84,930 results
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302. Bio-Metric Based Colour-Image-Encryption using Multi-Chaotic Dynamical Systems and SHA-256 Hash Algorithm.
- Author
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Rahul, B., Kuppusamy, K., and Senthilrajan, A.
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IMAGE encryption , *DYNAMICAL systems , *ALGORITHMS , *PIXELS - Abstract
This paper proposes a user-biometric-based image encryption using chaotic dynamical systems, SHA-256 hash function, and zigzag transformation. Three chaotic systems, namely, the Henon map, logistic map, and Lorenz system, are used to apply the chaotic properties to the encryption system. The hash value of the user biometric image is used to generate the initial value of the Henon map. The initial values for the logistic map and Lorenz system are generated from the hash value of the plain image. SHA-256 hash algorithm generates the hash values of the biometric and plain images. The plain image is scrambled using the two-dimensional chaotic values generated by the Henon map first. Next, the first scrambled image's pixels are XORed with the one-dimensional chaotic values generated from the logistic map and produce the second scrambled image. Finally, take the second scrambled image's pixels, and XOR them with the three-dimensional chaotic values generated from the Lorenz system and create the final encrypted image. The robustness and flexibility of the encryption system are analyzed using various security and performance analyses. The experiment results are compared with the existing algorithms to prove the efficiency of the proposed algorithm. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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303. Delayed impulsive stabilisation of discrete-time systems: a periodic event-triggering algorithm.
- Author
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Zhang, Kexue and Braverman, Elena
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DISCRETE-time systems , *ALGORITHMS - Abstract
This paper studies the problem of event-triggered impulsive control for discrete-time systems. A novel periodic event-triggering scheme with two tunable parameters is presented to determine the moments of updating impulsive control signals which are called event times. Sufficient conditions are established to guarantee asymptotic stability of the resulting impulsive systems. It is worth mentioning that the event times are different from the impulse times, that is, the control signals are updated at each event time but the actuator performs the impulsive control tasks at a later time due to time delays. The effectiveness of our theoretical result with the proposed scheme is illustrated by three examples. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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304. An automatic calibration algorithm for endoscopic structured light sensors in cylindrical environment.
- Author
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Alzuhiri, Mohand, Li, Zi, Li, Jiaoyang, Rao, Adithya, and Deng, Yiming
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PIPELINE inspection , *CALIBRATION , *NONDESTRUCTIVE testing , *DETECTORS , *ALGORITHMS , *ACQUISITION of data - Abstract
Structured light sensing systems, as one of the most common optical-based nondestructive evaluation techniques, have been widely applied for inline pipeline inspection. The sensor can be inserted inside the pipe to generate 3D visualisation and evaluate the cracks in the materials. The precise calibration of the camera-projector measurement system is of great significance to ensure the measurement accuracy of the 3D sensing system. Conventional calibration methods for structured light sensors involve complicated and time-consuming procedures and are easily affected by ambient light. The paper presents a novel algorithm to automatically calibrate the projection module and estimate the stereo parameters between the camera and the projector. The calibration algorithm exploits the cylindrical nature of the inspected pipe to create a set of geometric constraints and automatically calibrate the sensor without the need for reference calibration points. Experimental and simulation results showed that the algorithm could successfully estimate the projector's intrinsic and extrinsic parameters by simply acquiring the data inside a cylindrical pipe with a known diameter. The proposed algorithm highly reduces the data collection time for the calibration (only 53 s), improves the accuracy, and simplifies the calibration process. [ABSTRACT FROM AUTHOR]
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- 2024
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305. Finite-Time and Fixed-Time Bipartite Consensus of Multiple Euler–Lagrange Systems via Hierarchical Control Algorithm.
- Author
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Wang, Shuang, Han, Tao, Xiao, Bo, Zhan, Xi-Sheng, and Yan, Huaicheng
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EULER-Lagrange system , *BIPARTITE graphs , *LYAPUNOV stability , *ALGORITHMS - Abstract
This paper investigates the finite-time and fixed-time bipartite consensus problem of multiple Euler–Lagrange systems (MELSs) under directed interaction topologies, considering external disturbances. Two novel distributed hierarchical control algorithms are developed to address the challenging problems. Specifically, a new distributed estimator is designed to estimate the states of agents in finite/fixed-time. Moreover, based on the obtained estimations, the finite/fixed-time controller is presented to accomplish the bipartite consensus of the MELSs in the local control layer. By utilizing Lyapunov stability and the nearest neighbor-interactions theory, sufficient conditions for achieving the designed performance of the MELSs are derived. Simulation examples are provided to illustrate the effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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306. Insights into the Filtered-x LMS Algorithm in the Presence of Frequency Mismatch.
- Author
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Liu, Jian and Chen, Huawei
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ACTIVE noise control , *STOCHASTIC analysis , *SYSTEM dynamics , *ALGORITHMS , *DIFFERENCE equations , *SYSTEMS design - Abstract
The performance of a narrowband active noise control (NANC) system can be significantly degraded due to the frequency mismatch (FM). In this paper, the statistical performance of a typical FxLMS-based NANC system in the presence of FM is analyzed in detail. Difference equations governing the system dynamics and closed-form steady-state mean-square error expressions are derived and discussed. The stochastic analysis results reveal that the FM introduces small troublesome sinusoids into the NANC system. The controller has to track these sinusoids to minimize the residual noise, which leads to a serious performance deterioration. As a by-product, the optimal step sizes that minimize the effect of a relatively small FM are also derived. The findings significantly enrich our understanding of the stochastic behavior of the FxLMS algorithm in the presence of FM and also provide some useful information for NANC system design. Extensive simulations are conducted to confirm the validity of the analytical findings. [ABSTRACT FROM AUTHOR]
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- 2024
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307. Modified inertial extragradient algorithm with non-monotonic step sizes for pseudomonotone equilibrium problems and quasi-nonexpansive mapping.
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NGAMKHUM, THANYALUCK, PUNPENG, KOMKIND, and KHONCHALIEW, MANATCHANOK
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MONOTONE operators , *HILBERT space , *ALGORITHMS , *EQUILIBRIUM - Abstract
In this paper, we introduce a modified inertial extragradient algorithm with non-monotonic step sizes for approximating a common solution of the pseudomonotone equilibrium problem and the fixed point problem for the quasi-nonexpansive mapping in the framework of a real Hilbert space. Under some constraint qualifications of the scalar sequences, the strong convergence theorem of the introduced algorithm is presented by using the self-adaptive non-monotonic step size without prior information about the Lipschitz constants of bifunction. Some numerical experiments are provided to demonstrate the computational efficiency and advantages of the proposed algorithm. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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308. An intermixed algorithm for solving fixed point problems of proximal operators in Hilbert Spaces.
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KHUANGSATUNG, WONGVISARUT and KANGTUNYAKARN, ATID
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ALGORITHMS , *VISCOSITY - Abstract
The aim of this paper is to modify proximal operators in Hilbert spaces. We introduce an intermixed algorithm with viscosity technique to find the solution of fixed point problem of two proximal operators in a real Hilbert space, utilizing the modified proximal operators. Under some mild conditions, a strong convergence theorem is established for the proposed algorithm. We also apply our main result to the split feasibility problem. Finally we provide numerical examples for supporting the main result. [ABSTRACT FROM AUTHOR]
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- 2024
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309. Placement optimization of elastic spacers for multi-layer space membrane structure.
