Journal articles: 'Cascade algorithm'

1

Segal, M., and E. Weinstein. "The cascade EM algorithm." Proceedings of the IEEE 76, no. 10 (1988): 1388–90. http://dx.doi.org/10.1109/5.16341.

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Zhang, Shuyi, Bo Yang, Hong Xie, and Moru Song. "Applications of an Improved Aerodynamic Optimization Method on a Low Reynolds Number Cascade." Processes 8, no. 9 (September 14, 2020): 1150. http://dx.doi.org/10.3390/pr8091150.

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The effect of cascade aerodynamic optimization on turbomachinery design is very significant. However, for most traditional cascade optimization methods, aerodynamic parameters are considered as boundary conditions and rarely directly used as the optimization variables to realize optimization. Given this problem, this paper proposes an improved cascade aerodynamic optimization method in which an incidence angle and nine geometric parameters are used to parameterize the cascade and one modified optimization algorithm is adopted to find the cascade with the optimal aerodynamic performance. The improved parameterization approach is based on the Non-Uniform Rational B-Splines (NURBS) method, the camber line superposing thickness distribution molding (CLSTDM) method, and the plane cascade design method. To rapidly and effectively find the cascade with the largest average lift-drag ratio within a certain range of incidence angles, modified particle swarm optimization combined with the modified very fast simulated annealing algorithm (PSO-MVFSA) is adopted. To verify the feasibility of the method, a cascade with NACA4412 and a practical cascade are optimized. It is found that the average lift-drag ratios of two optimal performance cascades are respectively increased by 13.38% and 15.21% in comparison to those of two original cascades. Meanwhile, through optimizing the practical cascade of the Blade D500, under different volume flow rates, the pressure coefficient of the optimized cascade is increased by an average of more than 6.12% compared to that of the prototype, and the average efficiency is increased by 11.15%. Therefore, this improved aerodynamic optimization method is reliable and feasible for the performance improvement of cascades with a low Reynolds number.

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Bakir, F., S. Kouidri, T. Belamri, and R. Rey. "On a General Method of Unsteady Potential Calculation Applied to the Compression Stages of a Turbomachine—Part I: Theoretical Approach." Journal of Fluids Engineering 123, no. 4 (June 6, 2001): 780–86. http://dx.doi.org/10.1115/1.1399286.

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An algorithm using the singularity method was developed. It allows taking into account the interaction between fixed and mobile cascades. Its principle is based on the summation of discrete vortices distributed periodically on the rotor and stator profiles. The overall matrix, obtained by applying the boundary conditions, takes into account the complexity of the studied cascade geometry (presence or not of splitter blades, possibly variable pitch of the profiles, etc…) To illustrate the interest and the impact of the algorithm, two parametric studies on turbomachines cascade are presented: Planes cascade made up of a rotor and a stator (at the mean radius of an axial fan). Circular cascade made up of impeller and a volute (peripheral cascade of a centrifugal pump).

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Karlos, Stamatis, Nikos Fazakis, Sotiris Kotsiantis, and Kyriakos Sgarbas. "A Semisupervised Cascade Classification Algorithm." Applied Computational Intelligence and Soft Computing 2016 (2016): 1–14. http://dx.doi.org/10.1155/2016/5919717.

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Classification is one of the most important tasks of data mining techniques, which have been adopted by several modern applications. The shortage of enough labeled data in the majority of these applications has shifted the interest towards using semisupervised methods. Under such schemes, the use of collected unlabeled data combined with a clearly smaller set of labeled examples leads to similar or even better classification accuracy against supervised algorithms, which use labeled examples exclusively during the training phase. A novel approach for increasing semisupervised classification using Cascade Classifier technique is presented in this paper. The main characteristic of Cascade Classifier strategy is the use of a base classifier for increasing the feature space by adding either the predicted class or the probability class distribution of the initial data. The classifier of the second level is supplied with the new dataset and extracts the decision for each instance. In this work, a self-trained NB∇C4.5 classifier algorithm is presented, which combines the characteristics of Naive Bayes as a base classifier and the speed of C4.5 for final classification. We performed an in-depth comparison with other well-known semisupervised classification methods on standard benchmark datasets and we finally reached to the point that the presented technique has better accuracy in most cases.

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Lawton, W., S. L. Lee, and Zuowei Shen. "Convergence of multidimensional cascade algorithm." Numerische Mathematik 78, no. 3 (January 1, 1998): 427–38. http://dx.doi.org/10.1007/s002110050319.

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Fu, Yun Zhun, and Xu Zhang. "Research on Room Temperature Control of High Accuracy Constant Temperature Room Based on Cascade Control." Applied Mechanics and Materials 48-49 (February 2011): 976–79. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.976.

