Proposal of a Thermal Network Model for Fast Solution of Temperature Rise Characteristics of Aircraft Wire Harnesses by Tao Cao, Wei Li, Tianxu Zhao, Shumei Cui

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SGLT2 inhibitors and kidneys: mechanisms and main effects in diabetes mellitus patients by Vladimir V Salukhov, Yurii Sh. Khalimov, Sergey B. Shustov, Sergey I. Popov

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Advancing TinyML in IoT: A Holistic System-Level Perspective for Resource-Constrained AI by Leandro Antonio Pazmiño Ortiz, Ivonne Fernanda Maldonado Soliz, Vanessa Katherine Guevara Balarezo

“…By exploring architectural co-design strategies, algorithmic innovations, and pressing research gaps, this paper offers a roadmap for future investigations and industrial applications of AI in resource-constrained devices.…”
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A systematic review of machine learning-based remote sensing data analysis for geological and mined materials characterisation by Sureka Thiruchittampalam, Bikram Pratap Banerjee, Nancy F Glenn, Simit Raval

“…In addition, it discusses the challenges posed by high-dimensional data resulting from sensor capabilities, as well as the cost and time constraints associated with existing algorithms. Ultimately, the review underscores both the opportunities and limitations of current machine learning approaches in analysing geological and mined materials, emphasising the need for ongoing research to overcome these challenges and fully utilise machine learning-based remote sensing in the mining sector.…”
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House Value Estimation using Different Regression Machine Learning Techniques by Tarek Ghamrawi, Müesser Nat

“…This study investigates the effectiveness of various regression algorithms in estimating house values using a dataset sourced from Zillow.com, encompassing 15,000 residential properties from Denver, Colorado. …”
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Parallel Fractal Compression Method for Big Video Data by Shuai Liu, Weiling Bai, Gaocheng Liu, Wenhui Li, Hari M. Srivastava

“…Therefore, the compression method of big video data has become a challenging research topic at present. Performance of existing content-based video sequence compression method is difficult to be effectively improved. …”
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Optimizing coverage in wireless sensor networks using deep reinforcement learning with graph neural networks by G. Pushpa, R. Anand Babu, S. Subashree, S. Senthilkumar

“…To address these limitations, this research introduces a novel hybrid model that integrates Deep Reinforcement Learning (DRL) with Graph Neural Networks (GNN). …”
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A new method for routing protocols using hybrid fuzzy clustering in UWSNs by Xiaoju Wang, Bin Meng, Xuexu Yuan, Junwei Zhao

“…Simulation results prove that the protocol outperforms the DABC and IDACB algorithms by reducing routing packets by 29% and enhancing the packet delivery ratio by 19%. …”
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Smart Buildings and Digital Twin to Monitoring the Efficiency and Wellness of Working Environments: A Case Study on IoT Integration and Data-Driven Management by Giuseppe Piras, Sofia Agostinelli, Francesco Muzi

“…The system also aims to provide a tool for both monitoring and simulation/planning/decision support through the processing and development of machine learning (ML) algorithms. In relation to emergency management, real-time data can be acquired, allowing information to be shared with users and building managers through the creation of dashboards and visual analysis. …”
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Novel Opportunistic Network Routing Based on Social Rank for Device-to-Device Communication by Tong Wang, Yongzhe Zhou, Yunfeng Wang, Mengbo Tang

“…In recent years, there has been dramatic proliferation of research concerned with fifth-generation (5G) mobile communication networks, among which device-to-device (D2D) communication is one of the key technologies. …”
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Optimising offshore multiphase flowmeter technology to improve wet gas field efficiency by Rahimi Zaman Jusoh A. Rashid, MFaizal Mustafa, Idris Ismail, Nur Azlina Mohamed Mokmin

“…The findings demonstrate that MPFMs’ compatibility with lightweight constructions and capacity to manage high GVF scenarios significantly reduce operating costs and infrastructure needs. This research has proven the technological developments in MPFM design, such as improvements in sensor technology, data processing algorithms, and materials engineering. …”
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ANALISIS KINERJA MODEL STACKING BERBASIS RANDOM FOREST DAN SVM DALAM KLASIFIKASI RUMAH TANGGA BERDASARKAN GARIS KEMISKINAN MAKANAN DI PROVINSI JAWA BARAT by Ghardapaty Ghaly Ghiffary, Nabila Tri Amanda, Rizky Ardhani, Bagus Sartono, Aulia Rizki Firdawanti

“…The stacking method is an ensemble technique in machine learning that combines predictions from several base models to improve classification accuracy. This research applies the stacking method with two machine learning algorithms, namely Random Forest and Support Vector Machine (SVM) as base learners and logistic regression as a meta learner. …”
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Mammography-based artificial intelligence for breast cancer detection, diagnosis, and BI-RADS categorization using multi-view and multi-level convolutional neural networks by Hongna Tan, Qingxia Wu, Yaping Wu, Bingjie Zheng, Bo Wang, Yan Chen, Lijuan Du, Jing Zhou, Fangfang Fu, Huihui Guo, Cong Fu, Lun Ma, Pei Dong, Zhong Xue, Dinggang Shen, Meiyun Wang

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Effectiveness and Design of PBL-Based Project Approach for Non-Major University Computing Courses by Jung-In Choi, Sooyeon Yang

“…The Problem-Based Learning project approach, designed by the research team, provides a teaching and learning strategy in which students collaborate to analyze and extend code within real-world problem contexts while systematically exchanging feedback. …”
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Integration of Accelerometers and Machine Learning with BIM for Railway Tight- and Wide-Gauge Detection by Jessada Sresakoolchai, Chayutpong Manakul, Ni-Asri Cheputeh

“…These data are processed and analyzed using supervised machine-learning algorithms to classify and predict potential tight- and wide-gauge events. …”
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Attention-based hybrid contrastive learning for unsupervised person re-identification by Weihao Qin, Yongxia Li, Jianguang Zhang, Xianbin Wen, Jiajia Guo, Qi Guo

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Can the number of confirmed COVID-19 cases be predicted more accurately by including lifestyle data? An exploratory study for data-driven prediction of COVID-19 cases in metropolit... by Sungwook Jung

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A systematic review on the integration of explainable artificial intelligence in intrusion detection systems to enhancing transparency and interpretability in cybersecurity by Vincent Zibi Mohale, Ibidun Christiana Obagbuwa

“…Traditional IDS often rely on complex machine learning algorithms that lack transparency despite their high accuracy, creating a “black box” effect that can hinder the analysts’ understanding of their decision-making processes. …”
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Artificial Intelligence-Assisted Selection Strategies in Sheep: Linking Reproductive Traits with Behavioral Indicators by Ebru Emsen, Muzeyyen Kutluca Korkmaz, Bahadir Baran Odevci

“…Recent advancements in artificial intelligence (AI), including video tracking, wearable sensors, and machine learning (ML) algorithms, offer new opportunities to identify behavior-based indicators linked to key reproductive traits such as estrus, lambing, and maternal behavior. …”
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