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Liu, Xiang, Cai, Guoping, Fang, Guangqiang, and Lv, Liangliang
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EVIDENCE gaps , *ALGORITHMS - Abstract
• Dynamics of multi-layer membrane structure with elastic spacers is studied. • An optimization criterion to eliminate the crossing modes is proposed. • The optimal spacer positions are calculated by Particle Swarm Optimizer algorithm. In recent years, there has been a growing interest in the dynamics of space membrane structures. However, existing research primarily focuses on single-layer membrane structures, leaving a significant research gap in the study of multi-layer structures with elastic spacers. To address this gap, this paper studies the dynamics and interlayer spacing accuracy of multi-layer membrane structures with elastic spacers. Specifically, the research focuses on the placement optimization of elastic spacers. A novel optimization criterion for the elastic spacers has been proposed, and the Particle Swarm Optimizer (PSO) algorithm has been utilized to calculate the optimal spacers positions. Results show that optimally placed elastic spacers can eliminate the crossing modes and improve the interlayer spacing accuracy during vibration. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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310. Traversal Topology-Finding Method of Tensegrity Structure Based on Dynamic Programming.
- Author
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Lu, Jinyu, Xu, Zhiyin, and Liu, Jilei
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DYNAMIC programming , *ALGORITHMS , *TOPOLOGY - Abstract
Tensegrity structures, which consist of tension cables and compression rods, are widely used in various fields. It is particularly important to find the tensegrity with definite geometric configuration for the following research and application. This paper presents a traversal topology-finding method for tensegrity structures based on dynamic programming algorithm and ground structure method. After the designer has given the cable topology, the dynamic programming is adopted to realize the traversal selection of the rod. In order to reduce the traversal space and realize the constraint of rod length type, the rod is classified according to length. Compared with existing topology-finding methods, the algorithm can not only output all feasible topologies but also incorporate structural constraints, such as rod length type and prestressed stability, into the calculation process. Four tensegrity numerical examples illustrate the feasibility and effectiveness of the topology-finding method. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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311. On the p-adic zeros of the Tribonacci sequence.
- Author
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Bilu, Yuri, Luca, Florian, Nieuwveld, Joris, Ouaknine, Joël, and Worrell, James
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INTEGERS , *ALGORITHMS - Abstract
Let (T_n)_{n\in {\mathbb Z}} be the Tribonacci sequence and for a prime p and an integer m let \nu _p(m) be the exponent of p in the factorization of m. For p=2 Marques and Lengyel found some formulas relating \nu _p(T_n) with \nu _p(f(n)) where f(n) is some linear function of n (which might be constant) according to the residue class of n modulo 32 and asked if similar formulas exist for other primes p. In this paper, we give an algorithm which tests whether for a given prime p such formulas exist or not. When they exist, our algorithm computes these formulas. Some numerical results are presented. [ABSTRACT FROM AUTHOR]
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- 2024
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312. A new algorithm for p-adic continued fractions.
- Author
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Murru, Nadir and Romeo, Giuliano
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CONTINUED fractions , *SQUARE root , *ALGORITHMS - Abstract
Continued fractions in the field of p-adic numbers have been recently studied by several authors. It is known that the real continued fraction of a positive quadratic irrational is eventually periodic (Lagrange's Theorem). It is still not known if a p-adic continued fraction algorithm exists that shares a similar property. In this paper we modify and improve one of Browkin's algorithms. This algorithm is considered one of the best at the present time. Our new algorithm shows better properties of periodicity. We show for the square root of integers that if our algorithm produces a periodic expansion, then this periodic expansion will have pre-period one. It appears experimentally that our algorithm produces more periodic continued fractions for quadratic irrationals than Browkin's algorithm. Hence, it is closer to an algorithm to which an analogue of Lagrange's Theorem would apply. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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313. Fast, parallel, and cache-friendly suffix array construction.
- Author
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Khan, Jamshed, Rubel, Tobias, Molloy, Erin, Dhulipala, Laxman, and Patro, Rob
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SUFFIXES & prefixes (Grammar) , *PARALLEL algorithms , *DATA structures , *ALGORITHMS - Abstract
Purpose: String indexes such as the suffix array (sa) and the closely related longest common prefix (lcp) array are fundamental objects in bioinformatics and have a wide variety of applications. Despite their importance in practice, few scalable parallel algorithms for constructing these are known, and the existing algorithms can be highly non-trivial to implement and parallelize. Methods: In this paper we present caps-sa, a simple and scalable parallel algorithm for constructing these string indexes inspired by samplesort and utilizing an LCP-informed mergesort. Due to its design, caps-sa has excellent memory-locality and thus incurs fewer cache misses and achieves strong performance on modern multicore systems with deep cache hierarchies. Results: We show that despite its simple design, caps-sa outperforms existing state-of-the-art parallel sa and lcp-array construction algorithms on modern hardware. Finally, motivated by applications in modern aligners where the query strings have bounded lengths, we introduce the notion of a bounded-context sa and show that caps-sa can easily be extended to exploit this structure to obtain further speedups. We make our code publicly available at https://github.com/jamshed/CaPS-SA. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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314. Fast, parallel, and cache-friendly suffix array construction.
- Author
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Khan, Jamshed, Rubel, Tobias, Molloy, Erin, Dhulipala, Laxman, and Patro, Rob
- Subjects
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SUFFIXES & prefixes (Grammar) , *PARALLEL algorithms , *DATA structures , *ALGORITHMS - Abstract
Purpose: String indexes such as the suffix array (sa) and the closely related longest common prefix (lcp) array are fundamental objects in bioinformatics and have a wide variety of applications. Despite their importance in practice, few scalable parallel algorithms for constructing these are known, and the existing algorithms can be highly non-trivial to implement and parallelize. Methods: In this paper we present caps-sa, a simple and scalable parallel algorithm for constructing these string indexes inspired by samplesort and utilizing an LCP-informed mergesort. Due to its design, caps-sa has excellent memory-locality and thus incurs fewer cache misses and achieves strong performance on modern multicore systems with deep cache hierarchies. Results: We show that despite its simple design, caps-sa outperforms existing state-of-the-art parallel sa and lcp-array construction algorithms on modern hardware. Finally, motivated by applications in modern aligners where the query strings have bounded lengths, we introduce the notion of a bounded-context sa and show that caps-sa can easily be extended to exploit this structure to obtain further speedups. We make our code publicly available at https://github.com/jamshed/CaPS-SA. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
315. Two phase algorithm for bi-objective relief distribution location problem.
- Author
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Mishra, Mamta, Singh, Surya Prakash, and Gupta, Manmohan Prasad
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BIG data , *ALGORITHMS , *NP-hard problems , *GENETIC algorithms , *METAHEURISTIC algorithms - Abstract
The location planning of relief distribution centres (DCs) is crucial in humanitarian logistics as it directly influences the disaster response and service to the affected victims. In light of the critical role of facility location in humanitarian logistics planning, the study proposes a two-stage relief distribution location problem. The first stage of the model determines the minimum number of relief DCs, and the second stage find the optimal location of these DCs to minimize the total cost. To address a more realistic situation, restrictions are imposed on the coverage area and capacity of each DCs. In addition, for optimally solving this complex NP-hard problem, a novel two-phase algorithm with exploration and exploitation phase is developed in the paper. The first phase of the algorithm i.e., exploration phase identifies a near-optimal solution while the second phase i.e. exploitation phase enhances the solution quality through a close circular proximity investigation. Furthermore, the comparative analysis of the proposed algorithm with other well-known algorithms such as genetic algorithm, pattern search, fmincon, multistart and hybrid heuristics is also reported and computationally tested from small to large data sets. The results reveal that the proposed two-phase algorithm is more efficient and effective when compared to the conventional metaheuristic methods. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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316. A new semi-supervised clustering algorithm for probability density functions and applications.
- Author
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Nguyen-Trang, Thao, Nguyen-Hoang, Yen, and Vo-Van, Tai
- Subjects
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PARALLEL algorithms , *ALGORITHMS , *RESEARCH personnel , *PROBABILITY density function - Abstract
Semi-supervised clustering has gained significant attention from researchers due to its advantages over unsupervised clustering. However, existing studies have predominantly focused on discrete data. This paper pioneers the application of semi-supervised clustering to probability density functions. The proposed algorithm encompasses detailed implementation steps, a convergence proof, and the ability to address computational challenges. The algorithm has been effectively implemented on image data, resulting in the transformation of each image into a probability density function that is representative. In comparison to existing unsupervised algorithms, the efficacy of the proposed algorithm in partitioning and reducing computational costs is demonstrated through numerical examples and applications. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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317. Robust and compact maximum margin clustering for high-dimensional data.
