Predicting Stock Market by Sentiment Analysis and Deep Learning by Süreyya, Özögür Akyüz, Pınar, Karadayı Ataş, Aymane Benkhaldoun

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Advancements in Onboard Processing of Synthetic Aperture Radar (SAR) Data: Enhancing Efficiency and Real-Time Capabilities by Laura Parra Garcia, Gianluca Furano, Max Ghiglione, Valentina Zancan, Ernesto Imbembo, Christos Ilioudis, Carmine Clemente, Paolo Trucco

“…By leveraging these techniques, SAR systems can achieve improved operational efficiency, reduced data latency, and enhanced real-time capabilities. …”
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A Bayesian Network Approach to Predicting Severity Status in Nuclear Reactor Accidents with Resilience to Missing Data by Kaiyu Li, Ling Chen, Xinxin Cai, Cai Xu, Yuncheng Lu, Shengfeng Luo, Wenlin Wang, Lizhi Jiang, Guohua Wu

“…With the integration of simulation data and physical knowledge, the BN enables dynamic inference and remains robust under missing-data conditions—common in real-time energy monitoring. …”
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Fatores associados ao trabalho de operadores de checkout: investigação das queixas musculoesqueléticas Factors related to the work of checkout operators: research musculoskeletal c... by Clarissa Stefani Teixeira, Maricel Karina López Torres, Antonio Renato Pereira Moro, Eugenio Andrés Díaz Merino

“…For data analysis it used Spearman's correlation to test for associations, chi-square and Fisher's Exact Test to test the homogeneity of complaints related to socioeconomic variables, health and working conditions. …”
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The Influence of Net Profit Margin, Operating Cash Flow, Trade Volume, and Intellectual Capital on Firm Value in Infrastructure Sector Companies Listed on the Indonesian Stock Exch... by Dinda Amalia Putri, Lina Budiarti

“…The approach used in this study is quantitative with secondary data obtained from annual financial reports. The population consists of 69 infrastructure companies listed on the IDX, with 33 companies selected through purposive sampling. …”
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The Approach of Induced Generalized Neutrosophic Cubic Shapley Choquet Integral Aggregation Operators via the CODAS Method to Solve Distance-Based Multicriteria Decision-Making Pro... by Majid Khan, Muhammad Gulistan, Mohammed M. Al-Shamiri

“…Motivated by these characteristics NCSCI, we defined two aggregation operators’ induced-generalized neutrosophic cubic Shapley–Choquet integral arithmetic (IGNCSCIA) and operators’ induced-generalized neutrosophic cubic Shapley–Choquet integral geometric (IGNCSCIG) operators. …”
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Energy consumption evaluation of soil tillage operation using non-linear multibody tractor and plough models implemented in real-time simulator for different soils and speeds by Michele Vignati, Federico Cheli, Federico Biraghi, Marco E. Pezzola, Claudio Maroni

“…The model outputs vehicle dynamics information and ploughing operation data, allowing for operator inputs or simulated inputs. …”
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Rethinking global health through a better understanding of power, privilege, and influence – the narrative and voices of those who operate in the infectious diseases global health... by Prof Sipho Dlamini, Ms Muneera Rasheed, Dr Frank Kronenberg, Professor Esmita Charani

“…Results: To date 15 interviews have been conducted with participants predominantly from Southern Africa. Iterative analysis has demonstrated that data saturation is being reached. …”
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Safety Prejudging Method for Power Transformer Based on Multi-Prediction Model Fusion by Dianyang LI, Yujie ZHANG, Shanyuan WANG, Jian FENG, Hongzhe WANG, Ling QIN

“…The conventional analytical measures have not considered integrating multi-source heterogeneous data into grid equipment fault cause analysis, and the small sample-based unitary algorithm cannot well deal with diagnosis of multi-type fault equipment. …”
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Generative Adversarial Networks (GANs) for Image Augmentation in Farming: A Review by Zahid Ur Rahman, Mohd Shahrimie Mohd Asaari, Haidi Ibrahim, Intan Sorfina Zainal Abidin, Mohamad Khairi Ishak

“…Enhancing model performance in agricultural image analysis faces challenges due to limited datasets, biological variability, and uncontrolled environments. …”
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Privacy protection scheme of DBSCAN clustering based on homomorphic encryption by Chunfu JIA, Ruiqi LI, Yafei WANG

“…In order to reduce the risk of data privacy leakage in the process of outsourced clustering, a privacy protection scheme of DBSCAN clustering based on homomorphic encryption was proposed.In order to encrypt the float data in the actual scene, three data preprocessing methods for different data accuracy were given, and a policy for choosing a proper data preprocessing method based on data characteristics, accuracy and computational cost was also proposed.For the ciphertext comparison operation that was not supported by homomorphic encryption, a protocol between the client and the cloud server was designed to realize the function of ciphertext comparison.Theoretical analysis and experimental results show that the proposed scheme can ensure the security of data privacy, and has a higher clustering accuracy rate and lower time overhead.…”
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Privacy protection scheme of DBSCAN clustering based on homomorphic encryption by Chunfu JIA, Ruiqi LI, Yafei WANG

