The Concept of Post-Non-Classic al Methodological Strategy by Professor Olexander Oguy by Olha Chervinska

“…The article “The Historical-Social Genres in Post-Non-Classical Methodology: the Principles of Classification” (Issue 86, 2012) is a vivid example of a profound present-day academic research. …”
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Eliminating geometric distortion with dual-orbit Sentinel-1 SAR fusion for accurate glacial lake extraction in Southeast Tibet Plateau by Renzhe Wu, Guoxiang Liu, Xin Bao, Jichao Lv, Age Shama, Bo Zhang, Wenfei Mao, Jie Chen, Zhihan Yang, Rui Zhang

“…It extracts GLs using a majority voting integration of unsupervised classification algorithms constrained by historical GL center points. …”
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Kombinasi K-Means dan Support Vector Machine (SVM) untuk Memprediksi Unsur Sara pada Tweet by Wiga Maulana Baihaqi, Muliasari Pinilih, Miftakhul Rohmah

“…In the classification process using two validation methods, namely cross-fold validation of 5 times compared with 10-fold cross validation, the accuracy of the two validation methods is 64.18% and 63.68%, respectively. …”
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Characterization of the Complete Chloroplast Genomes and Phylogenetic Analysis of Sapotaceae by Wenyan He, Yumei Liu, Rui Gao, Zhiyu Song, Wentao Zhu, Jinliao Chen, Cuiyi Liang, Shasha Wu, Junwen Zhai

“…Although previous studies have made some progress in the phylogenetic relationships and classification of Sapotaceae, many issues remain unresolved and require further in-depth research. …”
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Accuracy and applicability assessment of vegetation types of the land cover products produced in China by Caixia Li, Lingting Lei, Xiang Jia, Xiaoyan Xiong, Xiaoli Zhang

“…Therefore, we analyzed the applicability of three land cover products produced by Chinese institutions, including 35 issues of CLCD, 3 issues of GlobeLand30 and 10 issues of GLC_FCS30D, in terms of temporal stability and spatial consistency, and developed a spatial accuracy assessment method to realize the spatial accuracy mapping of different land cover products using the multiscale geographically weighted regression model (MGWR). …”
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Presentation of Financial Assets in the Statistics of Foreign Economic Relations by V. N. Salin, L. Yu. Arhangelskaya, O. G. Tretyakova

“…The paper identifies the main directions for the statisticalstudy of financial assets, based on current international standards, taking into account national practice. Topical issues of theory and practice of observations and presentation of data on financial assets in foreign economic statistics, application of definitions and classifications of international standards to Russian official statistical activities are considered. …”
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Chinese GFL-Learners’ Connector Usage: A Corpus-Linguistic Study of Argumentative Learner Texts by Zekun Wu, Yuan Li

“…Many scholars have studied English as a Foreign Language (EFL) learners’ connector usage, but few studies have occurred in fields related to German, with deficiencies still present regarding issues such as the relatively limited classification of connectors, insufficient analytical dimensions, and lack of studies on learners at different levels. …”
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Research on a Target Detection Algorithm for Common Pests Based on an Improved YOLOv7-Tiny Model by He Gong, Xiaodan Ma, Ying Guo

“…However, traditional deep learning models face challenges in resource-constrained environments, such as insufficient accuracy, slow inference speed, and large model sizes, which hinder their practical application. To address these issues, this study proposes an improved YOLOv7-tiny model designed to deliver efficient, accurate, and lightweight pest detection solutions. …”
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HoloMine: A Synthetic Dataset for Buried Landmines Recognition Using Microwave Holographic Imaging by Emanuele Vivoli, Lorenzo Capineri, Marco Bertini

“…In this article, we propose a novel synthetic dataset for buried landmine detection to provide researchers with a valuable resource to observe, measure, locate, and address issues in landmine detection. The dataset consists of 41 800 microwave holographic images (2-D) and their holographic inverted scans (3-D) of different types of buried objects, including landmines, clutter, and pottery objects, and is collected by means of a microwave holography radar. …”
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Research on Network Intrusion Detection Model Based on Hybrid Sampling and Deep Learning by Derui Guo, Yufei Xie

