Distributed Statistical Analyses: A Scoping Review and Examples of Operational Frameworks Adapted to Health Analytics by Félix Camirand Lemyre, Simon Lévesque, Marie-Pier Domingue, Klaus Herrmann, Jean-François Ethier

“…However, these approaches assumed evenly and identically distributed data across nodes. Consequently, statistical procedures were derived to accommodate uneven node sample sizes and heterogeneous data distributions across nodes. …”
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User activity monitoring and automated office IT infrastructure management system by V.V. Vorotnikov, O.O. Shelukha, K.I. Matvieiev

“…This article presents the concept, architecture, and implementation of an intelligent microservice platform for monitoring user activity and automating the management of office IT infrastructure. …”
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Metaheuristic Optimization for Robust RSSD-Based UAV Localization with Position Uncertainty by Yuanyuan Zhang, Jiping Li, T. Aaron Gulliver, Huafeng Wu, Guangqian Xie, Xiaojun Mei, Jiangfeng Xian, Weijun Wang, Linian Liang

“…To mitigate the adverse effects of these issues, a novel received signal strength difference (RSSD)-based localization scheme based on a robust enhanced salp swarm algorithm (RESSA) is presented. In this algorithm, an elitism strategy based on tent opposition-based learning (TOL) is proposed to promote the leader to move around the food source. …”
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Customer active power consumption prediction for the next day based on historical profile by Ahmad A. Goudah, Mohamed El-Habrouk, Dieter Schramm, Yasser G. Dessouky

“…Calculating probabilities of being in each level (node) is also covered. Logistic Regression Algorithm is used to determine the most probable nodes for the next 25 hours in case of residential or industrial customers.…”
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Design and Linearization of a Doherty Power Amplifier in 45 nm CMOS Technology for 5G Applications by Alexandre Zem de Morais, André Augusto Mariano, Eduardo Gonçalves de Lima, Luis Schuartz, Bernardo Rego Barros de Almeida Leite

“…The PA is designed in a 45 nm node using a commercial CMOS process. DPD is applied using a memory polynomial model with an indirect learning structure to enhance its accuracy. …”
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Enhanced Efficiency in SMEs Attendance Monitoring: Low Cost Artificial Intelligence Facial Recognition Mobile Application by Hong-Danh Thai, Yeong-Seok Seo, Jun-Ho Huh

“…The AI Engine layer is built by applying a deep learning-based facial recognition model that was trained using a large dataset of collected employee faces. …”
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Self-Organizing TDMA: A Distributed Contention-Resolution MAC Protocol by Mahsa Derakhshani, Yahya Khan, Duc Tuong Nguyen, Saeedeh Parsaeefard, Atoosa Dalili Shoaei, Tho Le-Ngoc

“…The proposed SO-TDMA follows a cognition cycle where each node independently observes the operation environment, learns about the network traffic load, and then makes decisions to adapt the protocol for smart coexistence. …”
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A comprehensive IoT cloud-based wind station ready for real-time measurements and artificial intelligence integration by Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, Fernando Morgado-Dias

“…The presented system comprises a dedicated station frame, a self-sufficient solar power setup, an ultrasonic wind sensor, a data transmission node, cloud computing capabilities, and an end-user visualization application. …”
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Transcriptional Patterns of Nodal Entropy Abnormalities in Major Depressive Disorder Patients with and without Suicidal Ideation by Minxin Guo, Heng Zhang, Yuanyuan Huang, Yunheng Diao, Wei Wang, Zhaobo Li, Shixuan Feng, Jing Zhou, Yuping Ning, Fengchun Wu, Kai Wu

“…Previous studies have indicated that major depressive disorder (MDD) patients with suicidal ideation (SI) present abnormal functional connectivity (FC) and network organization in node-centric brain networks, ignoring the interactions among FCs. …”
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TATPat based explainable EEG model for neonatal seizure detection by Turker Tuncer, Sengul Dogan, Irem Tasci, Burak Tasci, Rena Hajiyeva