“…In order to reduce the risk of data privacy leakage in the process of outsourced clustering, a privacy protection scheme of DBSCAN clustering based on homomorphic encryption was proposed.In order to encrypt the float data in the actual scene, three data preprocessing methods for different data accuracy were given, and a policy for choosing a proper data preprocessing method based on data characteristics, accuracy and computational cost was also proposed.For the ciphertext comparison operation that was not supported by homomorphic encryption, a protocol between the client and the cloud server was designed to realize the function of ciphertext comparison.Theoretical analysis and experimental results show that the proposed scheme can ensure the security of data privacy, and has a higher clustering accuracy rate and lower time overhead.…”
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Prediction for Coastal Wind Speed Based on Improved Variational Mode Decomposition and Recurrent Neural Network by Muyuan Du, Zhimeng Zhang, Chunning Ji

“…Accurate and comprehensive wind speed forecasting is crucial for improving efficiency in offshore wind power operation systems in coastal regions. However, raw wind speed data often suffer from noise and missing values, which can undermine the prediction performance. …”
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Exploring data quality and use of the routine health information system in Ethiopia: a mixed-methods study by Joanna Schellenberg, Della Berhanu, Lars Åke Persson, Misrak Getnet, Joanna Busza, Tsion Tsegaye, Kalkidan Mekete, Magdelawit Mengesha, Abyot Adane, Tewabe M Adege, Mesoud M Ahmed, Habtamu A Anteneh, Emiamrew S Ayalew, Netsanet Berhanu, Tesfahun Bishaw, Eshetu Cherinet, Mamo Dereje, Tsega H Desta, Abera Dibabe, Heven S Firew, Freweini Gebrehiwot, Etenesh Gebreyohannes, Zenebech Gella, Addis Girma, Zuriash Halefom, Sorsa F Jama, Annika Janson, Binyam Kemal, Abiy Kiflom, Yidnekachew D Mazengiya, Meresha W Nega, Israel A Otoro, Tefera Taddele, Gulilat Tefera, Admasu Teketel, Miraf Tesfaye, Kidist Woldesenbet, Yakob Wondarad, Zemzem M Yusuf, Kidist Zealiyas, Mebratom H Zeweli, Seblewengel Lemma

“…The study was nested within a 2-year programme of the Operational Research and Coaching for government Analysts.Participants We visited 45 health posts, 1 district hospital, 16 health centres and 8 district offices for analysis of routine RHIS data and interviewed 117 staff members for the qualitative assessment.Outcome measures We assessed availability of source documents, completeness, timeliness and accuracy of reporting of routine data, and explored data quality and use perceptions.Results There was variable quality of both indicator and data element. …”
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Research and Application of Data-driven Forecast Method for Water Level Increment of Small and Medium-sized Rivers by DING Wu, LIN Hanxiong, WANG Hangang, ZHANG Wei, YANG Bin

“…Focusing on the forecast of flash flood disasters in small and medium-sized rivers,this paper adopts three data-driven forecast models to forecast the maximum water level increment.With Paitan Town,Zengcheng District,Guangzhou City as the research area,the mathematical modeling and accuracy evaluation of the three models are carried out.The analysis shows that the forecast accuracy of machine learning is the highest,but the forecast results are not interpretable.The forecast accuracy of the similarity analysis model is medium,and the prediction results have good cognition and interpretability.The overall prediction accuracy of the “rainfall-water level increment” relationship model is the lowest,but its operation is simple.The calculation of the similarity analysis model and machine learning model is relatively complex,relying on computer-aided calculation,and the results of the “rainfall-water level increment” relationship model can be plotted as graphs.Considering the forecast accuracy and convenience,multiple models such as the machine learning model and similarity analysis model can be applied for the forecast to improve the forecast accuracy if there is support from auxiliary equipment such as computers and mobile phone applications.Without support from computers and other basic equipment,the “rainfall-water level increment” relationship model can provide a convenient forecast method for flash flood forecast and early warning in small and medium-sized rivers.…”
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Analysis of cabbage production in Russia by O. A. Razin, T. N. Surikhina

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On Joint Progressively Censored Gumbel Type-II Distributions: (Non-) Bayesian Estimation with an Application to Physical Data by Mustafa M. Hasaballah, Mahmoud E. Bakr, Oluwafemi Samson Balogun, Arwa M. Alshangiti

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Integrating multi-dimensional data to reveal the mechanisms and molecular targets of baikening granules for treatment of pediatric influenza by Zhaoyuan Gong, Qianzi Che, Mingzhi Hu, Tian Song, Lin Chen, Haili Zhang, Ning Liang, Huizhen Li, Guozhen Zhao, Lijiao Yan, Xuefei Zhang, Bin Liu, Jing Guo, Nannan Shi

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Barriers to the Adoption of Big Data Analytics in Saudi Arabia’s Manufacturing Sector: An Interpretive Structural Modeling Approach by Almuhannad S. Alorfi, Naif Alsaadi

“…Big data analytics has the potential to greatly improve the operations of manufacturing industries, aid in decision making, and foster innovation. …”
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Machine learning for epithelial ovarian cancer platinum resistance recurrence identification using routine clinical data by Li-Rong Yang, Mei Yang, Liu-Lin Chen, Yong-Lin Shen, Yuan He, Zong-Ting Meng, Wan-Qi Wang, Feng Li, Zhi-Jin Liu, Lin-Hui Li, Yu-Feng Wang, Xin-Lei Luo

“…We used laboratory and clinical data to create models based on machine learning for EOC platinum resistance recurrence identification.MethodsThis study was designed as a retrospective cohort analysis. …”
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