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Iraqi Journal for Computer science and Mathematics 2025年第2期6卷 180-187页

作者： Elaraby, Ahmed Nechaevskiy, Andrey Saad, Aymen Department of Computer Science Faculty of Computers and Information South Valley University Qena83523 Egypt Cairo Egypt Meshcheryakov Laboratory of Information Technologies Joint Institute for Nuclear Research Joliot-Curie 6 Dubna141980 Russia Department of Information Technology Management Technical College Al-Furat Al-Awsat Technical University Kufa54003 Iraq School of Electrical Engineering Universiti Teknologi Malaysia Johor Skudai81310 UTM Malaysia

Deep learning’s rapid development is generating significant interest in its potential to improve medical imaging. It has shown promising results in detecting malignant lymphoma in histopathology medical images. Image classification methods are widely used to aid in making diagnoses from medical images. In recent years, deep learning methods have achieved high performance in detecting malignant lymphoma in histopathology images. This study proposes a novel approach to improving lymphoma diagnosis in histopathology images called the Lightweight Convolutional Neural Network (LWCNN). The proposed LWCNN model comprises multiple deep learning architectures, including a convolutional neural network (CNN) that has been trained to classify lymphoma subtypes based on histopathology images using ResNet50 and MobileNetV2. The LWCNN model aggregates the predictions of disparate architectures to arrive at a definitive diagnosis, leveraging the unique capabilities of each. A comprehensive dataset of annotated lymphoma histopathology images was assembled for the purpose of training the multi-deep learning model. To ensure a representative and diverse training set, the dataset was meticulously curated to encompass various subtypes of lymphoma. Performance evaluation of the proposed deep learning model for lymphoma classification using standard metrics revealed the following accuracies: LWCNN (97.34% training, 86.71% testing), ResNet50 (88.76% training, 86.37% testing), and MobileNetV2 (88.47% training, 86.60% testing). These results indicate that the LWCNN model significantly surpasses existing approaches in diagnostic accuracy. © 2025 The Author(s).

关键词： Photointerpretation

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Privacy-preserving and efficient user matching based on attribute encryption in mobile social networks

Privacy-preserving and efficient user matching based on attr...

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作者： Wu, Lei Zhao, Shengnan Wei, Xia Meng, Lingzhen School of Information Science and Engineering Shandong Normal University Jinan China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China

With the rapid popularity of social networking platforms, users can be matched when sharing their profiles. However, there is a risk of leakage of sensitive user information during the user matching process, which leads to the lack of user privacy protection. In this paper, we propose a privacy protection scheme based on the encryption of hidden attributes during user matching in mobile social networks, which uses linear secret sharing scheme (LSSS) as the access structure based on ciphertext policy attribute-based encryption (CP-ABE), and the match server can perform friend recommendation by completing bi-directional attribute matching determination without disclosing user attribute information. In addition, the use of selective keywords protects the privacy of requesters and publishers in selecting keywords and selecting plaintext attacks. The scheme reduces the encryption and decryption overhead for users by dividing encryption into a preparation phase and an online phase and shifting most of the decryption overhead from the requester to the match server. The experimental results show that the scheme ensures user privacy while effectively reducing communication overhead. © 2021 John Wiley & Sons, Ltd.

关键词： Cost reduction

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Two new multi-phase reliability growth models from the perspective of time between failures and their applications

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Chinese Journal of Aeronautics 2021年第5期34卷 341-349页

作者： Kunsong LIN Yunxia CHEN School of Reliability and Systems Engineering Beihang UniversityBeijing 100191China Science and Technology on Reliability and Environmental Engineering Laboratory Beihang UniversityBeijing 100191China

Aviation products would go through a multi-phase improvement in reliability performance during the research and development *** the literature,most of the existing reliability growth models assume a constant failure intensity in each test phase,which inevitably limits the scope of the *** address this problem,we propose two new models considering timevarying failure intensity in each *** proposed models borrow the idea from the accelerated failure-time *** is assumed that time between failures follow the log-location-scale distribution and the scale parameters in each phase do not change,which forms the basis for integrating the data from all test *** the test-find-test scenario,an improvement factor is introduced to construct the relationship between two successive location *** for the test-fix-test scenario,the instantaneous cumulative time between failures is assumed to be consistent with Duane model and derive the formulation of location *** ratio test is further utilized to test whether the assumption of constant failure intensity in each phase is *** applications with real reliability growth data show that the assumptions are reasonable and the proposed models outperform the existing models.

