Data acquisition varies by bat phonic group for 2 types of bat detectors when weatherproofed and paired in field settings by Zachary D. E. Kaiser, Joy M. O'Keefe

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ALGORITHM FOR complex SMOKE AND FLAME detection based on video surveillance systems data analysis by R. P. Bohush, D. A. Tychko

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Design of home fire detection system based on wireless multi-sensor data fusion by Wenbin CHENG, Lei DU, Yiyi LIU

“…Aiming at the shortcomings of false alarm and leakage alarm in the existing fire detection system and the complicated wiring,high cost and poor flexibility of the traditional wired fire detection system,a set of home fire detection system based on wireless multi-sensor data fusion was designed,to detect the fire safety hazards caused by kitchen equipment aging,electrical wiring aging or electrical equipment aging.The design of multi-sensor data fusion algorithm,fire detection system hardware framework and software implementation were described in detail.The simulation results show that the scheme has the characteristics of high accuracy and flexibility.…”
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Outlier detection in ground-measured solar resource data using statistical classification models by Chantelle Clohessy, Warren Brettenny, Waldo Abrahams

“…This study proposes the use of simulated outliers added to synthetic data to train and compare the effectiveness of traditional outlier detection methods and several statistical learning methods, including NN, naïve Bayes, support vector machines and advanced tree-based models for the purpose of outlier detection in this field. …”
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Application of the Genetic Algorithm in the Network Intrusion Detection System Using NSL-KDD Data by Naglaa Ibrahim, Hana Usman

“…For rules generation NSL-KDD Data Set is used which include, KDDTrain and KDDTest, 125973 and 22544 records respectively, each record  consists of 41 features and one class attribute for specifying   normal and abnormal connection (complete train and test data are used), In order to get rid of redundancy and inappropriate features Principal  Component Analysis (PCA) is used for selecting (5)  features. …”
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The Choice of Training Data and the Generalizability of Machine Learning Models for Network Intrusion Detection Systems by Marcin Iwanowski, Dominik Olszewski, Waldemar Graniszewski, Jacek Krupski, Franciszek Pelc

“…We propose a procedure consisting of cross-validation using various sets sharing some standard traffic classes combined with the t-SNE visualization. …”
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Substation Inspection Safety Risk Identification Based on Synthetic Data and Spatiotemporal Action Detection by Chengcheng Liu, Weihua Zhang, Weijin Xu, Bo Lu, Weijie Li, Xuefeng Zhao

“…Model training is conducted using three datasets: a real dataset, a synthetic dataset generated via a VWP, and a mixed dataset comprising both real and synthetic data. Finally, using the model trained on the real dataset as a baseline, the evaluation results on the test set shows that the use of synthetic datasets in training improves the model’s average precision by up to 10.7%, with a maximum average precision of 73.61%. …”
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Self-Healing Databases for Emergency Response Logistics in Remote and Infrastructure-Poor Settings by James McGarvey, Martha R. Grabowski, Buddy Custard, Steven Gabelein

“…<i>Conclusions:</i> The results show significant improvements in data cleaning and analysis, and for emergency response logistics data, planning, and analysis, along with future research and research needs in remote and infrastructure-poor settings.…”
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Depression detection based on dual path DCGAN data generation and classification-regression network by LU Jingxue, LI Hongyan, ZHENG Ruichao, QIN Ruizhen

“…The existing research on voice-based depression detection has many problems, such as complicated feature extraction, single data expansion and uncontrollable prediction bias in regression prediction. …”
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MeStanG—Resource for High-Throughput Sequencing Standard Data Sets Generation for Bioinformatic Methods Evaluation and Validation by Daniel Ramos Lopez, Francisco J. Flores, Andres S. Espindola

“…We propose a MeStanG as a resource for generating HTS Nanopore data sets to evaluate present and emerging bioinformatics pipelines. …”
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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection by Tomasz Kocejko

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ElectroCom61: A multiclass dataset for detection of electronic componentsMendeley Data by Md. Faiyaz Abdullah Sayeedi, Anas Mohammad Ishfaqul Muktadir Osmani, Taimur Rahman, Jannatul Ferdous Deepti, Raiyan Rahman, Salekul Islam

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Fusion of Multi-Task Neurophysiological Data to Enhance the Detection of Attention- Deficit/Hyperactivity Disorder by Kai-Feng Zhang, Shih-Ching Yeh, Eric Hsiao-Kuang Wu, Xiu Xu, Ho-Jung Tsai, Chun-Chuan Chen

“…The application of artificial intelligence and multimodal neurophysiological data in clinical settings sets a precedent for digital health, paving the way for future advancements in the field.…”
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Statistical Data-Generative Machine Learning-Based Credit Card Fraud Detection Systems by Xiaomei Feng, Song-Kyoo Kim

“…This study highlights the importance of robust data handling techniques in developing effective fraud detection systems, setting the stage for future research on combining different datasets and improving predictive accuracy in the financial sector.…”
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Anomaly Detection for PV Modules Using Multi-Modal Data Fusion in Aerial Inspections by Lourenco Sousa Pinho, Tiago Daniel Sousa, Celso D. Pereira, Andry M. Pinto

“…This paper contributes three major advancements to PV defect detection: a robust, standardized dataset built following IEC TS 62446-3 specifications with annotations from a real PV power plant, a novel multi-spectral approach that leverages early fusion of visual and thermal data captured via an AAV, and benchmark performance metrics for defect detection using state-of-the-art AI models. …”
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Validation of a Novel Data-Driven Algorithm to Detect Atypical Prescriptions in Radiation Therapy by Connor Thropp, MS, Jaroslaw Hepel, MD, Timothy Leech, Eric E. Klein, PhD, Qiongge Li, PhD

“…In that study, prototype analysis was conducted within a single institution with a single treatment site. The present study sets out to validate the robustness of the model by applying the model to multiple disease sites using a different institution’s data. …”
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Detection of Irrigated and Non-Irrigated Soybeans Using Hyperspectral Data in Machine-Learning Models by Izabela Cristina de Oliveira, Ricardo Gava, Dthenifer Cordeiro Santana, Ana Carina da Silva Cândido Seron, Larissa Pereira Ribeiro Teodoro, Mayara Favero Cotrim, Regimar Garcia dos Santos, Rita de Cássia Félix Alvarez, Carlos Antonio da Silva Junior, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro

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Electrophysiological Insights in Exergaming—Electroencephalography Data Recording and Movement Artifact Detection: Systematic Review by Carolina Rico-Olarte, Diego M Lopez, Bjoern M Eskofier, Linda Becker

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Investigation of the Internal Structure of Hard-to-Reach Objects Using a Hybrid Algorithm on the Example of Walls by Rafał Brociek, Józef Szczotka, Mariusz Pleszczyński, Francesca Nanni, Christian Napoli

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Enhanced schizophrenia detection using multichannel EEG and CAOA-RST-based feature selection by Mohammad Abrar, Abdu Salam, Ahmed Albugmi, Fahad Al-otaibi, Farhan Amin, Isabel de la Torre, Thania Candelaria Chio Montero, Perla Araceli Arroyo Gala

“…Thus, our research introduces a novel approach by integrating the multichannel EGG, Crossover-Boosted Archimedes Optimization Algorithm (CAOA), and Rough Set Theory (RST) for schizophrenia detection. It is a four-stage model. …”
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