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DMC-PID cascade control strategy was adopted to apply on high accuracy constant temperature air conditioning system because constant temperature room had large inertia, delaying, a few interference factors characteristics. The construction type of DMC-PID cascade control system was designed and the prediction model of inner loop and outer loop was determined, and then MATLAB software was applied to simulate and compare robust stability, tracking performance, anti-jamming capability characteristics of DMC-PID cascade control algorithms with other algorithms. Through studies, the overshoot of DMC-PID cascade control of room temperature reduced 2% in comparison with the PID algorithm, but was much larger than that of DMC algorithm. Its regulation time was nearly the same to that DMC algorithm, but cut down 25% in comparison with the PID algorithm. At last, the simulation result showed DMC-PID cascade control strategy application on temperature control of high accuracy constant temperature room had feasibility and effectiveness, and the control strategy had strong robust stability, tracking performance, anti- disturbance ability characteristics.

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Ye, Wenbin. "Multiplierless Multiple-Stage Cascaded FIR Filter Design." Journal of Circuits, Systems and Computers 24, no. 01 (November 10, 2014): 1550011. http://dx.doi.org/10.1142/s0218126615500115.

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It is well known that multiplierless finite impulse response (FIR) filters in multiple-stage cascade form can achieve lower hardware cost and lower coefficient sensitivity than that of single stage design. In this work, a novel algorithm is proposed for the design of multiplierless multiple-stage cascaded FIR filters. Unlike to the conventional algorithms in which the number of stages is fixed and usually is fixed to two, the number of stage in the proposed algorithm is automatically determined. The design examples show that the proposed algorithm significantly outperforms the best existing algorithm in terms of hardware cost and the design time is also saved.

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Zha, Feng, Jiang Ning Xu, and Bai Qing Hu. "Cascade Compensation Algorithm for Strapdown Inertial Navigation System." Advanced Materials Research 179-180 (January 2011): 989–99. http://dx.doi.org/10.4028/www.scientific.net/amr.179-180.989.

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The cascade compensation algorithm for no damp strapdown inertial navigation system (SINS) is designed based on control model and error characteristic of SINS level-loop. According to stability and frequency characteristic analysis for SINS level-loop, a compensation network, which is chosen to alter either the roots location or the frequency response of the system, is cascaded with the SINS level-loop to damp the oscillatory or accumulated errors. The network parameters are attained by designing the frequency characteristic using frequency domain performance indexes, which are transformed from the expected time domain indexes. The algorithm implementation of the compensator is competed by solving the first-order differential equations set, which is derived from Laplace transform of the compensation network using intermediate variables. Results of digital simulation and test on sea proved that the system attitude accuracy improved 1 order and the system position accuracy improved 1 time when the compensation network was cascaded into SINS.

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Zhang, Yu, Maksim Tsikhanovich, and Georgi Smilyanov. "History Sensitive Cascade Model." International Journal of Agent Technologies and Systems 3, no. 2 (April 2011): 53–66. http://dx.doi.org/10.4018/jats.2011040104.

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Diffusion is a process by which information, viruses, ideas, or new behavior spread over social networks. Traditional diffusion models are history insensitive, i.e. only giving activated nodes a one-time chance to activate each of its neighboring nodes with some probability. But history dependent interactions between people are often observed in the real world. This paper proposes the History Sensitive Cascade Model (HSCM), a model of information cascade through a network over time. The authors consider the “activation” problem of finding the probability of that a particular node receives information given that some nodes are initially informed. In this paper it is also proven that selecting a set of k nodes with greatest expected influence is NP-hard, and results from submodular functions are used to provide a greedy approximation algorithm with a 1–1/e–e lower bound, where e depends polynomially on the precision of the solution to the “activation” problem. Finally, experiments are performed comparing the greedy algorithm to three other approximation algorithms.

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Zhao, Wei Guo, and Li Ying Wang. "Application of Cascade-Correlation Algorithm in Cavitation Characteristics of Hydro Turbine." Advanced Materials Research 113-116 (June 2010): 250–53. http://dx.doi.org/10.4028/www.scientific.net/amr.113-116.250.

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The cascade correlation algorithm that is cascade-correlation(CC) algorithms, CC network structure and CC network weights learning algorithm are introduced, based on the real data in hydropower station, considering the cavitation characteristics, the network model is established based on CC algorithm, and the applications of CC and BP algorithm of turbine are compared. The results show that the CC algorithm is better than BP neural network, the results can be used in the optimal operation of hydropower, and it has a practical significance.

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Islam, M. Fakhrul, Joarder Kamruzzaman, and Guojun Lu. "Improved ANN Based Tap-Changer Controller Using Modified Cascade-Correlation Algorithm." Journal of Advanced Computational Intelligence and Intelligent Informatics 9, no. 3 (May 20, 2005): 226–34. http://dx.doi.org/10.20965/jaciii.2005.p0226.

