Smart Data-Enabled Conservation and Knowledge Generation for Architectural Heritage System by Ziyuan Rao, Guoguang Wang

“…In architectural heritage conservation, fragmented data practices and heterogeneous formats hinder knowledge extraction, limiting the translation of raw data into actionable conservation insights. …”
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Evaluation of Data Extracted from Floor Plans for Apartment Complex Remodeling by Dongik Shin, Hyeongmin Ryu, Jeeyeop Kim, Jinyoung Kim

“…The proposed method can continuously accumulate data from domestic apartment house remodeling projects and accelerate the process by shortening the time required for final decision-making in future remodeling projects.…”
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The Role of Digitalization in Data-Driven Decision Making in Supply Chain Management by I. G. Kamenev, D. A. Porohovnik

“…However, new systems that provide for the processing, storage, and analysis of data, as well as the visualization of this information and the results of its analysis, make it possible to link strategic goal-setting, KPIs, and supply chain resilience management directly with data flows about functional business processes, creating a “digital twin” of the enterprise. …”
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The openBIS Digital Platform for Instrumentation and Data Workflow in the Analytical Laboratory by Yousuf Hemani, Kilian Koch, Oscar Mendo-Diaz, Anusch Bachhofner, Simone Baffelli, Davide Bleiner

“…Two laboratory projects as case studies are described, consisting of a data pipeline and a complex dashboard for data collection, visualization and interaction. …”
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A Cognition Knowledge Representation Model Based on Multidimensional Heterogeneous Data by Dong Zhong, Yi-An Zhu, Lanqing Wang, Junhua Duan, Jiaxuan He

“…Aiming at the problem that the data sources of the knowledge base for constructing the cognitive knowledge graph are wide and heterogeneous, and there are entity semantic differences and knowledge system differences among different data sources, a multimodal entity semantic fusion model based on vector features and a system fusion framework based on HowNet are designed, and the environment description information such as object semantics, attributes, relations, spatial location, and context acquired by industrial robots and their own state information are unified and standardized. …”
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Leveraging the Potential of Novel Data in Power Line Communication of Electricity Grids by Christoph Balada, Max Bondorf, Sheraz Ahmed, Markus Zdrallek, Andreas Dengel

“…In addition, we present different use cases in asset management, grid state visualization, forecasting, predictive maintenance, and novelty detection to highlight the benefits of these types of data. …”
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Moisture prediction in chicken litter using hyperspectral data and machine learning by Ahmad Tulsi, Abdul Momin, Victoria Ayres

“…We employed two modeling approaches: Partial Least Squares Regression (PLSR) and Extreme Gradient Boosting (XGBoost), to assess performance using raw spectral data and under three preprocessing techniques designed to enhance data quality: Moving Average (MA), Multiplicative Scatter Correction (MSC), and Standard Normal Variate (SNV). …”
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Big IoT Data Analytics: Architecture, Opportunities, and Open Research Challenges by Mohsen Marjani, Fariza Nasaruddin, Abdullah Gani, Ahmad Karim, Ibrahim Abaker Targio Hashem, Aisha Siddiqa, Ibrar Yaqoob

“…Finally, open research challenges, such as privacy, big data mining, visualization, and integration, are presented as future research directions.…”
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XAI for Point Cloud Data Using Perturbations Based on Meaningful Segmentation by Raju Ningappa Mulawade, Christoph Garth, Alexander Wiebel

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scFocus: Detecting branching probabilities in single-cell data with SAC by Chunlin Chen, Zeyu Fu, Jiajia Yang, Huaqing Chen, Jiabao Huang, Shitian Qin, Chuhuai Wang, Xiaoqian Hu

“…Finally, an online analysis tool based on scFocus was developed, helping researchers and clinicians in the process and visualization of single-cell RNA sequencing data as well as the interpretation of these data through branch probabilities in a streamlined and intuitive way.…”
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INKA, an integrative data analysis pipeline for phosphoproteomic inference of active kinases by Robin Beekhof, Carolien van Alphen, Alex A Henneman, Jaco C Knol, Thang V Pham, Frank Rolfs, Mariette Labots, Evan Henneberry, Tessa YS Le Large, Richard R de Haas, Sander R Piersma, Valentina Vurchio, Andrea Bertotti, Livio Trusolino, Henk MW Verheul, Connie R Jimenez

