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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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Deep Learning Based Model for Stress Measurement in Online Social Networks 12th

Deep Learning Based Model for Stress Measurement in Online...

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12th International Conference on Computational Data and Social Networks, CSoNet 2023

作者： Gaurav, Akshat Gupta, Brij B. Chui, Kwok Tai Arya, Varsha Ronin Institute MontclairNJ07043 United States Department of Computer Science and Information Engineering Asia University Taichung City Taiwan Department of Electrical and Computer Engineering Lebanese American University Beirut Lebanon School of Science and Technology Hong Kong Metropolitan University Kowloon Hong Kong Asia University Taichung City Taiwan

ISBN: (纸本)9789819706686

Online Social Networks (OSNs) have become ubiquitous platforms for individuals to express their thoughts and emotions, making them valuable sources for studying mental health. This paper presents a novel Deep Learning-based approach for stress measurement in OSNs. We leverage a comprehensive dataset collected from Kaggle, specifically curated for stress analysis in social media. The proposed model demonstrates remarkable accuracy in identifying stress levels, paving the way for proactive mental health interventions and more targeted support systems in the digital age. This research contributes to the growing body of knowledge addressing mental health challenges in the online world, emphasizing the potential of AI and deep learning techniques in this critical domain. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Social networking (online)

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Predictive Maintenance for Industrial Equipment in Big Data: An Implementation with Random Forest

Predictive Maintenance for Industrial Equipment in Big Data:...

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2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Nainwal, Ankita Hussein, Layth Dixit, Krishna Kant Michaelson, Jacob Sehgal, Archana Gupta, Priyanka Graphic Era Deemed To Be University Department Of Computer Science & Engineering Dehradun India College Of Technical Engineering The Islamic University Department Of Computers Techniques Engineering Najaf Iraq Gla University Department Of Electrical Engineering Mathura India Saveetha School Of Engineering Saveetha Institute Of Medical And Technical Sciences Chennai India Lovely Professional University Phagwara India Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India

ISBN: (纸本)9798350366846

This research explores the realm of predictive maintenance for industrial equipment, employing and comparing four prominent machine learning algorithms: 'Random Forest, Support Vector Machines (SVM)', Neural Networks, and Gradient Boosting. The study intends to offer information on their effectiveness regarding the ability to accurately predict failures of equipment and estimate maintenance time. Results indicate that Random Forest and Neural Networks emerge as top performers, exhibiting high precision (Random Forest: The only difference is in terms of precision (Random Forest: 0.65, Neural Networks: 0.72), recall (Random Forest: 0.8, Neural Networks was the best as opposed to other measures where Random Forrest performed well and Neurenl network did not over fit.). These algorithms also demonstrate superior accuracy in estimating maintenance times, as reflected in the Mean Absolute Error (Random Forest: 5.12, Neural Networks: 5.45). The comparative study can detect subtle strengths and weaknesses that are useful to practitioners in terms of algorithm selection according to specific industry needs. This study supports the continuous development of PMP, highlighting that choices in algorithms are essential to increase efficiency levels at the operation level, minimize downtime, and further encourage sustainable manufacturing. © 2024 IEEE.

关键词： Support vector machines

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Quorum sensing-based interactions among drugs,microbes,and diseases

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science China(Life sciences) 2023年第1期66卷 137-151页

作者： Shengbo Wu Shujuan Yang Manman Wang Nan Song Jie Feng Hao Wu Aidong Yang Chunjiang Liu Yanni Li Fei Guo Jianjun Qiao School of Chemical Engineering and Technology Tianjin UniversityTianjin 300072China School of Computer Science and Engineering Central South UniversityChangsha 410083China State Key Laboratory of Chemical Engineering Tianjin UniversityTianjin 300072China Collaborative Innovation Center of Chemical Science and Engineering(Tianjin) Tianjin 300072China Key Laboratory of Systems Bioengineering Ministry of Education(Tianjin University)Tianjin 300072China School of Computer Science and Technology College of Intelligence and ComputingTianjin UniversityTianjin 300350China Department of Engineering Science University of OxfordOxford OX13PJUK Institute of Shaoxing Tianjin UniversityShaoxing 312300China

Many diseases and health conditions are closely related to various microbes,which participate in complex interactions with diverse drugs;nonetheless,the detailed targets of such drugs remain to be *** existing studies have reported causal associations among drugs,gut microbes,or diseases,calling for a workflow to reveal their intricate *** this study,we developed a systematic workflow comprising three modules to construct a Quorum Sensing-based Drug-Microbe-Disease(QSDMD)database(http://***/),which includes diverse interactions for more than 8,000 drugs,163 microbes,and 42 common *** interactions between microbes and more than 8,000 drugs have been systematically studied by targeting microbial QS receptors combined with a docking-based virtual screening technique and in vitro experimental ***,we have constructed a QS-based drug-receptor interaction network,proposed a systematic framework including various drug-receptor-microbe-disease connections,and mapped a paradigmatic circular interaction network based on the QS-DMD,which can provide the underlying QS-based mechanisms for the reported causal *** QS-DMD will promote an understanding of personalized medicine and the development of potential therapies for diverse *** work contributes to a paradigm for the construction of a molecule-receptor-microbe-disease interaction network for human health that may form one of the key knowledge maps of precision medicine in the future.