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Artificial Neural Network (ANN) based tap changer control of closed primary bus and cross network connected parallel transformers has demonstrated potential use in power distribution system. In those research works the proposed ANN for application in this control were developed using various algorithms and concluded that a network trained by Bayesian Regularization (BR) backpropagation algorithm produced the best performance measured in terms of correct tap changing decisions. However, further improvement of ANN based transformer tap changer operation is always desirable. A general rule for obtaining good generalization is to use the smallest network that solves the problem. In this paper, we show that a small sized ANN is obtainable for further improvement of transformer tap changer operation by modifying the standard Cascade-Correlation algorithm. The modification incorporates weight smoothing of output layer weights in Cascade-Correlation learning using Bayesian frame work. Experimental results demonstrate that significant improvement in performance is achieved when an ANN is trained by modified Cascade-Correlation algorithm instead of standard Cascade-Correlation or Bayesian Regularization backpropagation algorithm. A comparison of performances of different algorithms in application to transformer tap changer operation is analyzed and the results are presented.

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Choi, Myeong-Bok, and Sang-Un Lee. "Family of Cascade-correlation Learning Algorithm." Journal of Korean Institute of Intelligent Systems 15, no. 1 (February 1, 2005): 87–91. http://dx.doi.org/10.5391/jkiis.2005.15.1.087.

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CHEN, DI-RONG. "A CONSTRUCTION OF CONVERGENT CASCADE ALGORITHMS IN SOBOLEV SPACES." International Journal of Wavelets, Multiresolution and Information Processing 05, no. 05 (September 2007): 685–97. http://dx.doi.org/10.1142/s0219691307001987.

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Cascade algorithms play an important role in wavelet analysis and computer graphics. The paper considers the convergence of cascade algorithms in Sobolev spaces. With the help of the factorization of matrix masks, we give a sufficient condition for the convergence. The condition is expressed in the time domain. More importantly, an algorithm for the construction of convergent cascade algorithms in Sobolev space starting from any matrix mask satisfying a mild condition is presented. Examples are given to illustrate our theorems.

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Mohamed, Soha Abd El-Moamen, Marghany Hassan Mohamed, and Mohammed F. Farghally. "A New Cascade-Correlation Growing Deep Learning Neural Network Algorithm." Algorithms 14, no. 5 (May 19, 2021): 158. http://dx.doi.org/10.3390/a14050158.

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In this paper, a proposed algorithm that dynamically changes the neural network structure is presented. The structure is changed based on some features in the cascade correlation algorithm. Cascade correlation is an important algorithm that is used to solve the actual problem by artificial neural networks as a new architecture and supervised learning algorithm. This process optimizes the architectures of the network which intends to accelerate the learning process and produce better performance in generalization. Many researchers have to date proposed several growing algorithms to optimize the feedforward neural network architectures. The proposed algorithm has been tested on various medical data sets. The results prove that the proposed algorithm is a better method to evaluate the accuracy and flexibility resulting from it.

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Pavani, K. "Novel Vehicle Detection in Real Time Road Traffic Density Using Haar Cascade Comparing with KNN Algorithm based on Accuracy and Time Mean Speed." Revista Gestão Inovação e Tecnologias 11, no. 2 (June 5, 2021): 897–910. http://dx.doi.org/10.47059/revistageintec.v11i2.1723.

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Aim: The main objective of the paper is to detect objects in iconic real time traffic density videos from CCTVs and Cameras using Haar Cascade algorithm and to compare algorithms with K-Nearest Neighbour algorithm (KNN). In this case we tried improving the rate of accuracy in predicting the traffic density. Materials and methods: Haar Cascade algorithm is applied on 5 realistic videos and which consists of more than 250 frames. For the same we evaluated the Accuracy and Precision values. Harr-like function displays the vehicle’s visual structure, and the AdaBoost machine learning algorithm was used to create a classifier by combining individual classifiers. The significance value achieved for finding the accuracy and precision was 0.445 and 0.754 respectively. Results and Discussions: Detection of vehicles in high speed videos is performed by using Haar Cascade which has mean accuracy with 85.22% and mean precision with 90.63% and 60% of mean accuracy and 58.53% mean precision in KNN classifiers. Conclusion: The performance of the Haar Cascade appears to be better than KNN in terms of both Accuracy and Precision.

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Wang, Li Ying, Wei Guo Zhao, and Jian Min Hou. "Application of Cascade-Correlation Algorithm in Vibration Characteristics of Hydro Turbine." Advanced Materials Research 108-111 (May 2010): 1070–74. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.1070.

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The cascade correlation algorithm that is CC algorithms, CC network structure and CC network weights learning algorithm are introduced, based on the operation data of Wanjiazhai hydropower station, considering the pressure fluctuation, the network model of vibration characteristics is established based on CC algorithm, and the applications of CC and BP algorithm in vibration characteristics of turbine are compared. The results show that the CC algorithm is better than BP neural network, the results can be used in the optimal operation of hydropower, and it has a practical significance.

