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IEEE Conference on Wireless Communications and Networking

作者： Mohammad Hatami Nhan Thanh Nguyen Markku Juntti Centre for Wireless Communications University of Oulu Finland

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

This work studies joint waveform design and subcarrier allocation in a multiuser multicarrier monostatic joint communications and sensing (JCAS) system. We aim to design the JCAS transmit waveform with subcarrier allocation that maximizes the energy efficiency (EE) of the multiuser communications subject to the constraints on the minimum communications and sensing signal-to-interference-plus-noise ratios (SINRs) and transmit power budget. The formulated EE design problem is a mixed-integer non-convex fractional program, which is highly challenging to solve directly. To overcome the challenges, we leverage alternating optimization (AO) and divide the original problem into two subproblems, namely, the waveform design and subcarrier allocation. For the non-convex fractional objective function in the waveform design, we propose an efficient method combining two typical techniques in fractional programming, namely, the quadratic and Dinkelbach transforms, along with successive convex approximation (SCA). For the subcarrier allocation, we leverage quadratic transform and penalty function method. Numerical results demonstrate the effectiveness of the proposed method, showing a significant improvement in energy efficiency compared to a baseline scheme.

关键词： Lapping Transforms Radar programming linear programming Energy efficiency Sensors Resource management Optimization Signal to noise ratio

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A Novel Optimal Power Flow Method for Distributed New Energy Participation in Electricity Market

A Novel Optimal Power Flow Method for Distributed New Energy...

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IEEE Asia Power and Energy Engineering Conference (APEEC)

作者： Chen Lyu Menghua Fan Zheng Zhao State Grid Energy Research Institute Beijing China

ISBN: (数字)9798331517540

ISBN: (纸本)9798331517557

Due to the limitations of large-scale scheduling and control technology for distributed new energy, it is currently difficult for China to carry out large-scale market-oriented trading of distributed new energy. In response to this issue, this article conducts research on the optimal power flow algorithm for active distribution networks based on semi definite programming. Firstly, based on the operational characteristics of actual components such as distributed new energy and controllable loads in the distribution network, an optimal power flow analysis model for active distribution networks considering high proportion of distributed power sources is established. On this basis, the scheduling control schemes of continuous controllable equipment and discrete controllable equipment are taken as independent variables, and a multivariate objective function is established that takes into account economic, safety, and environmental attributes. A semi definite programming based optimal power flow analysis and calculation model for active distribution networks is proposed. Finally, the effectiveness of the proposed method was verified using an IEEE33 node example.

关键词： Economics Analytical models Distribution networks programming linear programming Electricity supply industry Safety Active distribution networks Load flow analysis Load modeling

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A Simheuristic Approach Cooperating Skill Optimization Algorithm with Ordinal Optimization

A Simheuristic Approach Cooperating Skill Optimization Algor...

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International Colloquium on Signal Processing & Its Applications, CSPA

作者： Shih-Cheng Horng Shieh-Shing Lin Department of Computer Science & Information Engineering Chao yang University of Technology Taichung Taiwan R.O.C Department of Electrical Engineering St. John's University Taipei Taiwan R.O.C

ISBN: (数字)9798331522193

ISBN: (纸本)9798331522209

The constrained discrete optimization problems (CDOP) have a stochastic objective function and deterministic inequality constraints. The CDOP is NP-hard due to the large and exponentially growing solution space. The ordinal optimization framework is treated as a recognized framework for resolving NP-hard problems. A simheuristic approach cooperating skill optimization algorithm with ordinal optimization is developed to solve this CDOP in a short time. The simheuristic approach comprises two levels. The skill optimization algorithm is used to construct a differentiated subset with a cursory estimate at the first level. Then, the ranking and selection method is used to find a superior solution from differentiated subsets in the second level. Finally, the approach is applied to the multiple-item inventory system's stock level optimization problem. A real-life example with 5 potential customers and 3 products is used to test the performance. Simulation results reveal that the simheuristic approach can obtain stable and excellent results on the CDOP.

关键词： NP-hard problem Simulation Heuristic algorithms Metaheuristics linear programming Time complexity Optimization Portfolios

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Multi-Timescale Loss Reduction Optimization Study of Distribution Network Considering Flexible Charging of Electric Vehicles

Multi-Timescale Loss Reduction Optimization Study of Distrib...

