Deep reinforcement learning based task allocation mechanism for intelligent inspection in energy Internet by Siya XU, Yifei XING, Shaoyong GUO, Chao YANG, Xuesong QIU, Luoming MENG

“…In order to reduce the cost and improve efficiency of power line inspection, UAV (unmanned aerial vehicle), which use mobile edge computing technology to access and process service data, are used to inspect power lines in the energy internet.However, due to the dynamic changes of UAV data transmission demand and geographical location, the edge server load will be unbalanced, which causes higher service processing delay and network energy consumption.Thus, an intelligent inspection task allocation mechanism for energy internet based on deep reinforcement learning was proposed.First, a two-layer edge network task offloading model was established to archive joint optimization of multi-objectives, such as delay and energy consumption.It was designed by comprehensively considering the route of UAV and edge nodes, different demands of services and limited service capabilities of edge nodes.Furthermore, based on Lyapunov optimization theory and dual-time-scaled mechanism, proximal policy optimization algorithm based deep reinforcement learning was used to solve the connection relationship and offloading strategy of edge servers between fixed edge sink layer and mobile edge access layer.The simulation results show that, the proposed mechanism can reduce the service request delay and system energy consumption while ensuring the stability of system.…”
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Study on Single Cycle Production Allocation and Supply Strategy for DCEs Based on the CVaR Criterion by Leiyan Xu, Zhiqing Meng, Gengui Zhou, Yunzhi Mu, Minchao Zheng

“…Subsequently, an approximate algorithm for solving the optimal total production amount is presented. …”
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Fuzzy Coordinated PI Controller: Application to the Real-Time Pressure Control Process by N. Kanagaraj, P. Sivashanmugam, S. Paramasivam

“…The proposed control algorithm is experimentally implemented for the real-time pressure control of a pilot air tank system and validated using a high-speed 32-bit ARM7 embedded microcontroller board (ATMEL AT91M55800A). …”
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Cluster-projected matrix product state: Framework for engineering exact quantum many-body ground states in one and two dimensions by Hidehiro Saito, Chisa Hotta

“…The key to find such a solution is a systematic protocol, which projects out excited states on every cluster using MPS and effectively entangles the cluster states. This algorithm not only offers an exact solution to general frustration-free Hamiltonian, but even provide the excited eigenstates by setting a proper target. …”
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Traffic classification in SDN-based IoT network using two-level fused network with self-adaptive manta ray foraging by Mohammed A. Aleisa

“…This paper presents a novel traffic classification framework for SDN-based IoT networks, introducing a Two-Level Fused Network integrated with a self-adaptive Manta Ray Foraging Optimization (SMRFO) algorithm. The framework automatically selects optimal features and fuses multi-level network insights to enhance classification accuracy. …”
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An outlook on structural biology after AlphaFold: tools, limits and perspectives by Serena Rosignoli, Maddalena Pacelli, Francesca Manganiello, Alessandro Paiardini

“…Indeed, user‐driven intervention is still as pivotal in the structure prediction process as in complementing state‐of‐the‐art algorithms with functional and biological knowledge.…”
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Load-to-store: exploit the time leakage of store buffer transient window by Ming TANG, Yifan HU

“…To research the vulnerability of modern microarchitecture and consider the mitigation, memory order buffer which was responsible for managing the execution order of memory access instructions was analyzed and found that load forward would directly bypass the data of dependent store instructions to load instructions, and speculative load would execute independent load instructions in advance.While bring efficiency optimizations, it might also lead to errors and corresponding blocking.The existing optimization mechanisms on the Intel Coffee Lake microarchitecture, and the leak attack scheme by using them were analyzed.Using the four execution modes of MOB and the corresponding duration, a variety of attacks were constructed including transient attack, covert channel, and recovery of the private key of the cryptographic algorithm.The time difference caused by MOB was used to leak the address of memory instructions, and the implementation of AES T table was attacked.Key recovery experiments were conducted on AES-128 with OpenSSL 3.0.0 on an Intel i5-9400 processor.The experimental results show that 30 000 sets of samples can recover a key byte with a probability of 63.6%.Due to the characteristics of memory order buffer, the concealment of the exploit is better than traditional cache time leaks.…”
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An Investigation of the Feasibility of Feedstock to Support the UK’s Sustainable Aviation Fuel Goals by Rebecca J. Chapman, Anton Hettiarachchige Don

“…These findings are fed into a novel weighting algorithm that is designed to assess a number of factors, including various technical characteristics and feasibility studies, as well as produce a detailed outlook of the future potential of each fuel blend. …”
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Modeling and Dynamical Analysis of the Water Resources Supply-Demand System: A Case Study in Haihe River Basin by Chongli Di, Xiaohua Yang

“…Then, the gray code hybrid accelerating genetic algorithm (GHAGA) is adopted to identify the unknown parameters of the system based on the statistic data (1998–2009). …”
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Cognitive Optimization in Assistive Living System Development by Alan Bowling, Fillia Makedon

“…Support for this approach stems from the artificial intelligence field where optimization is considered to be a critical aspect of cognition, and from the similarity between the performance metrics for the two problem domains. A search algorithm is developed using the bracketing and gradient methods as inherited knowledge. …”
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Gear Fault Diagnosis Based on APIT-SA-MEMD and FLLE by Ji Haofei, Liu Huiling, Dong Jiaqiang

