Advancement of a diagnostic prediction model for spatiotemporal calibration of earth observation data: a case study on projecting forest net primary production in the mid-latitude... by Eunbeen Park, Hyun-Woo Jo, Gregory Scott Biging, Jong Ahn Chun, Seong Woo Jeon, Yowhan Son, Florian Kraxner, Woo-Kyun Lee

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Exploring CycleGAN Technique for Improved Plant Disease Detection and Analysis by Ouyang Luyi

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A Comprehensive Analysis of the Security of ML Integrated CPS as Autonomous Vehicles by Kesava reddy, Kumudham R

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Reasons for the increase in cyber attacks: analysis of technical and non-technical factors by A. V. Vasilyev

“…This article presents an analysis of both technical and non-technical factors contributing to the growth in volume and diversity of cyber attacks. …”
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CEPHALOMETRIC ANALYSIS BASED ON CONE-BEAM COMPUTER TOMOGRAPHY (LITERATURE REVIEW) by Ye.Ye. Vyzhenko

“…Inaccuracies in the identification of landmarks on two-dimensional images can lead to measurement errors. Threedimensional analysis based on cone-beam computed tomography expands diagnostic possibilities in clinical practice. …”
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Analysis of Leafy Vegetable Nitrate Using a Modified Spectrometric Method by Tzu-Hsien Yu, Shuo-Ping Hsieh, Chien-Ming Su, Feng-Jung Huang, Chien-Che Hung, Lih-Ming Yiin

“…The nitrate contents ranged from 800 to 4,300 μg/g, with bok coy, celery, and pak choi being the highest. Data derived from spectrometry and HPLC were close to each other with most relative errors being within ±10% and were highly correlated with an R square value of 0.969. …”
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Polyomaviruses and the risk of breast cancer: a systematic review and meta-analysis by Tahoora Mousavi, Fatemeh Shokoohy, Mahmood Moosazadeh

“…The quality of each article was assessed using the Newcastle-Ottawa Scale (NOS) checklist. Data analysis was performed using STATA software, and standard errors of prevalence were calculated using the binomial distribution formula. …”
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Design and performance analysis of portable solar powered cooler for vaccine storage by Vicent Marwa, Thomas Kivevele, Baraka Kichonge, Juma Selemani

“…Moreover, the current model reaches a temperature of −12°C in 195 min and it has energy efficient with a COP of 4.5. Statistical analysis further confirms the reliability of the simulation results, with root mean square and mean absolute percentage errors of 6.587 and 24.2%, respectively. …”
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Savi’s pipistrelle (Hypsugo savii) in Ukraine: analysis of records and evidence of expansion by Igor Polischuk, Igor Zagorodniuk

“…The records belong to the period of intensive ultrasonic monitoring data of bat fauna in 2017–2018. All records have a number of similarities described in the article, in particular: a) belonging to the southern territories, b) predominance of records in spring or autumn, c) virtually all records were made in urban landscapes. …”
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Analysis of Common Causes of Out-of-Specification Results in the Test for Depressor Substances by TONG Xiyang, QUE Changtian, ZHANG Feng, ZHAO Lu, WANG Hongping

“…Based on a review of the literature and practical work experience, this article analyzes the causes of OOS in the test for depressor substances from the following five aspects: (1) an analysis of the impact of drug standards on OOS from three aspects: standard determination, standard content, and standard drafting; (2) personnel qualifications, including pre-employment training, compliance with standard operating procedures during experimental operations, and the ability to operate instruments; (3) factors related to cats, used as experimental animals in the test for depressor substances, including physiological characteristics, genetic background, and abnormal conditions during the experiment; (4) reference substances, reagents, test samples, and key instruments such as the multi-channel physiological signal instrument; (5) experimental operations including animal anesthesia, arterial and venous catheterization, drug administration, and data processing. …”
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Pengembangan Auto-AI Model Generatif Analisis Kompleksitas Waktu Algoritma Untuk Data Multi-Sensor IoT Pada Node-RED Menggunakan Extreme Learning Machine by Imam Cholissodin, Dahnial Syauqy, Dwi Ady Firmanda, Ibrahim Aji, Edy Rahman, Syazwandy Harahap, Fernando Septino

“…Based on the tests that have been carried out, the difference in value between the actual data and the prediction results in the size of the MAPE average value of 11.90%, which shows a fairly small error value. …”
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Comparative Analysis of Linear Regression and Neural Network Algorithms for Stock Price Prediction by Eldrianto Christian Wibowo, Ariya Dwika Cahyono

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Reliability analysis in curriculum development for social science education driven by machine learning by Rui Mao

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A Sub-Hourly Precipitation Dataset from a Pluviographic Network in Central Chile by Claudia Sangüesa, Alfredo Ibañez, Roberto Pizarro, Cristian Vidal-Silva, Pablo Garcia-Chevesich, Romina Mendoza, Cristóbal Toledo, Juan Pino, Rodrigo Paredes, Ben Ingram

“…Each station’s data was subjected to quality control procedures, including manual validation and correction of digitization errors to ensure data integrity. …”
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The FRIENDS preventive programme for reducing anxiety symptoms in children and adolescents: A systematic review and meta‐analysis by Trine Filges, Geir Smedslund, Tine Eriksen, Kirsten Birkefoss, Malene Wallach Kildemoes

“…Six studies did not report data that enabled calculation of effect sizes and standard errors. …”
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New insight into viscosity prediction of imidazolium-based ionic liquids and their mixtures with machine learning models by Amir Hossein Sheikhshoaei, Ali Sanati

“…Outlier detection using the Leverage method indicated that 95.11% of pure IL viscosity data and 94.92% of mixed ILs viscosity data are statistically valid.…”
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Cereal and Rapeseed Yield Forecast in Poland at Regional Level Using Machine Learning and Classical Statistical Models by Edyta Okupska, Dariusz Gozdowski, Rafał Pudełko, Elżbieta Wójcik-Gront

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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

“…The resulting model is evaluated using prediction error metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE). …”
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Transforming oil market analysis: A novel GAN + LSTM predictive framework by Prity Kumari, G.Y. Chandan, Satish Kumar M

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Study on Calculation of Cross-section Area of River Based on Analysis Method of Mid-point Distance Section by DANG Xicheng, LUO Yi, WANG Haiyan, LI Rong

“…The cross-section area is one of the key factors in flow measurement by velocity area method,and its calculation accuracy is directly related to the accuracy of flow measurement.Due to the complexity and diversity of the river section,the existing software algorithm cannot accurately judge the real position of the river flow through the large section data,resulting in the extraction error of the range of the cross section and the vertical depth.Therefore,with computer programming technology,this paper puts forward the analysis method of river mid-point distance section for identifying the position of river flow and judging the type of section,such as single section and compound section,extracting the water's edge and vertical line,and calculating the area.The application shows that the software can accurately analyze the river flow position under different hydraulic conditions by this method,and calculate the river cross-section area,achieving the purpose of algorithm design.This method can be widely used in automatic hydrological detection equipment or hydrological analysis software to improve the analysis ability of the equipment or software for cross-section flow area of river.…”
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