Interpretable Identification of Dynamic Adaptive Streaming over HTTP (DASH) Flows Based on Feature Engineering by Arkadiusz Biernacki

“…To address this issue, we proposed an unsupervised machine learning model to identify traffic generated by video applications from the three popular services, namely YouTube, Netflix, and Amazon Prime. …”
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Quantum equilibrium propagation for efficient training of quantum systems based on Onsager reciprocity by Clara C. Wanjura, Florian Marquardt

“…Abstract The widespread adoption of machine learning and artificial intelligence in all branches of science and technology creates a need for energy-efficient, alternative hardware. …”
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A simplified computational liver perfusion model, with applications to organ preservation by Daniel Emerson, Yoed Rabin, Levent Burak Kara

“…Additionally, we introduce the concept of a super lobule which enables a computational abstraction of biological liver lobules. User-tunable parameters allow for vasculatures of varying depth and topology to be generated. …”
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Shock Signal Trend Term Error Correction Method Based on Discrete Wavelet Transform and Low-Frequency Oscillator Combination by Peng Wang, Ming Yan, Lei Zhang, Ning Yang

“…The optimal wavelet parameters can be selected according to a low-frequency spectrum baseline fitted by the measured relative displacement to reject low-frequency trend term errors. …”
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Current-Limiting Strategy for Unbalanced Low-Voltage Ride Through of the SMSI-MG Based on Coordinated Control of the Generator Subunits by Jinjing Zhang, Xinggui Wang, Sheng Xue

“…The Light Gradient-Boosting Machine (LightGBM) is used to establish a mapping relationship between the parameters characterizing overcurrent and the reduction quantity in output active power of the SMSI-MG to implement the CCGU-based current-limiting strategy. …”
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Leveraging Variable Frequency Drive Data for Nondestructive Testing and Predictive Maintenance in Industrial Systems by Carl Lee Tolbert

“…Future advancements in artificial intelligence and machine learning could further refine automated fault detection by utilizing historical VFD data to predict system failures accurately. …”
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Imitation Modeling of Production Processes in FlexSim Environment by E. V. Lapteva, Yu. S. Lekareva, S. S. Umansky

“…The article studies imitation modeling use in agricultural machine-building. Brief description of FlexSim software is provided. …”
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Pengenal Gerakan dengan Joystick Akselerometer Menggunakan Filter Kalman by Khoirudin Fathoni, Dhidik Prastiyanto

“…Human Machine Interaction keeps growing and developing, one of development is through gesture recognition that detects acceleration in a movement. …”
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Element-resolved electrochemical database: AESEC polarization curves of ZnAlMg alloy coating constituents by Junsoo Han, Kevin Ogle

“…This demonstrates the possible use of AESEC-LSV for determining long-term elemental corrosion rates, as well as the use of element-specific electrochemical data as input parameters for more accurate machine learning based corrosion resistant alloy design. …”
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Rock Brittleness Evaluation Method Based on the Complete Stress-Strain Curve by ChenYang Liu, Yong Wang, XiaoPei Zhang, LiZhi Du

“…Brittleness plays an important role in the brittle failure process of rocks, and is also one of the important mechanical properties of rocks and a key indicator in rock engineering such as hydraulic fracturing, tunnelling machine borehole drilling and rockburst prediction. …”
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Application of Levy flight-based harmony search algorithm for the flexible job shop scheduling by Jun Li, Yang Zhou

“…Abstract The Flexible Job Shop Scheduling Problem (FJSP) is an extension of the classical job shop scheduling problem, which is characterized by the fact that each process can be processed on multiple candidate machines, and needs to solve the two subproblems of machine allocation and process sequencing simultaneously. …”
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Assessing Deep Learning Techniques for Remote Gauging and Water Quality Monitoring Using Webcam Images by Ruichen Xu, Binbin Wang

“…Motivated by routine webcam monitoring and recent advances in image-based machine learning research, in this technical paper, we evaluate three convolutional neural network (CNN) models including two deep neural network models (CNN3, VGG16, and ResNet50) in predicting river gauging, turbidity, dissolved oxygen, and dissolved organic matter in the Missouri River. …”
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Intelligent deep learning-based dual-task approach for robust power quality event classification by Lipsa Ray, Pampa Sinha, Siddhanta Pani, Anshuman Nayak, Kaushik Paul, Chitralekha Jena, Md. Minarul Islam, Taha Selim Ustun

“…Simulation evaluation demonstrates that the proposed model outperforms conventional machine learning and dense networks, achieving superior accuracy (99.7%), faster convergence (by 30%), and reduced computational cost (by 25%). …”
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Chaos Time Series Prediction Based on Membrane Optimization Algorithms by Meng Li, Liangzhong Yi, Zheng Pei, Zhisheng Gao, Hong Peng

“…This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ,m) and least squares support vector machine (LS-SVM) (γ,σ) by using membrane computing optimization algorithm. …”
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Multi-Performance Optimization of the Mechanical Characteristics of Basalt Fiber and Silicon Carbide-Filled Aluminum Matrix Composites by V. Veeranaath, S. G. Dinesh, G. Natarajan

“…The samples were also machined and tested for their mechanical, physical, and wear behavior as per ASTM standards. …”
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AI-Enhanced Photovoltaic Power Prediction Under Cross-Continental Dust Events and Air Composition Variability in the Mediterranean Region by Pavlos Nikolaidis

“…Importantly, all input parameters are sourced from publicly accessible, internet-based platforms, facilitating wide reproducibility and operational application. …”
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A hybrid Genetic Algorithm and Fuzzy Logic approach to ergonomic design of workstations in metal casting operations by Intan Berlianty, Irwan Soejanto, Indun Titisariwati, Favian Ersanta Andhika Putra, Wahyu Tri Utami, Mohamad Kamil Insani

“…Future research could further enhance the system by incorporating machine learning for improved predictive capabilities and expanded optimization of ergonomic parameters.…”
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Development of artificial intelligence models for well groundwater quality simulation: Different modeling scenarios. by Naser Shiri, Jalal Shiri, Zaher Mundher Yaseen, Sungwon Kim, Il-Moon Chung, Vahid Nourani, Mohammad Zounemat-Kermani

“…Information on qualitative parameters of these valuable resources is very crucial as it might affect its applicability from agricultural, drinking, and industrial aspects. …”
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Demographic consequences of damage dynamics in single-cell aging by Murat Tuğrul, Ulrich K. Steiner

“…We formulate an analytical approximation linking cellular and damage parameters to demographic aging patterns along mother cell lineages. …”
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Synergistic research on planter performance optimization and green low-carbon agricultural transformation under climate risk by Yan Shi, Pengfei Zhao, Zhengzhao Gu, Ye Li

“…While traditional planting strategies focused on parameters like seed depth, speed, and spacing, they often neglected environmental sustainability and adaptability to climate variability.MethodsTo bridge this gap, we introduced the Adaptive Precision Planter Optimization Model (APPOM), which leveraged real-time environmental sensing, machine learning, and multi-objective optimization to dynamically adjust key planting parameters. …”
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