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arXiv 2025年

作者： Jaiswal, Ragesh Kumar, Amit Yadav, Jatin Department of Computer Science and Engineering IIT Delhi India

Sorting is one of the most basic primitives in many algorithms and data analysis tasks. Comparison-based sorting algorithms, like quick-sort and merge-sort, are known to be optimal when the outcome of each comparison is error-free. However, many real-world sorting applications operate in scenarios where the outcome of each comparison can be noisy. In this work, we explore settings where a bounded number of comparisons are potentially corrupted by erroneous agents, resulting in arbitrary, adversarial outcomes. We model the sorting problem as a query-limited tournament graph where edges involving erroneous nodes may yield arbitrary results. Our primary contribution is a randomized algorithm inspired by quick-sort that, in expectation, produces an ordering close to the true total order while only querying Õ(n) edges. We achieve a distance from the target order π within (3 + ǫ)|B|, where B is the set of erroneous nodes, balancing the competing objectives of minimizing both query complexity and misalignment with π. Our algorithm needs to carefully balance two aspects – identify a pivot that partitions the vertex set evenly and ensure that this partition is "truthful" and yet query as few "triangles" in the graph G as possible. Since the nodes in B can potentially hide in an intricate manner, our algorithm requires several technical steps that ensure that progress is made in each recursive step. Additionally, we demonstrate significant implications for the Ulam-k-Median problem. This is a classical clustering problem where the metric is defined on the set of permutations on a set of d elements. Chakraborty, Das, and Krauthgamer gave a (2 − Ε) FPT approximation algorithm for this problem, where the running time is super-linear in both n and d. We give the first (2 − Ε) FPT linear time approximation algorithm for this problem. Our main technical result gives a strengthening of the results in Chakraborty et al. by showing that a good 1-median solution can be obtained from a

关键词： approximation algorithms

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An Efficient Resource Allocation Technique for Efficient Virtual Machine Placement Using Local Neighbor Search and Stochastic Random Process

An Efficient Resource Allocation Technique for Efficient Vir...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Firoz Khan Faisal Kalota Jeevanandam Jotheeswaran Center of Information and Computer Science Ball State University Indiana USA Technology Enabled Learning Alliance University Bangalore India

ISBN: (数字)9798331520182

ISBN: (纸本)9798331520199

Cloud computing environments efficiently utilize resources by managing diverse cloud users through virtualization techniques. Virtualization enhances resource utilization in Physical Machines (PMs). This paper introduces an efficient virtual machine placement algorithm based on an Improved Genetic Algorithm, which minimizes the Average Resource Idle Time of active PMs, thereby improving overall resource utilization in cloud data centers. Genetic algorithms are effective optimization methods for achieving high accuracy with fewer iterations. However, they often encounter local optimum problems and quick convergence. The proposed algorithm addresses these issues and is implemented using the CloudSim Plus simulator in a standard cloud environment. Results indicate the algorithm reduces resource waiting time in PMs by approximately 52% compared to other algorithms. Additionally, it minimizes the Average Waiting Time and Average Turnaround Time for Virtual Machine placement. Performance analysis confirms its effectiveness, regardless of the number of Virtual Machine requests or available Physical Machines.

关键词： Cloud computing Data centers Green products approximation algorithms Virtual machines Random processes Performance analysis Resource management Standards Genetic algorithms

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Efficient Parking Spot Allocation in a Grid-Based Parking Lot

Efficient Parking Spot Allocation in a Grid-Based Parking Lo...

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Computing for Sustainability and Intelligent Future (COMP-SIF), International Conference on

作者： Bhavika Gandham Sai Smrithi Muthukumar Trisha Vijayekkumaran Nagasarapu Sarayu Krishna Sreebha Bhaskaran Dept. of Computer Science and Engineering Amrita School of Computing Bengaluru Amrita Vishwa Vidyapeetham India

ISBN: (数字)9798331538538

ISBN: (纸本)9798331538545

Parking management in urban areas faces significant challenges, including congestion, inefficient allocation, and unauthorized use of parking spaces. Building on a previous study that proposes a dynamic parking management system using a grid-based structure that categorizes parking spots as long-term or short-term, allowing for flexible and efficient allocation, this study focuses on optimizing and extending the system for greater efficiency. The system incorporates and compares four algorithms—Dijkstra's, Bellman-Ford, Content-Based Search (CBS), and Jump Point Search (JPS)—along with a novel Combined Search Algorithm, designed to optimize parking allocation and exit determination. The proposed Combined Search Algorithm demonstrated superior efficiency through comprehensive evaluation, reducing allocation and exit determination times by approximately 18% compared to Dijkstra's, 25% to Bellman- Ford, 20% to CBS, and 15% to JPS. These results highlight the approach's potential to significantly improve parking management by optimizing resource utilization, minimizing conflicts, and enhancing user experience.

关键词： Heuristic algorithms Urban areas approximation algorithms Dynamic scheduling User experience Resource management Vehicle dynamics Sustainable development Optimization Faces

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An Improved Digital Power Measurement Algorithm with Window Functions for Substation

An Improved Digital Power Measurement Algorithm with Window ...

