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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Zhu, Dingzhou Huang, Guoheng Yuan, Xiaochen Chen, Xuhang Zhong, Guo Pun, Chi-Man Deng, Jie Guangdong University of Technology School of Computer Science and Technology China Macao Polytechnic University Faculty of Applied Sciences China Huizhou University School of Computer Science and Engineering China University of Macau Department of Computer and Information Science China Guangdong University of Foreign Studies School of Information Science and Technology China First Affiliated Hospital of Sun Yat-Sen University China

ISBN: (纸本)9798350386226

Due to the built-in light source within the endoscope, the illumination of bodily mucous can cause the formation of highlight regions due to reflection. This not only interferes with the diagnosis conducted by doctors but also poses a challenge to subsequent computer vision tasks. To tackle this issue, we introduce FAQNet, a network specifically designed for endoscopic image highlight removal. FAQNet seamlessly integrates multi-channel information leveraging quaternion convolution and spatial channel attention within our Quaternion Multi-Channel Fusion (QMCF) Module. This allows it to capture intricate details of color, texture, spatial information, and highlight characteristics within the imaged organ. Additionally, by employing frequency domain transformation and dilated convolution, the Contextual Information Integration (CII) Module effectively enlarges the receptive field, organizing contextual information between highlight regions and their surrounding areas. Lastly, the PixelShuffle Upsampling (PSU) Module generates the restored image. We validate our model's performance on two benchmark datasets, demonstrating its superiority over existing highlight removal methodologies. © 2024 IEEE.

关键词： Endoscopy

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Classification of Sleep-Related Disorders Using Machine Learning Techniques 25

Classification of Sleep-Related Disorders Using Machine Lear...

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25th International Arab Conference on Information technology, ACIT 2024

作者： Nasir, Ola Alazaidah, Raed Al-Safarini, Maram Y. Alamleh, Amneh Zaid, Ali Abu Mansur, Hasan Elrashidi, Ali Alzoubi, Haneen Bani-Bakr, Alaa Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan Zarqa University Faculty of Information Technology Department of Data Science and Ai Zarqa Jordan Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan American University of Madaba Faculty of Business Department of Accounting Madaba Jordan University of Business and Technology Department of Electrical Engineering Jeddah21432 Saudi Arabia Private University Faculty of It Applied Science Department of Computer Science Amman Jordan

ISBN: (纸本)9798331540012

Several people suffer from irregular sleep patterns, a problem that negatively affects their daily lives. It presents a multitude of challenges, including daytime distress, disturbances in sleep-wake patterns, feelings of unease, and a variety of other complications. Diabetes, obesity, and psychological disorders are among the diseases that may be responsible for this sleep disorder. Therefore, the primary aim of this research is to employ the robust capabilities of machine learning in forecasting sleep disorders. This research classifies three diseases: diabetes, obesity, and psychological disorders, using thirty-two different classifiers belonging to five learning strategies. The research compares and evaluates their predictive performance on four datasets. The comparative analysis includes four evaluation metrics: Accuracy, Precision, ROC Area, and MCC. The research results indicate that the best classifier is SGD, followed by LMT, while NBM is the weakest classifier. In addition, the research results revealed that the best strategy is Functions, followed by Rules, with Bayes being the least effective strategy. While conducting the experiment and analyzing the data, it is observed that the best feature selection method that yielded the most favorable outcome is the CorrelationAttributeEval. Furthermore, it has been found that the classification algorithm known as SGD achieved the highest Accuracy and Precision in categorizing the data. This indicates that the combination of CorrelationAttributeEval as the feature selection approach and SGD as the classification algorithm proved to be the most successful and efficient strategy for this research © 2024 IEEE.

关键词： Sleep research

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Design and Development of Offline Navigation System (ONS) Using the Smart Phone Sensors

Design and Development of Offline Navigation System (ONS) Us...

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2023 IEEE International Conference on Network, Multimedia and Information technology, NMITCON 2023

作者： Varadam, Deepak Agrawal, Yash Singh Rathore, Sumit Yashwanth Naik, Sugali Verma, Yash Pareta, Vishal M S Ramaiah University of Applied Sciences Faculty of Engineering and Technology Department of Computer Science and Engineering Bengaluru India M S Ramaiah University of Applied Sciences Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350300826

An Offline Navigation system to navigate the user without any connectivity is implemented by using smartphone sensors. The implementation of the system is carried out by extracting the relevant data from the smartphone sensors and discovering some meaningful insights from it. The offline navigation system is completely independent of GPS and any network connectivity such as Wi-Fi, Cellular Network, Bluetooth, etc. The system uses the Accelerometer sensor, Gyroscope sensor, and Magnetic sensor which are already present in the smartphone. The sensor fusion concept is used to combine the data from all the sensors and fuse it to give the device's orientation. The accelerometer sensor provides the acceleration of the device in all three directions. Similarly, the gyroscope sensor provides the angular velocity of the device, and the magnetometer sensor provides the magnetic fields. The data from all three sensors are combined to calculate the orientation angle such as pitch, roll, yaw, and azimuth of the device. The filtering algorithm used is known as Kalman Filter. It fuses the data from different sensors which results in less error on the combined data. The angles then use the position estimation algorithm and step detection algorithm, to find the next step and the coordinates of the device to track the user. The algorithm makes use of the previously determined coordinates of the device. © 2023 IEEE.