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Alkhafaji, Mohammed Ayad, and Yunus Uzun. "Design and Speed Control of SynRM using Cascade PID Controller with PSO Algorithm." International Journal of Renewable Energy Development 9, no. 1 (February 5, 2020): 69–76. http://dx.doi.org/10.14710/ijred.9.1.69-76.

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In recent years, the variable speed motor drive is supported over a fixed speed motor drive as per essentialness safeguarding, speed or position control and improvement of transient response characteristics. The aim of any speed controller is to take main signal that represent the reference speed and to drive the framework at that reference speed. This paper exhibits the design, simulation and control of synchronous reluctance motor (SynRM). In addition, the motor speed is controlled by utilizing a conventional PID controller that has been used from the cascaded structure. The Particle Swarm Optimization (PSO) was used to find the best parameters of the PID controller. Lead-Lag controller presents from the cascaded controller as the following period of control. The Space vector pulse width modulation (SVPWM) plot has been proposed to control the motor and make the motor work with no rotor confine contingent upon the info parameters that utilization in the simulation. An examination between both of PID tuned and PSO tuned controller affirms that the PSO gives dazzling control highlights to the motor speed and have an edge over the physically changing controller. Thus, this paper present investigation and simulation for the most precise procedures to control the speed reaction and torque reaction of synchronous reluctance motor (SynRM).©2020. CBIORE-IJRED. All rights reserved

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Li, Qiong, Dan Le, Haokun Mao, Xiamu Niu, Tian Liu, and Hong Guo. "Study on error reconciliation in quantum key distribution." Quantum Information and Computation 14, no. 13&14 (October 2014): 1117–35. http://dx.doi.org/10.26421/qic14.13-14-5.

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As one of the most important procedure in quantum key distribution system, the error reconciliation algorithm has drew many attentions. However, studies on the error reconciliation algorithm mainly focuses on the reconciliation efficiency. Since the ultimate goal of study on the error reconciliation is to find the most suitable algorithm for a quantum key distribution system and maximize the throughput rate of the whole system, the indicator of reconciliation efficiency is not full-scale enough to evaluate an error reconciliation algorithm. In this paper we propose a new evaluation scheme, including four direct indicators and one composite indicator to solve the problem. Following the new scheme, seven representative error reconciliation algorithms are simulated and compared thoroughly, i.e. BBBSS, the original Cascade and two improved Cascade algorithms, Winnow, and two LDPC based algorithms. Our works are very beneficial to the evaluation, comparison, selection and optimization of error reconciliation algorithms for a practical quantum key distribution system.

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Rastogi, Akanksha, and Beom Sahng Ryuh. "Teat detection algorithm: YOLO vs. Haar-cascade." Journal of Mechanical Science and Technology 33, no. 4 (April 2019): 1869–74. http://dx.doi.org/10.1007/s12206-019-0339-5.

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White, D. A. "A generalised algorithm for cascade mass balances." Chemical Engineering Science 48, no. 4 (February 1993): 819–21. http://dx.doi.org/10.1016/0009-2509(93)80148-j.

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Shen, Yi, and Song Li. "Cascade algorithm associated with Hölder continuous masks." Applied Mathematics Letters 22, no. 8 (August 2009): 1213–16. http://dx.doi.org/10.1016/j.aml.2009.01.032.

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Xie, Hong, Mingze Zhong, Yongkun Li, and John C. S. Lui. "Understanding Persuasion Cascades in Online Product Rating Systems: Modeling, Analysis, and Inference." ACM Transactions on Knowledge Discovery from Data 15, no. 3 (April 12, 2021): 1–29. http://dx.doi.org/10.1145/3440887.

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Online product rating systems have become an indispensable component for numerous web services such as Amazon, eBay, Google Play Store, and TripAdvisor. One functionality of such systems is to uncover the product quality via product ratings (or reviews) contributed by consumers. However, a well-known psychological phenomenon called “ message-based persuasion ” lead to “ biased ” product ratings in a cascading manner (we call this the persuasion cascade ). This article investigates: (1) How does the persuasion cascade influence the product quality estimation accuracy? (2) Given a real-world product rating dataset, how to infer the persuasion cascade and analyze it to draw practical insights? We first develop a mathematical model to capture key factors of a persuasion cascade. We formulate a high-order Markov chain to characterize the opinion dynamics of a persuasion cascade and prove the convergence of opinions. We further bound the product quality estimation error for a class of rating aggregation rules including the averaging scoring rule, via the matrix perturbation theory and the Chernoff bound. We also design a maximum likelihood algorithm to infer parameters of the persuasion cascade. We conduct experiments on both synthetic data and real-world data from Amazon and TripAdvisor. Experiment results show that our inference algorithm has a high accuracy. Furthermore, persuasion cascades notably exist, but the average scoring rule has a small product quality estimation error under practical scenarios.

