Effect of restoration methods on natural regeneration in the Brazilian Atlantic Forest by Casati Fernandes H, Manhães AP, Alonso JM, Mantuano D, Martini AMZ, Saavedra MM, Andrade MT, Sansevero JBB

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Path Planning of Quadrupedal Robot Based on Improved RRT-Connect Algorithm by Xiaohua Xu, Peibo Li, Jiangwu Zhou, Wenzhuo Deng

“…In view of the large randomness, redundant path nodes, and low search efficiency of RRT-connect in a complex obstacle environment, this study intends to develop a path-planning method combining RRT-connect and Informed RRT*. First, to solve the problem of large sampling randomness, the Informed RRT* algorithm is combined to adopt a simpler rectangle and limit the sampling range to the rectangle. …”
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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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Testing infrared camera surveys and distance analyses to estimate feral horse abundance in a known population by Kathryn A. Schoenecker, Paul F. Doherty Jr., Jacob S. Hourt, John P. Romero

“…We found the combination of IR surveys and distance sampling analysis to be a useful method to estimate feral horse abundance in sagebrush vegetation type, which had limited cover to obscure horses. …”
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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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PoE-Enabled Visible Light Positioning Network With Low Bandwidth Requirement and High Precision Pulse Reconstruction by Zhenghai Wang, Xuan Huang, Xuanbang Chen, Mengzhen Xu, Xiaodong Liu, Yuhao Wang, Xun Zhang

“…It achieves a positioning accuracy of 1.7 cm by using the reconstructed 2 GHz sampling rate in the case of a bandwidth of 50 MHz and a real sampling rate of 100 MHz. …”
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DEVELOPMENT OF METHODS FOR DETERMINATION OF SPECIFIC IMPURITIES IN THE GLUTATIONION RESTORED SUBSTANCE by K. A. Alexeeva, D. I. Pisarev, A. Yu. Malyutina, N. N. Boyko

“…A comparative analysis of the data obtained makes it possible to state that the OF-HPLC method with pre-column derivatization is more reliable, since it is more sensitive to impurities, and also makes it possible to study the UV profiles of impurity components better than the TLC method. …”
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Simple and accessible methods for quantifying isolated mucins for further evaluation by Hannah J. McIntire-Ray, Elex S. Rose, Stefanie Krick, Jarrod W. Barnes

“…In this study, we present a detailed workflow for the isolation, quantitation, and evaluation of mucin proteins. These methods are applicable to a variety of biological, mucin-containing samples from the airways and other mucosal organ systems. …”
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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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Interpolation methods for creating a scatter radiation exposure map by Elicardo Alves de Souza Goncalves, Celio Simonacci Gomes, Luis Fernando Oliveira, Marcelino Jose Anjos, Davi Ferreira Oliveira, Ricardo Tadeu Lopes

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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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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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Comparative evaluation of feature reduction methods for drug response prediction by Farzaneh Firoozbakht, Behnam Yousefi, Olga Tsoy, Jan Baumbach, Benno Schwikowski

“…This study presents the first comparative evaluation of nine different knowledge-based and data-driven feature reduction methods on cell line and tumor data. Our analysis employs six distinct machine learning models, with a total of more than 6,000 runs to ensure a robust evaluation. …”
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Gene expression data classification: some distance-based methods by Olusola Samuel Makinde

“…Micro-array dataset is a classical example of high throughput data characterized with more features(genes) than sample points(gene expression levels). …”
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