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Cevikalp, Hakan and Chome, Edward
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CLUSTER sampling , *MACHINE learning , *CONJUGATE gradient methods , *ALGORITHMS , *HYPERPLANES - Abstract
In the field of machine learning, clustering has become an increasingly popular research topic due to its critical importance. Many clustering algorithms have been proposed utilizing a variety of approaches. This study focuses on clustering of high-dimensional data using the maximum margin clustering approach. In this paper, two methods are introduced: The first method employs the classical maximum margin clustering approach, which separates data into two clusters with the greatest margin between them. The second method takes cluster compactness into account and searches for two parallel hyperplanes that best fit to the cluster samples while also being as far apart from each other as possible. Additionally, robust variants of these clustering methods are introduced to handle outliers and noise within the data samples. The stochastic gradient algorithm is used to solve the resulting optimization problems, enabling all proposed clustering methods to scale well with large-scale data. Experimental results demonstrate that the proposed methods are more effective than existing maximum margin clustering methods, particularly in high-dimensional clustering problems, highlighting the efficacy of the proposed methods. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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318. Digital quantification of the MMSE interlocking pentagon areas: a three-stage algorithm.
- Author
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Kim, Namhee, Truty, Timothy, Duke Han, S., Heo, Moonseong, Buchman, Aron S., Bennett, David A., and Tasaki, Shinya
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PENTAGONS , *MINI-Mental State Examination , *BINARY number system , *ALGORITHMS , *TASK performance - Abstract
The Mini-Mental State Examination (MMSE) is a widely employed screening tool for the severity of cognitive impairment. Among the MMSE items, the pentagon copying test (PCT) requires participants to accurately replicate a sample of two interlocking pentagons. While the PCT is traditionally scored on a binary scale, there have been limited developments of granular scoring scale to assess task performance. In this paper, we present a novel three-stage algorithm, called Quantification of Interlocking Pentagons (QIP) which quantifies PCT performance by computing the areas of individual pentagons and their intersection areas, and a balance ratio between the areas of the two individual pentagons. The three stages of the QIP algorithm include: (1) detection of line segments, (2) unraveling of the interlocking pentagons, and (3) quantification of areas. A set of 497 PCTs from 84 participants including their baseline and follow-up PCTs from the Rush Memory and Aging Project was selected blinded about their cognitive and clinical status. Analysis of the quantified data revealed a significant inverse relationship between age and balance ratio (beta = − 0.49, p = 0.0033), indicating that older age was associated with a smaller balance ratio. In addition, balance ratio was associated with perceptual speed (r = 0.71, p = 0.0135), vascular risk factors (beta = − 3.96, p = 0.0269), and medical conditions (beta = − 2.78, p = 0.0389). The QIP algorithm can serve as a useful tool for enhancing the scoring of performance in the PCT. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
319. Application of optimized Kalman filtering in target tracking based on improved Gray Wolf algorithm.
- Author
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Pang, Zheming, Wang, Yajun, and Yang, Fang
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KALMAN filtering , *OPTIMIZATION algorithms , *ALGORITHMS , *COVARIANCE matrices - Abstract
High precision is a very important index in target tracking. In order to improve the prediction accuracy of target tracking, an optimized Kalman filter approach based on improved Gray Wolf algorithm (IGWO-OKF) is proposed in this paper. Since the convergence speed of traditional Gray Wolf algorithm is slow, meanwhile, the number of gray wolves and the choice of the maximum number of iterations has a great influence on the algorithm, a nonlinear control parameter combination adjustment strategy is proposed. An improved Grey Wolf Optimization algorithm (IGWO) is formed by determining the best combination of adjustment parameters through the fastest iteration speed of the algorithm. The improved Grey Wolf Optimization algorithm (IGWO) is formed, and the process noise covariance matrix and observation noise covariance matrix in Kalman filter are optimized by IGWO. The proposed approach is applied into. The experiment results show that the proposed IGWO-OKF approach has low error, high accuracy and good prediction effect. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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320. Route planning of mobile robot based on improved RRT star and TEB algorithm.
- Author
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Yin, Xiong, Dong, Wentao, Wang, Xiaoming, Yu, Yongxiang, and Yao, Daojin
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MOBILE robots , *POTENTIAL field method (Robotics) , *ROBOT kinematics , *ALGORITHMS - Abstract
This paper presents a fusion algorithm based on the enhanced RRT* TEB algorithm. The enhanced RRT* algorithm is utilized for generating an optimal global path. Firstly, proposing an adaptive sampling function and extending node bias to accelerate global path generation and mitigate local optimality. Secondly, eliminating path redundancy to minimize path length. Thirdly, imposing constraints on the turning angle of the path to enhance path smoothness. Conducting kinematic modeling of the mobile robot and optimizing the TEB algorithm to align the trajectory with the mobile robot's kinematics. The integration of these two algorithms culminates in the development of a fusion algorithm. Simulation and experimental results demonstrate that, in contrast to the traditional RRT* algorithm, the enhanced RRT* algorithm achieves a 5.8% reduction in path length and a 62.5% decrease in the number of turning points. Utilizing the fusion algorithm for path planning, the mobile robot generates a superior, seamlessly smooth global path, adept at circumventing obstacles. Furthermore, the local trajectory meticulously conforms to the kinematic constraints of the mobile robot. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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321. Distributed dynamic event-triggered algorithm for optimization problem with time delay.
- Author
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Jiang, Lu, Xia, Lunchao, and Zhao, Zhongyuan
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MULTIAGENT systems , *UNDIRECTED graphs , *COMPUTER simulation , *ALGORITHMS , *DISTRIBUTED algorithms - Abstract
This paper focuses on studying the optimization problem of multi-agent systems (MAS) under undirected graph. To reduce the communication frequency among agents, a zero-gradient-sum (ZGS) algorithm based on dynamic event-triggered (DET) mechanism is investigated. The event-triggered condition of each agent only uses its own state information and the neighbor's state information at the previous triggering instants, without requiring continuous state information from the neighbor. In addition, the designed algorithm allows for the sampling period to be arbitrarily large. The Lyapunov method is utilized to derive the sufficient conditions that incorporate time delay and parameters. As the event is only checked at the periodic moment, zeno behavior can be directly excluded. Finally, numerical simulations demonstrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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322. Voltage Frequency Differential Protection Algorithm.
- Author
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Matišić, Zdravko, Antić, Tomislav, Havelka, Juraj, and Capuder, Tomislav
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RENEWABLE energy sources , *DISTRIBUTED power generation , *VOLTAGE , *ALGORITHMS , *ENERGY consumption - Abstract
Advancements in new technologies, a reduction in CO2 emissions, and the rising demand for energy are causing a growth in the share of renewable energy sources. In distribution networks, an increasing number of distributed generators (DGs) makes the utility grid's protection complex and demanding. Vector surge and rate-of-change-of-frequency are the established anti-islanding protection methods, recognizing that the standard paradigm for protection, involving distributed generation, cannot be set only once but has to be continuously updated following the requirements and changes in the system. One of the requirements is active participation in the preservation of system frequency and voltage, which can be interrupted if the DG trips and disconnects from the utility grid. Anti-islanding protection and spurious tripping can be avoided by implementing new algorithms and techniques. This paper presents a novel protection scheme based on a voltage frequency differential. The proposed algorithm employs remote and local frequency measurements in such a manner that, for the occurrence of a frequency difference, it is assumed that the DG is in an islanding state. In this article, we demonstrate the feasibility of the algorithm through numerical analysis of grid events and laboratory testing emulating real grid-measured values. The test results show that the algorithm is resilient to false tripping for non-islanding events and more reliable than conventional methods in islanding detection. The algorithm can be set to low-frequency differential values, drastically reducing the non-detection zone in any DG type, regardless of its size and voltage level at the point of common coupling. Unlike standard anti-islanding methods, the algorithm supports the ability of the DG to fault-ride through demand. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
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323. Focusing Algorithm of Range Profile for Plasma-Sheath-Enveloped Target.