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Electrical Automation and Artificial Intelligence (ICEAAI), International Conference on

作者： Ruogu Wang Qi Dong Xin Gao Xiaoteng Li Yanpeng Jin Yangyan Guo Electric Power science Research Institute State Grid Shaanxi Electric Power Company Xi'an Shaanxi China State Grid Shaanxi Electric Power Company Xi'an Shaanxi China Electric Power science Research Institute of State Grid Shaanxi Electric Power Company Xi'an Shaanxi China School of Electrical Engineering Xi'an University of Technology Xi'an Shaanxi China

ISBN: (数字)9798331506797

ISBN: (纸本)9798331506803

Aiming at the problems of uncertainty of wind and photovoltaic power output and disorderly charging of a large number of electric vehicles accessing the distribution network leading to the superposition of distribution network load peaks and the increase of network loss, a multi-timescale loss-reduction operation strategy of the distribution network considering electric vehicles is proposed. The probability distribution of EV behavior is established, and the EV charging output model conforming to the user's travel habit is built using the Latin hypercubic sampling method. Considering the influence of the deviation of the wind and photovoltaic output forecasts on different time scales, a multi-timescale optimal dispatch strategy based on the day-ahead-intraday is established, and a mathematical model is constructed by introducing the dynamic time-of-day tariff and using the network loss and the operating cost as the objective function. Different scenarios are simulated in the improved IEEE 33-bus system, and the comparative results show that the proposed optimization strategy is effective in reducing losses and smoothing load fluctuations, and the flexibility of EVs participating in the demand response of the grid reduces the impact of the wind and photovoltaic power integration while compensating for the deviation of the forecast of the wind and photovoltaic power outputs, thus maintaining the system balance.

关键词： Photovoltaic systems Uncertainty Smoothing methods Tariffs Distribution networks Optimal scheduling linear programming Mathematical models Wind forecasting Vehicle dynamics

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Enhancing Image Retrieval: A Survey and Insights on Feature Descriptor Preparation Methods

Enhancing Image Retrieval: A Survey and Insights on Feature ...

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International Symposium on Advanced Computing and Communication (ISACC)

作者： Srikanth Lukka Satya Keerthi Gorripati Department of Computer Science and Engineering AU TDR-HUB Andhra University Visakhapatnam Andhra Pradesh India Department of Computer Science and Engineering Gayatri Vidya Parishad College of Engineering (A) Visakhapatnam Andhra Pradesh India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

Feature descriptors play a crucial role in image retrieval by representing images in a compact and discriminative manner. This survey paper explores various techniques for preparing feature descriptors used in image retrieval systems. We categorize the approaches into traditional handcrafted descriptors and deep learning-based descriptors. For each category, we discuss popular techniques, their underlying principles, and their advantages and limitations. We also provide insights into recent advancements and benchmark datasets used for evaluation. In order to help academics and practitioners choose the best strategies for their applications, this survey attempts to give them a thorough grasp of feature descriptor preparation methods in image retrieval.

关键词： Surveys Codes Image retrieval Supervised learning Autoencoders Reinforcement learning Benchmark testing linear programming Intelligent systems Unsupervised learning

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A Deep Reinforcement Learning Object Detection Model Based on Improved Convolutional Attention Mechanism

A Deep Reinforcement Learning Object Detection Model Based o...

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International Conference on Communication Systems and Network Technologies (CSNT)

作者： Shengli Jiang Hongsheng Xu College of Electronic and Commerce Luoyang Normal University Luoyang China

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

Deep reinforcement learning is the combination of reinforcement learning and deep learning. Reinforcement learning is used to define the problem itself and optimize the objective function, and deep learning is used to solve the problems such as state representation and policy expression. The advantage of attention mechanism is the ability to focus on the important parts of the input information. Object detection is an important branch of computer vision. The detection accuracy is constantly improving, but it is still far from meeting the requirements of human beings. One of the main reasons is that the model lacks the ability to express the target to be detected. In order to solve the problem of low detection accuracy and slow speed in deep reinforcement learning object detection model, this paper proposes a deep reinforcement learning object detection model based on improved convolutional attention mechanism. Through experiments, it is found that the model has better performance in the detection task.

