Low-Observability Distribution System State Estimation by Graph Computing with Enhanced Numerical Stability by Zijian Hu, Hong Zhu, Lan Lan, Honghua Xu, Zichen Liu, Kexin Li, Jie Li, Zhinong Wei

“…In distribution systems, limited measurement configurations and communication constraints often result in a low success rate of data acquisition, posing challenges to both system observability and the real-time performance required by state estimation (SE). …”
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Data Allocation in Distributed Database based on CSO by Saadi Hamad Thalij

“…Data allocation problem (DAP) is a NP-Hard problem modelled as optimization problem. …”
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When Poor-Quality Data Meet Anonymization Models: Threats and Countermeasures by Abdul Majeed, Seong Oun Hwang

“…Similarly, low-quality data can inadvertently propagate bias in ML decisions, leading to conflict or disputes. …”
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A Distribution Network Expansion Project Classification Model Based on Data Augmentation and Dimensionality Reduction Method by Xin ZHOU, Jingxing LIN, Zhiwei XIE, Zheng ZHANG, Ruduo LIANG, Zuhong OU

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The use of bivariate spatial modeling of questionnaire and parasitology data to predict the distribution of Schistosoma haematobium in Coastal Kenya. by Hugh J W Sturrock, Rachel L Pullan, Jimmy H Kihara, Charles Mwandawiro, Simon J Brooker

“…<h4>Methodology</h4>Data from a questionnaire survey conducted by the Kenya Ministry of Education in Coast Province in 2009 were combined with available parasitological and environmental data in a Bayesian bivariate spatial model. …”
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Low-Scalability Distributed Systems for Artificial Intelligence: A Comparative Study of Distributed Deep Learning Frameworks for Image Classification by Manuel Rivera-Escobedo, Manuel de Jesús López-Martínez, Luis Octavio Solis-Sánchez, Héctor Alonso Guerrero-Osuna, Sodel Vázquez-Reyes, Daniel Acosta-Escareño, Carlos A. Olvera-Olvera

“…To this end, two of the most widely used libraries for the distributed training of deep learning models, PyTorch’s Distributed Data Parallel and Distributed TensorFlow, were implemented and evaluated using the ResNet50 model as a basis for image classification, and their performance was compared with modern environments such as Google Colab and a recent Workstation. …”
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An Unsupervised Machine Learning Approach to Identify Spectral Energy Distribution Outliers: Application to the S-PLUS DR4 Data by F. Quispe-Huaynasi, F. Roig, N. Holanda, V. Loaiza-Tacuri, Romualdo Eleutério, C. B. Pereira, S. Daflon, V. M. Placco, R. Lopes de Oliveira, F. Sestito, P. K. Humire, M. Borges Fernandes, A. Kanaan, C. Mendes de Oliveira, T. Ribeiro, W. Schoenell

“…Furthermore, by using eROSITA X-ray data, we also highlight the identification of candidates for very active low-mass stars. …”
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Investigating the Effects of Urban Sprawl on Carbon Distribution Using AHP-TOPSIS and MGWR Models by Seyed Reza Mousavi, Monire Mahmoudi Holasoo, Mehdi Shah Mohammad, Samira Heydari

“…The population and housing census data from 1395 (2016-2017) and the GIS data from the detailed plan of Urmia provide a basis for investigating population distribution, land use patterns, and carbon emission indicators across the city's neighborhoods. …”
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Holy Quran Kurdish Sorani translation dataset for language modellingMendeley Data by Muhammad Bamoki, Shakhawan Hares Wady, Soran Badawi

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Spectral Energy Distribution Modeling of BL Lacertae during a Large Submillimeter Outburst and Low X-Ray Polarization State by Ayon Mondal, Arijit Sar, Maitreya Kundu, Ritaban Chatterjee, Pratik Majumdar

“…The usual single-zone leptonic model with the lower-energy peak of the spectral energy distribution (SED) fit by the synchrotron emission from one distribution of relativistic electrons in the jet and inverse-Compton (IC) scattering of lower-energy photons from the synchrotron radiation in the jet itself (synchrotron self-Compton or SSC) or those from the broad-line region and torus by the same distribution of electrons cannot satisfactorily fit the broadband SED with simultaneous data at submillimeter, optical, X-ray, and GeV energies. …”
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Distributed Adaptive Coding Optimization for IoT Using Fulcrum Code and Model-Agnostic Meta-Learning (MAML) in Ultra-Low Latency Environments by Yair Rivera Julio, Angel Pinto, Rodrigo Garcia, Jose Aguilar, Nelson A. Perez-Garcia