- Author
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Shen, Fangfang, Chen, Xuyang, Bai, Bowen, Liu, Yanming, Li, Xiaoping, and Zhang, Zherui
- Subjects
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PLASMA sheaths , *ALGORITHMS , *HYPERSONIC aerodynamics , *PHASE velocity , *FOURIER transforms - Abstract
In this paper, a one-dimensional (1-D) range profile of the hypersonic target enveloped by a plasma sheath is investigated. Firstly, the non-uniform property of the plasma sheath is studied and its impact on the wideband electromagnetic (EM) wave is analyzed. A wideband radar echo model for the plasma-sheath-enveloped hypersonic target is constructed. Then, by exploiting the relationship among the incident depth, reflection intensity, and plasma velocity, it reveals that distinct scatter points in various areas of the target will suffer from varying reflection intensity and coupled velocity, leading to severe defocusing in the range profile. To tackle this issue, a novel focusing algorithm combing the Fractional Fourier Transform (FRFT) with the CLEAN technique is developed, which independently calculates the coupled plasma velocity and compensates for the phase error via a series of iterative procedures. Finally, the influence of the plasma sheath on the 1-D range profile and the effectiveness of the proposed focusing algorithm are validated through simulations. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
324. An Aerial Image Detection Algorithm Based on Improved YOLOv5.
- Author
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Shan, Dan, Yang, Zhi, Wang, Xiaofeng, Meng, Xiangdong, and Zhang, Guangwei
- Subjects
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ALGORITHMS , *SPINE , *SAMPLE size (Statistics) - Abstract
To enhance aerial image detection in complex environments characterized by multiple small targets and mutual occlusion, we propose an aerial target detection algorithm based on an improved version of YOLOv5 in this paper. Firstly, we employ an improved Mosaic algorithm to address redundant boundaries arising from varying image scales and to augment the training sample size, thereby enhancing detection accuracy. Secondly, we integrate the constructed hybrid attention module into the backbone network to enhance the model's capability in extracting pertinent feature information. Subsequently, we incorporate feature fusion layer 7 and P2 fusion into the neck network, leading to a notable enhancement in the model's capability to detect small targets. Finally, we replace the original PAN + FPN network structure with the optimized BiFPN (Bidirectional Feature Pyramid Network) to enable the model to preserve deeper semantic information, thereby enhancing detection capabilities for dense objects. Experimental results indicate a substantial improvement in both the detection accuracy and speed of the enhanced algorithm compared to its original version. It is noteworthy that the enhanced algorithm exhibits a markedly improved detection performance for aerial images, particularly under real-time conditions. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
325. Layout of Detection Array Based on Multi-Strategy Fusion Improved Adaptive Mayfly Algorithm in Bearing-Only Sensor Network.
- Author
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Chen, Zhan, Fang, Yangwang, Zhang, Ruitao, and Fu, Wenxing
- Subjects
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SENSOR networks , *ALGORITHMS , *FISHER information , *GENETIC algorithms , *PARTICLE swarm optimization - Abstract
The various applications of bearing-only sensor networks for detection and localization are becoming increasingly widespread and important. The array layout of the bearing-only sensor network seriously impacts the detection performance. This paper proposes a multi-strategy fusion improved adaptive mayfly algorithm (MIAMA) in a bearing-only sensor network to perform layout planning on the geometric configuration of the optimal detection. Firstly, the system model of a bearing-only sensor network was constructed, and the observability of the system was analyzed based on the Cramer–Rao Lower Bound and Fisher Information Matrix. Then, in view of the limitations of the traditional mayfly algorithm, which has a single initial population and no adaptability and poor global search capabilities, multi-strategy fusion improvements were carried out by introducing Tent chaos mapping, the adaptive inertia weight factor, and Random Opposition-based Learning. Finally, three simulation experiments were conducted. Through comparison with the Particle Swarm Optimization (PSO) algorithm, Mayfly Algorithm (MA), and Genetic Algorithm (GA), the effectiveness and superiority of the proposed MIAMA were validated. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
326. Enhancements in Radiological Detection of Metastatic Lymph Nodes Utilizing AI-Assisted Ultrasound Imaging Data and the Lymph Node Reporting and Data System Scale.
- Author
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Chudobiński, Cezary, Świderski, Bartosz, Antoniuk, Izabella, and Kurek, Jarosław
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LYMPH nodes , *RECEIVER operating characteristic curves , *EARLY detection of cancer , *ARTIFICIAL intelligence , *MULTIPLE regression analysis , *ULTRASONIC imaging , *METASTASIS , *QUALITY assurance , *ALGORITHMS - Abstract
Simple Summary: A novel approach for automatic detection of neoplastic lesions in lymph nodes is presented, which incorporates machine learning methods and the new LN-RADS scale. The presented solution incorporates different network structures with diverse datasets to improve the overall effectiveness. Final findings demonstrate that incorporating the LN-RADS scale labels improved the overall diagnosis, especially when compared with current, standard practices. The presented solution is meant as an aid in the diagnosis process. The paper presents a novel approach for the automatic detection of neoplastic lesions in lymph nodes (LNs). It leverages the latest advances in machine learning (ML) with the LN Reporting and Data System (LN-RADS) scale. By integrating diverse datasets and network structures, the research investigates the effectiveness of ML algorithms in improving diagnostic accuracy and automation potential. Both Multinominal Logistic Regression (MLR)-integrated and fully connected neuron layers are included in the analysis. The methods were trained using three variants of combinations of histopathological data and LN-RADS scale labels to assess their utility. The findings demonstrate that the LN-RADS scale improves prediction accuracy. MLR integration is shown to achieve higher accuracy, while the fully connected neuron approach excels in AUC performance. All of the above suggests a possibility for significant improvement in the early detection and prognosis of cancer using AI techniques. The study underlines the importance of further exploration into combined datasets and network architectures, which could potentially lead to even greater improvements in the diagnostic process. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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327. Mitigating voltage deviation, SOCs difference, and currents disparity in DC microgrids using a novel piecewise SOC‐based control method.
- Author
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Erfani Haghani Kerman, Ehsan, Abavisani, Mohammad Amin, Eydi, Mohammad, and Ghazi, Reza
- Subjects
- *
MICROGRIDS , *VOLTAGE , *ALGORITHMS - Abstract
Proper current sharing, DC bus voltage deviation reduction, and SOCs balancing, along with ensuring stability are the vital challenges of DC microgrids control algorithms. Addressing these challenges without communication links and a central controller is one of the priorities of control methods. Motivated by the above mentions, this paper presents a novel communication‐free control method. In this regard, a new parameter called "virtual current" is defined according to the unit current and its SOC. Then using a piecewise droop curve and the droop curve shift technique, the virtual current for each unit is determined. The units control coefficients and the relationship of the virtual current are allocated based on the location and power of the loads and RESs such that in the worst case; 1) SOCs are converged; 2) the DC bus voltage deviation is reduced; and 3) the current is appropriately distributed. The simulation and experimental results confirm that the proposed method can balance SOCs like SOC‐based methods and share power properly like piecewise droop methods while reducing DC bus voltage deviation. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