关键词： Attention mechanisms Accuracy Image recognition Object detection Deep reinforcement learning Feature extraction linear programming Classification algorithms Time factors Image classification

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Low-Correlation OFDM Waveform Design With Optimally Coded Sub-Carriers for the Joint Sensing and Communications

Low-Correlation OFDM Waveform Design With Optimally Coded Su...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Chunxuan Shi Yongzhe Li Ran Tao School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

We study the design of orthogonal frequency division multiplexing (OFDM) waveform for the joint sensing and communications (JSC), whose sub-carriers are to be optimally coded by a set of sequences. To obtain such waveform that simultaneously exploits frequency diversity and modulation flexibility for the JSC, we take the correlation level of waveform for sensing and the orthogonality of modulation sequences for communications into consideration. Specifically, we choose to minimize the integrated sidelobe level (ISL) of the OFDM waveform, and meanwhile, to ensure reasonable constraints enforced on sub-carriers with code modulations. In view of this, an ISL-minimization based design with respect to the modulation sequences is therefore formulated, which is generally non-convex. To tackle it, we introduce virtually auxiliary variables to help reformulate the original optimization problem, and then apply the framework of consensus alternating direction method of multipliers for finding solutions. Our major contributions also lie in elaborating an augmented Lagrangian for the newly obtained optimization problem via a first-order Taylor expansion on its objective function, based on which a closed-form solution is achieved for iterations. Simulation results verify the superiority of our proposed OFDM waveform design.

关键词： Closed-form solutions Speech coding OFDM Simulation Modulation Taylor series linear programming Sensors Speech processing Optimization

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A Spectral Projected Gradient Method for Computational Protein Design problem

arXiv

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arXiv 2025年

作者： Zheng, Yukai Li, Qingna School of Mathematics and Statistics Beijing Institute of Technology Beijing China School of Mathematics and Statistics Beijing Key Laboratory on MCAACI Beijing Institute of Technology Beijing China

In this paper, we consider the computational protein design (CPD) problem, which is usually modeled as 0/1 programming and is extremely challenging due to its combinatorial properties. As a quadratic semi-assignment problem (QSAP), the CPD problem has been proved to be equivalent to its continuous relaxation problem (RQSAP), in terms of sharing the same optimal objective value. However, since the current algorithm for solving this RQSAP uses the projected Newton method, which requires direct computation of the Hessian matrix, its computational cost remains quite high. Precisely for this reason, we choose to employ the spectral projected gradient (SPG) method to solve the CPD problem, whose effectiveness relies on choosing the step lengths according to novel ideas that are related to the spectrum of the underlying local Hessian. Specifically, we apply the SPG method in two distinct ways: direct solving the relaxation problem and applying a penalty method. Numerical results on benchmark instances verify the superior performance of our approach over the current algorithms in both quality and efficiency. © 2025, CC0.

关键词： linear programming

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Optimal Location Methodology for Multiple UPFCs to Reduce Transmission Congestion

Optimal Location Methodology for Multiple UPFCs to Reduce Tr...

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IEEE Southeastcon

作者： Muhammad Sarmad Tariq University of North Carolina Charlotte

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Transmission congestion is a major barrier between supplying cheap generation to load centers. Unified Power Flow Controller(UPFC) can help relive transmission congestion. For integrating a UPFC within the optimal power flow, a linear programming based formulation can be used which is easily implementable. Moreover, determining the optimal location of the UPFC is vital for maximizing the ability to manage the line loading of the power system. In this study, a simple and efficient method has been proposed, namely the Discrete Teaching Learning Based Optimization(DTLBO) to find the optimal location of multiple UPFCs for the 39 Bus and 118 Bus System.

关键词： Loading Education linear programming Power systems Topology Optimization Convergence Load flow

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Ranking-based Diversified Influence Maximization for Dynamic Social Networks

Ranking-based Diversified Influence Maximization for Dynamic...

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International Communication Systems and Networks and Workshops, COMSNETS

作者： Sunil Kumar Meena Shashank Sheshar Singh Kuldeep Singh Department of Computer Science University of Delhi New Delhi New Delhi India Department of Computer Science and Engineering Thapar Institute of Engineering and Technology Patiala India

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

Influence maximization (IM) is the task of selecting the most influential nodes in the network. IM achieves the goal of spreading information, influencing behaviour, or promoting sales of products. Existing studies in IM focus on maximizing the activated nodes in the static network and neglecting the communities. In this paper, we give a novel ranking-based algorithm that ranks the nodes based on their reachability and diversity. This paper proposes an objective function that considers both diversity and activated nodes to determine the diversity capability of the nodes. The proposed algorithm utilizes previous computation and integrates reachability centrality with the objective function to rank the nodes at a timestamp in a dynamic network. We execute the proposed and benchmark algorithms on five datasets. The experiments show that the suggested algorithm produces superior and competitive outcomes in comparison to the benchmark algorithms.

关键词： Social networking (online) Communication systems Heuristic algorithms Benchmark testing linear programming

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