关键词： Reliability growth Test-find-test strategy Test-fix-test strategy Time-varying failure intensity Time between failures

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A Low-RCS Microstrip Antenna Design with Concentric Ring Metasurface

A Low-RCS Microstrip Antenna Design with Concentric Ring Met...

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2023 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2023

作者： Ren, Aidi Yu, Chengwei Yang, Lixia Li, Yingsong Cui, Wei Anhui University School of Electronics and Information Engineering Hefei230031 China Aviation Key Laboratory of Science and Technology on Electromagnetic Environmental Effects Shenyang110000 China

ISBN: (纸本)9798350336740

This article proposes a microstrip patch antenna with low radar cross-section based on concentric ring metasurface. The radiating patch of the antenna is circular, and the metasurface units are arranged round on it in a concentric circular pattern. The impedance matching of the antenna is improved by slotting on the patch antenna and adding metallic vias. Due to the addition of metallic vias in the metasurface, the RCS reduction is achieved both inside and outside the band by inducing opposite surface currents;and new resonances are generated which in turn will increase the impedance bandwidth of the antenna. Simulation results show that the designed antenna has good radiation performance, with a working bandwidth of 6.17-8.97 GHz. There is a significant RCS reduction within the bandwidth of 5.45-9.46GHz, which can be used in stealth platforms. © 2023 IEEE.

关键词： Microstrip antennas

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A Ka-Band Duplex Ceramic High-Temperature Resistant Dielectric Rod Antenna 15

A Ka-Band Duplex Ceramic High-Temperature Resistant Dielectr...

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15th International Conference on Microwave and Millimeter Wave technology, ICMMT 2023

作者： Tao, Jia-Yi Yang, Zhi-Tao Deng, Hong-Wei Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering College of Integrated Circuits Nanjing China Science and Technology on Space Physics Laboratory Beijing China

ISBN: (纸本)9798350338874

In this paper, a Ka-band duplex dual-polarized high-temperature resistant dielectric rod antenna (DRA) is designed with high isolation. The pyramidal tapered DRA fed by waveguide is packaged by thermal protection shield and thermal insulation material. The rectangular microstrip patch antenna (MPA) connects with the other end of the waveguide. The waveguide is directly soldered to the dielectric substrate so that the vias virtually lengthen the waveguide into the dielectric substrate and suppress the propagation of surface waves. Duplex dual polarization is realized by first two modes TM10 and TM01, which are excited by orthogonal microstrip slot coupling. The center frequencies of two channels can be determined by the length and width of the rectangular patch. The isolation can be improved by bending at the open end of the microstrip feed lines. Due to the lower thermal conductivity of ceramic dielectric of DRA and longer gap between feed port and the top of thermal insulation material, the feed port temperature is kept below 135 for 2000s under the continuous temperature of 1200 . © 2023 IEEE.

关键词： Thermal conductivity

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Hardness Recognition of Fruit and Vegetable Based on Robot Tactile Perception 2

Hardness Recognition of Fruit and Vegetable Based on Robot T...