关键词： Accelerometers

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A variable structure model of neurons’ application in computer vision

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Multimedia Tools and Applications 2025年 1-11页

作者： Sridi, Alaeddine Attia, Mouna Bouallegue, Kais Electronics and Micro-Electronics Laboratory Faculty of Sciences of Monastir University of Monastir Monastir Tunisia The Higher Institute of Computer Science and Communication Technologies of Hammam Sousse University of Sousse Sousse Tunisia Laboratory of Computer Science Parallelism and Intelligent Communicating Systems Faculty of Sciences of Tunisia University of Tunis ELManar Tunis Tunisia Department of Electrical Engineering Higher Institute of Applied Sciences and Technology of Sousse University of Sousse Sousse Tunisia

The neuron doctrine defines the neuron as the basic unit of the nervous system, which drives the dynamic behavior of our organs. This has led to neurons becoming the focus of modern neuroscience research and to the rise of neurocomputing, in which we try to digitally simulate human behavior. The goal being to better understand the human nervous system and gain more control over neuron-related diseases, helping doctors establish faster and more reliable medical diagnoses. In this context, we aim to simulate eye diseases and vision problems by convolving input images using a new class of neural networks based on a variable structure model of neurons presented in [1]. In this work, we focus on recreating the common convolution filters as a first step. This is the first time in neurocomputing literature that dendritic neurons have been used for dynamic convolution kernels generation and eye diseases simulation. We start with a presentation of our upgrades to the model’s flexibility and accuracy. Then, we propose a novel kernel generator algorithm to convolve the input images. Finally, we show its promising results in creating the outline, pixelization, and night convolution kernels, as well as control some metrics, including brightness and data retention. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Neurons

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Minimizing energy consumption in fixed node networks using a novel neutrosophic model: comparative analysis with standard and existing algorithms

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International Journal of Information technology (Singapore) 2025年 1-15页

作者： Ghimire, Sangam Bhurtel, Nirjal Jha, Sudan Ahmad, Sultan Abdeljaber, Hikmat A. M. Nazeer, Jabeen Department of Computer Science and Engineering Kathmandu University 28 kilo Bagmati Dhulikhel 45210 Nepal Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-kharj 11942 Saudi Arabia School of Computer Science and Engineering Lovely Professional University Punjab Phagwara 144411 India Department of Computer Science Faculty of Information Technology Applied Science Private University Amman Jordan MEU Research Unit Middle East University Amman 11831 Lebanon

The growing development and utilization of networked systems has led to more concern regarding the energy efficiency of these systems. In this paper, we present a novel approach to minimizing energy consumption in fixed node network for which we propose a new Neutrosophic model. This model leverages the unique strengths of Neutrosophic logic to enhance the efficiency by minimizing the energy consumption. The simulation of results is performed using Matplotlib (Python) with implementation parameters such as number of nodes (n) and additive white Gaussian noise (AWGN) (η). Additionally, we show a comparative analysis between the proposed model and other prevalent approaches used in minimizing energy consumption in networked systems. The comparative results shows improvement in energy efficiency, showcasing the potential of the proposed model as an alternative for optimizing energy consumption in networked systems. This work highlights the effectiveness of the proposed model and opens new avenues for future advancements in energy-efficient networked system using Neutrosophic approach. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Comparative analysis Energy-consumption optimization Networked systems Neutrosophic model Sensitivity analysis

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RAFA-Net: Region Attention Network for Food Items and Agricultural Stress Recognition

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2025年第1期3卷 121-133页

作者： Bera, Asish Krejcar, Ondrej Bhattacharjee, Debotosh Birla Institute of Technology and Science Department of Computer Science and Information Systems Pilani333031 India University of Hradec Kralove Center for Basic and Applied Science Faculty of Informatics and Management Hradec Kralove50003 Czech Republic Skoda Auto University Mlada Boleslav29301 Czech Republic Universiti Teknologi Malaysia Malaysia Japan International Institute of Technology Kuala Lumpur81310 Malaysia Jadavpur University Department of Computer Science and Engineering Kolkata700032 India

