Dynamic spatiotemporal graph network for traffic accident risk prediction by Pengcheng Zhang, Wen Yi, Yongze Song, Penggao Yan, Peng Wu, Ammar Shemery, Keith Hampson, Albert P. C. Chan

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Discovering CRISPR-Cas system with self-processing pre-crRNA capability by foundation models by Wenhui Li, Xianyue Jiang, Wuke Wang, Liya Hou, Runze Cai, Yongqian Li, Qiuxi Gu, Qinchang Chen, Peixiang Ma, Jin Tang, Menghao Guo, Guohui Chuai, Xingxu Huang, Jun Zhang, Qi Liu

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Mask R-CNN aided fruit surface temperature monitoring algorithm with edge compute enabled internet of things system for automated apple heat stress management by Basavaraj R. Amogi, Rakesh Ranjan, Lav R. Khot

“…In orchard evaluations (2022 season), the resulting algorithm ported on CPSS was able to accurately segment (dice similarity coefficient = 0.89) and estimate apple FST with < 0.5 °C error compared to ground truth data. With compute time of about 37 s, data processing time was reduced by 22 % over previous algorithm. …”
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Panoramic Assessment Method of Substation Equipment Health Status Based on Multisource Monitoring and Deep Convolution Neural Network under Edge Computing Architecture by Zhu-xing Ma, Li-shuo Zhang, Hao Gu, Zi-zhong Xin, Zhe Kang, Zhao-lei Wang

“…In view of the low efficiency of the traditional manual evaluation method of substation equipment status under the background of complex environment, a panoramic evaluation method of substation equipment health status based on multisource monitoring and deep convolution neural network under edge computing architecture is proposed. Firstly, a panoramic sensing system for substation equipment is built based on edge computing, and an edge computing server is deployed in the substation to process the massive data obtained from multisource monitoring nearby. …”
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Efficient Time-Series InSAR Data Processing via Modular Cloud-Native Parallelization by Peichen Yu, Chao Wang, Yixian Tang, Weikang Zhang, Lichuan Zou, Shaoyang Guan, Haihang You, Hong Zhang

“…Based on the concept of cloud-native computing, this study proposes a modular, multinode parallel framework for time-series interferometric SAR (InSAR) processing. …”
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Analysis of Data and Feature Processing on Stroke Prediction using Wide Range Machine Learning Model by Untari Novia Wisesty, Tjokorda Agung Budi Wirayuda, Febryanti Sthevanie, Rita Rismala

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Reducing Execution Time of Pixel-Based Machine Learning Classification Algorithms Using Parallel Processing Concept by Aliaa Mahmoud, Mohammed Younis

“…Parallel processing is essential in machine learning to meet the computational requirements resulting from the complexity of algorithms and the size of the dataset, by taking advantage of the computational resources of parallel processing that can distribute computational operations across multiple processors. …”
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Vaccination Schedules Recommended by the Centers for Disease Control and Prevention: From Human-Readable to Machine-Processable by Xia Jing, Hua Min, Yang Gong, Mytchell A. Ernst, Aneesa Weaver, Chloe Crozier, David Robinson, Dean F. Sittig, Paul G. Biondich, Samuil Orlioglu, Akash Shanmugan Boobalan, Kojo Abanyie, Richard D. Boyce, Adam Wright, Christian Nøhr, Timothy D. Law, Arild Faxvaag, Lior Rennert, Ronald W. Gimbel

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Implementasi Metode Profile Matching dan Multi Factor Evaluation Process (MFEP) Dalam Seleksi Pencari Kerja by Heru Purwanto, Arfhan Prasetyo, Rachmat Suryadithya

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Enhanced Underwater Image Restoration and Clarity Optimization Using Advanced Digital Image Processing Techniques by Gopirajan Punniyakotti Varadharajan, Pradeep T., Charan R.

“…Also, the presented method if free from training samples, thus allowing the benefits of computationally efficient and real-time processing that machine learning models wouldn't have. …”
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Parallel processing of past and future memories through reactivation and synaptic plasticity mechanisms during sleep by Khaled Ghandour, Tatsuya Haga, Noriaki Ohkawa, Chi Chung Alan Fung, Masanori Nomoto, Mostafa R. Fayed, Hirotaka Asai, Masaaki Sato, Tomoki Fukai, Kaoru Inokuchi

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Controlling tangential flow filtration in biomanufacturing processes via machine learning: A literature review by Bastian Oetomo, Ling Luo, Yiran Qu, Michele Discepola, Sandra E. Kentish, Sally L. Gras

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Algorithm for Generating Bifurcation Diagrams Using Poincaré Intersection Plane by Luis Javier Ontañón-García, Juan Gonzalo Barajas-Ramírez, Eric Campos-Cantón, Daniel Alejandro Magallón-García, César Arturo Guerra-García, José Ricardo Cuesta-García, Jonatan Pena-Ramirez, José Luis Echenausía-Monroy

“…This work contributes to the study of dynamic systems by providing the reader with accessible tools for studying any dynamic system under established standards and reducing the computational time required for these types of studies by implementing these algorithms utilizing the multi-core processors found in modern computers.…”
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An SDR-Based GNSS-R CubeSat Payload: Hardware Development and Optimization of the Onboard Processing by Shah Zahid Khan, Yasir M. O. Abbas, Edwar Edwar, Abdul-Halim Jallad, Adriano Camps

“…This way the payload selectively processes the raw data, significantly reducing the computational load. …”
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Variance exchange process: overcoming the problem of singular information matrices in quadratic three−variable response designs by Okim Ikpan, Felix Nwobi

“… Many a time, in a variance exchange process looking for D-optimal designs, the initial designs of all quadratic components of three-variable response polynomials produce non-invertible information matrices. …”
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Task distribution offloading algorithm of vehicle edge network based on DQN by Haitao ZHAO, Tangwei ZHANG, Yue CHEN, Houlin ZHAO, Hongbo ZHU

“…In order to achieve the best balance between latency,computational rate and energy consumption,for a edge access network of IoV,a distribution offloading algorithm based on deep Q network (DQN) was considered.Firstly,these tasks of different vehicles were prioritized according to the analytic hierarchy process (AHP),so as to give different weights to the task processing rate to establish a relationship model.Secondly,by introducing edge computing based on DQN,the task offloading model was established by making weighted sum of task processing rate as optimization goal,which realized the long-term utility of strategies for offloading decisions.The performance evaluation results show that,compared with the Q-learning algorithm,the average task processing delay of the proposed method can effectively improve the task offload efficiency.…”
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Fog-Enabled Machine Learning Approaches for Weather Prediction in IoT Systems: A Case Study by Buket İşler, Şükrü Mustafa Kaya, Fahreddin Raşit Kılıç

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Feature-Centric Video Transmission and Analytics in Large-Scale Internet of Video Things by Hongan Wei, Yuxiang Liu, Kejian Hu, Liqun Lin, Youjia Chen, Tiesong Zhao, Wanjian Feng

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Influence of Reflow Cycles of the Pb–Free/Pb Hybrid Assembly Process on the IMCs Growth Interface of Micro-Solder Joints by Xinyuan He, Qi Zhang, Qiming Cui, Yifan Bai, Lincheng Fu, Zicong Zhao, Chuanhang Zou, Yong Wang

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Preserving Big Data Privacy in Cloud Environments Based on Homomorphic Encryption and Distributed Clustering by Shatha A. Baker

“… Cloud computing has grown in popularity in recent years because to its efficiency, flexibility, scalability, and the services it provides for data storage and processing. …”
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