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4th International Meeting for Applied Geoscience and Energy, IMAGE 2024

作者： Mu, Wentao Zhang, Weiyi Zhang, Jianlei Tian, Zhenping BGP CNPC China National Engineering Research Center of Oil&Gas Exploration Computer Software China

Seismic diffractions generated by small-scale faults, inhomogeneities, and discontinuities contain quantities of valuable information and thus can be used for seismic interpretation in the exploitation of hydrocarbon reservoirs. Separating diffractions in migrated dip-angle domain gather is an effective method in diffraction separation. We developed a procedure in diffraction separation including using envelop to reduce the error caused by cycle skipping while detecting the Fresnel zone and calculating weighing coefficient to enhance diffraction signals. No extra dip field is required by our method and thus the efficiency of the whole model building and imaging is improved. Furthermore, our method protected the signals generated by diffractors within the Fresnel zone and thus improves the accuracy of the diffractors. Application of the new method to complex synthetic and field data reveals its ability to reliably image and enhance diffractions in the dip-angle domain. The promising results in terms of both image and attributes reveal a high potential for improved diffraction information. © 2024 Society of Exploration Geophysicists and the American Association of Petroleum Geologists.

关键词： Model buildings

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A Low-complexity DOA Estimation Method for Nested Array via Root-MUSIC 24

A Low-complexity DOA Estimation Method for Nested Array via ...

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8th International Conference on Electronic Information Technology and computer engineering, EITCE 2024

作者： Huang, Juntan Xu, Shufang College of Electrical and Power Engineering Hohai University Jiangsu Nanjing China College of Computer Science and Software Engineering Hohai University Jiangsu Nanjing China

ISBN: (纸本)9798400710094

The nested array results in a hole-free difference coarray (DCA) after virtualization, enhancing the utilization of virtual array elements. MUSIC algorithm is an algorithm with high estimation accuracy, but the angle search process has high complexity. In this paper, we propose a spatial smoothing root-MUSIC (SS-root-MUSIC) algorithm based on nested arrays to reduce complexity. Firstly, we obtain the equivalent signals of the DCA and recover the rank through virtualization and spatial smoothing. Then we use the root-MUSIC polynomial to get the DOA estimation results. The proposed SS-root-MUSIC has low computational complexity by avoiding the angle search process while ensuring the estimation accuracy. Theoretical and simulation results confirm the superiority of the proposed SS-root-MUSIC algorithm. © 2024 Copyright held by the owner/author(s).

关键词： Virtualization

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Introduction to the Special Issue on Formal Methods and Models for System Design

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ACM Transactions on Embedded Computing Systems 2025年第3期24卷 1-3页

作者： Brandt, Jens Saha, Indranil Zhang, Lijun Hochschule Niederrhein Krefeld Germany Department of Computer Science and Engineering Indian Institute of Technology Kanpur Kanpur India State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

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Evaluating the Efficacy of Large Language Models in Automating Academic Peer Reviews 23

Evaluating the Efficacy of Large Language Models in Automati...

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23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Weiminzhao Mahmoud, Qusay H. Ontario Tech University Department of Electrical Computer and Software Engineering OshawaONLlG 0CS Canada

ISBN: (纸本)9798350374889

This paper explores the application of large language models (LLMs) in automating the peer review process for academic papers, a critical area for enhancing the efficiency and consistency of scholarly publication. We utilized GPT-4-0125 to automatically generate reviews for 20 papers sourced from *** and analyzed the AI-generated peer reviews for quality and effectiveness. The analysis includes a detailed assessment of the text properties of the reviews, such as sentiment, revealing that LLM-generated reviews tend to be more uniformly positive than their human-written counterparts. In addition, we conducted a user survey in which participants attempted to distinguish between AI-generated and human-written reviews. The survey results indicated a low correct identification rate, suggesting that participants often could not discern the origin of the review, thereby highlighting the potential of LLMs to mimic human-like review qualities. However, the study also identifies limitations in LLM's performance, particularly concerning the variability in review quality, which appears to correlate with the model's vocabulary usage of the generated content. © 2024 IEEE.