328. Piecewise DMD for oscillatory and Turing spatio-temporal dynamics.
- Author
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Alla, Alessandro, Monti, Angela, and Sgura, Ivonne
- Subjects
- *
OSCILLATIONS , *DIFFUSION , *ALGORITHMS - Abstract
Dynamic Mode Decomposition (DMD) is an equation-free method that aims at reconstructing the best linear fit from temporal datasets. In this paper, we show that DMD does not provide accurate approximation for datasets describing oscillatory dynamics, like spiral waves, relaxation oscillations and spatio-temporal Turing instability. Inspired by the classical "divide and conquer" approach, we propose a piecewise version of DMD (pDMD) to overcome this problem. The main idea is to split the original dataset in N submatrices and then apply the exact (randomized) DMD method in each subset of the obtained partition. We describe the pDMD algorithm in detail and we introduce some error indicators to evaluate its performance when N is increased. Numerical experiments show that very accurate reconstructions are obtained by pDMD for datasets arising from time snapshots of certain reaction-diffusion PDE systems, like the FitzHugh-Nagumo model, a λ - ω system and the DIB morpho-chemical system for battery modeling. Finally, a discussion about the overall computational load and the future prediction features of the new algorithm is also provided. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
329. Comparative Performance Study of DVR Using Adaptive LMS Filtering-Based Algorithms.
- Author
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Kassarwani, Neelam, Ohri, Jyoti, and Singh, Alka
- Subjects
- *
FILTERS & filtration , *PERFORMANCE theory , *ADAPTIVE control systems , *ALGORITHMS , *COMPARATIVE studies - Abstract
In the distribution system, voltage sags and swell have adverse effects on sensitive and critical loads. Dynamic Voltage Restorer (DVR) play a vital role to mitigate voltage sags and swell through its organized control when connected in series with the system. Various conventional control schemes have been reported for the control of DVR. The performance of DVR with these schemes has been successful in the mitigation of voltage sags/swell, but drawbacks, such as undershoot, and overshoot during sag dynamics are observed in the regulated load terminal voltage. These drawbacks may cause malfunctioning of the equipment connected and hence their elimination is indispensable. With this inspiration, a novel Adaline filter-based adaptive control scheme using learning-rate parameter-based Least-Mean-Square algorithm has been proposed. This scheme has the capability to overcome the drawbacks with the conventional control schemes thus improving the performance of DVR. In this paper, the performance of DVR using proposed algorithm is compared with that using synchronous reference frame (SRF)-based conventional control scheme. The performance is studied and validated through simulation results under different voltage sag and swell conditions in MATLAB software using Sim Power System toolboxes. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
330. A novel algorithm for maximum power point tracking using computer vision (CVMPPT).
- Author
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Ahmadi, Morteza, Abrari, Masoud, Ghanaatshoar, Majid, and Khalafi, Ali
- Subjects
- *
ALGORITHMS , *DIGITAL electronics , *ENERGY harvesting , *COMPUTER vision - Abstract
The behavior of an illuminated solar module can be characterized by its power-voltage curve. Tracking the peak of this curve is essential to harvest the maximum power by the module. The position of the peak varies with temperature and irradiance and needs to be traced. Under partial shading conditions, the number of peaks increases and makes it more difficult to find the global maximum power point (MPP). Various methods are used for maximum power point tracking (MPPT) that are based on iterations. These methods are time-consuming and fail to work satisfactorily under rapidly changing environmental conditions. In this paper, a novel algorithm is proposed that for the first time, utilizes computer vision to find the global maximum power point. This algorithm, which is implemented in Matlab/Simulink, is free of voltage iterations and gives the real-time data for the maximum power point. The proposed algorithm increases the speed and the reliability of the MPP tracking via replacing analogue electronics calculations by digital means. The validity of the algorithm is experimentally verified. [ABSTRACT FROM AUTHOR]
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- 2024
- Full Text
- View/download PDF
331. A secure and highly efficient blockchain PBFT consensus algorithm for microgrid power trading.
- Author
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Yao, Zhongyuan, Fang, Yonghao, Pan, Heng, Wang, Xiangyang, and Si, Xueming
- Subjects
- *
MICROGRIDS , *BLOCKCHAINS , *DENIAL of service attacks , *CONSENSUS (Social sciences) , *ALGORITHMS , *DISTRIBUTED algorithms - Abstract
There are a series of challenges in microgrid transactions, and blockchain technology holds the promise of addressing these challenges. However, with the increasing number of users in microgrid transactions, existing blockchain systems may struggle to meet the growing demands for transactions. Therefore, this paper proposes an efficient and secure blockchain consensus algorithm designed to meet the demands of large-scale microgrid electricity transactions. The algorithm begins by utilizing a Spectral clustering algorithm to partition the blockchain network into different lower-level consensus set based on the transaction characteristics of nodes. Subsequently, a dual-layer consensus process is employed to enhance the efficiency of consensus. Additionally, we have designed a secure consensus set leader election strategy to promptly identify leaders with excellent performance. Finally, we have introduced an authentication method that combines zero-knowledge proofs and key sharing to further mitigate the risk of malicious nodes participating in the consensus. Theoretical analysis indicates that our proposed consensus algorithm, incorporating multiple layers of security measures, effectively withstands blockchain attacks such as denial of service. Simulation experiment results demonstrate that our algorithm outperforms similar blockchain algorithms significantly in terms of communication overhead, consensus latency, and throughput. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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332. Taylor-Spotted Cat Optimization (Taylor-SCO): An Energy-Efficient Cluster Head Selection Algorithm with Improved Trust Factor for Data Routing in WSN.
- Author
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Kalburgi, Shivaraj and Manimozhi, M.
- Subjects
- *
WIRELESS sensor networks , *ROUTING algorithms , *ALGORITHMS , *AGRICULTURE , *ENERGY consumption , *COMPUTER network security , *OWLS - Abstract
Wireless Sensor Network (WSN) has inexpensive, small, and less energy sensor nodes, which are allocated in random ways in particular areas for measuring the phenomenon or events in that field. In recent days, WSN has played a vital role in various applications, like industrial monitoring, medical treatments, agricultural monitoring, and military operations. However, the security challenges and network lifetime are the main issues in the existing methods. In order to overcome these issues, the Taylor-Spotted Cat Optimization (Taylor-SCO) approach is devised in this paper. Here, the Cluster Heads (CHs) are selected based on the developed optimization method, named Taylor CSO. Moreover, the delay, distance, and energy parameters are considered for effective Cluster Head Selection (CHS). Here, route maintenance is also done for increasing network lifetime and reducing complexities. In addition, the Modified K-Vertex Disjoint Paths Routing (KVDPR) model is established for routing. The modification of KVDPR is carried out using several factors, such as link reliability, throughput, and various trust factors. Moreover, the developed Taylor-SCO algorithm is developed by combining the Spotted Hyena Optimizer (SHO), Cat Swarm Optimization (CSO) algorithm, and Taylor series. The Taylor-SCO achieved better performance with energy consumption, trust, and throughput of 0.00037 J, 0.51, and 793160 kbps. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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333. Beyond the Algorithm: Understanding How ChatGPT Handles Complex Library Queries.