Deep convolutional neural networks (CNNs) have facilitated remarkable success in recognizing various food items and agricultural stress. A decent performance boost has been witnessed in solving the agro-food challenges by mining and analyzing region-based partial feature descriptors. Also, computationally expensive ensemble learning schemes fusing multiple CNNs have been studied in earlier works. This work proposes a region attention scheme for modeling long-range dependencies by building a correlation among different regions within an input image. The attention method enhances feature representation by learning the usefulness of context information from complementary regions. Spatial pyramidal pooling and average pooling pairs aggregate partial descriptors into a holistic representation. Both pooling methods establish spatial and channelwise relationships without incurring extra parameters. A context gating scheme is applied to refine the descriptiveness of weighted attentional features, which is relevant for classification. The proposed region attention network for food items and agricultural stress recognition method, dubbed RAFA-Net, has been experimented on three public food datasets, and has achieved state-of-the-art performances with distinct margins. The highest top-1 accuracy of RAFA-Net is 91.69%, 91.56%, and 96.97% on the UECFood-100, UECFood-256, and MAFood-121 datasets, respectively. In addition, better accuracies have been achieved on two benchmark agricultural stress datasets. The best top-1 accuracies on the Insect Pest (IP-102) and PlantDoc-27 plant disease datasets are 92.36%, and 85.54%, respectively;implying RAFA-Net's generalization capability. © 2023 IEEE.

关键词： Plant diseases

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Highly birefringent hexagonal porous core photonic crystal fiber for polarization maintaining integrated THz-photonics applications

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Optical and Quantum Electronics 2024年第10期56卷 1-20页

作者： Linsie, A. Alice Mondal, Shyamal Prince, Shanthi Department of Electronics and Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Ramapuram600089 India Department of Applied Physics Defence Institute of Advanced Technology Maharashtra411025 India Department of Electronics and Communication Engineering College of Engineering and Technology SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India

For high birefringence photonic crystal fibres (PCF) operating in terahertz (THz) regime, an outstanding model of slotted porous core with triangular lattice-based hexagonal shape cladding has been presented in this study. In this proposed THz-PCF, a five-layer circular air holes arranged in hexagon configuration have been placed in the cladding area, and five rectangular air holes have been positioned in core region for investigating the THz-PCF in polarization maintaining applications. The asymmetrical rectangular slots in core area creates difference between x and y polarized THz waves to offer high birefringence. The compact geometry of hexagonal structure in cladding offers more useful power confinement. The designed PCF offers high birefringence of 0.0866, low effective material loss of 0.0786 cm−1, core power fraction of 42.7%, less confinement loss of 0.02598 cm−1, low dispersion of 0.0963 ps/THz/cm and very less effective area of 0.03 µm2 in a broad frequency range of 0.1–2.3 THz, according to the Finite Element Method based simulation results in COMSOL Multiphysics software. These features enable the proposed PCF to be a better choice for numerous applications like polarization filtering, sensing, short distance communication, etc. in THz photonic integrated circuits. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Birefringence

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Simultaneous explanation of XTE J1814-338 and HESS J1731-347 objects using K− and K¯0 condensates

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Physical Review D 2025年第6期111卷 L061308-L061308页

作者： M. Veselský V. Petousis P. S. Koliogiannis Ch. C. Moustakidis J. Leja Institute of Experimental and Applied Physics Czech Technical University Prague 110 00 Czechia Department of Physics Faculty of Science University of Zagreb Bijenička cesta 32 Zagreb 10000 Croatia Department of Theoretical Physics Aristotle University of Thessaloniki 54124 Thessaloniki Greece Faculty of Mechanical Engineering—Slovak University of Technology in Bratislava Bratislava 81231 Slovakia

The recent observation of the compact star XTE J1814-338 with a mass of M=1.2−0.05+0.05M⊙ and a radius of R=7−0.4+0.4 km, together with the HESS J1731-347, which has a mass of M=0.77−0.17+0.20M⊙ and a radius of R=10.4−0.78+0.86 km, shows they provide evidence for the possible presence of exotic matter in the core of neutron stars and significantly enhance our understanding of the equation of state for the dense nuclear matter. In the present study, we investigate the possible existence of negative charged kaons and neutral antikaons in neutron stars by employing the relativistic mean field model with first order kaonic (K− and K0¯) condensates. To the best of our knowledge, this represents a first alternative attempt aimed to explain the bulk properties of the XTE J1814-338 object and at the same time the HESS J1731-347 object, using a mixture of kaon condensation in dense nuclear matter. In addition, we compare our analysis approach with the recent observation of PSR J0437-4715 and PSR J1231-1411 pulsars, proposing that to simultaneously explain the current variety of astrophysical objects, it is essential to resurrect a scenario of two distinct branches, each corresponding to a different composition of nuclear matter.