“…By utilizing these levels, we have created an automaton and this automaton has three nodes (each node defines each level). In the feature extraction phase, transition tables of these nodes has been extracted. …”
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Distinguishing atypical parotid carcinomas and pleomorphic adenomas based on multiphasic computed tomography radiomics nomogram: a multicenter study by Lin-Wen Huang, Jian-Chao Liang, Pei-Kun Cai, Zhi-Ping Cai, Mei-Lin Chen, Jia-Wei Pan, Yong-Feng Wen, Yun-Jun Yang, Zhen-Yu Xu, Ya-Bin Jin, Zhi-Feng Xu

“…Key discriminative features — cluster shade, run-length non-uniformity and first-order mean, extracted via wavelet or exponential filters — significantly differentiated atypical PCAs from PAs.ConclusionThe CT-based radiomics nomogram, supplemented by machine learning, effectively differentiates atypical PCAs from PAs, presenting a non-invasive diagnostic tool that could guide treatment decisions and reduce the need for invasive procedures.…”
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Passive Synchronization Based Energy-Efficient MAC Protocol over M2M Wireless Networks by Pranesh Sthapit, Jae-Young Pyun

“…Network information is embedded into the synchronization frame so that mobile nodes can learn about their neighbors just by scanning the synchronization channel. …”
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An Efficient Recommendation Algorithm Based on Heterogeneous Information Network by Ying Yin, Wanning Zheng

“…Therefore, this paper proposes an efficient recommendation algorithm based on heterogeneous information network, which uses the characteristics of graph convolution neural network to automatically learn node information to extract heterogeneous information and avoid errors caused by the manual search for metapaths. …”
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A Mobile Computing Framework for Pervasive Adaptive Platforms by Olivier Brousse, Jérémie Guillot, Gilles Sassatelli, Thierry Gil, François Grize, Michel Robert

“…This framework enables the platform to adapt itself to application requirements at high-level while using hardware acceleration at node level. The resulting programming solution has been used to program three collaborative robotic applications in which robots learn tasks and evolve for achieving a better adaptation to their environment.…”
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A Quantum Implementation Model for Artificial Neural Networks by Ammar Daskin

“… The learning process for multilayered neural networks with many nodes makes heavy demands on computational resources. …”
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Multi dynamic temporal representation graph convolutional network for traffic flow prediction by Zuojun Wu, Xiaojun Liu, Xiaoling Zhang

“…Moreover, a multiaspect fusion module is presented, which combines auxiliary hidden states learned from traffic volume with primary hidden states derived from traffic speed. …”
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Study on Nuclear Accident Precursors Using AHP and BBN by Sujin Park, Huichang Yang, Gyunyoung Heo, Muhammad Zubair, Rahman Khalil Ur

“…We tried to prioritize the lessons learned from Fukushima accident to demonstrate the feasibility of the proposed methodology.…”
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Distributed Beamforming for Relay Assisted Multiuser Machine-to-Machine Networks by Chen Chen, Lin Bai, Meiping Feng, Minhua Huang, Tian Tian

“…Since global CSI is often unavailable due to geometric locations, power limitation, or other constraints of the relay nodes in M2M networks, our work aims to develop distributed algorithms that each relay node individually learns its own beamforming weights with local CSI. …”
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Network analysis of cognitive function, glycemic–lipid profiles, and hepatic–renal function in individuals with diverse drinking patterns by Shuqi Xu, Shuqi Xu, Shuqi Xu, Shuqi Xu, Ranran Zhao, Ranran Zhao, Ranran Zhao, Jincheng Wang, Jincheng Wang, Jincheng Wang, Xue Yang, Xue Yang, Xue Yang, Lan Wang, Lan Wang, Lan Wang, Cuixia An, Cuixia An, Cuixia An, Xueyi Wang, Xueyi Wang, Xueyi Wang, Ran Wang, Ran Wang, Ran Wang

“…TC and AST presented the highest expected influence centrality. …”
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Crack Identification for Bridge Condition Monitoring Combining Graph Attention Networks and Convolutional Neural Networks by Feiyu Chen, Tong Tong, Jiadong Hua, Chun Cui

“…Then, the output features of the CNN model are considered as nodes of the graph. Considering the spatial relationship among the patches in the original image, the node from the central patch is connected to the nodes from its neighboring patches to constitute a graph structure, which can be input into a GAT model to learn the relationship among the nodes and update the features. …”
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