“…This multipronged, stringent analysis enables ranking of kinase activity and visualization of kinase–substrate networks in a single biological sample. …”
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A guide to the BRAIN Initiative Cell Census Network data ecosystem. by Michael Hawrylycz, Maryann E Martone, Giorgio A Ascoli, Jan G Bjaalie, Hong-Wei Dong, Satrajit S Ghosh, Jesse Gillis, Ronna Hertzano, David R Haynor, Patrick R Hof, Yongsoo Kim, Ed Lein, Yufeng Liu, Jeremy A Miller, Partha P Mitra, Eran Mukamel, Lydia Ng, David Osumi-Sutherland, Hanchuan Peng, Patrick L Ray, Raymond Sanchez, Aviv Regev, Alex Ropelewski, Richard H Scheuermann, Shawn Zheng Kai Tan, Carol L Thompson, Timothy Tickle, Hagen Tilgner, Merina Varghese, Brock Wester, Owen White, Hongkui Zeng, Brian Aevermann, David Allemang, Seth Ament, Thomas L Athey, Cody Baker, Katherine S Baker, Pamela M Baker, Anita Bandrowski, Samik Banerjee, Prajal Bishwakarma, Ambrose Carr, Min Chen, Roni Choudhury, Jonah Cool, Heather Creasy, Florence D'Orazi, Kylee Degatano, Benjamin Dichter, Song-Lin Ding, Tim Dolbeare, Joseph R Ecker, Rongxin Fang, Jean-Christophe Fillion-Robin, Timothy P Fliss, James Gee, Tom Gillespie, Nathan Gouwens, Guo-Qiang Zhang, Yaroslav O Halchenko, Nomi L Harris, Brian R Herb, Houri Hintiryan, Gregory Hood, Sam Horvath, Bingxing Huo, Dorota Jarecka, Shengdian Jiang, Farzaneh Khajouei, Elizabeth A Kiernan, Huseyin Kir, Lauren Kruse, Changkyu Lee, Boudewijn Lelieveldt, Yang Li, Hanqing Liu, Lijuan Liu, Anup Markuhar, James Mathews, Kaylee L Mathews, Chris Mezias, Michael I Miller, Tyler Mollenkopf, Shoaib Mufti, Christopher J Mungall, Joshua Orvis, Maja A Puchades, Lei Qu, Joseph P Receveur, Bing Ren, Nathan Sjoquist, Brian Staats, Daniel Tward, Cindy T J van Velthoven, Quanxin Wang, Fangming Xie, Hua Xu, Zizhen Yao, Zhixi Yun, Yun Renee Zhang, W Jim Zheng, Brian Zingg

“…We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. …”
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Digital ecosystem for FAIR time series data management in environmental system science by J. Bumberger, M. Abbrent, N. Brinckmann, J. Hemmen, R. Kunkel, C. Lorenz, P. Lünenschloss, B. Palm, T. Schnicke, C. Schulz, H. van der Schaaf, D. Schäfer

“…The ecosystem comprises three core components: the Sensor Management System (SMS) for detailed metadata registration and management; time.IO, a platform for efficient time series data storage, transfer, and real-time visualization; and the System for Automated Quality Control (SaQC), which ensures data integrity through real-time analysis and quality assurance. …”
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Rear-End Crash Risk Analysis considering Drivers’ Visual Perception and Traffic Flow Uncertainty: A Hierarchical Hybrid Bayesian Network Approach by Naikan Ding, Linsheng Lu, Nisha Jiao

“…This study investigated the association between traffic flow uncertainty, drivers’ visual perception, car-following behavior, roadway and vehicular characteristics, and rear-end crash risk variation and compared the crash risk variation prediction with and without specific flow-level data. …”
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Post hoc analysis of a randomized placebo-controlled trial suggests potential visual benefits of branched-chain amino acids in retinitis pigmentosa by Tomoko Hasegawa, Hanako Ohashi Ikeda, Hiroyasu Abe, Yoko Amino, Takayuki Nakagawa, Harue Tada, Manabu Miyata, Akio Oishi, Satoshi Morita, Akitaka Tsujikawa

“…The eligibility screening visual-field test could be affected by psychological factors, such as patients’ concentration or motivation, leading to better-than-usual screening test results and making them less appropriate as baseline data.…”
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Visual Perception of Environmental Elements Analysis in Historical District Based on Eye-Tracking and Semi-Structured Interview: A Case Study in Xining, Taishan by Xing Jiang, Xinxiang Wu, Fangting Chen, Zonghan Chen, Ziang Li

“…ErgoLAB was used to generate eye-tracking metrics and heat maps based on eye movement data, and ROST-CM6 software was used to generate word frequency and emotional degree data for interview text. …”
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A Time-Varying Multivariate Noncentral Contaminated Normal Copula Model and Its Application to the Visualized Dependence Analysis of Hong Kong Stock Markets by Zhenyu Xiao, Jie Wang, Teng Yuan Cheng, Kuiran Shi

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Prevalence and associated factors of visual impairment among preschool children in selected kindergarten schools in Addis Abeba, Ethiopia,2023 cross-sectional study by Kirubel Asmelash, Hanna Gebre, Girum W. Gebriel Gesese, Yordanos Girma, Hiwot Berhanu Andualem

“…A multistage sampling technique was used to select the study participants. Data were collected by trained data collectors via a structured questionnaire and physical examination. …”
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Penerapan Model Pembelajaran Bahasa Arab Berbasis SAVI (Somatis, Auditori, Visual, Intelektual) dalam Meningkatkan Hasil Belajar pada Peserta Didik by Koderi Koderi

“…This study is aimed at acquiring  obtaining empirical data "The influence of Arabic language-based learning model SAVI (somatic visual auditory intellectual) in improving the learning outcomes of students of class VIII in MTs Negeri 2 Bandar Lampung in 2016/2017". …”
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Efficacy of anti-VEGF and laser photocoagulation in the treatment of visual impairment due to diabetic macular edema: a systematic review and network meta-analysis. by Stephane Régnier, William Malcolm, Felicity Allen, Jonathan Wright, Vladimir Bezlyak

“…<h4>Objective</h4>Compare the efficacy of ranibizumab, aflibercept, laser, and sham in the first-line treatment of diabetic macular edema (DME) to inform technology assessments such as those conducted by the UK National Institute for Health and Care Excellence (NICE).<h4>Data sources</h4>MEDLINE, Embase, Cochrane Library, congress abstracts, ClinicalTrials.gov registry and Novartis data on file.…”
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