A Study of Everyday Aesthetics and (De)Alienation in Wim Wenders’ Alice in the Cities by Zakia Kalam

“…The article will also explore Wenders’ technique of defamiliarization as a method to critically highlight the transformative potential of everyday. …”
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Automatic Registration of Multi-Temporal 3D Models Based on Phase Congruency Method by Chaofeng Ren, Kenan Feng, Haixing Shang, Shiyuan Li

“…The second experiment further reveals the significant impact of different 3D transformation models. The experimental results show that the coordinates obtained based on position and orientation system (POS) data have significant positioning errors, while the method proposed in this study can reduce the coordinate errors between the two-period models. …”
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Deep Reinforcement Learning-Based Distribution Network Planning Method Considering Renewable Energy by Liang Ma, Chenyi Si, Ke Wang, Jinshan Luo, Shigong Jiang, Yi Song

“…Finally, the representative test case is selected to verify the effectiveness of the proposed method, which indicates that the proposed method can improve the efficiency of DNP and promote the digital transformation of DNP.…”
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Inoculation method and disease evaluation of tomato chlorotic virus (ToCV) in Solanum lycopersicum by Dan Zhao, Tianchen Xia, Tao Zhou, Lifu Zhao, Xiaoping Zhu, Biao Gong

“…Here, we presented a method for constructing the ToCV-infectious clones using binary vector pCass-Rz and Agrobacterium-mediated transformation system. …”
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Recent Advances in Deep Learning-Based Spatiotemporal Fusion Methods for Remote Sensing Images by Zilong Lian, Yulin Zhan, Wenhao Zhang, Zhangjie Wang, Wenbo Liu, Xuhan Huang

“…Nevertheless, traditional fusion methods often encounter difficulties when dealing with complicated fusion scenarios. …”
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A Collaborative Transit Signal Priority Method Considering Gaming among Traffic Participants by Bing Wu, Haishan Wang, Yanli Wang, Ben Zhai, TanXing Xue

“…Different from previous studies, Co-TSP uses game theory to realize collaborative optimization, instead of transforming the problem into a single objective optimization problem by weighting. …”
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Deep learning vulnerability detection method based on optimized inter-procedural semantics of programs by Yan LI, Weizhong QIANG, Zhen LI, Deqing ZOU, Hai JIN

“…In recent years, software vulnerabilities have been causing a multitude of security incidents, and the early discovery and patching of vulnerabilities can effectively reduce losses.Traditional rule-based vulnerability detection methods, relying upon rules defined by experts, suffer from a high false negative rate.Deep learning-based methods have the capability to automatically learn potential features of vulnerable programs.However, as software complexity increases, the precision of these methods decreases.On one hand, current methods mostly operate at the function level, thus unable to handle inter-procedural vulnerability samples.On the other hand, models such as BGRU and BLSTM exhibit performance degradation when confronted with long input sequences, and are not adept at capturing long-term dependencies in program statements.To address the aforementioned issues, the existing program slicing method has been optimized, enabling a comprehensive contextual analysis of vulnerabilities triggered across functions through the combination of intra-procedural and inter-procedural slicing.This facilitated the capture of the complete causal relationship of vulnerability triggers.Furthermore, a vulnerability detection task was conducted using a Transformer neural network architecture equipped with a multi-head attention mechanism.This architecture collectively focused on information from different representation subspaces, allowing for the extraction of deep features from nodes.Unlike recurrent neural networks, this approach resolved the issue of information decay and effectively learned the syntax and semantic information of the source program.Experimental results demonstrate that this method achieves an F1 score of 73.4% on a real software dataset.Compared to the comparative methods, it shows an improvement of 13.6% to 40.8%.Furthermore, it successfully detects several vulnerabilities in open-source software, confirming its effectiveness and applicability.…”
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Dual-context enhanced knowledge representation learning method in hyper-relational knowledge graphs by Jiahang Li, Qilong Han, Dan Lu, Lijie Li

“…This operation addresses the issue that most methods neglect the learning of relation representations, with these methods typically updating using a parameter matrix without considering the crucial information within HKGs. …”
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Liver Semantic Segmentation Method Based on Multi-Channel Feature Extraction and Cross Fusion by Chenghao Zhang, Lingfei Wang, Chunyu Zhang, Yu Zhang, Peng Wang, Jin Li

“…To address these challenges, this study proposes an improved U-Net-based liver semantic segmentation method that enhances segmentation performance through optimized feature extraction and fusion mechanisms. …”
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RESEARCH OF METHODS TO SUPPORT DATA MIGRATION BETWEEN RELATIONAL AND DOCUMENT DATA STORAGE MODELS by Mariia Peretiatko, Mariia Shirokopetleva, Natalya Lesna