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Tunable and wideband high-performance rare earth-doped Ni-Mg-Cu-Zn nano ferrite-based meta-absorbers for C-band application

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Journal of Rare Earths 2025年第1期43卷 124-132,I0005页

作者： Majid Niaz Akhtar Magbool Alelyani Fatimah Mohammed AAlzahrani Abdullah Almohammedi Sabih Qamar MABaqir MIrfan Muhammad Azhar Khan Kheir SAlbarkaty ZAAlrowaili MSAl-Buriahi Institute of Physics The Islamia University of Bahawalpur63100BahawalpurPakistan Department of Radiological Sciences College of Applied Medical ScienceKing Khalid University61421bhaSaudi Arabia Department of Chemistry College of SciencePrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabi Department of Physics Faculty of ScienceIslamic University of Madinah42352.Saudi Arabia Department of Chemical Engineering Muhammad Nawaz Sharif University of Engineering and Technology(MNSUET)60000MultanPakistan Department of Electrical and Computer Engineering COMSATS University IslamabadSahiwal Campus57000Pakistan Department of Physics Umm Al-Qura UniversityMakkah24382Saudi Arabia Department of Physics College of ScienceJouf UniversityP.O.Box:201474331SakakaSoudi Arabia Department of Physics Sakarya University6900SakaryaTurkey

Due to advanced technology,electromagnet interference and dissipation problems in the electronic and portable devices at GHz range are increasing *** absorbing materials with outstanding electromagnetic properties,wide bandwidth,and strong absorption are highly *** present investigation deals with the preparation of Ni-Mg-Cu-Zn(NMCZ)substituted nano ferrites with composition of Ni_(0.3)Mg_(0.2)Cu_(0.3)Zn_(0.2)X_(0.02)Fe_(1.98)O_(4)(X=Nd,Ho,Pr,Gd,Yb).X-ray diffraction(XRD),Fourier transform infrared spectroscopy(FTIR),field emission scanning electron microscopy(FESEM),transmission electron microscopy(TEM),a vibratory sample magnetometer(VSM),and a Vector network analyzer(VNA)were used to investigate these rare earth-doped nanocrystalline ferrites'*** reveals the single spinel phase structure in all Ni-Mg-Cu-Zn *** spectroscopy shows the presence of tetrahedral and octahedral bands of spinel *** images reveal the lowest agglomeration for the Ho-doped NMCZ nano-spinel ferrites *** images show the hexagon shapes of the Yb-and Nd-doped NMCZ ***-doped NMCZ ferrites show more coercivity than other rare earth metals substituted NMCZ nanocrystalline *** analysis was used to calculate the magnetic features like initial permeability,magnetic anisotropy constant,remanence,coercivity,and magnetic ***-frequency switching field distributions(SFD)analyses were also *** characteristics such as losses,permittivity,modulus,Q,ac conductivity,and impedance of the Nd^(-),Ho^(-),Pr^(-),Gd^(-),Yb-doped Ni-Mg-Cu-Zn ferrites were *** minimum reflection loss(-57.3 dB)is found at 1.4 GHz for Pr-doped Ni-Mg-Cu-Zn ferrite ***,the reflection loss(RL)of-53.9 dB at 2.9 GHz is observed for Ho-doped Ni-Mg-Cu-Zn ferrite *** magnetization,low coercivity,outstanding magnetodielectric,and absorption properties of theNd^(-),Ho^(-),Pr^(-),Gd^(-)and Yb^(-)doped Ni-Mg

关键词： Rare earths Reflection loss Cubic phase Magnetodielectric Ni-Mg-Cu-Zn(NMCZ)meta-absorber

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Interpreting pulsar timing array data of gravitational waves with Ekpyrosis-bouncing cosmology

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Physical Review D 2025年第4期111卷 043508-043508页

作者： Taotao Qiu Mian Zhu School of Physics Huazhong University of Science and Technology Wuhan 430074 China Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University 30-348 Krakow Poland

Recent pulsar timing array (PTA) experiments have reported strong evidence of the stochastic gravitational wave background (SGWB). If interpreted as primordial gravitational waves, the signal favors a strongly blue-tilted spectrum. On the other hand, the Ekpyrosis-bouncing cosmology with a strongly blue-tilted gravitational wave spectrum, i.e., nT≃2, offers a potential explanation for the observed SGWB signal. In this paper, we construct a concrete Ekpyrosis-bouncing model, and show its capacity to intepret the PTA result without pathologies. Both tensor and scalar perturbations are analyzed with constraints from the current observations.

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