关键词： Adversarial machine learning

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Group Signature with Time-Bound Keys for Secure E-health Record Sharing

Group Signature with Time-Bound Keys for Secure E-health Rec...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Lu, Junze Hu, Chunqiang Ruan, Conghao Cai, Bin Xiang, Tao Chongqing University School of Big Data & Software Engineering China Chongqing University College of Computer Science China

ISBN: (纸本)9798350386226

With the advent of various mobile IoT devices, a large amount of e-health record (EHR) data has been generated. This data has great potential to improve medical research. However, there are many challenges regarding the sharing of medical data. Firstly, users are more inclined to interact anonymously. Secondly, verifying the validity of certificates in the case of anonymous interactions is challenging. In addition, it is necessary to uncover the identities of the actual interacting parties in the event of malicious behavior. Therefore, we address the above challenges and propose group signatures with time constraints to support anonymous and traceable EHR data sharing. First, we propose a group signature scheme that supports traceability. Second, to address the issue of validating anonymous certificates, we propose group signatures with time constraints that enable dynamic updates to validity. Through this, we can dynamically revoke group members. Lastly, security proofs and efficiency analyses demonstrate that our scheme is both secure and efficient. © 2024 IEEE.

关键词： Electronic health record

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Green Computing Adoption: Understanding the Role of Individual, Social, and Organizational Factors 19

Green Computing Adoption: Understanding the Role of Individu...

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19th International Conference on Evaluation of Novel Approaches to software engineering, ENASE 2024

作者： Anni, Fahima Akter Islam, Muhammad Rezaul Sadia, Farzana Hasan, Mahady Rokonuzzaman, M. Department of Software Engineering Independent University Bangladesh Dhaka Bangladesh Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh Department Electrical and Computer Engineering North South University Dhaka Bangladesh

ISBN: (纸本)9789897586965

This study investigates the factors influencing the attitudes of software developers and IT professionals towards Green Information Technology (GIT) in Bangladeshi IT/software firms and examines their impact on engagement in green computing practices. Data was collected from 130 participants. A thorough literature review was conducted. The findings highlight key individual factors that influence employees’ attitudes, including awareness, knowledge, and perception of environmental issues. The study demonstrates the connection with GIT attitudes and behavior modification, especially through stated usage of green computing methods. Data analysis confirms 5 out of 8 hypotheses and reveals the complexity of the relationships between the constructs. The report promotes the adoption of Green IT technology by software companies in Bangladesh and highlights the significance of an organized office system integrating Green IT. Limitations include a relatively small sample size and the multidimensional nature of the relationships between the constructs. The findings can assist software companies in addressing customer concerns about the performance and functionality of green computing practices, ultimately promoting sustainable computing practices in the IT sector of Bangladesh. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Green computing

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Enhancing chain-of-thought reasoning in large language models through text style diversity and prompt fusion 3

Enhancing chain-of-thought reasoning in large language model...

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3rd International Conference on Electronic Information engineering, Big Data, and computer Technology, EIBDCT 2024

作者： Li, Weichen Pan, Weimin School of Computer Science National Pilot Software Engineering School Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781510680449

In order to reduce the impact of public health emergencies on the normal life of residents, at the same time to prevent the secondary spread of diseases caused by improper methods in the management process. On the premise of reducing the overall operation cost as much as possible, based on the basic data such as the number of quarantinable population, the number of daily necessities distribution points, and transportation network of 9 administrative areas in Changchun during the epidemic isolation and prevention period in 2022, this paper uses the entropy weight method to score each community and set the number of delivery points, so as to judge whether the actual plan is reasonable. In order to further optimize, with the minimum service cost of all the selected delivery points and the premise of meeting the distribution demand, save as much as possible, reduce the number of sites, and minimize the site radius of each sorting point as the goal, the total number of selected delivery points should not exceed the set total. A multi-objective site selection planning model was established for constraints. Sensitivity analysis was performed on the number of sites to determine the optimal number of sites, and cluster analysis was used to obtain the optimal site selection coordinates and cell numbers corresponding to the drop points. As a result, the number of sites was greatly reduced and the efficiency of material distribution was improved. Considering that the less people flow in the context of the epidemic, the better, this paper also uses the improved k-means algorithm for the actual plan, and finally gets the following number of delivery points in each district: 168 in Erdao District, 53 in Jingyue District, 239 in Nanguan District, 292 in Kuancheng District, 303 in Chaoyang District, 25 in steam open district, 69 in economic open District, and 222 in Green Park. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Sensitivity analysis

