Deterministic Quantum Dense Coding Based on Non-Maximal Entangled Channel by Xuanxuan Xin, Zhixing Li, Zhen Wang

“…Our scheme represents a substantial improvement over existing probabilistic methods and paves the way for more efficient quantum communication protocols.…”
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Transforming user story definition: From deterministic to AI-powered automation by Andra-Paula AVASILOAIE, Augustin SEMENESCU, Eduard-Cristian POPOVICI, Ionuț-Cosmin CHIVA

“…Despite its efficiency, the deterministic tool lacked adaptability across different domains. …”
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Deterministic nanoantenna array design for stable plasmon-enhanced harmonic generation by Jeong Tae-In, Oh Dong Kyo, Kim San, Park Jongkyoon, Kim Yeseul, Mun Jungho, Kim Kyujung, Chew Soo Hoon, Rho Junsuk, Kim Seungchul

“…This spatial beam inhomogeneity can cause power instability of the emitted harmonics when the lateral beam position is not stable which we observed in plasmon-enhanced third-harmonic generation (THG). Hence, we propose a method for deterministically designing the density of a nanoantenna array to decrease the instability of the beam position-dependent THG yield. …”
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Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis by Ben Gabrielson, Hanlu Yang, Trung Vu, Vince Calhoun, Tulay Adali

“…These methods’ efficiencies are often due to their randomized natures; however, deterministic methods can provide better approximations, and can perform feature selection, highlighting a meaningful subset that well-represents the entire tensor. …”
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Energy-efficient control of thermal comfort in multi-zone residential HVAC via reinforcement learning by Zheng-Kai Ding, Qi-Ming Fu, Jian-Ping Chen, Hong-Jie Wu, You Lu, Fu-Yuan Hu

“…Energy efficient control of thermal comfort has been already an important part of residential heating, ventilation, and air conditioning (HVAC) systems. …”
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An Under-Sampled Line Array Element Signal Reconstruction Method Based on Compressed Sensing Theory by Tongjing SUN, Mengwei ZHOU, Lei CHEN

“…This method is not limited by the array configuration and constructs a deterministic measurement matrix that satisfies the restricted isometry property (RIP). …”
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Fast and Deterministic Underwater Point Cloud Registration for Multibeam Echo Sounder Data by Liang Zhao, Lan Cheng, Tingfeng Tan, Chun Cao, Feihu Zhang

“…Given the prevalence of outliers and noise in underwater acoustic measurements, the BnB method is employed to provide globally deterministic solutions. …”
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AI-assisted super-resolution cosmological simulations IV: An emulator for deterministic realizations by Xiaowen Zhang, Patrick Lachance, Ankita Dasgupta, Rupert A. C. Croft, Tiziana Di Matteo, Yueying Ni, Simeon Bird, Yin Li

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RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…These methods have high computational costs and are not efficient for real-time applications.MethodsTo address these issues, this paper presents a Quantum-behaved Particle Swarm Optimization model enhanced by deep reinforcement learning (RL-QPSO Net) aimed at improving global optimality and adaptability in path planning. …”
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Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense network by Xue WANG, Jing LIU, Jiani SUN, Jizhen ZHANG, Zhihong QIAN

“…In order to solve problems of high power consumption, spectrum shortage and low energy efficiency in the ultra-intensive 5G mobile communication scenario, a resource allocation algorithm based on the maximum energy efficiency for the two-layer heterogeneous cellular non-orthogonal multiple access network was proposed.The original NP-hard optimization problem on the downlink communication link of ultra-dense scene was divided into two subproblem, such as frequency resource allocation and power allocation, which became a deterministic constraint optimization problem.The frequency resource allocation scheme of different user groups was obtained by using base station clustering based on the improved k-means algorithm and users grouping based on spectral clustering algorithm.The fraction of energy efficiency optimization was transformed into a solvable continuous convex optimization problem and power distribution was realized by Dinkelbach method, and the Lagrange multiplier iterative algorithm, respectively.Jointly optimize system energy efficiency in terms of base station clustering, user grouping, resource block allocation and power allocation, which minimized the inter-cluster interference and intra-cluster interference of the base station efficiently.The simulation results show that the proposed algorithm is better on energy efficiency and computational efficiency compared with existing algorithms.…”
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Multi robot exploration using an advanced multi-objective salp swarm algorithm for efficient coverage and performance by Ali El Romeh, Seyedali Mirjalili

