Sentiment Analysis on the PT Pertamina Corruption Case using IndoBERT and RCNN Methods by Wildan Jaya Kusoema, Ichsan Ibrahim

“…Systematically evaluating hyperparameter combinations for three-class public opinion data, and 3.Utilizing YouTube comments as a relevant source of informal public discourse. …”
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Navigating Samarinda's climate: A comparative analysis of rainfall forecasting models by Mislan, Andrea Tri Rian Dani

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Synthetic Financial Data: A Case Study Regarding Polish Limited Liability Companies Data by Aleksandra Szymura

“…Analysis on high quality synthetic data allows conclusions similar to analysis on real data to be achieved, while retaining privacy and without publishing sensitive data to third parties.…”
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Integrated remote sensing, machine learning and geospatial approach for site selection of sewage treatment plants in the metropolitan city by S. Rajalakshmi, S. Subathradevi, Abdulaziz G. Alghamdi, Hadeel Alsolai

“…This study presents an integrated framework combining remote sensing (RS), geographic information systems (GIS), machine learning (ML), and multi-criteria decision analysis (MCDA) to identify suitable sites for sewage treatment plants (STPs). …”
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ML-Driven Transistor Self-Heating Analysis From TCAD to Large IP Circuits by Simon Thomann, Nico Mayr, Albi Mema, Hussam Amrouch

“…To this end, we have used TCAD to generate a distributed channel temperature map data set. We propose a technology-agnostic methodology for extracting localized temperature data on the circuit level using the trained machine learning model (with a mean error of 0.1 K). …”
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Evaluating Customer Segmentation Techniques in the Retail Sector by Nur Diyabi, Duygu Çakır, Ömer Melih Gül, Tevfik Aytekin, Seifedine Kadry

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A Review of Traffic Flow Prediction Methods in Intelligent Transportation System Construction by Runpeng Liu, Seong-Yoon Shin

“…This paper comprehensively reviews the traffic flow prediction methods used in ITSs and divides them into three categories: statistics-based, machine learning-based, and deep learning-based methods. Although statistics-based methods have lower data requirements and machine learning methods have faster calculation speeds, this paper concludes that deep learning methods have the best overall effect after a comprehensive analysis of the principles, advantages, limitations, and practical applications of each method. …”
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Analysis of Factors Influencing Perceived Academic Achievement in Quantitative Courses Among Distance Learners by Folashade Afolabi

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A Survey on Anti-Money Laundering Techniques in Blockchain Systems by Leyuan Liu, Xiangye Li, Tian Lan, Yakun Cheng, Wei Chen, Zhixin Li, Sheng Cao, Weili Han, Xiaosong Zhang, Hongfeng Chai

“…It categorizes existing AML techniques into three primary approaches: rule-based methods, such as transaction parameter threshold setting, address-entity association analysis, and cross-chain association analysis; machine learning-based approaches, including support vector machines, logistic regression, decision trees, random forests, k-means clustering, and combining off-chain information; and deep learning-based methodologies, encompassing convolutional neural networks, recurrent neural networks, graph neural networks, and transformer-based models. …”
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Deep Neural Network for Cure Fraction Survival Analysis Using Pseudo Values by Ola Abuelamayem

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Understanding the Promotion of Self-Regulated Learning in Upper Secondary Schools: How can Teaching Quality Criteria contribute? by Mathias Mejeh, Barbara Stampfli, Tina Hascher

“…We conducted seven focus groups involving a total of N = 49 secondary school students, and the data was analyzed using qualitative content analysis. …”
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Multi-atlas multi-modality morphometry analysis of the South Texas Alzheimer’s Disease Research Center postmortem repository by Nicolas Honnorat, Mariam Mojtabai, Karl Li, Jinqi Li, David Michael Martinez, Tanweer Rashid, Morgan Smith, Margaret E Flanagan, Elyas Fadaee, Morgan Fox Torres, Mallory Keating, Kevin Bieniek, Sudha Seshadri, Mohamad Habes

“…In this work, we report the very first morphometry analysis conducted with this new data set. We describe the processing pipelines that were specifically developed to exploit the available MRI sequences, and we explain how we addressed several postmortem neuroimaging challenges, such as the separation of brain tissues from fixative fluids, the need for updated brain atlases, and the tissue contrast changes induced by brain fixation. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…The models were built using real patient data from the Zigong Fourth People’s Hospital, which included 167 features from 2008 patients. …”
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LISTENING AND SPEAKING SKILLS AS LEARNING AND TARGET NEEDS IN BUSINESS ENGLISH PROGRAM FOR TOUR GUIDE DIPLOMA STUDENTS IN KENYA. by Douglas Ondara Orang'i

“…Needs analysis is an important step in any syllabus design and particularly that which touches on ESP. …”
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Species identification in sausage samples using near-infrared spectroscopy and linear discriminant analysis by Mohadeseh Pirhadi, Nabi Shariatifar, Gholamreza Jahed Khaniki, Massoud Amanlou, Parisa Sadighara, Ebrahim Molaee-Aghaee, Sohrab Pirhadi

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Identification of shared mechanisms between Alzheimer's disease and atherosclerosis by integrated bioinformatics analysis by Jukun Wang, Jing Yao, Zhe Wang

“…WIPF3, was identified as the most affected gene in both diseases using weighted gene co-expression network analysis, machine-learning-based Lasso Cox regression analysis and random forest analysis. …”
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Potential shared mechanisms in atopic dermatitis and type 2 diabetes identified via transcriptomic and machine learning approaches by Yang Zhang, Qiangman Wei, Qianzhi Chen

“…In this study, we integrated transcriptomic data from both AD and T2DM using differential gene expression analyses (DEGs), gene set variation analysis (GSVA), and machine learning algorithms to uncover common features of these diseases. …”
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Analysis to Predict the Number of New Students At UNU Pasuruan using Arima Method by Fachri Ayudi Fitrony, Laksmita Dewi Supraba, Tessa Rantung, I Made Artha Agastya, Kusrini Kusrini

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Resting-state EEG microstate analysis reveals potential biomarkers for subclinical insomnia by Yujie Shi, Mengqi Ji, Fan Zhong, Rui Jiang, Zhuhong Chen, Chi Zhang, Yuting Li, Junpeng Zhang, Wen Wang

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LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields by Joshua A Vita, Amit Samanta, Fei Zhou, Vincenzo Lordi

“…Model ensembles are effective tools for estimating prediction uncertainty in deep learning atomistic force fields. However, their widespread adoption is hindered by high computational costs and overconfident error estimates. …”
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