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Energy Storage and Conversion (ISESC), CPSS & IEEE International Symposium on

作者： Jinping Zhao Tianqi Gu Honglei Guo Yuhang Sun Yiyina Teng Lei Guo Beiing Smartchp Microelectronics Technology Company Limited Beijing China Yanshan University Qinhuangdao China

ISBN: (数字)9798350380514

ISBN: (纸本)9798350380521

The real-time digital measurement technique is one of the most important issues for the smart power substation. To enhance the ability of substations to measure electric power and to address the challenges of substation metering data not being able to be centrally computed and the difficulty of handling massive multi-time frequency data computation at the power substation. A new digital power measurement method is proposed based on the Hanning window function to reduce the spectral leakage. The signal is converted from the time domain to the frequency domain using a fully-phase fast Fourier transform, and harmonic parameters are obtained through polynomial approximation-based single-spectrum interpolation. The calculation accuracy is enhanced by using a variable forgetting factor Recursive Least Squares algorithm, with coefficients updated through an adaptive linear combiner, significantly improving the speed and accuracy of the measurement for power substation.

关键词： Interpolation Power measurement Substations Accuracy Fast Fourier transforms Measurement techniques approximation algorithms Polynomials Real-time systems Time-domain analysis

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An SDDP Algorithm for Multistage Stochastic Programs with Decision-Dependent Uncertainty

An SDDP Algorithm for Multistage Stochastic Programs with De...

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Simulation Winter Conference

作者： Nazlican Arslan Oscar Dowson David P. Morton Industrial Engineering & Management Sciences Northwestern University Evanston IL USA Dowson Farms Auckland NEW ZEALAND

ISBN: (数字)9798331534202

ISBN: (纸本)9798331534219

Stochastic programming provides mathematical models and algorithms for optimizing decisions under uncertainty. In formulating a stochastic program we typically assume that the probability distributions governing the random parameters are independent of the problem's decisions. Here, we study a multistage stochastic program with decision-dependent uncertainty. At each stage, binary decisions choose from a set of probability distributions and can increase the likelihood of favorable outcomes at a certain cost. We develop a variant of the stochastic dual dynamic programming (SDDP) algorithm to approximately solve this class of problems, using a convex relaxation of the algorithm's subproblems. This allows us to handle a type of large-scale multistage decision-dependent stochastic program, which was previously inaccessible. We provide computational results for a multi-product newsvendor problem with binary marketing options.

关键词： Uncertainty Costs Reviews Heuristic algorithms Statistical learning Stochastic processes Stars approximation algorithms Probability distribution Space exploration

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Green Wave Control Strategy for Optimal Energy Consumption by Model Predictive Control in Electric Vehicles

Green Wave Control Strategy for Optimal Energy Consumption b...

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Human-Computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Furkan Ozkan M. Selcuk Arslan Hatice Mercan Dept. of Mechatronics Engineering Yildiz Technical University Istanbul Turkey School of Computing Engineering and the Built Environment Glasgow Caledonian University Glasgow United Kingdom

ISBN: (数字)9798350394634

ISBN: (纸本)9798350394641

Electric vehicles are becoming increasingly popular as a sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The strategy consists of three components: a fuel consumption model, a powertrain model, and an optimization algorithm. These components work together to generate an optimal vehicle control plan that minimizes energy usage while maintaining desired performance levels. The green wave control strategy utilizes anticipated roadway information to vary the vehicle's speed within a preset speed window, ensuring an energy-saving operation. The results show that the green wave control strategy can lead to significant fuel savings, making electric vehicles even more sustainable and cost-effective.

关键词： Energy consumption Electric potential Green products Electric vehicles approximation algorithms Prediction algorithms Fuels

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Positive Communities on Signed Graphs That Are Not Echo Chambers: A Clique-Based Approach

Positive Communities on Signed Graphs That Are Not Echo Cham...

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International Conference on Data Engineering

作者： Alexander Zhou Yue Wang Lei Chen M. Tamer Özsu Hong Kong University of Science and Technology Shenzhen Institute of Computing Sciences Hong Kong University of Science and Technology Guangzhou University of Waterloo

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

An area of research on communities in signed networks aims to find structures in which each user in the graph is connected to other members in their community by more positive edges than negative edges, indicating a positive experience for the user. However, some of these communities are ‘echo chambers', a rising area of concern in modern discourse regarding social media, which contain almost exclusively positive edges indicating all users trust each other with little or no push-back. Here exists an interesting contradiction, when finding a ‘positive’ community often times the resulting structure may be the negative ‘echo chamber’. In this work we propose a signed graph community substructure named the $(\epsilon,\ \phi)$ -Clique which is the best of both worlds, where each user is happy to be in their community (indicated by have a proportion of positive edges $\geq\epsilon$ for each node) as well as there existing a level of disagreement in the system (indicated by the community having a proportion of negative edges $\geq \phi$ ). From this definition, we design algorithms to exactly find the Maximum $(\epsilon,\ \phi)$ -Clique containing a query user, utilising heuristics to combat the NP-Hard and NP-Hard to approximate nature of the problem. We perform experiments to examine the improvements in efficiency of our algorithms to the proposed baseline as well as examine example community outputs to show the effectiveness of our structure.

