Protecting Location Privacy for Outsourced Spatial Data in Cloud Storage by Feng Tian, Xiaolin Gui, Jian An, Pan Yang, Jianqiang Zhao, Xuejun Zhang

“…As cloud computing services and location-aware devices are fully developed, a large amount of spatial data needs to be outsourced to the cloud storage provider, so the research on privacy protection for outsourced spatial data gets increasing attention from academia and industry. …”
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Enhancing Real Estate Data Analytics Education with Digital Badges by Jeffrey G. Robert, Marc R. Zaldivar, Helen Ajao, Zhenhuan Yang

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Prefetching Scheme for Massive Spatiotemporal Data in a Smart City by Lian Xiong, Zhengquan Xu, Hao Wang, Shan Jia, Li Zhu

“…It maps the history of user access requests to the spatiotemporal attribute domain by analyzing the characteristics of spatiotemporal data in a smart city. According to the spatial locality and time stationarity of user access, correlation analysis is performed and variation rules are identified for the history of user access requests. …”
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Spatial integration of multi-omics single-cell data with SIMO by Penghui Yang, Kaiyu Jin, Yue Yao, Lijun Jin, Xin Shao, Chengyu Li, Xiaoyan Lu, Xiaohui Fan

“…Through comprehensive analysis of real-world data, SIMO uncovers multimodal spatial heterogeneity, offering deeper insights into the spatial organization and regulation of biological molecules. …”
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Parallel graph-based anomaly detection technique for sequential data by Ahmed Farag, Hatem Abdelkader, Rashed Salem

“…In this paper, a parallel outlier detection technique is developed to detect the outliers in the sequential data. …”
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Fair payments for privacy-preserving aggregation of mobile crowdsensing data by Mallikarjun Reddy Dorsala, V.N. Sastry, Sudhakar Chapram

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The application of blockchain technology in data trading: a systematic review by Wei Xiong, Huaibin Shao, Hong Ge

“…In the era of exponential data growth, the imperative to establish secure and efficient data trading mechanisms has become paramount. …”
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The usefulness of big data in creating innovations. The example of Google Trends by Joanna Hernik

“…As a consequence, various types of data can be used by enterprises for their development but they often do not take advantage of this opportunity. …”
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Contemporary Recommendation Systems on Big Data and Their Applications: A Survey by Ziyuan Xia, Anchen Sun, Jingyi Xu, Yuanzhe Peng, Rui Ma, Minghui Cheng

“…The review spans historical developments to cutting-edge innovations, with a focus on big data analytics applications, state-of-the-art recommendation models, and evaluation using prominent datasets like MovieLens, Amazon Reviews, Netflix Prize, Last.fm, and Yelp. …”
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Network‐assisted protein identification and data interpretation in shotgun proteomics by Jing Li, Lisa J Zimmerman, Byung‐Hoon Park, David L Tabb, Daniel C Liebler, Bing Zhang

“…Abstract Protein assembly and biological interpretation of the assembled protein lists are critical steps in shotgun proteomics data analysis. Although most biological functions arise from interactions among proteins, current protein assembly pipelines treat proteins as independent entities. …”
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Fingerprint-Based Deduplication for Renewable Energy Data On-Site Analyzing by Zeng Zeng, Liyuan Gao, Hongyue Ma, Wenjing Li

“…By studying fine-grained data fingerprinting and neural network-based renewable energy data edge-analysis technologies, we have enabled edge processing of data, reducing latency and privacy issues, and enhancing the system’s real-time processing capabilities and responsiveness.…”
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New Experimental Data of CO2 Solubility in an Amine Solvent by Stefania Moioli, Valentina Schiattarella

“…A detailed specific experimental procedure has been defined and the unit has been firstly operated for validation, by collection of solubility data of CO2 into a 30% wt. MonoEthanolAmine (MEA) solvent, one of the most developed solvents already industrially used. …”
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A panel data model to predict airline passenger volume by Xiaoting Wang, Junyu Cai, Junyan Wang

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Use of satellite data for detecting icebergs and evaluating the iceberg threats by I. A. Bychkova, V. G. Smirnov

“…Te main objective of the research is to develop methods for detecting icebergs using satellite radar data and high space resolution images in the visible spectral range. …”
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Evaluating Game-Based Learning in informal contexts with Data Science by Xavier Rubio-Campillo, Kevin Marín-Rubio, Celia Corral-Vázquez

“…This work presents a methodology for analyzing GBL experiences based on data science and the data collection functionalities offered by current game development platforms. …”
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Evaluating convergence between two data visualization literacy assessments by Erik Brockbank, Arnav Verma, Hannah Lloyd, Holly Huey, Lace Padilla, Judith E. Fan

“…Together, these findings suggest opportunities for development of more comprehensive assessments of data visualization literacy that are organized by components that better account for detailed behavioral patterns.…”
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Chaotic and Quasi-periodic Regimes in the Covid-19 Mortality Data by Ekrem Aydıner, Erkan Yılmaz

“…For these reasons, the three-year Covid-19 data of these countries were analyzed. Detailed chaotic attractors analyses were performed for each country and Lyapunov exponents were obtained. …”
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Exploring the science and data foundation for Federal public lands decisions. by Alison C Foster, Andrew T Canchola, Travis S Haby, Sarah K Carter

“…Of individual resource analysis sections within EAs, 24% contained ≥1 science citation and 21% contained ≥1 data citation. …”
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USING HYPERSPECTRAL DATA FORMONITORING AND OBSERVATION OF FABA BEAN CROP GROWTH by Tarek FOUDA, Abeer ABDELSALAM

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Noise Reduction in CWRU Data Using DAE and Classification with ViT by Jun-gyo Jang, Soon-sup Lee, Se-yun Hwang, Jae-chul Lee

“…The fault types of mechanical equipment were classified using the vision transformer (ViT) technique, a deep learning technique that has been actively used in recent image analysis research. Additionally, the classification performance of the ViT-based technique for vibration time series data was comparatively validated against existing classification algorithms. …”
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