Thermodynamic Modeling of Hashtag Dynamics for Social Media Clustering: A Maxwell-Boltzmann Approach by Krishnan Batri, Rajermani Thinakaran, Bhuvana Jayabalan, L. Karthikeyan, S. Lakshmi, R. Sowrirajan, Sivaram Murugan

“…The approach enables more accurate identification of topic clusters, revealing distinct discourse patterns that conventional methods fail to capture.…”
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Bibliometric Analysis of Research Productivity and Impact at the University of Dodoma: by Josephine Wilfred Ogondiek

“… This study provides a bibliometric analysis of research publications from the University of Dodoma (UDOM) between 2007 and 2022, offering a comprehensive evaluation of the institution's scholarly output. By examining citation metrics and academic publications, the research reveals key patterns that shed light on the effectiveness and impact of UDOM's research initiatives. …”
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Hybrid Blockchain-Based Multi-Operator Resource Sharing and SLA Management by Sidra Tul Muntaha, Qasim Z. Ahmed, Faheem A. Khan, Zaharias D. Zaharis, Pavlos I. Lazaridis

“…We propose a hybrid blockchain-based framework for multi-operator resource sharing and SLA management in 5G Standalone (5GSA) networks. Leveraging Hyperledger Fabric (HLF), we implement secure resource sharing between multiple seller Mobile Network Operators (MNOs) and a single buyer MNO, evaluating HLF’s performance in terms of transaction latency and throughput. …”
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Enhanced Deep Autoencoder-Based Reinforcement Learning Model with Improved Flamingo Search Policy Selection for Attack Classification by Dharani Kanta Roy, Hemanta Kumar Kalita

“…Intrusion detection has been a vast-surveyed topic for many decades as network attacks are tremendously growing. This has heightened the need for security in networks as web-based communication systems are advanced nowadays. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…By integrating wavelet-based feature extraction with machine learning-driven analysis, this approach enhances the ability to detect complex wave propagation patterns, leading to more precise subsurface modeling. …”
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A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

“…The dominant factors causing productivity differences are still uncertain, which hinders productivity improvement. To further evaluate the primary factors controlling productivity, a new method for assessing productivity-influencing factors was developed, based on the production dynamic parameters of 36 vertical cluster wells and using neural networks to predict bottom-hole flowing pressure. …”
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Advances in gait research related to Alzheimer’s disease by Shuding Yan, Xiaoping Yun, Qiang Liu, Zhenmei Hong, Yufan Chen, Shuijing Zhang

“…In the future, it is hoped that with the results of clinical manifestations, neuroimaging, and electrophysiology, simple and objective gait analysis results can be used as an alternative biomarker for cognitive decline to diagnose dementia early.Research objectiveThis research offers a comprehensive scoping review of the contemporary landscape of clinical gait evaluation. It delineates the pertinent concepts of gait analysis and machine learning in AD and elucidates the intricate interplay between gait patterns and cognitive status.MethodsA comprehensive literature search was conducted within PubMed for all articles published until march 18, 2024, using a set of keywords, including “machine learning and gait “and “gait and Alzheimer.” original articles that met the selection criteria were included.Results and significanceA strong correlation exists between autonomous gait and cognitive attributes, necessitating further investigation into the selective interplay between gait and mental factors. …”
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A dual-adaptive stochastic reinforcement chimp optimization algorithm for fire detection and multidimensional problem solving by Ziyang Zhang, Lingye Tan, Diego Martín, Leren Qian, Mohammad Khishe, Pradeep Jangir

“…We evaluate TASR-CHOA against 4 categorical optimization techniques as well as 18 top IEEE CEC-BC algorithms. …”
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Fast2Vec, a modified model of FastText that enhances semantic analysis in topic evolution by Ayu Pertiwi, Azhari Azhari, Sri Mulyana

“…Additionally, the model effectively categorized topics into four distinct evolution patterns (diffusion, shifting, moderate fluctuations, and stability), enabling a deeper understanding of evolution topic interests and their dynamic characteristics. …”
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Masked and Noise-Masked Multimodal Brain Tumor Image Segmentation Using SegFormer and Shared Encoder Framework by K. Hemalatha, P. R. Vishnu Vardhan, Alfred Dharmaraj Aravindraj, S. Hari Hara Sudhan

“…Additionally, noise-masking introduces a controlled Gaussian noise into the MRI images creating random variations in the pixel intensities and thereby encouraging the model to learn the invariant and essential patterns in MRI images. Evaluation on Brain Tumor Segmentation (BraTS2020) challenge dataset demonstrates that MNMS outperforms conventional convolutional neural network (CNN) based methods, achieving superior accuracy and Dice Similarity Coefficient (DSC) scores. …”
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Attention-Driven Hybrid Ensemble Approach With Bayesian Optimization for Accurate Energy Forecasting in Jeju Island’s Renewable Energy System by Muhammad Ali Iqbal, Joon-Min Gil, Soo Kyun Kim

