Reinforcement Learning for Optimizing Renewable Energy Utilization in Buildings: A Review on Applications and Innovations by Panagiotis Michailidis, Iakovos Michailidis, Elias Kosmatopoulos

“…The integration of renewable energy systems into modern buildings is essential for enhancing energy efficiency, reducing carbon footprints, and advancing intelligent energy management. …”
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Permanent Magnets in Sustainable Energy: Comparative Life Cycle Analysis by Svetlana Orlova, Anton Rassõlkin

“…Methodological issues such as data quality, choice of functional units, and system complexity affect LCA accuracy, as inconsistencies in data or scope led to potential distortions in environmental assessments. …”
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Fault Diagnosis of Power Equipment Based on Improved SVM Algorithm by Youle Song, Yuting Duan, Tong Rao

“…However, fault diagnosis of power equipment faces challenges such as high dimensionality, complexity, and nonlinearity. Therefore, this study proposes an improved support vector machine model, combined with grey wolf optimization algorithm, aimed at improving the accuracy and efficiency of power equipment fault diagnosis. …”
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Evaluating the Effectiveness of Dimensionality Reduction on Machine Learning Algorithms in Time Series Forecasting by Rida Zaheer, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Ramzan Talib

“…High dimensionality of time series data can lead to computational inefficiencies and increased complexity. Dimensionality reduction techniques play a crucial role in handling the high-dimensional nature of time series data essential information while reducing computational complexity. …”
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Temporal Pyramid Alignment and Adaptive Fusion of Event Stream and Image Frame for Keypoint Detection and Tracking in Autonomous Driving by Peijun Shi, Chee-Onn Chow, Wei Ru Wong

“…Additionally, the framework incorporates a Dynamic Inference Path Selection mechanism, guided by input complexity, to optimize computational resource allocation, along with a dynamic noise suppression mechanism to improve the robustness of feature extraction. …”
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Quantitatively Distinguishing the Factors Driving Runoff and Sediment Yield Variations in Karst Watersheds by Si Cheng, Xingxiu Yu, Zhenwei Li, Xianli Xu, Kelin Wang

“…To address this issue, the Pearson correlation and random forest were first to select the dominant factors influencing runoff and SY. …”
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Genetic variability of soybean pod maturity traits for environmental resilience and stress resistance using the Hayman model by G.W.A. Susanto, A. Sulistyo, M.J. Mejaya, R.D. Purwaningrahayu, Y. Prayogo, F.C. Indriani, R. Budiono, S.W. Indiati, M.S.Y.I. Bayu

“…Cross-diallel statistical analysis and genetic variant components were estimated using the Hayman method.FINDINGS: The study showed that soybean pods' maturity (GJ-1, GJ-2, GJ-3, DL-1, and DL-2) had complex gene actions, namely additive, non-additive and reciprocal effects. …”
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Developing stock sentiment rank metric for forecasting stock sentiments: a statistical perspective by Rachna Sable, Aman Singh, Sudhanshu Gupta, Shivani Goel, Pallavi Parlewar

“…The research offers an overview of models based on scalability metrics, assessment delay, deployment costs, implementation of complexity, and accuracy. This paper delves further into the limitations and complexities of sentiment analysis in the stock market, offering suggestions for future research to tackle these issues. …”
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OSBF: One-Sided Box Filter for Edge-Preserving Image Processing by Yuanhao Gong

“…Such selection imposes the non-linearity, which preserves the edges and corners. …”
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Optimizing Labour Contractor Choices with MCDM: A Modern Approach to Construction Management by Khartode Bhagyashree, Shewale Manisha, Gobinath R.