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Ju, Y. P., and C. H. Zhang. "Multi-point and multi-objective optimization design method for industrial axial compressor cascades." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 225, no. 6 (May 25, 2011): 1481–93. http://dx.doi.org/10.1177/0954406210395878.

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Modern aerodynamic optimization design methods for the industrial axial compressor cascade mainly aim at improving both design point and off-design point performance. In this study, a multi-point and multi-objective optimization design method is established for the cascade, particularly aiming at widening the operating range while maintaining good performance at the acceptable expense of computational load. The design objectives are to maximize the static pressure ratio and minimize the total pressure loss coefficient at the design point, and to maximize the operating range for the positive and negative incidences. To alleviate the computational load, a design of experiment (DOE)-based GA–BP-ANN model is constructed to rapidly approximate the cascade aerodynamic performance in the optimization process. The artificial neural network (ANN) is trained by the genetic algorithm (GA) technique and back propagation (BP) algorithm, where the training cascades are sampled by the DOE method and analysed by the computational fluid dynamics method. The multi-objective genetic algorithm is used to search for a series of Pareto-optimum solutions, from which an optimal cascade is found out whose objectives are all better than (ABT) those of the original design. The ABT cascade is characterized by the lower camber and higher turning angle, leading to better aerodynamic performance in a widened operating range. Compared with the original design, the ABT cascade decreases the total pressure loss coefficient by 1.54 per cent, 23.4 per cent, and 7.87 per cent at the incidences of 5°, −9°, and 13°, respectively. The established optimization design method can be extended to the three-dimensional aerodynamic design of axial compressor blade.

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Guan, Zhi Jin, Wei Ping Ding, and Xue Yun Cheng. "Cascade Network in Reversible Logic Gate Based on Series Connection." Applied Mechanics and Materials 241-244 (December 2012): 3075–79. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.3075.

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This paper analyzes and proves that the relationship between the output results of the homotypic Toffoli gate which is series cascade and the number of the gates which are series cascade. In order to guarantee the convergence of the process of the series cascade, we gave the counting results of the series cascade network for Toffoli gates, and proved that in the input vector (0, 1, …, 2n-1), the number of the bit vectors with Hamming weight H(w)≥n-1 is equal to the bit number of bit vectors plus 1, and obtained the conclusion that there are (n+1)! kinds of transformation for Toffoli gate series cascade network. Simultaneously we provide the series cascade network algorithm of the Toffoli gates. The reversible network cascade system designed by the above algorithm verified the validity of this algorithm.

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Benini, E., and A. Toffolo. "A parametric method for optimal design of two-dimensional cascades." Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy 215, no. 4 (June 1, 2001): 465–73. http://dx.doi.org/10.1243/0957650011538721.

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A parametric method for optimal design of two-dimensional cascades, based on the coupling between a genetic algorithm and a commercial computational fluid dynamics code, is introduced. The results of cascade geometry optimization for a large range of inlet and outlet flow angle pairs are presented. The method is a simple as well as effective tool for the optimal design of cascades for axial flow pumps.

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Huang, Jin Hui, A. Ming Hao, Xiao Long Li, and Long Hua She. "Nonlinear Cascade Control of the Joint-Structure in EMS High Speed Maglev Train." Advanced Materials Research 765-767 (September 2013): 1992–97. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.1992.

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In order to strengthen the high-speed maglev trains anti-disturbance ability, the traditional linear cascade control algorithm has been improved. Firstly, the mathematical model of the joint-structure in the high-speed maglev train was established according to the dynamics and electromagnetism theory.Secondly,the advantages and disadvantages of the linear cascade control algorithm were analysed.Thirdly,the relationship between the current loop and position loop control parameters and the system performance was discussed .Finally,the nonlinear cascade control algorithm of the joint-structure in high-speed maglev train was introduced. In the algorithm,the current loop controller gain would be reduced when the positional deviation increases. At the same time, the gain of the position loop controller would be increased. The simulation results show that the suspension joint-structure gap changes caused by the failure of a single suspension point or disturbing force ,of systems with nonlinear cascade control algorithm were less than that of systems with linear cascade control algorithm. The new algorithm can improve the anti-disturbance ability of the maglev train,It can also ensure the safety and comfort of passengers.

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Kim, Tae-yun, and Suk-seung Hwang. "Cascade AOA Estimation Algorithm Based on Flexible Massive Antenna Array." Sensors 20, no. 23 (November 28, 2020): 6797. http://dx.doi.org/10.3390/s20236797.

