Adaptive Context-Aware Generative Adversarial Network for Low-quality Image Enhancement by Xingyu Pan, Fengling Chen

“…However, current methods still face with two issues: (1) They commonly earn a deterministic generation mapping between low-quality and normal images via relying on pixel-level reconstruction, leading to improper brightness and noise in the enhancing process. (2) They use only one type of generative model, either explicit or implicit, which limits flexibility and efficiency of models. …”
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Differentiable Imaging: Progress, Challenges, and Outlook by Ni Chen, David J. Brady, Edmund Y. Lam

“…We identify emerging challenges in numerical modeling, computational efficiency, and system integration, with particular focus on how digital twin architectures may provide solutions for next-generation adaptive imaging systems. …”
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PSYCHOLOGICAL ASPECTS OF FORMATION OF A PRACTICE-ORIENTED ENVIRONMENT IN EDUCATIONAL INSTITUTIONS OF THE MINISTRY OF INTERNAL AFFAIRS OF RUSSIA by O. A. Ulyanina

“…The following main blocks of the program were highlighted and characterised: target, deterministic, content, medium, technological, analytically monitored, organisational and procedural. …”
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Generative adversarial models for extreme geospatial downscaling by Guiye Li, Guofeng Cao

“…Given an input, the method can produce a multitude of plausible high-resolution samples instead of one single deterministic result. …”
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Stochastic simulation of soil moisture dynamics in farmland in the eastern region of the Songnen Plain. by Bo Meng, Jin Wang, Fanxiang Meng, Ennan Zheng, Tianxiao Li, Bowen Tang

“…Soil moisture is the core of the hydrological cycle in agroecosystems, and most of the studies on soil moisture dynamics modeling adopt deterministic research methods, which are not well suited to study the hydrological processes in agricultural fields under changing conditions. …”
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Quantum reinforcement learning in continuous action space by Shaojun Wu, Shan Jin, Dingding Wen, Donghong Han, Xiaoting Wang

“…To overcome this limitation, we introduce a quantum Deep Deterministic Policy Gradient (DDPG) algorithm that efficiently addresses both classical and quantum sequential decision problems in continuous action spaces. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…To address these limitations, this study employs the covariance matrix decomposition method to generate 3D lognormal random fields for soil parameters, enabling efficient modeling of spatial variability. …”
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Optimization of Thermal Insulation Parameters for Vertical Perimeters in Buildings with Single-Layer Walls by Walery Jezierski, Paula Szczepaniak, Cezary Leszczyński

“…Using THERM 7.6 software for computational experiments, data were obtained to develop deterministic mathematical models of these relationships. …”
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An Improved Toeplitz Measurement Matrix for Compressive Sensing by Xu Su, Yin Hongpeng, Chai Yi, Xiong Yushu, Tan Xue

“…In this paper, Toeplitz matrix is employed and optimized as a deterministic measurement matrix. A hardware platform for signal efficient acquisition and reconstruction is built by field programmable gate arrays (FPGA). …”
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Time-Delayed Feedback Control in the Multiple Attractors Wind-Induced Vibration Energy Harvesting System by Qin Guo, Zhongkui Sun, Ying Zhang, Wei Xu

“…In the deterministic case, the time delay can control efficiently the birhythmic properties; thus one can realize a dividing line in the parameter plane that separates the space into two subspaces of generically distinct nature. …”
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Robust Traffic Signal Retiming Based on Queue Service Time Estimation Using Low-Penetration Connected Vehicle Data by Chengchuan An, Weihua Zhang, Yinpu Wang, Siping Ke, Jingxin Xia

“…However, the existing methods are mostly deterministic and do not well consider the uncertainty in both traffic demand and capacity. …”
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Degeneralization Algorithm for Generation of Büchi Automata Based on Contented Situation by Laixiang Shan, Jun Qin, Mingshi Chen, Zheng Qin