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Image Inpainting with GANs on LOKI Dataset

Image Inpainting with GANs on LOKI Dataset

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2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024

作者： Binici, Rıfkı Can Onan, Aytug Koch, Reinhard Schröder, Simon-Martin Software Engineering Izmir Katip Celebi University Izmir Turkey Computer Science Kiel University Kiel Germany

ISBN: (纸本)9798350379433

Inpainting images becomes crucial, especially when dealing with the challenging LOKI zooplankton dataset. This research presents a novel framework for image inpainting, designed to optimize results through a systematic approach. Our proposed framework effectively addresses these challenges, enhancing both the qualitative and quantitative aspects of inpainting quality. Through evaluation on the LOKI dataset, we achieved an overall Dice score of 0.7604, indicating a high level of accuracy. Additionally, the inclusion of squared masks proved advantageous in predicting missing components across images. Our innovative framework for inpainting plankton images in the LOKI dataset overcomes limitations by enabling inpainting within square-shaped regions, without requiring prior pixel location knowledge. This approach leverages a MultiRes-UNet generator, two discriminator networks with EfficientNet architecture, and a pretrained feature extractor network (VGG19), resulting in efficient performance in terms of our task. © 2024 IEEE.

关键词： Image reconstruction

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Verification of Musical Education with Face Images Using Convolutional Neural Network and Vision Transformers 5

Verification of Musical Education with Face Images Using Con...

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5th International Conference on Neural Networks and Neurotechnologies, NeuroNT 2024

作者： Polyak, Mark D. Senichenkova, Yana O. Saint Petersburg State University of Aerospace Instrumentation Department of Computer Technologies and Software Engineering Saint-Petersburg Russia

ISBN: (纸本)9798350363739

This research investigates whether machine learning techniques can be used to study the relationship between physical appearance and personality or other characteristics. Specifically, it explores the hypothesis that a person's profession may influence their facial features. The study focuses on musicians of a symphony orchestras as a specific example. A dataset of photographs was collected, including both symphony orchestra musicians and non-musicians. Three neural networks were used to solve the problem of classifying the images into two categories (musicians vs. non-musicians): VGG-Face, CLIP-ViT, and Google ViT. These neural networks extracted numerical representations (embeddings) from the images. The embeddings were then used to train support vector machines, a type of machine learning algorithm. The study compares the amount of information captured by the embeddings from each of the three neural network models. © 2024 IEEE.

关键词： Embeddings

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Reference Trustable Decoding: A Training-Free Augmentation Paradigm for Large Language Models 38

Reference Trustable Decoding: A Training-Free Augmentation P...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Shi, Luohe Yao, Yao Li, Zuchao Zhang, Lefei Zhao, Hai National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan430072 China Department of Computer Science and Engineering Shanghai Jiao Tong University China

Large language models (LLMs) have rapidly advanced and demonstrated impressive capabilities. In-Context Learning (ICL) and Parameter-Efficient Fine-Tuning (PEFT) are currently two mainstream methods for augmenting LLMs to downstream tasks. ICL typically constructs a few-shot learning scenario, either manually or by setting up a Retrieval-Augmented Generation (RAG) system, helping models quickly grasp domain knowledge or question-answering patterns without changing model parameters. However, this approach involves trade-offs, such as slower inference speed and increased space occupancy. PEFT assists the model in adapting to tasks through minimal parameter modifications, but the training process still demands high hardware requirements, even with a small number of parameters involved. To address these challenges, we propose Reference Trustable Decoding (RTD), a paradigm that allows models to quickly adapt to new tasks without fine-tuning, maintaining low inference costs. RTD constructs a reference datastore from the provided training examples and optimizes the LLM's final vocabulary distribution by flexibly selecting suitable references based on the input, resulting in more trustable responses and enabling the model to adapt to downstream tasks at a low cost. Experimental evaluations on various LLMs using different benchmarks demonstrate that RTD establishes a new paradigm for augmenting models to downstream tasks. Furthermore, our method exhibits strong orthogonality with traditional methods, allowing for concurrent usage. Our code can be found at https://***/ShiLuohe/ReferenceTrustableDecoding. © 2024 Neural information processing systems foundation. All rights reserved.

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