ZenLDA: Large-Scale Topic Model Training on Distributed Data-Parallel Platform by Bo Zhao, Hucheng Zhou, Guoqiang Li, Yihua Huang

“…The novelty of ZenLDA consists of three main aspects: (1) it converts the commonly used serial Collapsed Gibbs Sampling (CGS) inference algorithm to a Monte-Carlo Collapsed Bayesian (MCCB) estimation method, which is embarrassingly parallel; (2) it decomposes the LDA inference formula into parts that can be sampled more efficiently to reduce computation complexity; (3) it proposes a distributed LDA training framework, which represents the corpus as a directed graph with the parameters annotated as corresponding vertices and implements ZenLDA and other well-known inference methods based on Spark. …”
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Effective Detection of Cloud Masks in Remote Sensing Images by Yichen Cui, Hong Shen, Chan-Tong Lam

“…The model uses an improved residual module to capture the multi-scale features of clouds more effectively. MDU-Net first extracts the feature maps using four residual modules at different scales, and then sends them to the context information full flow module for the first up-sampling. …”
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Re‐evaluating fetal scalp pH thresholds: An examination of fetal pH variations during labor by Aude Girault, Camille Le Ray, Charles Garabedian, François Goffinet, Xavier Tannier

“…The aim of the study was to investigate if pH drop rate accelerates at the common thresholds (7.25 and 7.20) and to explore the possibility of identifying more accurate thresholds. Material and methods A retrospective study was conducted at a tertiary maternity hospital between June 2017 and July 2021. …”
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Blended therapy for adolescents with chronic health conditions to increase fatigue-related self-efficacy (Booster): protocol for a single-case multiple baseline study by Maartje D. Stutvoet, Anouk Vroegindeweij, Jan Houtveen, Raphaële R. L. van Litsenburg, Elise van de Putte, Remco C. Veltkamp, Sanne L. Nijhof

“…Discussion Booster uses innovative methods by combining tailored ESM-insight, mHealth and healthcare professional support. …”
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IMPLEMENTATION OF THE DBSCAN METHOD FOR CLUSTER MAPPING OF EARTHQUAKE SPREAD LOCATION by Muhammad Bariklana, Achmad Fauzan

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Method of anti-confusion texture feature descriptor for malware images by Yashu LIU, Zhihai WANG, Hanbing YAN, Yueran HOU, Yukun LAI

“…It is a new method that uses image processing and machine learning algorithms to classify malware samples in malware visualization field.The texture feature description method has great influence on the result.To solve this problem,a new method was presented that joints global feature of GIST with local features of LBP or dense SIFT in order to construct combinative descriptors of malware gray-scale images.Using those descriptors,the malware classification performance was greatly improved in contrast to traditional method,especially for those samples have higher similarity in the different families,or those have lower similarity in the same family.A lot of experiments show that new method is much more effective and general than traditional method.On the confusing dataset,the accuracy rate of classification has been greatly improved.…”
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Evidence Prediction Method Based on Sentence Selection for Legal Documents by Huijie Bai

“…In order to solve the problem that it is difficult to find evidence from a large number of legal document statements and the irrelevant statements in a large number of document sample data will cause a great interference to the prediction results and further improve the accuracy of evidence prediction, this paper puts forward an intelligent evidence criterion prediction method for legal documents based on the comprehensive consideration of legal problems, the nature of statements, and the characteristics of answers. …”
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New Method for the Determination of DL-Histidine by FIA and Chemiluminometric Detection by Baghdad Science Journal

“…Using 70?l. sample linear plot with a coefficient of determination 95.79% for (5-60) mmol.L-1 while for a quadratic relation C.O.D = 96.44% for (5-80) mmol.L-1 and found that guadratic plot in more representative. …”
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Battery Life Evaluation Method Based on Temporal Convolution Network by SUN Yushu, AN Juan, HUANG Cunqiang, ZHANG Shunzhen, DANG Yanyang, PEI Wei, TANG Xisheng

“…In contrast, RUL will irreversibly decrease as the service time increases, which can provide a more reliable criterion for evaluation. To predict RUL, the same five key features (cycle time, average voltage, voltage sample entropy, temperature sample entropy, current) along with capacity are used. …”
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A Synergistic CNN-DF Method for Landslide Susceptibility Assessment by Jiangang Lu, Yi He, Lifeng Zhang, Qing Zhang, Jiapeng Tang, Tianbao Huo, Yunhao Zhang

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A method for PCR-free library preparation for sequencing palaeogenomes. by Kirstin Henneberger, Axel Barlow, Federica Alberti, Michaela Preick, Silviu Constantin, Doris Döppes, Wilfried Rosendahl, Michael Hofreiter, Johanna L A Paijmans

