Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies by Leonidas Theodorakopoulos, Aristeidis Karras, Alexandra Theodoropoulou, Georgios Kampiotis

“…GraphX’s strength was in processing batch in-memory workloads typical of blockchain and machine learning model optimization, while Flink excelled in processing stream data, which is timely and important to the IoT world. …”
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Detection of Indoor Building Lighting Fixtures in Point Cloud Data using SDBSCAN by Humairah Mansor, Shazmin Aniza Abdul Shukor, Razak Wong Chen Keng, Nurul Syahirah Khalid

“…However, this led to the high amount of data that needs to be processed and requires a specific method, especially to detect lighting fixtures. …”
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Big data and AI for gender equality in health: bias is a big challenge by Anagha Joshi, Anagha Joshi, Anagha Joshi

“…In this perspective, firstly the promise of big data and machine learning applications in the context of women's health is elaborated. …”
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Multiagent Semantical Annotation Enhancement Model for IoT-Based Energy-Aware Data by Kaleem Razzaq Malik, Tauqir Ahmad, Muhammad Farhan, Farhan Ullah, Kashif Amjad, Shehzad Khalid

“…Improving extraction of sensor-based data for energy awareness and then annotating it and converting it into semantically enabled form for analyzing results with the use of improved tools and applications are the focus of this research. …”
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Review of Energy Efficiency Evaluation Indexes Related to Data Center Cooling Systems by Wang Bo, Guo Yanhua, Shao Shuangquan, Tu Qiu, Li Qianli

“…For the annual operation index of chillers in Chinese data centers, the annual coefficient of performance(ACOP) is applicable.…”
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Diverse explanations from data-driven and domain-driven perspectives in the physical sciences by Sichao Li, Xin Wang, Amanda Barnard

“…Our analysis underscores the importance of considering multiple perspectives when interpreting ML models in scientific contexts and highlights the critical need for scientists to maintain control over the interpretation process, balancing data-driven insights with domain expertise to meet specific scientific needs. …”
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Neural Networks vs. Regression: A Comparative Analysis in Medical Data Processing by Minodora ANDOR, Gheorghe Ioan MIHALAŞ

“…The optimization process for NN required extensive trial and error, as no universal guidelines for parameter selection were applicable in this context. Discussion. Our findings highlight a real challenge in medical AI applications for data processing: when dealing with small datasets, neural networks do not necessarily outperform classical methods. …”
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Transforming tabular data into images via enhanced spatial relationships for CNN processing by Hameedah A. Alenizy, Jawad Berri

“…Abstract Convolutional neural networks (CNNs), renowned for their efficiency in image analysis, have revolutionized pattern and structure recognition in visual data. Despite their success in image-based applications, CNNs face challenges when applied to tabular data due to the lack of inherent spatial relationships among features. …”
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Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection by Mulugeta Weldezgina Asres, Christian Walter Omlin, Long Wang, David Yu, Pavel Parygin, Jay Dittmann, the CMS-HCAL Collaboration

“…The proliferation of sensors brings an immense volume of spatio-temporal (ST) data in many domains, including monitoring, diagnostics, and prognostics applications. …”
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An Innovative Coded Language for Transferring Data via a Haptic Thermal Interface by Yosef Y. Shani, Simon Lineykin

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The Importance of DNA Data Banks in the Identification of Unidentified Bodies: A Case Report by Amin Bakhtiyari, Masoud Ghadipasha, Hanie Bakhtiyari

“…Right now, we have a DNA data bank for criminals in Iran. However, the creation of a DNA data bank for everyone is emphasized in this study due to various applications, such as identifying unidentified bodies. …”
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Beyond Information Distortion: Imaging Variable-Length Time Series Data for Classification by Hyeonsu Lee, Dongmin Shin

“…In real-world applications, these data are often collected with variable sample lengths, which can pose challenges for classification models that typically require fixed-length inputs. …”
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European collaborations for safe and efficient dismantling: digital twins, ontology and data exchange by Jacques Marie-Bénédicte, Räty Antti, Cabrerizo Joseph A. Ridao, Daniska Dusan

“…PLEIADES demonstrated the usefulness and efficiency of this concept using data of three real nuclear sites. Starting in the second half of 2024, the DORADO project will continue this work by creating a holistic digital data-driven platform as a BIM/DT (Building-Information-Model/Digital-Twin) and by integrating new digital tools into a coherent suite customized for decommissioning applications. …”
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Data Aggregation and Scheduling to Optimize Information Freshness In Multi-Hop IoT Networks by Xueling Wu, Long Qu, Maurice J. Khabbaz

“…The rapid proliferation of Internet of Things (IoT) devices with sensing, monitoring, and control capabilities has fueled the emergence of diverse real-time IoT applications. These applications often require the efficient transmission of collected sensitive data to centralized or distributed processing units, such as cloud servers, edge nodes, or fog computing platforms—to enable timely responses. …”
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Requirements Analysis of Data Center Network Routing Algorithm Based on SDN Architecture by Zifu Fan, Chunling Wu, Jinhong Wang

“…With the development of SDN technology, SDN-based data center network will be more extensive. The applications of SDN technology in data center network were focused on; the technical characteristics of modern data center network and SDN technology were analyzed firstly, and a modern data center network architecture based on SDN was designed. …”
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Mixed Inverse Gaussian Analysis of Covariance for Censored Data: A Bayesian Approach by Ehsan Mesdaghi, Afshin Fallah, Rahman Farnoosh, Gholamhossein Yari

“…This paper proposes a model for analysis of covariance (ANCOVA) of censored data obtained from a positively skewed population by using the mixed inverse Gaussian (MIG) distribution. …”
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Optimizing UAV sprayer performance using field data and machine learning approaches by Doğan Güneş, Hideo Hasegawa

“…This integrated approach demonstrates the potential of combining field data with simulation and machine learning to optimize UAV spraying strategies, offering a framework for broader applications in sustainable agriculture.…”
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Latency Estimation-Based Data Delivery Scheme for Vehicular Ad Hoc Networks by Haigang Gong, Lingfei Yu, Ke Liu, Fulong Xu, Xiaomin Wang

“…Data delivery is the most compelling issue for the applications in vehicular ad hoc networks. …”
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Data Mining Techniques for Predictive Maintenance in Manufacturing Industries a Comprehensive Review by Chinthamu Narender, Ashish, P Mathiyalagan, B Devananda Rao, S Kannadhasan, M Suganya

“…Predictive maintenance (PdM) is one of the major methods used in modern manufacturing to realize downtime minimization, lower the cost of maintenance and maximize machine service life by analyzing the collected data using data mining methodologies. However existing works mainly focus on conventional ML models without provide systems design real world applications systems and do not include any dimension related to network security dimension, cost and benefit analyzing dimension utility dimension and light weight A.I model for edge computing. …”
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A data-driven multicriteria decision model for healthcare workforce retention strategies by Debora Di Caprio, Sofia Sironi, Fan-Yun Lan, Ramin Rostamkhani

“…The methodology has been implemented with data collected from healthcare workers employed in three healthcare institutions in Northern Taiwan. …”
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