Deep Learning Model for Feature Extraction and Anomaly Recognition in High-Dimensional Energy Metering Data by Huakun Que, Zetao Jiang, Zhifeng Zhou, Yongsheng He, Xin Liu

“…Objectives: This study aims to develop a deep learning-based method to detect anomalies in high-dimensional energy metering data, overcoming the limitations of existing techniques that struggle with data complexity and lack effective contextual analysis. …”
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Design and Development of an Application for Recording Income and Expenditure Data at Darrel's Cake Shop Prabumulih City by Nadyah Seftivia, Muchlis, Nurmayanti

“…The aim of this research is to create an application for recording income and expenditure data at Darrell's Cake Shop, Prabumulih City. …”
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Analyzing risk factors and handling imbalanced data for predicting stroke risk using machine learning by Adiwijaya Adiwijaya, Nur Ghaniaviyanto Ramadhan

“…This research highlights the importance of preemptive measures against stroke by utilizing predictive techniques on clinical data, with the Random Forest model proving most effective in forecasting stroke probability.…”
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Stacked LSTM for Short-Term Wind Power Forecasting Using Multivariate Time Series Data by Manisha Galphade, V. B. Nikam, Biplab Banerjee, Arvind W. Kiwelekar, Priyanka Sharma

“…To improve the performance, data preprocessing is carried out using two techniques such as removal of missing values and imputing missing values using Random Forest Regressor (RFR). …”
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A Data-Driven Approach to Estimating the Impact of Audiovisual Art Events Through Web Presence by Andreas Giannakoulopoulos, Minas Pergantis, Aristeidis Lamprogeorgos, Stella Lampoura

“…This data-driven approach is made possible through web data extraction techniques and the use of generative artificial intelligence, which allows for structured information extraction from an endless variety of websites. …”
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Exploring Purpose-Driven Methods and a Multifaceted Approach in Dam Health Monitoring Data Utilization by Zhanchao Li, Ebrahim Yahya Khailah, Xingyang Liu, Jiaming Liang

“…It discusses monitoring components, data acquisition processes, and sensor roles, stressing the need to integrate environmental, operational, and structural data for decision making. …”
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Predicting Student Academic Performance at Higher Education Using Data Mining: A Systematic Review by Sarah A. Alwarthan, Nida Aslam, Irfan Ullah Khan

“…The main objective of this paper is to highlight the recently published studies for predicting student academic performance in higher education. Moreover, this study aims to identify the most commonly used techniques for predicting the student's academic level. …”
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Utilizing machine learning and digital twin technology for rock parameter estimation from drilling data by Abdullah Khan, Yiming Li, Muhammad Shoaib, Umair Sajjad, Fuxin Rui

“…This review aims to provide a detailed understanding of the application and effectiveness of these methodologies for extracting rock parameters from drilling data.…”
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A model-based approach to detection of the circulating melanoma cells from the photoacoustic cytometry data by Yurii M. Ishbulatov, Viktoriia V. Skazkina, Anatoly S. Karavaev, Olga A. Inozemtseva, Daniil N. Bratashov, Arkady S. Abdurashitov, Oleg V. Grishin, Alexey N. Hramkov, Vladimir P. Zharov

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Big Data Analytics in E-commerce Driving Business Decisions Through Customer Behavior Insights by Pande Pooja, Kulkarni Adokshaja Krishnarao, P Balamurugan, S Balakrishnan, Ramalingam Vanaja, R Revathi

“…Moreover, it combines privacy-preserving techniques and ethical data governance that enables businesses to do so while building trust with their customers. …”
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Topic Modeling Approach on Twitter Data Relevant to Political Changes During the COVID-19 Pandemic by M. G. D. S. Hansika, K. S. Ranasinghe, R. A. H. M. Rupasingha

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Enhancing Crack Segmentation With Limited Data: SinGAN-Based Synthesis and Blending of Textures and Cracks by Farhan Mahmood, Myrto Inglezou, Panagiotis Chatzakos, Antonis Porichis

“…Recognizing the challenges in generating sufficiently varied and realistic data for training robust detection models, we leverage SinGAN’s capacity to generate textures from single images and introduce procedural techniques for the generation of synthetic cracks using Simplex noise. …”
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Mobilisation of Data From Natural History Collections Can Increase the Quality and Coverage of Biodiversity Information by Bryony Blades, Cristina Ronquillo, Joaquín Hortal

“…In this study, we aim to quantify potential gains to insect data on the Global Biodiversity Information Facility (GBIF) through further digitisation of natural history collections, assess to what degree this would fill biases in spatial and environmental record coverage, and deepen understanding of environmental bias with regard to climate rarity. …”
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Analysis of different IDS-based machine learning models for secure data transmission in IoT networks by Gladić Dejana, Petrovački Jelena, Sladojević Srdan, Arsenović Marko, Ristić Sonja

“…Based on the results of the experiment, the most effective model and preprocessing technique were proposed.…”
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Simultaneous EEG-fNIRS Data Classification Through Selective Channel Representation and Spectrogram Imaging by Chayut Bunterngchit, Jiaxing Wang, Zeng-Guang Hou

“…However, existing research in this domain has grappled with the challenge of the efficient selection of features, resulting in the underutilization of the temporal richness of EEG and the spatial specificity of fNIRS data.To effectively address this challenge, this study proposed a deep learning architecture called the multimodal DenseNet fusion (MDNF) model that was trained on two-dimensional (2D) EEG data images, leveraging advanced feature extraction techniques. …”
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Leveraging Multilingual Transformer for Multiclass Sentiment Analysis in Code-Mixed Data of Low-Resource Languages by Muhammad Kashif Nazir, Cm Nadeem Faisal, Muhammad Asif Habib, Haseeb Ahmad

“…This study aims to present a novel approach for multiclass sentiment analysis of low-resource, code-mixed datasets using multilingual transformers. …”
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Hybrid Deep Learning Models for Predicting Student Academic Performance by Kuburat Oyeranti Adefemi, Murimo Bethel Mutanga, Vikash Jugoo

“…Educational data mining (EDM) is instrumental in the early detection of students at risk of academic underperformance, enabling timely and targeted interventions. …”
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Developing a GIS Model for Identifying Bear Corridors with Open-Source Data: The Romanian Context by Sanda Roșca, Alexandru Chira, Iuliu Vescan, Ștefan Bilașco, Ioan Fodorean, András-István Barta, Vasile Ceuca, Paul Sestraș

“…The fragmentation of the bears’ habitat is the main cause of conflict occurrences between bears and the human population, which have occurred increasingly often in recent years. The main aim of this study is the ecological diagnosis of lands populated with bears in Romania to identify the highest quality habitats within the hunting grounds and to identify possible ecological corridors aimed at preserving the connectivity between them, using GIS spatial analysis techniques and taking into account the ecological conditions needed for the brown bear to survive. …”
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Evaluating suitability of regression models in small data regimes using concrete with recycled copper tailings as a case study by Ahed Habib, Samer Barakat, Samir Dirar, Salah Al-Toubat, Zaid A. Al-Sadoon

“…This study investigates the performance of different regression models combined with various data preprocessing techniques in contexts where data is limited. …”

A digital intelligence visualization health monitoring device for Alzheimer’s disease patients based on WBAN technology by Minghong Zheng, Yi Wu, Changqing Weng

“…In the WBAN monitoring visualization group, we innovated a digital kit called AD-Cloud, which consists of a flexible wearable data collection and transmission device with a star topology, a progressive convolutional neural framework for remote data visualization with high arithmetic power, and an interactive mobile application. …”
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