“…These ideas are implemented in a conversion algorithm used to build a property automaton corresponding to the given LTL formulae. We compare our method to previous work and show that it is more efficient for four sets of random formulae generated by LBTT.…”
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Bio-inspired cryptography based on proteinoid assemblies. by Panagiotis Mougkogiannis, Essam Ghadafi, Andrew Adamatzky

“…We present an innovative cryptographic technique inspired by the self-assembly processes of proteinoids-thermally stable proteins that form spontaneously under prebiotic conditions. By emulating the deterministic yet complex interactions within proteinoid assemblies, the proposed method generates secure encryption keys and algorithms. …”
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Decomposing Imaginary-Time Feynman Diagrams Using Separable Basis Functions: Anderson Impurity Model Strong-Coupling Expansion by Jason Kaye, Zhen Huang, Hugo U. R. Strand, Denis Golež

“…We present a deterministic algorithm for the efficient evaluation of imaginary-time diagrams based on the recently introduced discrete Lehmann representation (DLR) of imaginary-time Green’s functions. …”
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Leading Degree: A Metric for Model Performance Evaluation and Hyperparameter Tuning in Deep Learning-Based Side-Channel Analysis by Junfan Zhu, Jiqiang Lu

“…To attain an effective generic side-channel evaluation metric, we investigate the deterministic component of power consumption, find that the elements of score vector under a key follow a linearly transformed chi-square distribution approximately, and some wrong key hypotheses usually with top scores provide great assistance in model performance evaluation, and finally we propose a new metric called Leading Degree (LD) as well as its simplified version LD-simplified for measuring model performance, which offers similar accuracy but much better generality and efficiency compared with the classical side-channel benchmark metric TGE1, and offers similar generality and efficiency but significantly better accuracy compared with recently proposed sidechannel metrics like Label Correlation and Cross Entropy Ratio. …”
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Microfluidic device for both active and passive cell separation techniques: A review by Muhammad Asraf Mansor, Muhammad Asyraf Jamrus, Chong Kar Lok, Mohd Ridzuan Ahmad, Michal Petrů, Seyed Saeid Rahimian Koloor

“…In order to limit the extent of this work, our primary emphasis is on six common methods of cell separation: acoustophoresis, dielectrophoresis, magnetophoresis, inertial, pinched flow fractionation (PFF), and deterministic lateral displacement (DLD). …”
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FORECASTING AND OPTIMIZATION OF CATALYTIC CRACKING UNIT OPERATION UNDER CONDITIONS OF FUZZY INFORMATION by Narkez Boranbayeva, Batyr Orazbayev, Leila Rzayeva, Zhalal Karabayev, Murat Alibek, Baktygul Assanova

“…The complexity of this process and the presence of fuzzy information caused by fuzzy initial data require the development of new modeling and optimization methods. Existing traditional models based on deterministic methods are often insufficient under uncertainty. …”
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Artificial Intelligence in UAV Flight Controls: Deep Reinforcement Learning Based Altitude-Hold Strategies for Fixed-Wing UAVs by Hasan Raza Khanzada, Adnan Maqsood, Abdul Basit

“…The deep deterministic policy gradient (DDPG) method was chosen to suit environments with continuous action spaces. …”
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Quality of Experience Optimization for AR Service in an MEC Federation System by Huong Mai do, Tuan Phong Tran, Myungsik Yoo

“…We propose an improved deep deterministic policy gradient algorithm for efficient solution exploration. …”
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Longitudinal Hierarchical Control of Autonomous Vehicle Based on Deep Reinforcement Learning and PID Algorithm by Jialu Ma, Pingping Zhang, Yixian Li, Yuhang Gao, Jiandong Zhao

“…A hierarchical longitudinal control system that integrates deep deterministic policy gradient (DDPG) and proportional–integral–derivative (PID) control algorithms was proposed in this paper to ensure safe and efficient vehicle operation. …”
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