- Author
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Yang, Sharon Q. and Mason, Sarah
- Subjects
- *
WORLD Wide Web , *LIBRARY reference services , *T-test (Statistics) , *PLAGIARISM , *ARTIFICIAL intelligence , *STATISTICAL sampling , *QUESTIONNAIRES , *ACADEMIC libraries , *LIBRARIANS , *DESCRIPTIVE statistics , *INFORMATION services , *INFORMATION retrieval , *CONFIDENCE intervals , *ALGORITHMS , *REFERENCE interviews (Library science) - Abstract
The introduction of ChatGPT 3.5 in November 2022 ignited a sensation in the academic community, leaving many astounded by its capabilities. This new release more closely emulates human responses than its predecessors. Among its remarkable capabilities, it can answer questions, catalog items in MARC21, recommend reading lists, and make suggestions on a wide array of topics. To assess ChatGPT’s efficacy in aiding library users, the authors of this paper conducted an experiment comparing ChatGPT’s performance with that of librarians in answering reference questions. Thirty questions were randomly selected from the transaction log of the reference inquiries between June 1, 2023 to July 31, 2023 at the Rider University Libraries. These queries constituted 34% of the total user questions during this two-month period. The authors compared the answers by ChatGPT and those by reference librarians for their accuracy, relevance, and friendliness. The findings indicate that reference librarians markedly outperformed their robotic counterpart. An evident issue arises from ChatGPT’s deficiency in understanding local policies and practices. This consequently hinders its ability to provide satisfactory answers in those areas. OpenAI posits that ChatGPT’s proficiency can be enhanced through targeted fine-tuning using locally specific information. At the moment, ChatGPT remains a great tool for librarians. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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334. Probing bad theories with the dualization algorithm. Part I.
- Author
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Giacomelli, Simone, Hwang, Chiung, Marino, Fabio, Pasquetti, Sara, and Sacchi, Matteo
- Subjects
- *
GAUGE field theory , *ALGORITHMS - Abstract
Recently an algorithm to build SL(2, ℤ) duals, including mirror duals, of 3d N = 4 quiver theories and their 4d N = 1 uplift has been introduced. In this work we use this new tool to study the so-called bad theories. Our approach allows us to determine exactly indices/partition functions for generic values of fugacities/real mass and FI parameters revealing their surprising feature: the 4d index/3d partition function of a bad theory behaves as a sum of distributions rather than an ordinary function of the deformation parameters. We focus on the bad SQCD, with U(Nc) gauge group in 3d and USp(2Nc) in 4d, while in an upcoming paper we will consider linear quivers which, in the 3d case, have both unitary and special unitary bad nodes. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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- View/download PDF
335. Power equipment vibration visualization using intelligent sensing method based on event-sensing principle.
- Author
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Mingzhe Zhao, Xiaojun Shen, Lei Su, and Zihang Dong
- Subjects
- *
VISUALIZATION , *AMPLITUDE estimation , *DETECTORS , *ALGORITHMS , *ALGEBRA - Abstract
Vibration measurements can be used to evaluate the operation status of power equipment and are widely applied in equipment quality inspection and fault identification. Event-sensing technology can sense the change in surface light intensity caused by object vibration and provide a visual description of vibration behavior. Based on the analysis of the principle underlying the transformation of vibration behavior into event flow data by an event sensor, this paper proposes an algorithm to reconstruct event flow data into a relationship correlating vibration displacement and time to extract the amplitude-frequency characteristics of the vibration signal. A vibration measurement test platform is constructed, and feasibility and effectiveness tests are performed for the vibration motor and other power equipment. The results show that event-sensing technology can effectively perceive the surface vibration behavior of power and provide a wide dynamic range. Furthermore, the vibration measurement and visualization algorithm for power equipment constructed using this technology offers high measurement accuracy and efficiency. The results of this study provide a new noncontact and visual method for locating vibrations and performing amplitude-frequency analysis on power equipment. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
336. Infrared image target detection for substation electrical equipment based on improved faster region-based convolutional neural network algorithm.
- Author
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Wu, Changdong, Wu, Yanliang, and He, Xu
- Subjects
- *
CONVOLUTIONAL neural networks , *INFRARED imaging , *SPINE , *INFRARED equipment , *ALGORITHMS , *FEATURE extraction - Abstract
Substation electrical equipment generates a massive number of infrared images during operation. However, the overall quality of the infrared images is low and it lacks image detail information. When using traditional target detection algorithms for detection, feature extraction poses great difficulties. Therefore, to address this problem, this paper proposes a target detection algorithm based on the improved faster region-based convolutional neural network (Faster R-CNN). It achieves the correct identification of different types of electrical equipment in infrared images. First, the algorithm improves the backbone network of Faster R-CNN for feature extraction. An InResNet structure is proposed to replace the residual block structure of the original ResNet-34 network, which enhances the richness of feature extraction. Second, the rectified linear unit activation function in the original feature extraction network is replaced by the exponential linear unit activation function, and group normalization is used instead of batch normalization as the network normalization method. Then, the dense connection structure is introduced into the ResNet-34 network, and the whole network is called residual dense connection network. Finally, the improved Faster R-CNN is compared to the original Faster R-CNN, a single-shot multibox detector, and you only look once v3 plus spatial pyramid pooling. The experimental results show that the improved algorithm has the highest mean average precision and average recall for most of the substation electrical equipment in infrared images. Moreover, from the confidence level of the detected electrical equipment and the accuracy of the prediction box, the improved Faster R-CNN has the best performance. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
337. Fairness, assumptions, and guarantees for extended bounded response LTL+P synthesis.
- Author
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Cimatti, Alessandro, Geatti, Luca, Gigante, Nicola, Montanari, Angelo, and Tonetta, Stefano
- Subjects
- *
FAIRNESS , *LOGIC , *ALGORITHMS - Abstract
Realizability and reactive synthesis from temporal logics are fundamental problems in formal verification. The complexity of these problems for linear temporal logic with past (LTL+P) led to the identification of fragments with lower complexities and simpler algorithms. Recently, the logic of extended bounded response LTL+P ( LTL EBR + P for short) has been introduced. It allows one to express safety languages definable in LTL+P and it is provided with an efficient, fully symbolic algorithm for reactive synthesis. This paper features four related contributions. First, we introduce GR-EBR , an extension of LTL EBR + P with fairness conditions, assumptions, and guarantees that, on the one hand, allows one to express properties beyond the safety fragment and, on the other, it retains the efficiency of LTL EBR + P in practice. Second, we the expressiveness of GR-EBR starting from the expressiveness of its fragments. In particular, we prove that: (1) LTL EBR + P is expressively complete with respect to the safety fragment of LTL+P , (2) the removal of past operators from LTL EBR + P results into a loss of expressive power, and (3) GR-EBR is expressively equivalent to the logic GR(1) of Bloem et al. Third, we provide a fully symbolic algorithm for the realizability problem from GR-EBR specifications, that reduces it to a number of safety subproblems. Fourth, to ensure soundness and completeness of the algorithm, we propose and exploit a general framework for safety reductions in the context of realizability of (fragments of) LTL+P. The experimental evaluation shows promising results. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
338. Using data mining methods for risk assessment and intervention planning in diabetic patients.
- Author
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Ramanathan, Vanisree, Mhamane, Sharyu, Pawar, Jayesh, K., Nisha P., Kumar, Ujjwal, Tripathi, Shailesh, Pradhan, Keerti B., and Bhattacharya, Sudip
- Subjects
- *
DIABETES risk factors , *TREATMENT of diabetes , *BLOOD sugar analysis , *MEDICAL protocols , *RISK assessment , *PREPROCEDURAL fasting , *PREDIABETIC state , *DATA mining , *MEDICAL informatics , *CLUSTER analysis (Statistics) , *FOOD consumption , *SEX distribution , *AGE distribution , *DESCRIPTIVE statistics , *ALGORITHMS - Abstract
Introduction: Data mining in healthcare is a nascent arena of research in healthcare. Heterogeneity of Diabetes Mellitus in terms of clinical presentation calls for newer methods of research to study potential risk factors. Aim: The paper aims to use clustering techniques to identify the relationship between the four variables, namely the pre-prandial and postprandial sugar level, age and sex. Methods: The data was taken from a diagnostic laboratory in Wagholi, Pune. We conducted K-mean algorithm, EM algorithm, model-based clustering and t-mixture model. Results: It is evidenced that the data was best fitted to the t-mixture model. Our 50% samples were people with diabetes, 17% had prediabetes. Trivial correlation existed between age and sugar level. Males and females were equally at risk of having diabetes. Data presented concludes that age and sex have no effect on the risk of having diabetes. Data mining can be used to deduce meaningful clusters to drive plan-based interventions in the population. Conclusion: Methods of data mining can be used to deduce meaningful clusters in a heterogeneous dataset thus providing policymakers and healthcare researchers with novel information that will potentially contribute in formulating evidence-based policies. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