“…The combination of fluctuating consumer demand patterns and high variability across different energy sources presents significant challenges in maintaining a reliable balance between supply and demand. …”
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Enhancing Genomic Data Representation Through BERT-LSTM Hybrid Architecture by Kyeong Ho Kim, Minji Kim, Sohui Kim, Jong-Min Lee

“…Our method processes genetic sequence data through k-mer tokenization and employs BERT to capture complex patterns, followed by LSTM to preserve essential sequential information while creating fixed-size representations. …”
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High-throughput behavioral screening in Caenorhabditis elegans using machine learning for drug repurposing by Antonio García-Garví, Antonio-José Sánchez-Salmerón

“…The results highlight the potential of machine learning models to enhance automated phenotypic screening in animal models, providing a more robust and quantitative evaluation of treatment effects by considering more complex and subtle patterns.…”
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A Flexible Constrained ICA Approach for Multisubject fMRI Analysis by Hanlu Yang, Trung Vu, Ehsan Ahmed Dhrubo, Vince D. Calhoun, Tülay Adali

“…Large-scale analysis of functional connectivity within intrinsic brain networks using functional magnetic resonance imaging (fMRI) data has been widely used for identifying biomarkers in various psychiatric disorders. …”
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Exosomal lncRNA profiles in patients with HFrEF: Evidence for KLF3-AS1 as a novel diagnostic biomarker by Lei Wang, Yanan Zhang, Jiapu Wang, Xiao Jiang, Gang Wang, Haixiong Wang, Yan Shu, Han Huiyuan

“…PPI network analysis identified INS, CTNNB1, and CAT as the most prominent hub genes, whereas MDM2, MYH6, ENAH, and KLF3-AS1 were significantly enriched in the RBP interaction network. …”
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Europe's adaptation to the energy crisis: reshaped gas supply–transmission–consumption structures and driving factors from 2022 to 2024 by C. Zhou, B. Zhu, A. Halff, A. Halff, S. J. Davis, Z. Liu, S. Bowring, S. B. Arous, P. Ciais

“…Total gas consumption fell by 19.0 %, which was driven by (1) consumer behavioral changes in household heating (contributed to 29 % of the total reduction; the following numbers are also percentage contributions to the total reduction); (2) drops in industrial production (25 %); (3) heating drops due to the warmer winter temperatures (11 %); (4) shifts towards renewable electricity including wind, solar, and hydro (10 %); (5) a decline in gas-powered electricity generation (9 %); (6) adoption of energy-efficient heat pumps for industrial gas heating (4 %); (7) shifts towards non-renewable electricity including coal, oil, and nuclear (1 %); and (8) other unmodeled factors (11 %). We evaluated the benefits and costs associated with these pattern changes and discussed whether these changes would potentially lead to long-term structural changes in the EU energy dynamics. …”
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Azithromycin treatment response as a probe to attribute bacterial etiologies of diarrhea using molecular diagnostics: a reanalysis of the Antibiotics for Children with Severe Diarr... by Jennifer Cornick, Jennifer Cornick, Sarah Elwood, James Platts-Mills, Patricia Pavlinac, Patricia Pavlinac, Karim Premji Manji, Christopher R. Sudfeld, Christopher P. Duggan, Christopher P. Duggan, Queen Dube, Naor Bar-Zeev, Karen Kotloff, Karen Kotloff, Samba O. Sow, Sunil Sazawal, Benson Singa, Benson Singa, Judd L. Walson, Judd L. Walson, Farah Naz Qamar, Tahmeed Ahmed, Ayesha De Costa, Elizabeth T. Rogawski McQuade

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Gird Congestion Management Based on the Renewable Energy Zones and Clustering of Grid Congestion Conditions by Yujiro Tanno, Akihisa Kaneko, Yasuhiro Hayashi, Yuki Itoda, Wataru Wayama, Kevin Tomsovic

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Improving automated scoring of prosody in oral reading fluency using deep learning algorithm by Kuo Wang, Xin Qiao, George Sammit, Eric C. Larson, Joseph Nese, Akihito Kamata

“…This study proposed and evaluated an approach focusing on specific prosodic features using a deep-learning neural network. …”
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A selective CutMix approach improves generalizability of deep learning-based grading and risk assessment of prostate cancer by Sushant Patkar, Stephanie Harmon, Isabell Sesterhenn, Rosina Lis, Maria Merino, Denise Young, G. Thomas Brown, Kimberly M. Greenfield, John D. McGeeney, Sally Elsamanoudi, Shyh-Han Tan, Cara Schafer, Jiji Jiang, Gyorgy Petrovics, Albert Dobi, Francisco J. Rentas, Peter A. Pinto, Gregory T. Chesnut, Peter Choyke, Baris Turkbey, Joel T. Moncur

“…For cancer grading, a Gleason pattern detector was trained on tiles using a ResNet50 convolutional neural network and a selective CutMix training strategy involving a mixture of real and artificial examples. …”
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