“…The proposed system offers a practical and innovative approach to address the complexities associated with labour contractor selection, ultimately leading to optimized resource utilization and enhanced project outcomes.…”
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A Lightweight Deep Learning Network with an Optimized Attention Module for Aluminum Surface Defect Detection by Yizhe Li, Yidong Xie, Hu He

“…Additionally, we introduced an optimized Convolutional Block Attention Module (CBAM) to further enhance network efficiency. Furthermore, we employed the genetic K-means algorithm to optimize prior region selection, and a lightweight Ghost model to reduce network complexity by 14.3%, demonstrating the superior performance of the Ghost model in terms of loss function optimization during training and validation as well as in terms of detection accuracy, speed, and stability. …”
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Interference Reduction by Millimeter Wave Technology for 5G-Based Green Communications by Tin-Yu Wu, Tse Chang

“…Because the number of macro-cells will affect the communication quality and the computational complexity, this paper especially focuses on three factors of a network: delay, capacity, and path loss, and purposes to figure out the most energy-efficient BS densities for 5G-based green communications.…”
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Fast Nonparametric Inference of Network Backbones for Weighted Graph Sparsification by Alec Kirkley

“…We then construct an efficient and provably optimal greedy algorithm to identify the backbone minimizing our objectives, whose run-time complexity is log-linear in the number of edges. …”
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Assessing Lightweight Folding UAV Reliability Through a Photogrammetric Case Study: Extracting Urban Village’s Buildings Using Object-Based Image Analysis (OBIA) Method by Junyu Kuang, Yingbiao Chen, Zhenxiang Ling, Xianxin Meng, Wentao Chen, Zihao Zheng

“…The classification accuracy of the three selected algorithms exceeded 80%, with the KNN classifier achieving an accuracy of 91% and a Kappa coefficient of 0.87, which robustly demonstrate the reliability of the UAV data and validate the feasibility of the proposed approach in complex cases. …”
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Mangrove Extraction Algorithm Based on Orthogonal Matching Filter-Weighted Least Squares by Yongze Li, Jin Ma, Dongyang Fu, Jiajun Yuan, Dazhao Liu

“…However, mangroves typically grow in coastal and near-shore areas with complex water colors, where traditional mangrove extraction algorithms face challenges such as unclear region segmentation and insufficient accuracy. …”
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Comparison of active site mutations at subsite + 2 of Anoxybacillus ayderensis A9 β-glucosidase for hydrolysis of pNPG and polydatin by Numan Saleh Zada, Ali Osman Belduz, Abdulrahman H. Alessa, Halil Ibrahim Güler, Mine Karaoğlan, Malik Badshah, Aamer Ali Shah, Aasia Kalsoom, Samiullah Khan

“…Based on structural and bioinformatics analysis an area near + 2 subsite of the active site pocket of BglA9 was selected and single point mutations were introduced with the aim to enhance the catalytic efficiency of the enzyme towards pNPG and polydatin. …”
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Promiscuity in Polyphenol–Protein Interactions—Monitoring Protein Conformational Change upon Polyphenol–Protein Binding by Nano-Differential Fluorimetry (Nano-DSF) by Dorothea Schmidt, Amelie Wohlers, Nikolai Kuhnert

“…As a major advantage, measurements are carried out at a high dilution, avoiding the precipitation of polyphenol–protein complexes, allowing the rapid and efficient acquisition of quantitative and qualitative binding data. …”
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Bayesian curriculum generation in sparse reward reinforcement learning environments by Onur Akgün, N. Kemal Üre

“…Successful task completion triggers the generation of more complex tasks, whereas encountering challenges results in the maintenance or minor adjustment of task complexity. …”
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Evaluation of automated streaking patterns in urine culture for clinical workflow optimization by Yasuhide Kawamoto, Norihito Kaku, Norihiko Akamatsu, Fujiko Mitsumoto-Kaseida, Takahiro Takazono, Kosuke Kosai, Hiroo Hasegawa, Koichi Izumikawa, Hiroshi Mukae, Katsunori Yanagihara

“…This study highlighted the critical role of streaking pattern selection in automated streaking systems. While the performance varied depending on the bacterial load and sample complexity, certain patterns demonstrated superior single-colony isolation and consistency. …”
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Sulfonic acid-functionalised zeolites for fructose dehydration into 5-hydroxymethylfurfural by Huaizhong Xiang, Yao Zhang, Xin Zhong, Boji Wang, Charalampos Drivas, Mark A Isaacs, Aina Syahida Jamal, Zhipeng Qie, Qiang Zhang, Shaojun Xu, Jesús Esteban, Christopher M A Parlett, Xiaolei Fan

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