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2nd International Conference on Robotics, Artificial Intelligence and Intelligent Control, RAIIC 2023

作者： Lan, Huijuan Zhang, Dunfeng Wei, Jingyi Liang, Shuang Southwest University of Science and Technology School of Information Engineering Mianyang China Southwest University of Science and Technology Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Mianyang China School of Northwestern Polytechnical University Xian China

ISBN: (纸本)9798350328004

Aiming at the inaccurate recognition of fruit and vegetable hardness in the damage-free grasping operation of picking robot, we propose a method called proper orthogonal decomposition-artificial neural network (POD-ANN) in this paper. First, the symmetrical clamping mechanism of two fingered manipulator is constructed, and the pressure series data set is established through the fingertip flexible tactile sensor. Second, the classification and recognition results of the collected tactile feature sequences are compared with support vector machine (SVM) and K - nearest neighbor (KNN) algorithms. The comparison results show that the POD-ANN algorithm achieves a recognition rate of 88.1% on the two finger robotic arm platform, which has higher recognition accuracy compared to the other two methods. Simultaneously, it also shows great potential in tactile classification tasks. © 2023 IEEE.

关键词： Hardness

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Empowering Smart Homes with Fog Computing for IoT Connectivity

Empowering Smart Homes with Fog Computing for IoT Connectivi...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Najim, Ali Hamza Mahdi, Ali Jafer Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq AI-Zahraa University for Women Department of Scientific Affairs Bangi43600 Malaysia College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

Innovative grid technology leverages information and Communication technology (ICT) to enhance energy efficiency and mitigate losses. This paper introduces a 'novel three-tier hierarchical framework for smart homes within the Internet of Things (IoT)' ecosystem, addressing the current shortage of intelligent solutions that underutilize IoT advantages. Our framework's primary objective is to elevate smart homes to the microgrid level, enabling the seamless integration from the microgrid's renewable distributed energy sources and attaining maximum energy efficiency. In addition to traditional data processing, we propose the application of fog computing in smart homes. Through a rigorous simulation using real smart meter datasets, our study demonstrates that fog computing, mainly when using predictive filtering, may drastically cut down on the amount of data being sent and the load on the home's network. This innovation holds immense potential for revolutionizing energy management and resource allocation in the context of smart homes, thus contributing to a sustainable and efficient future. This research represents a critical step towards harnessing the power of IoT and fog computing in smart grids and homes, offering a promising path towards more intelligent, eco-friendly, and energy-efficient living spaces. © 2024 IEEE.

关键词： Smart homes

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Efficient Drinking Water Quality Analysis using Machine Learning Model with Hyper-Parameter Tuning 7

Efficient Drinking Water Quality Analysis using Machine Lear...

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7th International Conference on Intelligent Computing and Control systems, ICICCS 2023

作者： Maheswari, M Uma Sudharsanan, R. Arthy, M. Jenefer, Anne Oormila, L. Samuthira Pandi, V. RMD Engineering College Department of Electrical and Electronics Engineering Tamil Nadu India SRM Institute of Science and Technology Department of Information Technology Tamil Nadu Ramapuram India SRM Institute of Science and Technology Department of Data Science and Business Systems Tamil Nadu Kattankulathur India Panimalar Engineering College Department of Electronics and Communication Engineering Tamil Nadu India Agni College of Technology Department of Computer Science Engineering Tamil Nadu India SRM Institute of Science and Technology Department of Electronics Ad Communication Engineering Tamilnadu Ramapuram India

ISBN: (纸本)9798350397253

The conventional approaches to determining the quality of water include costly and lengthy statistical and laboratory testing;hence, the concept of real-time monitoring is no longer applicable in the modern day. The disastrous implications of poor water quality demand that there be a remedy that is both more expedient and more realistic. This research study examines a variety of supervised machine learning algorithms in order to identify the quality of the water. A variety of variables, such as the pH value, the hardness, the solids, the chloramines, the sulfates, the conductivity, the organic carbon, the trihalomethanes, the turbidity, and the potability of the water, are essential for determining the quality of the water. Random Forest (RF) and Decision Tree (DT) are used in order to ascertain the caliber of the water that is suitable for human consumption. The standard laboratory approach for testing the quality of water is one that takes a lot of time and may be somewhat expensive at times. In a very short length of time, the algorithms that are proposed in this study are able to provide an estimation of the quality of drinking water. DT has a height accuracy F1 score of 99%, whereas RF has a score of 87.86% and a precision of 82.36%. The difference in these two scores is due to the fact that DT's precision is lower. The suggested method demonstrates its potential for usage in real-time water quality monitoring systems by achieving appropriate accuracy with a minimal set of parameters. To prove the usefulness of this program, this is essential. © 2023 IEEE.