“…To solve this problem, an intelligent fault diagnosis method based on adaptive projection intrinsically transformation sine-assisted multivariate empirical mode decomposition (APIT-SA-MEMD) and Floyd local linear embedding (FLLE) algorithm is proposed. Multivariate empirical mode decomposition of adaptive projection intrinsically transformation has modal aliasing phenomenon, so APIT-SA-MEMD is proposed to reduce the modal aliasing phenomenon existing in traditional empirical mode decomposition. …”
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Using rule association to generate data collection policies by Pei CHEN, Fenghua LI, Zifu LI, Yunchuan GUO, Lin CHENG

“…Collecting security-related data of devices effectively is the foundation of analyzing network threats accurately.Existing data collection methods (full data collection, sampling based data collection and adaptive data collection) do not consider the validity of the collected data and their correlation, which will consume too much collection resources, resulting in low collection yield.To address this problem, considering the factors (relationship between node attributes, network topology relationship, threat status, node resource and node similarity) that impact collection costs and benefits, a rule association method to generate collection policies was designed.In the method, two types of association rules (inter-node association rules and inter-event association rules) were adopted to generate candidate data collection items and reduced the scope of data collection.Then, a multi-objective program was designed to maximize collection benefits and minimize collection costs.Further, a genetic algorithm was designed to solve this program.Proposed method was compared with existing data collection methods.The experimental results show that the number of the collected data records of proposed method is 1 000~3 000 less than that of others per 12 hours, and the validity of the collected data of proposed method is about 4%~10% higher than others, which proves the effectiveness of the proposed method.…”
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Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board Game by Shahenda Sarhan, Mohamed Abu ElSoud, Hebatullah Rashed

“…So in this paper we proposed a new algorithm based on LSPI called Least-Squares Continuous Action Policy Iteration (LSCAPI). …”
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Cognitive Inference Device for Activity Supervision in the Elderly by Nilamadhab Mishra, Chung-Chih Lin, Hsien-Tsung Chang

“…To frame the CI-device, we propose a device design framework along with an inference algorithm and implement the designs through an artificial neural model with different configurations, mapping the CI-device’s functions to minimise the device’s prediction error. …”
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A new neurodynamic model with Adam optimization method for solving generalized eigenvalue problem by Ebrahim Ganjalipour, Khadijeh Nemati, Amir Hosein Refahi Sheikhani, Hashem Saberi Najafi

“…The experiments demonstrate that our algorithm using Adam optimizer, in comparison with other stochastic optimization methods like gradient descent works well in practice and improves complexity and accuracy of convergence.…”
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Enhanced Modeling and Control of Organic Rankine Cycle Systems via AM‐LSTM Networks Based Nonlinear MPC by Yang Sun, Ming Du, Xiao Qi

“…Furthermore, a multi‐objective optimization approach that integrates nonlinear model predictive control (NMPC) with the multiverse optimizer (MVO) algorithm is implemented to ensure effective control under varying operating conditions and constraints. …”
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Internal Leakage Diagnosis of a Hydraulic Cylinder Based on Optimization DBN Using the CEEMDAN Technique by Peng Zhang, Xinyuan Chen

“…The reconstructed signals are regarded as the input of the optimization DBN, and the particle swarm optimization simulated annealing (PSOSA) algorithm is adopted to identify the four internal leakage levels. …”
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Solving linear Fredholm-Stieltjes integral equations of the second kind by using the generalized Simpson’s rule by A. Asanov, S. Yanık

“…The graph of these results is plotted. An algorithm of this application is given by using Maple. …”
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Identification on the structures of block ciphers using machine learning by Ruiqi XIA, Manman LI, Shaozhen CHEN

“…Cryptographic identification is a critical aspect of cryptanalysis and a fundamental premise for key recovery.With the advancement of artificial intelligence, cryptanalysis based on machine learning has become increasingly mature, providing more effective methods and valuable insights for cryptographic identification.The distinguishability experiments were performed based on the Machine Learning to identify the structures of block ciphers in conditions of random keys.The identification of two structures of block ciphers from theoretical and experimental angles was studied.The differences of features in two structures’ cipher texts have been deduced by introducing the runs distribution index, feature distribution functions, KL-divergence, etc.After completing the feasibility research, experiments to identify the structures of two block ciphers using two Machine Learning models and the runs distribution index were conducted.The experiments were divided into two groups: single algorithm group and mixture algorithms group.It is found that the accuracy of both groups are more than 80%, which is around 40% higher than former work.The problem of identifying the structures of Block Ciphers in the conditions of random keys is solved in detail.Meanwhile, differences between the two structures of block ciphers are verified, which can serve as a reference for the design of cryptography algorithms.…”
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Development of a standardized data collection and intelligent fabric quality prediction system for the weaving department by Ning Dai, Lunjun Li, Kaixin Xu, Zhehao Lu, Xudong Hu, Yanhong Yuan

“…This study leverages the standardization and interoperability features of open platform communications unified architecture technology to facilitate data acquisition within the weaving department, establishing a reliable Internet of Things framework that supports subsequent fabric quality prediction, and optimizing the back propagation neural network through the K-means clustering algorithm and particle swarm optimization to predict the type and number of fabric defects. …”
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