“…This study proposes an enhanced network intrusion detection model, 1D-TCN-ResNet-BiGRU-Multi-Head Attention (TRBMA), aimed at addressing the issues of incomplete learning of temporal features and low accuracy in the classification of malicious traffic found in existing models. …”
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Liberating the mental health and wellbeing benefits of laughing alone: a new taxonomic model and scoping review for future research by Freda Gonot-Schoupinsky, Xavier Gonot-Schoupinsky, Mark Weeks

“…While solitary laughter can be symptomatic of mental health issues, one motivation of this review was to explore whether it can also offer mental health benefits. …”
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Digital Twins for Smarter Iranian Cities: A Future Studies Perspective by Nader Zali, Ali Soltani, Peyman Najafi, Salima Ebadi Qajari, Mehrdad Mehrju

“…Using a futures studies approach, the study employs the Delphi method, MICMAC (Matrix Impact Cross-Reference Multiplication Applied to a Classification) technique, and SISMW (Strategic Uncertainties and Strengths Weaknesses Opportunities and Threats Matrix) methodologies to analyse these factors. …”
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Permutation Entropy for Signal Analysis by Bill Kay, Audun Myers, Thad Boydston, Emily Ellwein, Cameron Mackenzie, Iliana Alvarez, Erik Lentz

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Modelling of energy demand prediction system in potato farming using deep learning method by Riswanti Sigalingging, Nasha Putri Sebayang, Noverita Sprinse Vinolina, Lukman Adlin Harahap

“…A system using deep learning methods, specifically the Convolutional Neural Network (CNN), was also developed to accurately predict the classification of potato plant growth phases using image data. …”
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Counter-imaging Australia’s agricultural landscapes for digital sustainability communication by Joshua Zeunert, Alys Daroy

“…The methodology integrates systematic spatial-statistical analysis, typological classification, continental-scale field research, a visual method for drone-image capture, and the immersive online dissemination archive. …”
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Research on the construction and application of problem-method-oriented academic graph empowered by LLM by Qigang Liu, Yinfan Wang, Lifeng Mu, Jun Li

“…Experiments on widely used benchmark datasets show that the proposed multi-relation extraction model is able to achieve at least 8.01% and 8.65% improvement on entity identification and relation classification respectively, compared with state-of-the-art models. …”
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Comparative study of imputation strategies to improve the sarcopenia prediction task by Shakhzod Karimov, Dilmurod Turimov, Wooseong Kim, Jiyoun Kim

“…Additionally, KNN and MICE emerged as effective imputation techniques, preserving the original data distribution and enabling more accurate classification outcomes. Conclusion This study underscores the pivotal role of imputation methods in maintaining data integrity and enhancing predictive accuracy in sarcopenia research. …”
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Review of Certificateless Authentication Scheme for Vehicular Ad Hoc Networks by Abdulaziz Zaid A. Aljarwan, Md Asri Bin Ngadi

“…PKI-based authentication methods, on the other hand, do not fit our objective, given the high computational overhead, certificate management issues, and centralization risk involved in V2V authentication protocols. …”
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Application of a dynamo-based intelligent drawing review program in the general code for building fire protection - Case study of subsection 7.4.7 by Yong Xu, Min Liu, Taiyang Zhang, Hongyuan Tang, Yingda Zhang

“…The program enables classification of evacuation components—exits, walkways, and stairs—and formulates visual review logic to automate the verification of total net evacuation widths. …”
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Semantic enhancement and cross-modal interaction fusion for sentiment analysis in social media. by Guangyu Mu, Ying Chen, Xiurong Li, Li Dai, Jiaxiu Dai

“…However, modality fusion in sentiment analysis can introduce a lot of noise because of the differences in semantic representations among various modalities, ultimately impacting the accuracy of classification results. Thus, this paper presents a Semantic Enhancement and Cross-Modal Interaction Fusion (SECIF) model for sentiment analysis to address these issues. …”
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