Dynamic Split Computing Framework for Multi-Task Learning Models: A Deep Reinforcement Learning Approach by Haneul Ko, Sangwon Seo, Sangheon Pack

“…To minimize the average task completion time across multiple tasks and the energy consumption of the IoT device, we formulate a Markov decision process problem. The formulated problem is solved using a model-free DRL algorithm (i.e., a deep deterministic policy gradient). …”
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Double difference earthquake location with graph neural networks by Ian W. McBrearty, Gregory C. Beroza

“…Our results suggest that a GNN approach to double-difference relocation is a promising direction for scaling to very large catalogs and gaining new insights into the relocation problem. Graphical Abstract…”
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Development of Impact Factors Reverse Analysis Method for Software Complexes’ Support Automation by Andrii Pukach, Vasyl Teslyuk, Nataliia Lysa, Liubomyr Sikora

“…This research represents a corresponding and developed specialized impact factors reverse analysis method for software complexes’ support automation; it is intended for the analysis of impact factors affecting the supported software’s (or processes of its comprehensive support) subjective perception results, as one of the constituent tasks of the more complex problem of software complexes’ support automation. …”
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How do events shape the media agenda on Islam and Muslims in Western Europe? An analysis of news events in Germany, the UK and France (2000–2020) by Liriam Sponholz, Anna-Maria Meuth

“…However, negativity is an inherent feature of media logic. Defining Islam and Muslims as the problem e.g. the “bad news”, in turn, is neither inherent to media logic nor a natural consequence of events. …”
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A Method for Detecting Tomato Maturity Based on Deep Learning by Song Wang, Jianxia Xiang, Daqing Chen, Cong Zhang

“…Therefore, in this study, an improved YOLOv8 algorithm is proposed to address the problem of tomato fruit ripeness detection in complex scenarios, which is difficult to carry out accurately. …”
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Digital Spectral Analysis by means of the Method of Averag Modified Periodograms Using Binary-Sign Stochastic Quantization of Signals by V. N. Yakimov

“…A special feature of this quantization is the use of a randomizing uniformly distributed auxiliary signal as a stochastic continuous quantization threshold (threshold function). …”
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Improving the Efficiency of Heat Power Generation from Household Drains by S. N. Osipov, A. V. Zakharenko

“…In order to solve this problem an assessment of the existing theoretical and practical approaches to the provision of water flow in technological pipelines which allows determining the optimal value of the slope of the surface has been fulfilled.…”
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Recycling as a Strategic Direction to Improve Efficiency of Steel Industry in the Russian Federation by V. V. Smirnov

“…In this regard the Russian Federation faces the problem of re-creation of institutional foundation of metal scrap collection and recycling as well as creation of mechanisms to manage this industry efficiently. …”
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Hammering Test for Tile Wall Using Deep Learning by Atsushi Ito, Masafumi Koike, Masako Saito, Katsuhiko Hibino

“…Furthermore, because the test is conducted manually, it is time-consuming, especially for large-scale structures. The most critical problem is the shortage of skilled inspectors due to retirement. …”
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Cross-Domain Fault Diagnosis of Rotating Machinery Under Time-Varying Rotational Speed and Asymmetric Domain Label Condition by Siyuan Liu, Jinying Huang, Peiyu Han, Zhenfang Fan, Jiancheng Ma

“…In practical engineering, the asymmetric problem of the domain label space is inevitable owing to the prior fault information of the target domain being difficult to completely obtain. …”
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GAT-ADNet: Leveraging Graph Attention Network for Optimal Power Flow in Active Distribution Network With High Renewables by Dinesh Kumar Mahto, Mahipal Bukya, Rajesh Kumar, Akhilesh Mathur, Vikash Kumar Saini

“…To perform the optimal operation, OPF plays a pivotal role in solving a complex optimization problem due to the system’s operational constraints and the provided OPF solutions. …”
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Explainable artificial intelligence with fusion-based transfer learning on adverse weather conditions detection using complex data for autonomous vehicles by Khaled Tarmissi, Hanan Abdullah Mengash, Noha Negm, Yahia Said, Ali M. Al-Sharafi

“…Besides, the XAIFTL-AWCDAV model performs feature extraction by fusing three models: EfficientNet, SqueezeNet, and MobileNetv2. …”
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Prediction of microbe-drug associations using a CNN-Bernoulli random forest model by Zihao Song, Qingnuo Li, Jincheng Zhao, Qinggang Bu, Zekang Bian, Jia Qu

“…The model constructs feature vectors for all microbe-drug pairs based on known associations, microbe similarity, and drug similarity. …”
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Mobile malware detection method using improved GhostNetV2 with image enhancement technique by Yao Du, CaiXia Gao, Xi Chen, MengTian Cui, LiLi Xu, AoJi Ning

“…Abstract In recent years, image-based feature extraction and deep learning classification methods are widely used in the field of malware detection, which helps improve the efficiency of automatic malicious feature extraction and enhances the overall performance of detection models. …”
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Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…When a fault occurs in the distribution network, the sensor device based on optimal configuration collects fault feature data, combines it with the FCM clustering algorithm to classify nodes according to fault feature similarity, and divides the most significant fault-affected section as the core fault area. …”
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A Lightweight Method for Road Defect Detection in UAV Remote Sensing Images with Complex Backgrounds and Cross-Scale Fusion by Wenya Zhang, Xiang Li, Lina Wang, Danfei Zhang, Pengfei Lu, Lei Wang, Chuanxiang Cheng

“…Moreover, the CAA attention mechanism is employed to strengthen the model’s global feature extraction abilities; (2) a cross-scale feature fusion strategy known as GFPN is developed to tackle the problem of diverse target scales in road damage detection; (3) to reduce computational resource consumption, a lightweight detection head called EP-Detect has been specifically designed to decrease the model’s computational complexity and the number of parameters; and (4) the model’s localization capability for road damage targets is enhanced by integrating an optimized regression loss function called WiseIoUv3. …”
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Bayesian curriculum generation in sparse reward reinforcement learning environments by Onur Akgün, N. Kemal Üre

“…Diverging from traditional methodologies, this algorithm utilizes Bayesian networks to dynamically create tasks by altering problem parameters, thereby impacting task difficulty. …”
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Geography, poverty and development: An interdisciplinary debate / Geografi a, pobreza e desenvolvimento: um debate interdisciplinar by Anand Prasad Mishra

“…n emerging feature of contemporary development studies in India is the deployment of an interdisciplinary approach involving geographical location, level of poverty, nature of development and planning etc. …”
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Deriving structure from evolution: metazoan segmentation by Paul François, Vincent Hakim, Eric D Siggia

“…Abstract Segmentation is a common feature of disparate clades of metazoans, and its evolution is a central problem of evolutionary developmental biology. …”
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The Generation of 150 km Echoes Through Nonlinear Wave Mode Coupling by William J. Longley

“…Abstract A fundamental problem in plasma turbulence is understanding how energy cascades across multiple scales. …”
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