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The Angle-of-Arrival (AOA) has a variety of applications in civilian and military wireless communication fields. Due to the rapid development of the location-based service (LBS) industry, the importance of the AOA estimation technique has increased. Although a large antenna array is necessary to estimate accurate AOA information of many signals, the computational complexity of conventional AOA estimation algorithms, such as Multiple Signal Classification (MUSIC), is dramatically increased. In this paper, we propose a cascade AOA estimation algorithm employing CAPON and Beamspace MUSIC, based on a flexible (on/off) antenna array. First, this approach roughly finds AOA groups, including several signal AOAs using CAPON, by applying some of the antenna elements. Then, it estimates each signal AOA in the estimated AOA groups using Beamspace MUSIC by applying the full size of the antenna array. In addition to extremely low computational complexity, the proposed algorithm also has similar estimation performance to that of MUSIC. In particular, the proposed cascade AOA estimation algorithm is highly efficient when employing a massive antenna array. Representative computer simulation examples are provided to illustrate the AOA estimation performance of the proposed technique.

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Anh, Nguyen Ngoc, Nguyen Xuan Hai, Hồ Hữu Thắng, Phan Bao Quoc Hieu, and Truong Van Minh. "An algorithms to improve the energy resolution of two-step cascade spectrum." Science and Technology Development Journal - Natural Sciences 4, no. 4 (November 1, 2020): First. http://dx.doi.org/10.32508/stdjns.v4i4.860.

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The present paper proposes an algorithm to improve the energy resolution of two-step cascade spectrum. The energy resolution plays an important role in the domain of gamma spectrum analysis. The better the energy resolution is, the better the ability of peak resolving is. The algorithm is constructed based on an analyze of energy resolution of the summation amplitude of coincident pulses spectrometer using the analogue technique. The algorithm proposed has been tested on some two-step cascade spectra of 164Dy nucleus obtained from the (n, ) reaction experiment using the gamma – gamma coincidence spectrometer at Dalat Nuclear Research Institute. Two-step cascade spectra corresponding to the cascade decays from the compound state to final states whose energies are 0, 74, and 242 keV have been evaluated. The results obtained show that the energy resolution of the two-step cascade spectrum has been reduced by 1.05 to 2.04 times within the energy range of 586 to 6830 keV. Our algorithm can therefore be applied to improve the ability of peak deconvolution, the accuracy, and the realibility in analyzing two-step cascade spectra.

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Khryashchev, V. V., A. A. Lebedev, and A. L. Priorov. "ENHANCEMENT OF FAST FACE DETECTION ALGORITHM BASED ON A CASCADE OF DECISION TREES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W4 (May 10, 2017): 237–41. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w4-237-2017.

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Face detection algorithm based on a cascade of ensembles of decision trees (CEDT) is presented. The new approach allows detecting faces other than the front position through the use of multiple classifiers. Each classifier is trained for a specific range of angles of the rotation head. The results showed a high rate of productivity for CEDT on images with standard size. The algorithm increases the area under the ROC-curve of 13% compared to a standard Viola-Jones face detection algorithm. Final realization of given algorithm consist of 5 different cascades for frontal/non-frontal faces. One more thing which we take from the simulation results is a low computational complexity of CEDT algorithm in comparison with standard Viola-Jones approach. This could prove important in the embedded system and mobile device industries because it can reduce the cost of hardware and make battery life longer.

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LI Zhihui, and LIU Zhi. "The Application of Cascade EM Algorithm to MUD." International Journal of Digital Content Technology and its Applications 7, no. 4 (February 28, 2013): 607–14. http://dx.doi.org/10.4156/jdcta.vol7.issue4.73.

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Dapeng Luo, Longsheng Wei, and Mengyan Zhang. "Improving Online Learning Algorithm from Adaptive Cascade Classifier." International Journal of Advancements in Computing Technology 4, no. 21 (November 30, 2012): 145–56. http://dx.doi.org/10.4156/ijact.vol4.issue21.18.

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Afshar, M. H., and M. Daraeikhah. "Cascade stilling basin design using continuous ant algorithm." Proceedings of the Institution of Civil Engineers - Water Management 161, no. 3 (June 2008): 151–59. http://dx.doi.org/10.1680/wama.2008.161.3.151.

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Springer, Paul L., and Sandeep Gulati. "Parallelizing the cascade-correlation algorithm using time warp." Neural Networks 8, no. 4 (January 1995): 571–77. http://dx.doi.org/10.1016/0893-6080(94)00103-s.

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Ying, Xiang, Yulin Zhang, Mei Yu, Xi Wei, Jialin Zhu, Jie Gao, Zhiqiang Liu, et al. "Cascade marker removal algorithm for thyroid ultrasound images." Medical & Biological Engineering & Computing 58, no. 11 (August 25, 2020): 2641–56. http://dx.doi.org/10.1007/s11517-020-02216-7.