“…The following results were obtained: the possibilities of relational algebra and set theory in the context of data models and queries are used, as well as in model redesign, the strategy of migration of data models is chosen, which provides relational and document-oriented data models, the algorithm of application of this method is described. Conclusions: because of the work, the main methods of migration support for different data storage models are analyzed, with the help of relational algebra, set theory a mathematical model is built, and an algorithm for transforming a relational data model into a document-oriented data model is taken into account. …”
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A Small-Sample Scenario Optimization Scheduling Method Based on Multidimensional Data Expansion by Yaoxian Liu, Kaixin Zhang, Yue Sun, Jingwen Chen, Junshuo Chen

“…Therefore, this paper proposes a small-sample scenario optimization scheduling method based on multidimensional data expansion. Firstly, based on spatial correlation, the daily power curves of PV power plants with measured power are screened, and the meteorological similarity is calculated using multicore maximum mean difference (MK-MMD) to generate new energy output historical data of the target distributed PV system through the capacity conversion method; secondly, based on the existing daily load data of different types, the load historical data are generated using the stochastic and simultaneous sampling methods to construct the full historical dataset; subsequently, for the sample imbalance problem in the small-sample scenario, an oversampling method is used to enhance the data for the scarce samples, and the XGBoost PV output prediction model is established; finally, the optimal scheduling model is transformed into a Markovian decision-making process, which is solved by using the Deep Deterministic Policy Gradient (DDPG) algorithm. …”
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Application of the generalized point source method for solving boundary value problems of mathematical physics by Sergey Yu. Knyazev, Elena E. Shcherbakova

“…Materials and Methods . The proposed method is based on the transformation of the original mathematical physics equation to a simpler inhomogeneous equation with the known fundamental solution. …”
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Study on the stability of waste rock filling in goaf based on dynamic comprehensive analysis method by Gongyong Wu, Xingxin Nie, Linhai Zhao, Zongli Li

“…It specifically focused on an individual underground metal mine cavity by integrating numerical simulation analysis techniques with onsite displacement monitoring methods. By simulating stress-strain conditions during different stages of cavity formation and subsequent treatments while considering onsite displacement monitoring data, this study extensively analyzed how these treatments impact rock stress levels, strain conditions within rocks themselves, and the stability of the surface riverbed. …”
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Spatiotemporal coupling and regional differences analysis between agricultural land use efficiency and rural revitalization in the Yellow River Basin by Shuai Liu, Hao Zhang, Guoxin Jiang

“…In this regard, we put forward suggestions such as transforming the primitive development mode, adhering to the concept of integrated basin development, and emphasizing regionally differentiated policies to provide inspiration for achieving coupling coordination between the two.…”
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A robust encrypted traffic identification scheme based on graph neural network by LI Mengxiang, PENG Chuang, WANG Hao, HUANG Chaoming, TAN Xiaobin

“…The current methods for identifying network traffic are generally designed and tested for specific network environments or datasets, making it difficult to generalize and apply to complex and ever-changing actual network environments. …”
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Se suspendre aux lendemains de Fessenheim – une approche croisée sur les traces visibles et invisibles d’un territoire nucléaire en transformation. by Élise Alloin, Florence Fröhlig

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Effect of Thawing and Reheating Methods on Quality and Volatile Flavor of Frozen Prepared Monopterus albus by PAN Yang, LI Han, ZHANG Ying, YANG Qian, CHEN Jiwang, LIAO E

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Understanding software solutions in the routines of administrative employees of an oil company by Eduardo Starling do Rego Monteiro, Erick Cardoso da Silva Figueira, Sandra Regina da Rocha-Pinto

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Analyzing Racial Differences in Imaging Joint Replacement Registries Using Generative Artificial Intelligence: Advancing Orthopaedic Data Equity by Bardia Khosravi, MD, MPH, MHPE, Pouria Rouzrokh, MD, MPH, MHPE, Bradley J. Erickson, MD, PhD, Hillary W. Garner, MD, Doris E. Wenger, MD, Michael J. Taunton, MD, Cody C. Wyles, MD

“…By visualizing race-based differences, this method aids in identifying bias in downstream tasks, fostering the development of fairer healthcare practices.…”
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Solving American Option Pricing Models by the Front Fixing Method: Numerical Analysis and Computing by R. Company, V. N. Egorova, L. Jódar

“…This paper presents an explicit finite-difference method for nonlinear partial differential equation appearing as a transformed Black-Scholes equation for American put option under logarithmic front fixing transformation. …”
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