Automatic dependent surveillance-broadcast (ADS-B) anomalous messages and attack type detection: deep learning-based architecture by Waqas Ahmed, Ammar Masood, Jawad Manzoor, Sedat Akleylek

“…This research makes several key contributions to address these challenges. First, it presents a comprehensive review of state-of-the-art machine learning and deep learning techniques, critically analyzing existing methodologies for ADS-B intrusion detection. …”
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An inductive learning-based method for predicting drug-gene interactions using a multi-relational drug-disease-gene graph by Jian He, Yanling Wu, Linxi Yuan, Jiangguo Qiu, Menglong Li, Xuemei Pu, Yanzhi Guo

“…To realize inductive learning, this study generated an innovative idea of transforming known node vectors derived from the DDG graph into representations of unseen nodes using node similarities as weights, enabling inductive predictions for the unseen DGIs. …”
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Noise Impact Analysis of School Environments Based on the Deployment of IoT Sensor Nodes by Georgios Dimitriou, Fotios Gioulekas

“…This work presents an on-field noise analysis during the class breaks in Greek school units (a high school and a senior high school) based on the design and deployment of low-cost IoT sensor nodes and IoT platforms. …”
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Directional migration of recirculating lymphocytes through lymph nodes via random walks. by Niclas Thomas, Lenka Matejovicova, Wichat Srikusalanukul, John Shawe-Taylor, Benny Chain

“…We complement the empirical machine learning based approach by modelling lymphocyte passage through the lymph node insilico. …”
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An Optimised CNN Hardware Accelerator Applicable to IoT End Nodes for Disruptive Healthcare by Arfan Ghani, Akinyemi Aina, Chan Hwang See

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Power transmission system’s fault location, detection, and classification: Pay close attention to transmission nodes by Chiagoziem C. Ukwuoma, Dongsheng Cai, Olusola Bamisile, Ejiyi J. Chukwuebuka, Ekong Favour, Gyarteng S.A. Emmanuel, Acen Caroline, Sabirin F. Abdi

“…This study, therefore, presents a fault localization, detection, and classification model for transmission systems that concentrate on the key distribution nodes. …”
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Game Strategies for Data Transfer Infrastructures Against ML-Profile Exploits by Nageswara S. V. Rao, Chris Y. T. Ma, Fei He

“…Data transfer infrastructures composed of Data Transfer Nodes (DTN) are critical to meeting distributed computing and storage demands of clouds, data repositories, and complexes of supercomputers and instruments. …”
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Wearable device for axillary lymph node screening in breast cancer based on infrared thermography and artificial intelligence by Xiaoying Zhong, Jinqiu Deng, Ping Lu, Zhichao Zuo, Yu Zhao, Yidong Zhou, Xuefei Wang

“…Abstract Background Breast cancer (BC) is the most prevalent cancer among women worldwide, and patients with metastasis to axillary lymph nodes (ALN) experience significantly lower survival rates. …”
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Prediction of Post-Diagnostic Decisions for Tested Hand Grenades’ Fuzes Using Decision Trees by Dariusz AMPUŁA

“…A sheet with risk assessment and standard error for the learning sample and the v-fold cross-check were presented. …”
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Weirdnodes: centrality based anomaly detection on temporal networks for the anti-financial crime domain by Salvatore Vilella, Arthur Capozzi, Marco Fornasiero, Dario Moncalvo, Valeria Ricci, Silvia Ronchiadin, Giancarlo Ruffo

“…Unlike many existing approaches that rely on rule-based algorithms or general machine learning models, WeirdNodes harnesses the evolving structure and relationships within financial transaction networks. …”
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Federated Learning Enhanced MLP–LSTM Modeling in an Integrated Deep Learning Pipeline for Stock Market Prediction by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

“…Abstract In this study, the research presents the Federated Learning Enhanced Multi-Layer Perceptron (Fed-MLP) Long Short-Term Memory that is suggested by the research. …”
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Goistrat: gene-of-interest-based sample stratification for the evaluation of functional differences by Carlos Uziel Pérez Malla, Jessica Kalla, Andreas Tiefenbacher, Gabriel Wasinger, Kilian Kluge, Gerda Egger, Raheleh Sheibani-Tezerji

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Anomaly Detection and Localization via Graph Learning by Olabode Amusan, Di Wu

“…Phasor measurement units (PMUs) are being installed at an unprecedented rate on power systems, offering unique situation awareness capability. This paper presents a graph learning-based method for detecting and locating anomalies using PMU data. …”
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Deep graph representation learning: methods, applications, and challenges by ZHANG Xulong, QU Xiaoyang, XIAO Chunguang, WANG Jianzong

“…This paper presents a comprehensive survey of graph representation learning methods, categorizing them into traditional graph embedding methods and Graph Neural Network (GNN) based approaches. …”
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The Literal Translation Hypothesis in ESP Teaching/Learning Environments by Pedro A. Fuertes-Olivera, Carmen Piqué-Noguera

“…Within this framework, this paper presents evidence that the literal translation hypothesis is possible in ESP; it offers the results of a pilot study that sheds light on how this hypothesis may work, and also discusses its usability in the context of ESP learning. …”
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Travel route recommendation with a trajectory learning model by Xiangping Wu, Zheng Zhang, Wangjun Wan

“…However, capturing the latent patterns in complex trajectory data for accurate route planning presents a significant challenge. Existing route recommendation methods commonly face two major problems: first, inadequate integration of multi-source data, which fails to fully consider the potential factors affecting route choice; and second, limited capability to capture road network characteristics, which restricts the effective application of node features and negatively impacts recommendation accuracy. …”
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Data Poison Detection Schemes for Distributed Machine Learning by Yijin Chen, Yuming Mao, Haoyang Liang, Shui Yu, Yunkai Wei, Supeng Leng

“…Distributed machine learning (DML) can realize massive dataset training when no single node can work out the accurate results within an acceptable time. …”
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PLGNN: graph neural networks via adaptive feature perturbation and high-way links by Meixia He, Peican Zhu, Yang Liu, Keke Tang

“…Specifically, the Accuracy improved by an average of 2.6% on five node classification datasets, and an average of 2.1% on five graph classification datasets.…”
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Q-Learning Enabled Green Communication in Internet of Things by Mukesh Kumar, Sushil Kumar, Ankita Jaiswal, Pankaj Kumar Kashyap

“…To alleviate the problem of stochastic link quality as channel gain reinforcement based Q-learning energy balanced routing is presented in this paper. …”
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Detecting susceptible communities and individuals in hospital contact networks: a model based on social network analysis by Yixuan Yang, Sony Peng, Sophort Siet, Sadriddinov Ilkhomjon, Phonexay Vilakone, Seok-Hoon Kim, Doo-Soon Park

“…The goal of our work is to identify susceptible communities with patients and healthcare workers, and analyse the independent contact networks of various roles to determine the high-influence nodes within the hospital contact network. If these high-influence nodes are part of the susceptible community, they should be the focus of observation to prevent the spread of the virus. …”
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