关键词： quorum sensing drugs microbe-disease association microbe-host interaction gut microbiota personalized medicine

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Screening and Characterization of Aroma and Flavor-Producing Bacteria and Yeast from Traditional Fermented Food and Beverages of Northeast, India 2nd

Screening and Characterization of Aroma and Flavor-Producing...

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2nd NIELIT's International Conference on Communication, Electronics and Digital Technologies, NICEDT 2024

作者： Borthakur, Debashree Barlaskar, Esha Medhi, Smriti Priya Sharma, Bipin Kumar Department of Microbiology Tripura University Tripura India Department of Bio Sciences Assam Don Bosco University Assam Guwahati India School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Northern Ireland Belfast United Kingdom Department of Computer Science and Engineering Assam Don Bosco University Assam Guwahati India

ISBN: (纸本)9789819736003

Fermented foods in India are diverse and play a significant role in the country's culinary traditions. These foods are often categorized based on their base material and include a variety of items with reported medicinal properties. Some examples of these fermented foods are: Dahi, Gundruk, Sinki, Inziangsang, Iromba, etc. While there were initially limited reports on the extraction of lactic acid bacteria (LAB) from Indian fermented dishes, the growing awareness toward the health benefits associated with LAB has spurred increased research in this domain. LAB are known for their probiotic properties, promoting gut health and overall well-being. The increasing interest in the health benefits attributed to lactic acid bacteria (LAB) offers a valuable opportunity for food microbiologists to delve deeper into the study and exploration of fermented foods. In the current study, bacteria and yeast were isolated from the different traditional fermented foods of northeast, and their potential of flavor production was studied. These isolated strains were used to check the potential of undergoing fermentation and flavor production by inoculating the isolated strains in the raw milk for the development of novel probiotic products. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Yeast

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Computational investigation of the structural and electrolyte properties of the extended family of lithium (thio)boracite materials: Li4B7O12Cl and beyond

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Physical Review Materials 2024年第6期8卷 065401-065401页

作者： D. Cory Lynch Yan Li Pieremanuele Canepa N. A. W. Holzwarth Department of Physics Department of Materials Science and Engineering Department of Electrical and Computer Engineering Texas Center for Superconductivity at the

Motivated by previous investigations that showed very promising high ionic conductivities within relatively stable framework structures, we report a systematic first-principles study of the extended family of lithium (thio)boracites, consisting of eight chemical compositions. Three of the compositions—Li4B7O12Cl, Li4Al3B4O12Cl, and Li6B7S13Cl—are comparable to synthesized and analyzed materials reported in the experimental literature. The five additional compositions—Li4B7S12Cl, Li4Al3B4S12Cl, Li6B7O13Cl, Li6Al3B4O13Cl, and Li6Al3B4S13Cl—are predicted from the computational modeling and analysis presented in this paper. For each material, idealized ordered rhombohedral, cubic, or monoclinic ground-state structures are determined. Through various methodologies including thermodynamic, voltage window, and harmonic phonon analyses, stability is assessed for all eight Li (thio)boracite-derived compositions. Based on the dominant energetics of density functional theory, an analysis of the thermodynamically accessible phases predicts stability for Li4B7O12Cl only. The analysis of the voltage windows of these materials suggests that the sulfur materials are much more reactive in contact with lithium metal than their oxygen counterparts. This reactivity problem has been identified in other highly conducting solid electrolytes and various mitigation methods discussed in the literature look promising. Within the harmonic approximation, phonon analysis predicts that all eight materials are dynamically stable in their ground-state structures. Future investigations will focus on the performance of the family of lithium (thio)boracites, including ionic conductivity predictions and ion migration mechanisms.

关键词： Batteries First-principles calculations Ionic transport Structural properties

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LASS: A Novel and Economical Data Augmentation Framework Based on Language Models for Debiasing Opinion Summarization 31

LASS: A Novel and Economical Data Augmentation Framework Bas...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Zhang, Yanyue Li, Pengfei Lai, Yilong He, Yulan Zhou, Deyu School of Computer Science and Engineering Key Laboratory of Computer Network and Information Integration Ministry of Education Southeast University China Department of Informatics King's College London United Kingdom The Alan Turing Institute United Kingdom

ISBN: (纸本)9798891761964

As more than 70% of reviews in the existing opinion summary data set are positive, current opinion summarization approaches are hesitant to generate negative summaries given the input of negative texts. To address such sentiment bias, a direct approach without the reliance on a specific structure is to generate additional data based on large language models to balance the emotional distribution of the dataset. However, large-scale data augmentation based on large language models faces an apparent disadvantage, the expensive costs. Therefore, in this paper, we propose LASS, a novel data augmentation framework based on both LArge and Small language models for debiaSing opinion summarization. Specifically, a small number of synthesized negative reviews is obtained by rewriting the positive text via a large language model. Then, a disentangle reconstruction model is trained based on the generated data. After training, a large amount of synthetic data can be obtained by decoding the new representation obtained from the combination of different sample representations and filtering based on perplexity degree and sentiment classification. Experiments have proved that LASS can effectively alleviate emotional bias, similar to using only large models, but in a more economical way. © 2025 Association for Computational Linguistics.

