 0, then the diseases are vanishing;if λ∆1 (∞) ∆1 (h0) ≤ 0, then the disease are spreading;if λ∆1 (∞) ∆1 (h0) > 0, then for any given µ1, there exists a µ0 such that spreading happens as µ2 ∈ (µ0, +∞), and vanishing happens as µ2 ∈ (0, µ0). Finally, numerical examples are presented to corroborate the correctness of the obtained theoretical findings and to further understand the influence of an impulsive intervention and expansion capacity on the spreading of the diseases. Our results show that both the increase of impulse intensity and the decrease of expansion capacity have a positive contribution to the prevention and control of the *** Codes 35R35, 35R12, 92B05 Copyright © 2024, The Authors. All rights reserved.

关键词： Expansion

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Recent Advances of Chimp Optimization Algorithm:Variants and Applications

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Journal of Bionic Engineering 2023年第6期20卷 2840-2862页

作者： Mohammad Sh.Daoud Mohammad Shehab Laith Abualigah Mohammad Alshinwan Mohamed Abd Elaziz Mohd Khaled Yousef Shambour Diego Oliva Mohammad AAlia Raed Abu Zitar College of Engineering Al Ain University112612Abu DhabiUnited Arab Emirates College of Computer Sciences and Informatics Amman Arab UniversityAmman11953Jordan Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan MEU Research Unit Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains Malaysia11800Pulau PinangMalaysia Faculty of Information Technology Applied Science Private UniversityAmman 11931Jordan Department of Mathematics Faculty of ScienceZagazig UniversityZagazig 7120001Egypt The Custodian of the Two Holy Mosques Institute for Haj and Umrah Research Umm Al-Qura UniversityMakkah 24382Saudi Arabia Depto.de Innovacio'n Basada en la Informacio'n y el Conocimiento Universidad de GuadalajaraCUCEI45129 GuadalajaraMexico Cyber Security Department Faculty of Science and Information TechnologyAl Zaytoonah University of JordanAmman 11733Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu Dhabi38044 Abu DhabiUnited Arab Emirates School of Engineering and Technology Sunway University Malaysia27500Petaling JayaMalaysia

Chimp Optimization Algorithm(ChOA)is one of the recent metaheuristics swarm intelligence *** has been widely tailored for a wide variety of optimization problems due to its impressive characteristics over other swarm intelligence methods:it has very few parameters,and no derivation information is required in the initial ***,it is simple,easy to use,flexible,scalable,and has a special capability to strike the right balance between exploration and exploitation during the search which leads to favorable ***,the ChOA has recently gained a very big research interest with tremendous audiences from several domains in a very short ***,in this review paper,several research publications using ChOA have been overviewed and ***,introductory information about ChOA is provided which illustrates the natural foundation context and its related optimization conceptual *** main operations of ChOA are procedurally discussed,and the theoretical foundation is ***,the recent versions of ChOA are discussed in detail which are categorized into modified,hybridized,and paralleled *** main applications of ChOA are also thoroughly *** applications belong to the domains of economics,image processing,engineering,neural network,power and energy,networks,*** of ChOA is also *** review paper will be helpful for the researchers and practitioners of ChOA belonging to a wide range of audiences from the domains of optimization,engineering,medical,data mining,and *** well,it is wealthy in research on health,environment,and public ***,it will aid those who are interested by providing them with potential future research.

关键词： Artificial intelligence Nature-inspired optimization algorithms Chimp optimization algorithm Optimization problems

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Active Connectivity Fundamentals for TSCH Networks of Mobile Robots

Active Connectivity Fundamentals for TSCH Networks of Mobile...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Charalampos Orfanidis Paul Pop Xenofon Fafoutis Department of Applied Mathematics and Computer Science Technical University of Denmark

ISBN: (数字)9781665495127

ISBN: (纸本)9781665495134

Time Slotted Channel Hopping (TSCH) is a medium access protocol defined in the IEEE 802.15.4 standard which have been proven to be one of the most reliable options when it comes to industrial applications. TSCH has been designed to be utilized in static network topologies. Thus, if an application scenario requires a mobile network topology, TSCH does not perform reliably. In this paper we introduce active connectivity for mobile application scenarios, such as mobile robots. This is a feature that enables the option to regulate physical characteristics such as the speed of a node as it moves, in order to keep being connected to the TSCH network. We model the active connectivity approach through a basic example where two nodes are moving towards the same direction to infer the main principles of the introduced approach. We evaluate the active connectivity feature through simulations and quantify trade-off between connectivity and application-layer performance.