339. Multiobjective Optimization of Chaotic Image Encryption Based on ABC Algorithm and DNA Coding.
- Author
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Yu, Jinwei, Xie, Wei, and Zhang, Langwen
- Subjects
- *
IMAGE encryption , *OPTIMIZATION algorithms , *ALGORITHMS , *DATA privacy , *DNA , *ENTROPY (Information theory) - Abstract
As digital communication and storage continue to expand, the protection of image privacy information becomes increasingly critical. To safeguard sensitive visual information from unauthorized access, this paper proposes a novel image encryption scheme that integrates multiobjective Artificial Bee Colony (ABC) optimization algorithm and DNA coding. Multiple evaluation metrics including correlation relationship, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), and information entropy are collaboratively optimized by the ABC algorithm. The proposed method begins with the application of the SHA-256 algorithm to generate keys and random sequences using chaotic systems. These sequences are then employed for shuffling, DNA coding, decoding, and diffusion, generating initial encrypted images. Subsequently, the encrypted images serve as individuals within the ABC algorithm to determine optimal parameters of the chaotic systems and the best ciphertext image. Simulation experiments demonstrate that the ciphertext images achieved excellent results in information entropy, pixel correlation coefficient, NPCR, and UACI. The integration of the multiobjective ABC optimization algorithm with DNA coding in our proposed image encryption scheme results in heightened security, as evidenced by superior performance in various metrics. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
340. Quantum state clustering algorithm based on variational quantum circuit.
- Author
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Fang, Pengpeng, Zhang, Cai, and Situ, Haozhen
- Subjects
- *
QUANTUM states , *ALGORITHMS , *MACHINE learning , *LEARNING communities - Abstract
Clustering, a well-studied problem in the machine learning community, becomes even more intriguing with the emergence of quantum machine learning. Specifically, exploring clustering techniques for quantum data, such as quantum states, holds great interest. This paper introduces a quantum state clustering algorithm that utilizes variational quantum circuits. Our algorithm transforms the clustering problem into a parameter optimization task involving parametric quantum circuits. Each cluster is represented by a variational quantum circuit (VQC), which learns to extract the distinctive feature of its corresponding cluster during the optimization process. To guide the optimization of circuit parameters, we design an objective function that encourages each cluster's feature extractor to produce features similar to states within its own cluster and dissimilar to states in other clusters. We construct four quantum state datasets for testing the effectiveness of our algorithm. The numerical results demonstrate that our algorithm can achieve satisfying performance. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
341. The improved strategy of BOA algorithm and its application in multi-threshold image segmentation.
- Author
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Wang, Lai-Wang and Hung, Chen-Chih
- Subjects
- *
IMAGE segmentation , *OPTIMIZATION algorithms , *ALGORITHMS , *DIFFERENTIAL evolution , *IMAGE processing , *GAUSSIAN distribution - Abstract
In response to the low efficiency and poor quality of current seed optimization algorithms for multi-threshold image segmentation, this paper proposes the utilization of the normal distribution in the cluster distribution mathematical model, the Levy flight mechanism, and the differential evolution algorithm to address the deficiencies of the seed optimization algorithm. The main innovation lies in applying the BBO algorithm to image multi threshold segmentation, providing a new perspective and method for image segmentation tasks. The second significant progress is the combination of Levy flight dynamics and differential evolution algorithm (DEA) to improve the BBO algorithm, thereby enhancing its performance and image segmentation quality. Therefore, a multi-threshold image segmentation model based on the optimized seed optimization algorithm is developed. The experimental results showed that on the function f1, the iteration of the improved seed optimization algorithm was 53, the Generational Distance value was 0.0020, the Inverted Generational Distance value was 0.098, and the Spacing value was 0.051. Compared with the other two algorithms, the improved seed optimization algorithm has better image segmentation performance and clearer image segmentation details. In summary, compared with existing multi-threshold image segmentation methods, the proposed multi-threshold image segmentation model based on the improved seed optimization algorithm has a better image segmentation effect and higher efficiency, can significantly improve the quality of image segmentation, has positive significance for the development of image processing technology, and also provides references for the improvement and application of optimization algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
342. A negative selection algorithm with human-in-the-loop for anomaly detection.
- Author
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Li, Chunling and Zhang, Yi
- Subjects
- *
ALGORITHMS , *INTRUSION detection systems (Computer security) , *DETECTORS - Abstract
The existing negative selection algorithms can not improve their detection performance by human intervention during the testing process. This paper proposes a negative selection algorithm with human-in-the-loop for anomaly detection. It uses self-sample clusters to train detectors with a nonrandom strategy. Its detectors and self-sample clusters fully cover state space without overlapping each other. It locally adjusts detectors and self-sample clusters with human intervention to improve its detection performance during the testing process. Experiments were performed on two synthetic datasets and the Iris dataset from the UCI repository to assess its performance. The results show that it outperforms the other anomaly detection methods in most cases. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
343. Embedded Particle Size Measurement Method of Metal Mineral Polished Section Using Gaussian Mixture Model Based on Expectation Maximization Algorithm.
- Author
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Peng, Hao, Luo, Chaoxi, He, Lifang, and Tang, Haopo
- Subjects
- *
GAUSSIAN mixture models , *PARTICLE size determination , *MINERALS , *METALS , *ALGORITHMS , *PYRITES - Abstract
The study of process mineralogy plays a very important role in the field of mineral processing and metallurgy, in which the measurement of mineral-embedded particle size is one of the main research areas. The manual measurement method using a microscope has many problems, such as heavy workload and low measurement accuracy. In order to solve this problem, this paper proposes a Gaussian mixture model based on an expectation maximization (EM) algorithm to measure the embedded particle sizes of minerals of polished metal sections. Experiments are here performed on the polished section images of ilmenite and pyrite, and we compared the results with a microscope. The experimental results show that the proposed method has higher precision and accuracy in measuring the embedded particle sizes of metal minerals. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
344. The Algorithm Holy: TikTok, Technomancy, and the Rise of Algorithmic Divination.
- Author
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St. Lawrence, Emma
- Subjects
- *
SOCIAL media mobile apps , *WITCHCRAFT , *DIVINATION , *DANCE , *ALGORITHMS , *SINGING , *SUBCULTURES , *POPULAR music - Abstract
The social media app TikTok was launched in the US in 2017 with a very specific purpose: sharing 15-s clips of singing and dancing to popular songs. Seven years and several billion downloads later, it is now the go-to app for Gen Z Internet users and much better known for its ultra-personalized algorithm, AI-driven filters, and network of thriving subcultures. Among them, a growing community of magical and spiritual practitioners, frequently collectivized as Witchtok, who use the app not only share their craft and create community but consider the technology itself a powerful partner with which to conduct readings, channel deities, connect to a collective conscious, and transcend the communicative boundaries between the human and spirit realms—a practice that can be understood as algorithmic divination. In analyzing contemporary witchcraft on TikTok and contextualizing it within the larger history of technospirituality, this paper aims to explore algorithmic divination as an increasingly popular and powerful practice of technomancy open to practitioners of diverse creed and belief. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