关键词： Water quality

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Multimodal Classification and Out-of-distribution Detection for Multimodal Intent Understanding

arXiv

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arXiv 2024年

作者： Zhang, Hanlei Zhou, Qianrui Xu, Hua Su, Jianhua Evans, Roberto Gao, Kai State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing100084 China School of Information Science and Engineering Hebei University of Science and Technology Shijiazhuang050018 China

Multimodal intent understanding is a significant research area that requires effectively leveraging multiple modalities to analyze human language. Existing methods face two main challenges in this domain. Firstly, they have limitations in capturing nuanced and high-level semantics underlying complex in-distribution (ID) multimodal intents. Secondly, they exhibit poor generalization when confronted with unseen out-of-distribution (OOD) data in real-world scenarios. To address these issues, we propose a novel method for both ID classification and OOD detection (MIntOOD). We first introduce a weighted feature fusion network that models multimodal representations effectively. This network dynamically learns the importance of each modality, adapting to multimodal contexts. To develop discriminative representations that are conducive to both tasks, we synthesize pseudo-OOD data from convex combinations of ID data and engage in multimodal representation learning from both coarse-grained and fine-grained perspectives. The coarse-grained perspective focuses on distinguishing between ID and OOD binary classes, while the fine-grained perspective enhances the understanding of ID data by incorporating binary confidence scores. These scores help to gauge the difficulty of each sample, improving the classification of different ID classes. Additionally, the fine-grained perspective captures instance-level interactions between ID and OOD samples, promoting proximity among similar instances and separation from dissimilar ones. We establish baselines for three multimodal intent datasets and build an OOD benchmark. Extensive experiments on these datasets demonstrate that our method significantly improves OOD detection performance with a 3-10% increase in AUROC scores while achieving new state-of-the-art results in ID classification. 1 Copyright © 2024, The Authors. All rights reserved.

关键词： Semantics

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Geoacoustic inversion in shallow water by matching the vertical-particle-velocity

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Chinese Journal of Acoustics 2023年第3期42卷 288-306页

作者： TAN Peng SUN Mei QIN Jixing YANG Desen Acoustic Science and Technology Laboratory Harbin Engineering UniversityHarbin 150001 Key Laboratory of Marine Information Acquisition and Security(Harbin Engineering University) Ministry of Industry and Information TechnologyHarbin 150001 College of Underwater Acoustic Engineering Harbin Engineering UniversityHarbin 150001 School of Physics and Electronic Engineering Taishan UniversityTaian 271000 State Key Laboratory of Acoustics Institute of AcousticsChinese Academy of SciencessBeijing 100190

Bottom acoustic parameters are vital for studying sound propagation properties and their applications in ocean *** propagation properties and normal-mode structure of vertical-particle-velocity in an ocean environment with a thermocline in shallow water were studied in the Yellow *** Results reveal that high energy of the verticalparticle-velocity exists at most depth except for near-bottom depth when the source and receiver are both below the ***,high-order modes contribute more to the verticalparticle-velocity and vertical-particle-velocity-based matched-field-processing(MFP)inversion method can be highly sensitive to bottom parameters compared to sound ***,the effects of the bottom absorption coefficient on the vertical-particle-velocity-based MFP inversion method are *** is shown that accurate sound velocity,density and water depth can be obtained only when the bottom absorption coefficient is set close to the real value during *** using the vertical-particle-velocity signals recorded by vector hydrophones during the experiment and determining the bottom sound velocity,bottom density and water depth under different bottom absorption coefficients,stable inversion results were *** transmission losses of the sound pressure at different ranges were used to invert the bottom absorption *** transmission losses of sound pressure calculated using the inverted bottom parameters are consistent with the experimental results obtained from the pressure hydrophones in the experiment.

关键词： shallow ocean particle

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