“…The exponential growth of the Internet of Things (IoT) has amplified the demand for energy-conscious, low-latency, and efficient data transmission techniques. …”
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Enhancing Data Security in Distributed Systems Using Homomorphic Encryption and Secure Computation Techniques by Parihar Bhawana, Kiran Ajmeera, Valaboju Sabitha, Rashid Syed Zahidur, Liyakat Kazi Kutubuddin Sayyad, D R Anita Sofia Liz

“…In addition, the hardware efficiency and network efficiency encryption algorithms have been integrated in our model, securing real-time performance in distributed-systems scenarios. …”
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The impact of meteorological conditions on cardiovascular and cerebrovascular diseases in different microclimatic zones of low-latitude mountainous areas by Zhengjing Du, Fang Xiong, Yanjing Tang, Xiaoling Xia, Yuandong Hu, Fangfang Wang

“…We aimed to investigate the association between meteorological conditions and CVD occurrence in Guizhou province.MethodsUtilizing daily incidence cases for CVD alongside concurrent meteorological data from four microclimate representative stations in Guizhou Province during 2021-2022, we firstly performed random forest and decision tree analysis to identify the significant meteorological factors influencing the incidence of CVD, and then we applied distributed lag non-linear model (DLNM) to assess the effect of meteorological factors on CVD incidence.ResultsCritical meteorological factors associated with CVD incidence include diurnal temperature range (DTR), temperature change between neighboring days (TCN), diurnal pressure range (DPR), pressure change between neighboring days (PCN), and minimum temperature. …”
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Big data processing using hybrid Gaussian mixture model with salp swarm algorithm by R. Saravanakumar, T. TamilSelvi, Digvijay Pandey, Binay Kumar Pandey, Darshan A. Mahajan, Mesfin Esayas Lelisho

“…The outcomes have been compared with well-known methods like fuzzy C-means and K-means approaches, and the results show that the proposed method effectively distributes accurate data processing to cluster nodes with low latency. …”
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Distributed Algorithm for Traffic Data Collection and Data Quality Analysis Based on Wireless Sensor Networks by Nan Ding, Guozhen Tan, Wei Zhang, Hongwei Ge

“…Focusing on the urban traffic data collection, this paper proposes a distributed algorithm to collect the traffic data based on sensor networks and improve the reliability of data by quality analysis. …”
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Optimal Autonomous Control for Distribution Transformer Area With High Photovoltaic Penetration Based on CSBO-LSTM by Yukai Wei, Chun He, Zhuo Chen, Yinyuan Guo, Zongyuan Li

“…With the large-scale deployment of distributed photovoltaic (PV) and energy storage system (ESS) in distribution network transformer area, problems such as low management efficiency and difficult collaborative regulation have become increasingly prominent. …”
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Regression for Astronomical Data with Realistic Distributions, Errors, and Nonlinearity by Tao Jing, Cheng Li

“…We have developed a new regression technique, the maximum likelihood (ML)–based method and its variant, the Kolmogorov–Smirnov (KS) test–based method, designed to obtain unbiased regression results from typical astronomical data. A normalizing flow model is employed to automatically estimate the unobservable intrinsic distribution of the independent variable and the unobservable correlation between uncertainty level and intrinsic value of both independent and dependent variables from the observed data points in a variational-inference-based empirical Bayes approach. …”
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GD-Det: Low-Data Object Detection in Foggy Scenarios for Unmanned Aerial Vehicle Imagery Using Re-Parameterization and Cross-Scale Gather-and-Distribute Mechanisms by Rui Shi, Lili Zhang, Gaoxu Wang, Shutong Jia, Ning Zhang, Chensu Wang

“…To tackle these issues, we propose GD-Det, a low-data object detection model with high accuracy, specifically designed to handle limited sample sizes and low-quality images. …”
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Design of Instrumentation and Control Components of Power Distribution Systems by Y. A. Klimenko, Y. E. Lvovich, A. P. Preobrazhensky

“…This was taken into account in the developed models and algorithms.Results. The possibilities of managing and monitoring manufacturing processes (MP) for the production of components of low-voltage power distribution systems were shown in terms of checking the operability and correct functioning of processing equipment. …”
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Solving a low-carbon routing problem for perishable distribution food by Martinson Yeboah Appiah, Sun Huaping

“…In this case, the optimisation problem Food distribution system is solved by developing a low-carbon Routing Problem (LRP) model. …”
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