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Goldman, A. J., and Prasoon Tiwari. "Allowable processing orders in the accelerated cascade algorithm." Discrete Applied Mathematics 13, no. 2-3 (March 1986): 213–21. http://dx.doi.org/10.1016/0166-218x(86)90083-1.

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Xiong, Hui Yun, and Juan Zhao. "An Image Retrieval Method Based on Machine Learning and SVM." Applied Mechanics and Materials 631-632 (September 2014): 474–77. http://dx.doi.org/10.4028/www.scientific.net/amm.631-632.474.

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Image recognition has been a research hotspot in the field of machine learning; this paper puts forward a kind of cascade algorithm based on SVM and AdaBoost. The algorithm to select the sample pretreatment, fixed size of window image segmentation into different areas, then using Haar - like rectangular figure characteristics of integral method for feature extraction, finally using AdaBoost cascade classifier to classify the SVM training. Through the face recognition experiments show AdaBoost cascade of SVM algorithm improve the classification accuracy, error rate get reduced obviously.

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Chau, Khanh Ngan, and Nghi Thanh Doan. "DENSE SIFT FEATURE AND LOCAL NAIVE BAYES NEAREST NEIGHBOR FOR FACE RECOGNITION." Scientific Journal of Tra Vinh University 1, no. 28 (December 1, 2017): 56–63. http://dx.doi.org/10.35382/18594816.1.28.2017.46.

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Human face recognition is a technology which is widely used in life. There have been much effort on developing face recognition algorithms. In this paper, we present a new methodology that combines Haar Like Features - Cascade of Boosted Classifiers, Dense Scale-Invariant Feature Transform (DSIFT), Local Naive Bayes Nearest Neighbor (LNBNN) algorithm for the recognition of human face. We use Haar Like Features and the combination of AdaBoost algorithm and Cascade stratified model to detect and extract the face image, the DSIFT descriptors of the image are computed only for the aligned and cropped face image.Then, we apply the LNBNN algorithms for object recognition. Numerical testing on several benchmark datasets using our proposed method for facerecognition gives the better results than other methods. The accuracies obtained by LNBNN method is 99.74 %.

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Gu, Wei, Yong Gang Wu, and Jin Cheng Wu. "Application of Chaotic Univariate Marginal Distribution Algorithm to Economic Dispatch Control of Cascade Hydropower Plants." Advanced Materials Research 516-517 (May 2012): 1326–31. http://dx.doi.org/10.4028/www.scientific.net/amr.516-517.1326.

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The economic dispatch control of cascade hydropower plants is a large scale non-linear constrained optimization problem, which plays an important role in cascade reservoirs daily optimal. This paper proposes a chaotic univariate marginal distribution algorithm (CUMDA) to solve the economic dispatch problem of cascade hydropower plants. In the proposed method, a chaotic search is integrated with univariate marginal distribution algorithm (UMDA) to effectively avoid premature convergence, chaotic sequences combine with adaptive approach are applied to help algorithm escape from local optimal trap. The feasibility of the proposed method is demonstrated for economic dispatch control of a test cascade hydro system. The simulation results show that the proposed method can obtain higher quality solution.

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Tian, Ai-Qing, Shu-Chuan Chu, Jeng-Shyang Pan, Huanqing Cui, and Wei-Min Zheng. "A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station." Sustainability 12, no. 3 (January 21, 2020): 767. http://dx.doi.org/10.3390/su12030767.

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Pigeon-inspired optimization (PIO) is a new type of intelligent algorithm. It is proposed that the algorithm simulates the movement of pigeons going home. In this paper, a new pigeon herding algorithm called compact pigeon-inspired optimization (CPIO) is proposed. The challenging task for multiple algorithms is not only combining operations, but also constraining existing devices. The proposed algorithm aims to solve complex scientific and industrial problems with many data packets, including the use of classical optimization problems and the ability to find optimal solutions in many solution spaces with limited hardware resources. A real-valued prototype vector performs probability and statistical calculations, and then generates optimal candidate solutions for CPIO optimization algorithms. The CPIO algorithm was used to evaluate a variety of continuous multi-model functions and the largest model of hydropower short-term generation. The experimental results show that the proposed algorithm is a more effective way to produce competitive results in the case of limited memory devices.

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Chen, Wei, Binghui Peng, Grant Schoenebeck, and Biaoshuai Tao. "Adaptive Greedy versus Non-Adaptive Greedy for Influence Maximization." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (April 3, 2020): 590–97. http://dx.doi.org/10.1609/aaai.v34i01.5398.