关键词： Data assimilation

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CoChain: High Concurrency Blockchain Sharding via Consensus on Consensus 42

CoChain: High Concurrency Blockchain Sharding via Consensus ...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Li, Mingzhe Lin, You Zhang, Jin Wang, Wei Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Research Institute of Trustworthy Autonomous Systems Computer Science and Engineering Department China Hong Kong University of Science and Technology Computer Science and Engineering Department Hong Kong Institute of High Performance Computing and Agency for Science Technology and Research Singapore

ISBN: (纸本)9798350334142

Sharding is an effective technique to improve the scalability of blockchain. It splits nodes into multiple groups so that they can process transactions in parallel. To achieve higher parallelism and concurrency at large scales, it is desirable to maintain a large number of small shards. However, simply configuring small shards easily results in a higher fraction of malicious nodes inside shards, causing shard corruption and compromising system security. Existing sharding techniques hence demand large shards, at the expense of limited concurrency. To address this limitation, we propose CoChain: a blockchain sharding system that can securely configure small shards for enhanced concurrency. CoChain allows some shards to be corrupted. For security, each shard is monitored by multiple other shards. The latter reach a cross-shard Consensus on the Consensus results of their monitored shard. Once a corrupted shard is found, its subsequent consensus will be taken over by another shard, hence recovering the system. Via Consensus on Consensus, CoChain allows the existence of shards with more fraction of malicious nodes ( © 2023 IEEE.

关键词： Blockchain

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Enhance Image-to-Image Generation with LLaVA-generated Prompts 5

Enhance Image-to-Image Generation with LLaVA-generated Promp...

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5th International Conference on Information science, Parallel and Distributed Systems, ISPDS 2024

作者： Ding, Zhicheng Li, Panfeng Yang, Qikai Li, Siyang Columbia University Fu Foundation School of Engineering and Applied Science New York United States University of Michigan Department of Electrical and Computer Engineering Ann Arbor United States University of Illinois Urbana-Champaign Department of Computer Science Urbana United States Pace University Lubin School of Business New York United States

ISBN: (纸本)9798350352719

This paper presents a novel approach to enhance image-to-image generation by leveraging the multimodal capabilities of the Large Language and Vision Assistant (LLaVA). We propose a framework where LLaVA analyzes input images and generates textual descriptions, hereinafter LLaVA-generated prompts. These prompts, along with the original image, are fed into the image-to-image generation pipeline. This enriched representation guides the generation process towards outputs that exhibit a stronger resemblance to the input image. Extensive experiments demonstrate the effectiveness of LLaVA-generated prompts in promoting image similarity. We observe a significant improvement in the visual coherence between the generated and input images compared to traditional methods. Future work will explore fine-tuning LLaVA prompts for increased control over the creative process. By providing more specific details within the prompts, we aim to achieve a delicate balance between faithfulness to the original image and artistic expression in the generated outputs. © 2024 IEEE.

关键词： Visual languages

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Experimental Demonstration of a Data Collection System and an Effective Relaying Model in a UAV Network 1

Experimental Demonstration of a Data Collection System and a...

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1st Asian Conference on Communication and Networks, ASIANComNet 2024

作者： Abdulsattar, Nejood F. Ward, Zahraa Hassan Shrivastava, Neeraj Ghafour, Rizgar Rahman Abbas, Fatima Hashim Habelalmateen, Mohammed I. Department of Computer Technical Engineering Al-Diwaniyah Iraq Mazaya University College Department of Computer Techniques Engineering DhiQar Iraq Medicaps University Department of Electrical Engineering MP Indore India National University of Science and Technology Dhi Qar Iraq Al-Mustaqbal University Medical Laboratories Techniques Department Hillah Iraq The Islamic University College of Technical Engineering Department of Computer Technical Engineering Najaf Iraq

ISBN: (纸本)9798350367003

In recent times, unmanned aerial vehicles (UAVs) are constructed in the vehicular network. Through this technology the communication becomes more flexible and efficient but still it consists of certain drawbacks in terms of device deployment and data collection. For that purpose, in this article an efficient data collection system and effective relaying model (DCERM-UAV) is constructed in the aerial vehicles to improve the network stability. The core concentrations of these models are providing effective data aggregation, relaying among the vehicles and improving deployment of it. Through this process the stability of the vehicles is increased and that leads to high quality communication among them. The parameters which are used to analyses the performance of the network model are energy efficiency, energy consumption, network throughput, routing overhead and data delivery ratio. From the final results it gets proven that the DCERM-UAV achieves maximum efficiency when compared with the earlier research works. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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