“…Here we present an amplification-free library preparation method based on a benchmark library preparation protocol in palaeogenomics based on single-stranded DNA, and demonstrate suitability of the new method for a range of sample types. …”
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Multi-adversarial domain adaptation method based on feature correction by Yong ZHANG, Haoshuang LIU, Qi ZHANG, Wenzhe LIU

“…Domain adaptation can transfer labeled source domain information to an unlabeled but related target domain by aligning the distribution of source domain and target domain.However, most existing methods only align the low-level feature distributions of the source and target domains, failing to capture fine-grained information within the samples.To address this limitation, a feature correction-based multi-adversarial domain adaptation method was proposed.An attention mechanism to highlight transferable regions was introduced in this method and a feature correction module was deployed to align the high-level feature distributions between the two domains, further reducing domain discrepancies.Additionally, to prevent individual classifiers from overfitting their own noisy pseudo-labels,dual classifier co-training was proposed and the feature aggregation property of graph neural networks was utilized to generate more accurate source domain labels.Extensive experiments on three benchmark datasets for transfer learning demonstrate the effectiveness of the proposed method.…”
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Multi-scale convolutional neural networks (CNNs) for landslide inventory mapping from remote sensing imagery and landslide susceptibility mapping (LSM) by Baoyi Zhang, Jiacheng Tang, Yuke Huan, Lei Song, Syed Yasir Ali Shah, Lifang Wang

“…Subsequently, the refined landslide inventory, with more precise boundaries, is integrated into LSM process. …”
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Proposal of automated computational method to support Virginia tobacco classification by Leonel P. C. Tedesco, Adriano da C. de Freitas, Rolf F. Molz, Jacques N. C. Schreiber

“…In addition, the existence of an automated comparative procedure, helping to perform the classification, can make this process faster and more transparent. In order to implement the method, non-invasive to the agricultural product, 250 samples of Virginia tobacco digital images in the RGB and HSV color models were analyzed. …”
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Contrastive learning method for leak detection in water distribution networks by Rongsheng Liu, Tarek Zayed, Rui Xiao

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An Introduction to the Composite Element Method Applied to the Vibration Analysis of Trusses by Marcos Arndt, Roberto Dalledone Machado, Mildred Ballin Hecke

“…This paper introduces a new type of Finite Element Method (FEM), called Composite Element Method (CEM). …”
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Investigating the Onion Skin Method for Solving Simple Linear Equations by Syahida Abdul Ghani, Masitah Shahrill, Hardimah Said

“…This research may inspire teachers to use alternative methods when instructing students on solving fundamental linear equations, allowing them to modify their instruction or develop more practical lessons for teaching.…”
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GDPR-oriented intelligent checking method of privacy policies compliance by Xin LI, Peng TANG, Xiheng ZHANG, Weidong QIU, Hong HUI

“…The implementation of the EU’s General Data Protection Regulation (GDPR) has resulted in the imposition of over 300 fines since its inception in 2018.These fines include significant penalties for prominent companies like Google, which were penalized for their failure to provide transparent and comprehensible privacy policies.The GDPR, known as the strictest data protection laws in history, has made companies worldwide more cautious when offering cross-border services, particularly to the European Union.The regulation's territorial scope stipulates that it applies to any company providing services to EU citizens, irrespective of their location.This implies that companies worldwide, including domestic enterprises, are required to ensure compliance with GDPR in their privacy policies, especially those involved in international operations.To meet this requirement, an intelligent detection method was introduced.Machine learning and automation technologies were utilized to automatically extract privacy policies from online service companies.The policies were converted into a standardized format with a hierarchical structure.Through natural language processing, the privacy policies were classified, allowing for the identification of relevant GDPR concepts.In addition, a constructed GDPR taxonomy was used in the detection mechanism to identify any missing concepts as required by GDPR.This approach facilitated intelligent detection of GDPR-oriented privacy policy compliance, providing support to domestic enterprises while they provided cross-border services to EU users.Analysis of the corpus samples reveals the current situation that mainstream online service companies generally fail to meet GDPR compliance requirements.…”
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EEG Data Augmentation Method Based on the Gaussian Mixture Model by Chuncheng Liao, Shiyu Zhao, Xiangcun Wang, Jiacai Zhang, Yongzhong Liao, Xia Wu

“…This paper proposes a new method based on the Gaussian Mixture Model (GMM): First, we use the GMM to decompose data samples of the same category to obtain Gaussian coefficients and take the product of the probability coefficient and the weight matrix as the feature matrix. …”
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Sequence-Information Recognition Method Based on Integrated mDTW by Boliang Sun, Chao Chen

“…More importantly, compared to deep -learning-based methods, the proposed method has a simpler structure and higher interpretability. …”
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