关键词： IEEE 802.15 Standard Network topology Reinforcement learning Sensor systems Topology Mobile nodes Mobile applications

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Multi Spectral Feature Extraction to Improve Lung Sound Classification using CNN

Multi Spectral Feature Extraction to Improve Lung Sound Clas...

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International Conference on Signal Processing and Integrated Networks (SPIN)

作者： Rishabh Dhirendra Kumar Department of Computer Science University of Delhi Delhi India Department of Applied Mathematics Delhi Technological University Delhi India

The principal method for screening and diagnosing lung disorders is auscultation of respiratory sounds. In the medical field, automated auscultation is a new research field that helps with faster disease diagnosis. The task of automated auscultation is to classify the respiratory sound, which requires a dataset to build a classification model. Deep learning networks are a popular method for producing such classification models, which require a large number of samples to train. Unfortunately, even the largest publicly accessible respiratory sound dataset (ICBHI 2017) of 5.5 hours total length contains only 6898 respiratory cycles, which is still insufficient for training deep learning networks. In this research work, data augmentation and smart padding techniques are utilised to account for the ICBHI dataset’s class imbalance. Further, we have suggested to extract several features from the audio signal, such as MFCC, Chroma STFT, Mel-Spectrogram, Spectral Contrast, and Tonnetz, for better representation of the samples in a class. Further, we have obtained the statistical features such as mean and standard deviation for developing the classification model. We have utilised a deep learning-based CNN architecture for the classification of the learned features. The proposed method achieved a score of 74.08% for a 60-40 train-test split and 75.04% for an 80-20 train-test split, outperforming all state-of-the-art lung sound classification methods.

关键词： Deep learning Training Lung Signal processing Feature extraction Medical diagnosis Task analysis

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Unsupervised Learning for Detection of Radio Frequency Interference Signals

Unsupervised Learning for Detection of Radio Frequency Inter...

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2024 International Conference on Intelligent Systems for Cybersecurity, ISCS 2024

作者： Singh, Brahampal Singh, Vijai Pal Bajpai, Anukool Bulla, Chetan Parikh, Swapnil Maranan, Ramya Trinity Institute of Innovations in Professional Studies Department of Cs and It Delhi201 308 India Trinity Institute of Innovations in Professional Studies Department of Applied Mathematics Uttar Pradesh 201 310 India Ggsip University Department of Computer Science New Delhi110 009 India Department of Business Intelligence Synechron Karnataka Bangalore560001 India Parul Institute of Engineering and Technology Parul University Department of Computer Science and Engineering Gujarat India Saveetha School of Engineering Department of Research and Innovation Tamil Nadu Chennai602105 India

ISBN: (纸本)9798350375237

In order to ensure that wireless communication systems operate at their best, it's crucial to develop reliable methods for detecting RF interference. This study compares two unsupervised anomaly detection algorithms, Support Vector Data Description (SVDD) and One-Class Support Vector Machine (SVM), using a small training database. We evaluated these algorithms by detecting various types of RF interference signals, including Continuous Interference (CI), Continuous Wave Interference (CWI), and Modulated Continuous Wave Interference (MCWI). While previous works have made strides in RF interference detection, they have some limitations. For example, some methods may struggle with accurately detecting RF interference in dynamic environments or when faced with varying interference patterns. Additionally, certain algorithms may exhibit reduced performance when dealing with low signal-to-noise ratios or in the presence of complex interference sources. To address these challenges, both SVDD and One-Class SVM (OCS) algorithms are used and described the methodology for evaluating their performance. Throughout the experiments, how well SVDD and OCS could identify abnormal interference signals are measured using the precision metric. The findings revealed that employing normalization techniques like feature scaling over a range or robust normalization significantly improved the accuracy of RF interference detection. Importantly, SVDD consistently outperformed OCS in this regard. © 2024 IEEE.

关键词： Support vector machines

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Short-Term Wireless Connectivity Prediction for Connected Agricultural Vehicles

Short-Term Wireless Connectivity Prediction for Connected Ag...