关键词： Social networking (online) Heuristic algorithms approximation algorithms Data engineering

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R-Wave Detection Algorithm Based on Central Difference and Adaptive Multi-Threshold

R-Wave Detection Algorithm Based on Central Difference and A...

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Computer Information Science and Application Technology (CISAT), International Conference on

作者： Ke Xu Huibin Wang Sikai Guo Wenping Chen College of Information Science and Engineering Hohai University HHU Nanjing China

ISBN: (数字)9798350375107

ISBN: (纸本)9798350375114

As a non-invasive method for diagnosing heart diseases, electrocardiography (ECG) relies on R-wave detection as a foundational step for other ECG waveform analysis. To further meet the demands for accuracy and real-time detection of R-waves in automatic ECG analysis, this paper proposes a low-complexity, fast, and reliable real-time R-wave detection algorithm. An R-wave detection method based on central difference and adaptive multi-threshold is designed. First, this paper proposes the use of central difference for R-wave enhancement, effectively improving the detection capability for low amplitude and low slope R-waves. Secondly, an adaptive multi-threshold strategy is proposed, which adaptively adjusts the current detection threshold based on the detected R-wave amplitude and RR interval, making it suitable for R-wave detection in cases of sudden changes in RR interval and R-wave amplitude. The proposed algorithm’s performance was evaluated using ECG signals from the MIT-BIH database, achieving an overall sensitivity, positive predictive value, and detection error rate of 99.73%, 99.82%, and 0.46%, respectively. The processing time for a 30-minute ECG recording is approximately 0.52 seconds. The results indicate that the algorithm is accurate, efficient, and suitable for real-time automatic ECG analysis.

关键词： Accuracy Sensitivity Machine learning algorithms Electrocardiography Prediction algorithms approximation algorithms Real-time systems Recording Reliability Detection algorithms

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CRIS-b: A High-Speed Unified Modulo Reduction Algorithm and Hardware Architecture for CRYSTALS-Kyber

CRIS-b: A High-Speed Unified Modulo Reduction Algorithm and ...

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International Conference on VLSI Design

作者： Alip Majumdar Rahul Shrestha School of Computing and Electrical Engineering Indian Institute of Technology Mandi

ISBN: (数字)9798331522445

ISBN: (纸本)9798331522452

This paper presents highly reliable algorithm and high-speed hardware architecture for a unified modulo reduction for CRYSTALS-Kyber. This new architecture for modulo reduction is capable of operating at a maximum clock frequency of 351.62 MHz on Artix-7 FPGA platform, consuming a latency of 5 clock cycles, which is approximately 35.24% faster than state-of-the-art implementations. In this work, we have alleviated the size expansion problem of intermediate value of the conventional Barrett algorithm (which is one of the fastest and most reliable algorithm for modulo reduction, reported in literature) by suggesting a new technique, referred as “Conditional $R$ -index Switching for $b$ -value Minimization (CRIS-b)”. We propose a unified modulo reduction design handling both positive and negative spectrum numbers for all arithmetic modulo operations in a butterfly unit of Number Theoretic Transform(NTT).

关键词： Accuracy Switches Very large scale integration Reliability theory approximation algorithms Minimization Hardware Quantum cryptography Clocks Arithmetic

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Artificial Bee Colony Optimization to Accelerate High-Speed Serial I/O Tx Equalization

Artificial Bee Colony Optimization to Accelerate High-Speed ...

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VLSI Test Symposium

作者： Cesar A. Sanchez-Martinez Paulo Lopez-Meyer Andres Viveros-Wacher I/O Pathfinding Laboratory Intel Corporation Guadalajara Jalisco Mexico Data Center and AI Intel Corporation Guadalajara Jalisco Mexico Client Computing Group Intel Corporation Guadalajara Jalisco Mexico

ISBN: (数字)9798331521448

ISBN: (纸本)9798331521455

A critical activity during electrical testing for High-Speed Serial l/O is the search for optimal Tx equalization settings that yield the cleanest eye diagram possible. Typical practices consist of performing an exhaustive grid search over two variables to define the best solution region, known as the pre-cursor and the post-cursor. This work introduces a methodology to obtain a precise approximation to the optimal equalization values based on the artificial bee colony (ABC) heuristic optimization algorithm. This algorithm explores the solution space with fewer combinations than the typically used procedure. In this work we demonstrate experimentally that the ABC algorithm converges to the solution region of the equalization settings in 36% of the time needed by a grid search. The algorithm was tested on PCIe Gen 5, but lower speed PCIe generations and other interfaces subject to Tx equalization could benefit from these optimization tools, e.g. CXL, UPI, DMI, etc.

关键词： Visualization Technological innovation Heuristic algorithms Very large scale integration Artificial bee colony algorithm approximation algorithms Space exploration Proposals Optimization Testing

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