SS-EMERGE - self-supervised enhancement for multidimension emotion recognition using GNNs for EEG by Chirag Ahuja, Divyashikha Sethia

“…Abstract Self-supervised learning (SSL) is a potent method for leveraging unlabelled data. Nonetheless, EEG signals, characterised by their low signal-to-noise ratio and high-frequency attributes, often do not surpass fully-supervised techniques in cross-subject tasks such as Emotion Recognition. …”
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Stochastic Fractal Search for Bayesian Network Structure Learning Under Soft/Hard Constraints by Yinglong Dang, Xiaoguang Gao, Zidong Wang

“…A Bayesian network (BN) is an uncertainty processing model that simulates human cognitive thinking on the basis of probability theory and graph theory. Its network topology is a directed acyclic graph (DAG) that can be manually constructed through expert knowledge or automatically generated through data learning. …”
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On the Impact of Labeled Sample Selection in Semisupervised Learning for Complex Visual Recognition Tasks by Eftychios Protopapadakis, Athanasios Voulodimos, Anastasios Doulamis

“…These approaches are explored in the context of four semisupervised learning techniques, i.e., graph-based approaches (harmonic functions and anchor graph), low-density separation, and smoothness-based multiple regressors, and evaluated in two real-world challenging computer vision applications: image-based concrete defect recognition on tunnel surfaces and video-based activity recognition for industrial workflow monitoring.…”
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Wireless resource allocation for distributed caching system:motivation, challenge and solution by Li WANG, Zhiyong FENG, Ping ZHANG

“…To solve such problems, the distributed caching system was introduced into the wireless collaboration network by allowing users to cache popular content items cooperatively, for effective content sharing among users with low energy consumption,high reliability and low latency,while offloading base station and backhaul data traffic. …”
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Model Konseling Berorientasi Hipnosis untuk Meningkatkan Kebahagiaan pada Mahasiswa by Sahira Anggita, Cucu Arumsari, Aam Imaddudin

“…The population used is students of the Muhammadiyah University of Tasikmalaya class of 2021, with the subjects sampled to be given interventions and students with a low happiness level. The data analysis technique used is a visual analysis by looking directly at the trend line on the graph and statistical analysis using PND (Percentage Non-Overlapping Data) calculations to test the effectiveness of the interventions provided. …”
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Integrative evaluation of nutrient status in the paddy soil by FANG Ping, XIE Jin-liang

“…The systemic cluster graph was gained based on the general scores of 23 soil samples. …”
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Evaluating Global Machine Learning Models for Tropical Cyclone Dynamics and Thermodynamics by Pankaj Lal Sahu, Sukumaran Sandeep, Hariprasad Kodamana

“…However, they consistently underestimated maximum sustained wind speeds compared to NWP models and observations. The low bias in TC intensity forecasts by MLWP models is linked to similar bias in their training data, along with the double penalization effect. …”
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Performance Analysis of FGO Windowing Strategies for PDR+GNSS Fusion Architecture by Amjad Hussain Magsi, Luis Enrique Diez Blanco

“…While FGO has also gained popularity in Simultaneous Localization and Mapping (SLAM) applications, its reliance on batch data processing, referred to as Batch Factor Graph Optimization (BFGO) and which is used as the baseline for this study, results in significant computational overhead, making it impractical for real-time or resource-constrained scenarios. …”
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Identifying the Latitude and Longitude of ATMs in ATM Networks by Niloofar Haghjoo, Mohammad rahmati, Ali Zare Mirakabad

“…Objective The geographical positioning of Automated Teller Machines (ATMs) is a pivotal data point that significantly aids in the analytical process and decision-making for a multitude of critical banking and economic determinations. …”
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Predicting student achievement through peer network analysis for timely personalization via generative AI by Ivica Pesovski, Petar Jolakoski, Vladimir Trajkovik, Zuzana Kubincova, Michael A. Herzog

“…Centrality measures were calculated from this directed graph to classify students into low-achieving and high-achieving groups for two-class classification, and into low-achieving, high-achieving, and neutral groups for three-class classification. …”
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Using accelerometer Analysis to Assess Physical Activity and Sedentary Behavior in Syrian Adults by Mahfouz Al-Bachir, Husam Ahmad