345. Algorithms and Faith: The Meaning, Power, and Causality of Algorithms in Catholic Online Discourse.
- Author
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Sierocki, Radosław
- Subjects
- *
ONLINE algorithms , *ALGORITHMS , *ARTIFICIAL intelligence , *COMPUTER programming , *DISCOURSE analysis - Abstract
The purpose of this article is to present grassroots concepts and ideas about "the algorithm" in the religious context. The power and causality of algorithms are based on lines of computer code, making a society influenced by "black boxes" or "enigmatic technologies" (as they are incomprehensible to most people). On the other hand, the power of algorithms lies in the meanings that we attribute to them. The extent of the power, agency, and control that algorithms have over us depends on how much power, agency, and control we are willing to give to algorithms and artificial intelligence, which involves building the idea of their omnipotence. The key question is about the meanings and the ideas about algorithms that are circulating in society. This paper is focused on the analysis of "vernacular/folk" theories on algorithms, reconstructed based on posts made by the users of Polish Catholic forums. The qualitative analysis of online discourse makes it possible to point out several themes, i.e., according to the linguistic concept, "algorithm" is the source domain used in explanations of religious issues (God as the creator of the algorithm, the soul as the algorithm); algorithms and the effects of their work are combined with the individualization and personalization of religion; algorithms are perceived as ideological machines. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
346. An Improved Sorting Algorithm for Periodic PRI Signals Based on Congruence Transform.
- Author
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Dong, Huixu, Ge, Yuanzheng, Zhou, Rui, and Wang, Hongyan
- Subjects
- *
WAVELET transforms , *MATHEMATICAL decoupling , *ALGORITHMS , *SIGNALS & signaling - Abstract
Recently, a signal sorting algorithm based on the congruence transform has been proposed, which is effective in dealing with the staggered Pulse Repetition Interval (PRI) signals. It can effectively sort the staggered PRI signals and obtain the sub-PRI sequence directly without sub-PRI ranking, and it is less affected by interfered pulses and pulse loss. Nevertheless, we find that the algorithm causes pseudo-peaks in the remainder histogram when sorting signals such as sliding PRI, sinusoidal PRI, etc. (collectively referred to as periodic PRI signal in this paper) and pseudo-peaks will cause errors in signal sorting. To solve the issue of pseudo-peaks when sorting periodic PRI signals, an improved sorting algorithm based on congruence transform is proposed. According to the analysis of the congruence characteristics of the periodic PRI signal, a novel method is proposed to identify pseudo-peaks based on the histogram peak amplitude and symmetric difference set. The signal sorting algorithm based on congruence transform is improved to achieve a good sorting effect on periodic PRI signals. Simulation experiments demonstrate that the novel algorithm can effectively sort periodic PRI signals and improve Precall, Pd, and Pf by 6.9%, 5.1%, and 3.2%, respectively, compared to the typical similar algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
347. Joint watermarking encryption compression algorithm for securing an e-healthcare application.
- Author
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Abderrahmane, Daham and Mohamed, Ouslim
- Subjects
- *
DIGITAL watermarking , *WAVELET transforms , *DIGITAL image watermarking , *TELERADIOLOGY , *WATERMARKS , *DISCRETE wavelet transforms , *ALGORITHMS - Abstract
Radiological imaging generates large data volumes for diagnosing. These data volumes still constitute an immense challenge for individual radiology practices, either when complying with the archive, hacker manipulation or swiftly distributing images among specialists as part of the diagnostic process. Analyzing images through illegal distortions may lead to inaccurate medical decisions. Watermarking techniques can be used to authenticate images, detect, and recover illegal changes made to teleradiology images as well. In this paper, a new blind medical image watermarking joint cryptocompression system is proposed to simultaneously achieve watermarking and compression. A discrete wavelet transform is applied to the medical image to locate different frequency sub-bands. The watermark is scrambled using one-dimensional chaotic map generator with uniform distribution modulo-one transformations for generating highly independent and uniformly distributed random chaotic sequences. A particle cryptocompression algorithm is applied for the insertion step: the scrambled watermark is inserted into the highest singular value derived from the compressed low-frequency sub-band, ensuring a delicate balance between imperceptibility and robustness. From the conducted tests and comparison of the obtained results with other techniques, we concluded that the robustness of the algorithm under various attacks was improved by the excellent value of the NC parameter, especially in the case of compression and geometric attacks. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
348. Adaptive Fractional-Order Multi-Scale Optimization TV-L1 Optical Flow Algorithm.
- Author
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Yang, Qi, Wang, Yilu, Liu, Lu, and Zhang, Xiaomeng
- Subjects
- *
OPTICAL flow , *OPTIMIZATION algorithms , *ANT algorithms , *ALGORITHMS , *SWARM intelligence , *SEARCH algorithms - Abstract
We propose an adaptive fractional multi-scale optimization optical flow algorithm, which for the first time improves the over-smoothing of optical flow estimation under the total variation model from the perspective of global feature and local texture balance, and solves the problem that the convergence of fractional optical flow algorithms depends on the order parameter. Specifically, a fractional-order discrete L1-regularization Total Variational Optical Flow model is constructed. On this basis, the Ant Lion algorithm is innovatively used to realize the iterative calculation of the optical flow equation, and the fractional order is dynamically adjusted to obtain an adaptive optimization algorithm with strong search accuracy and high efficiency. In this paper, the flexibility of optical flow estimation in weak gradient texture scenes is increased, and the optical flow extraction rate of target features at multiple scales is greatly improved. We show excellent recognition performance and stability under the MPI_Sintel and Middlebury benchmarks. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
349. Intelligent Algorithms Enable Photocatalyst Design and Performance Prediction.
- Author
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Wang, Shifa, Mo, Peilin, Li, Dengfeng, and Syed, Asad
- Subjects
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PHOTOCATALYSTS , *ARTIFICIAL neural networks , *OPTIMIZATION algorithms , *PHOTOCATALYSIS , *ALGORITHMS , *ARTIFICIAL intelligence , *POLLUTANTS - Abstract
Photocatalysts have made great contributions to the degradation of pollutants to achieve environmental purification. The traditional method of developing new photocatalysts is to design and perform a large number of experiments to continuously try to obtain efficient photocatalysts that can degrade pollutants, which is time-consuming, costly, and does not necessarily achieve the best performance of the photocatalyst. The rapid development of photocatalysis has been accelerated by the rapid development of artificial intelligence. Intelligent algorithms can be utilized to design photocatalysts and predict photocatalytic performance, resulting in a reduction in development time and the cost of new catalysts. In this paper, the intelligent algorithms for photocatalyst design and photocatalytic performance prediction are reviewed, especially the artificial neural network model and the model optimized by an intelligent algorithm. A detailed discussion is given on the advantages and disadvantages of the neural network model, as well as its application in photocatalysis optimized by intelligent algorithms. The use of intelligent algorithms in photocatalysis is challenging and long term due to the lack of suitable neural network models for predicting the photocatalytic performance of photocatalysts. The prediction of photocatalytic performance of photocatalysts can be aided by the combination of various intelligent optimization algorithms and neural network models, but it is only useful in the early stages. Intelligent algorithms can be used to design photocatalysts and predict their photocatalytic performance, which is a promising technology. [ABSTRACT FROM AUTHOR]
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- 2024
- Full Text
- View/download PDF
350. Personalized Treatment Policies with the Novel Buckley-James Q-Learning Algorithm.
- Author
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Lee, Jeongjin and Kim, Jong-Min
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MACHINE learning , *ALGORITHMS , *SURVIVAL analysis (Biometry) , *TIME management , *PATIENT care , *REINFORCEMENT learning - Abstract
This research paper presents the Buckley-James Q-learning (BJ-Q) algorithm, a cutting-edge method designed to optimize personalized treatment strategies, especially in the presence of right censoring. We critically assess the algorithm's effectiveness in improving patient outcomes and its resilience across various scenarios. Central to our approach is the innovative use of the survival time to impute the reward in Q-learning, employing the Buckley-James method for enhanced accuracy and reliability. Our findings highlight the significant potential of personalized treatment regimens and introduce the BJ-Q learning algorithm as a viable and promising approach. This work marks a substantial advancement in our comprehension of treatment dynamics and offers valuable insights for augmenting patient care in the ever-evolving clinical landscape. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
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