“…AMET combines the deterministic structure of Coordinated Multi-Robot Exploration (CME) with the adaptive search capabilities of the Multi-Objective Salp Swarm Algorithm (MSSA) to achieve a balanced trade-off between exploration efficiency and mapping accuracy. …”
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Hybrid lion and exponential PSO-based metaheuristic clustering approach for efficient dynamic data stream management by M. Ananthi, K. Valarmathi, A. Ramathilagam, R. Praveen

“…It adopted different methods of stochastic optimization and deterministic clustering techniques for centring the clusters in an optimal manner. …”
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EADRL: Efficiency-aware adaptive deep reinforcement learning for dynamic task scheduling in edge-cloud environments by J. Anand, B. Karthikeyan

“…Experimental evaluations demonstrate that EADRL achieves significant improvements over existing benchmark methods, including DRL-based approaches such as Double DQN (DDQN), Deep Deterministic Policy Gradient (DDPG), and Server Real-Time Performance Deep Reinforcement Learning (SRP-DRL), as well as heuristic-based methods like Best-Fit, Random, and Earliest Idle Time First (EITF). …”
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Disrupted topologic efficiency of white matter structural connectome in migraine: a graph-based connectomics study by Yanliang Mei, Dong Qiu, Zhonghua Xiong, Xiaoshuang Li, Peng Zhang, Mantian Zhang, Xue Zhang, Yaqing Zhang, Xueying Yu, Zhaoli Ge, Zhe Wang, Binbin Sui, Yonggang Wang, Hefei Tang

“…However, there is a paucity of research employing graph theory analysis to explore changes in the whole brain structural networks in patients with CM and EM. Methods The individual structural brain connectome of 60 patients with CM, 34 patients with EM, and 39 healthy control participants were constructed by using deterministic diffusion-tensor tractography. …”
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Distributed Unmanned Aerial Vehicle Cluster Testing Method Based on Deep Reinforcement Learning by Dong Li, Panfei Yang

“…In the process of the collaborative work of Unmanned Aerial Vehicle (UAV) clusters, the cluster communication node test is often carried out by a single-node test, which leads to poor topology and robustness of the overall network system, an imbalanced communication network load, and high complexity of the communication test, which seriously affects the diversified needs of current users and the efficiency of large-scale task processing. To solve this problem, a distributed method for UAV cluster testing, called UTDR (distributed UAV cluster Testing method by using Deep Reinforcement learning), based on the Deep Deterministic Policy Gradient (DDPG) is proposed in this work. …”
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Secure THz Communication in 6G: A Two-Stage DRL Approach for IRS-Assisted NOMA by Muhammad Shahwar, Manzoor Ahmed, Touseef Hussain, Muhammad Sheraz, Wali Ullah Khan, Teong Chee Chuah

“…Utilizing the deep deterministic policy gradient (DDPG) algorithm, we introduce a two-stage policy learning approach designed to optimize secrecy energy efficiency (SEE) while ensuring secure communication, even in the presence of multiple eavesdroppers (Eves). …”
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A novel discontinuous-Galerkin deterministic neutronics model for fusion applications: development and benchmarking by Timo J. Bogaarts, Felix Warmer

“…Fast predictive neutronic capabilities are therefore crucial for an efficient design process. For this purpose, we have developed a new deterministic neutronics method, capable of quickly and accurately assessing the neutron response of a fusion reactor, even in three-dimensional geometry. …”
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Deterministic Trajectory Design and Attitude Maneuvers of Gradient-Index Solar Sail in Interplanetary Transfers by Marco Bassetto, Giovanni Mengali, Alessandro A. Quarta

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Linearized MILP Model With Improved Soft Actor-Critic Algorithm for Dynamic and Efficient Active Distribution Network Planning by Jinlin Liao, Guilian Wu, Jia Lin

“…Finally, the feasibility and efficiency of the proposed method are verified by comparing the proposed MILP model and the traditional nonlinear planning model for distributed networks through multi-scenario case analysis. …”
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Highly durable and energy‐efficient probabilistic bits based on h‐BN/SnS2 interface for integer factorization by Joon‐Kyu Han, Jun‐Young Park, Shania Rehman, Muhammad Farooq Khan, Moon‐Seok Kim, Sungho Kim

“…Recent advancements in probabilistic computing approaches have demonstrated significant potential for addressing these problems more efficiently than conventional deterministic computing methods. …”
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