“…The aim of the present study was to determine PA and SB by triaxial accelerometer (ActiGraph GTX3 GT3X+, ActiGraph, Pensacola, FL. 32502 USA) in Syrian adults that affected by age, marital, body mass index (BMI), education, and smoking status. …”
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Research on fault localization method of valve area in converter station based on metric learning and knowledge reasoning by WEI Yun, LI Xianwei, ZHANG Yanlong, CAO Hui, XU Dan, QIU Junhong

“…A triplet of electrical quantity-switch quantity-fault type is formed, which stores fault location knowledge in the form of a knowledge graph, and designs a knowledge graph inference algorithm to achieve fault location based on waveform data analysis. …”
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The “Smart Home” Heat Supply System Based on District Heating with the Utilization of Secondary Energy Resources Using a heat Pump by I. L. Iokova, M. B. Perekhval, I. E. Migutskii

“…For clarity of the obtained data, a graph depicting the total steam load required for heating as a function of ambient temperature is constructed, as well as a graph showing the steam load as a function of the duration of the ambient temperature. …”
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Integrated single-cell and bulk RNA dequencing to identify and validate prognostic genes related to T Cell senescence in acute myeloid leukemia by Mengyao Sha, Jun Chen, Haifeng Hou, Huaihui Dou, Yan Zhang

“…Univariate and multivariate regression analyses were performed to screen prognostic genes using the AML Cohort in The Cancer Genome Atlas (TCGA) Database (TCGA-LAML), and risk models were constructed to identify high-risk and low-risk patients. Line graphs showing the survival of patients with AML were created based on the independent prognostic factors, and Receiver Operating Characteristic Curve (ROC) curves were used to calculate the predictive accuracy of the line graph. …”
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A rolling bearing fault diagnosis method based on GADF-CWT-GCNN by ZHANG Xiaoli, LUO Xin, LI Min, LIANG Wang, WANG Fangzhen

“…Then the data enhancement technique is used to expand the sample sub-graph to meet the input requirements of the network. …”
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Application of the Image Processing Method and the Beer-Lambert Law for Assessing Sea Water Intrusion in Rivers by Ehsan Kahrizi

“…The "Concentration Contour" graph shows high salinity concentrations near the bottom 10 cm of the flume. …”
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Fibre tracing in biomedical images: An objective comparison between seven algorithms. by Youssef Arafat, Cristina Cuesta-Apausa, Esther Castellano, Constantino Carlos Reyes-Aldasoro

“…To compare the algorithms, four biomedical data sets with vastly distinctive characteristics were selected. …”
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Linear Total Variation Approximate Regularized Nuclear Norm Optimization for Matrix Completion by Xu Han, Jiasong Wu, Lu Wang, Yang Chen, Lotfi Senhadji, Huazhong Shu

“…Matrix completion that estimates missing values in visual data is an important topic in computer vision. Most of the recent studies focused on the low rank matrix approximation via the nuclear norm. …”
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An Ontology-Based Framework for Complex Urban Object Recognition through Integrating Visual Features and Interpretable Semantics by Xiao Xie, Xiran Zhou, Jingzhong Li, Weijiang Dai

“…Especially for the complex urban objects, which varies in geometrical shapes, functional structures, environmental contexts, etc, due to the heterogeneity between low-level data features and high-level semantics, the features derived from remote sensing data alone are limited to facilitate an accurate recognition. …”
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Rancang Bangun ECG Simulator Menggunakan Digital to Analog Converter R-2R by Mulyatno Saimi

“…Memiliki output 10 terminal  standard ECG.  Kontrol dan pengolahan sinyal menggunakan Arduino pro mini, data digitalisasi ECG diperoleh dengan memperbesar cetakan sinyal ECG pada kertas kotak-kotak/grid, data sinusoidal dibuat menggunakan fungsi sin microsoft excel, sedang data digitalisasi square memberikan nilai output high dan low. …”
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