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International Conference on Intelligent Transportation

作者： Brynjar Örn Grétarsson Charalampos Orfanidis Letizia Marchegiani Xenofon Fafoutis Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Department of Engineering and Architecture University of Parma Italy

Robots and autonomous vehicles have been integrated in our life and utilized in a plethora of application scenarios, including intelligent transportation, industrial automation and smart agriculture. Several of the these applications might be functioning in environments where cellular network coverage is low or non-existent. In a case like this, lower bandwidth networks and vehicle-to-vehicle communication can be used to keep the application operating safely, even with less active features. In such settings, disconnection events can be avoided if deteriorating communication links are detected early so that prevention measures can be taken. In this paper we investigate how we can predict if a communication link will be terminated in the near future based on the recent trend of the signal. We propose a deep neural network framework which is executed onboard and we evaluate its performance based on simulation and real word data. The results show that we can predict the termination of a link up to 7 seconds into the future with 72.38% accuracy and 86.38% recall.

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Teaching An Old Dog New Tricks: Porting Legacy Code to Heterogeneous Compute Architectures With Automated Code Translation

arXiv

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arXiv 2025年

作者： Nytko, Nicolas Reisner, Andrew Moulton, J. David Olson, Luke N. West, Matthew Department of Computer Science University of Illinois at Urbana-Champaign United States Applied Computer Science Los Alamos National Laboratory New Zealand Applied Mathematics and Plasma Physics Los Alamos National Laboratory New Zealand Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign United States

Legacy codes are in ubiquitous use in scientific simulations;they are well-tested and there is significant time investment in their use. However, one challenge is the adoption of new, sometimes incompatible computing paradigms, such as GPU hardware. In this paper, we explore using automated code translation to enable execution of legacy multigrid solver code on GPUs without significant time investment and while avoiding intrusive changes to the codebase. We developed a thin, reusable translation layer that parses Fortran 2003 at compile time, interfacing with the existing library Loopy (Klöckner 2014) to transpile to C++/GPU code, which is then managed by a custom MPI runtime system that we created. With this low-effort approach, we are able to achieve a payoff of an approximately 2–3× speedup over a full CPU socket, and 6× in multi-node settings. © 2025, CC BY-SA.

关键词： Investments

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Dispersive Vertex Guarding for Simple and Non-Simple Polygons

arXiv

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arXiv 2024年

作者： Fekete, Sándor P. Mitchell, Joseph S.B. Rieck, Christian Scheffer, Christian Schmidt, Christiane Department of Computer Science TU Braunschweig Braunschweig Germany Department of Applied Mathematics and Statistics Stony Brook University Stony BrookNY United States Department of Electrical Engineering and Computer Science Bochum University of Applied Sciences Bochum Germany Department of Science and Technology Linköping University Norrköping Sweden

We study the Dispersive Art Gallery Problem with vertex guards: Given a polygon P, with pairwise geodesic Euclidean vertex distance of at least 1, and a rational number;decide whether there is a set of vertex guards such that P is guarded, and the minimum geodesic Euclidean distance between any two guards (the so-called dispersion distance) is at least . We show that it is NP-complete to decide whether a polygon with holes has a set of vertex guards with dispersion distance 2. On the other hand, we provide an algorithm that places vertex guards in simple polygons at dispersion distance at least 2. This result is tight, as there are simple polygons in which any vertex guard set has a dispersion distance of at most 2. Copyright © 2024, The Authors. All rights reserved.

关键词： Optimization

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Optimizing Fresh Food Supply Chains: Leveraging 3PL for Carbon Reduction and Profit Maximization - A Game-Theoretic Analysis

Optimizing Fresh Food Supply Chains: Leveraging 3PL for Carb...

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IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： Anil Dhanda Divya Aggarwal Lovely Jain Priyansh Tyagi Mandeep Mittal Abhay Bansal Department of Mathematics Amity Institute of Applied Sciences Amity University Noida Uttar Pradesh India Department of Mathematics School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (数字)9798350385922

ISBN: (纸本)9798350385939

Mounting pressure on governments to reduce carbon emissions has forced them to impose regulations on supply chain members. Carbon cap-and-trade regulation has been widely adopted as a means to reduce carbon emissions. A fresh food supply chain involving a Manufacturer, 3PL, and a retailer is introduced. The 3PL is used by the manufacturer for its logistics because of its expertise, resources, and sustainable practices, Also many third-party logistics companies(3PL) offer refrigerated logistics services to the retailer and the 3PL has an overabundance of carbon permits. Trading of permits occurs and the impact on the retail price, the price of refrigerated logistics services in different carbon trading options, without carbon trade, inner carbon trade, and inner and outer carbon trade is studied. The prices are optimized through a game-theoretic approach, we model the trading of carbon permits as a leader-follower game with the 3PL as leader and Retailer as followers. The items are assumed to be of imperfect quality when delivered to the retailer by the 3PL.

关键词： Costs Supply chains Government Carbon dioxide Emissions trading Games Regulation

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