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We consider the adaptive influence maximization problem: given a network and a budget k, iteratively select k seeds in the network to maximize the expected number of adopters. In the full-adoption feedback model, after selecting each seed, the seed-picker observes all the resulting adoptions. In the myopic feedback model, the seed-picker only observes whether each neighbor of the chosen seed adopts. Motivated by the extreme success of greedy-based algorithms/heuristics for influence maximization, we propose the concept of greedy adaptivity gap, which compares the performance of the adaptive greedy algorithm to its non-adaptive counterpart. Our first result shows that, for submodular influence maximization, the adaptive greedy algorithm can perform up to a (1-1/e)-fraction worse than the non-adaptive greedy algorithm, and that this ratio is tight. More specifically, on one side we provide examples where the performance of the adaptive greedy algorithm is only a (1-1/e) fraction of the performance of the non-adaptive greedy algorithm in four settings: for both feedback models and both the independent cascade model and the linear threshold model. On the other side, we prove that in any submodular cascade, the adaptive greedy algorithm always outputs a (1-1/e)-approximation to the expected number of adoptions in the optimal non-adaptive seed choice. Our second result shows that, for the general submodular cascade model with full-adoption feedback, the adaptive greedy algorithm can outperform the non-adaptive greedy algorithm by an unbounded factor. Finally, we propose a risk-free variant of the adaptive greedy algorithm that always performs no worse than the non-adaptive greedy algorithm.

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Zhu, Zhong Hao, and Hong Min Gao. "Cascade Reservoirs Optimal Scheduling Method Based on Chaotic Ant Colony Algorithm." Advanced Materials Research 919-921 (April 2014): 1230–33. http://dx.doi.org/10.4028/www.scientific.net/amr.919-921.1230.

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On the basis of the analysis of the basic information of the river basin reservoirs and application of chaotic ant colony algorithm, the medium-and long-term optimization operation model is established, which regards the maximum annual generation capacity of the cascade hydropower stations as the main purpose. The simulation result shows the algorithm improves the total annual power generation of the cascade reservoirs, and finally provides an effective solution to solve the cascade reservoirs optimization operation problem.

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Storti, Mario, Jorge D’Eli´a, and Sergio Idelsohn. "CVBEM Formulation for Multiple Profiles and Cascades." Applied Mechanics Reviews 48, no. 11S (November 1, 1995): S203—S210. http://dx.doi.org/10.1115/1.3005073.

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A numerical algorithm based on the CVBEM (from Complex Variable Boundary Element Method) for plane incompressible potential flow around aerofoils and cascades is described. The method is based on the representation of the complex disturbance velocity by means of a Cauchy-type integral around the foil. The Cauchy density function is approximated piecewise linearly and a linear system on the nodal values is obtained by collocation at the nodes. The Kutta condition is imposed via a Lagrange multiplier, in contrast with the least-squares formulation used in a previous work. For cascades, the problem is conformally mapped by a simple hyperbolic function (exponential or hyperbolic tangent) to a related problem with only one profile and one or two poles. Thus, the cascade problem is accurately solved with minor modifications to the single profile code and at the same cost of a single profile computation. Finally, several numerical examples are shown: single Joukowski and NACA profiles, interference coefficients for the flat plate cascade and a plane cascade at the external cylindrical section of an industrial fan.

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Khalyasmaa, Alexandra, Stanislav Eroshenko, Anna Arestova, Sergey Mitrofanov, Anastasiya Rusina, and Alexey Kolesnikov. "Integrating GIS technologies in hydro power plant cascade simulation model." E3S Web of Conferences 191 (2020): 02006. http://dx.doi.org/10.1051/e3sconf/202019102006.

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The paper presents the calculation algorithm for water-energy regime of a hydroelectric power plants cascade. The block diagram of the algorithm is given for implementing the simulation model and automating the process of calculating the regime. The proposed algorithm allows to evaluate the efficiency of the cascade, as well as to optimize the regime according to various criteria. Additionally, an option is proposed for integrating GIS monitoring data into the calculation algorithm.

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Hua, Bing, Nan Zhang, and Mohong Zheng. "Satellite magnetic/momentum wheel attitude control technology based on PIO cascade-saturation algorithm." World Journal of Engineering 18, no. 4 (March 26, 2021): 645–50. http://dx.doi.org/10.1108/wje-10-2020-0536.

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Purpose Taking into account the factors of torque saturation and angular velocity limitation during the actual attitude maneuver of the satellite, as well as the difficulty of parameter selection in the design of attitude control algorithm, the purpose of this paper is to propose a satellite magnetic/momentum wheel attitude control technology based on pigeon-inspired optimization (PIO) cascade-saturation control law optimization. Design/methodology/approach The optimal parameters are calculated through the PIO algorithm and then the parameters are used in the cascade-saturation control law to control the actuator findings-mathematical simulation results show that the cascade-saturation control law optimization algorithm based on PIO can shorten the adjustment time and reduce the steady-state error. Findings Compared with traditional attitude maneuver control with given parameters, the PIO algorithm can accurately calculate the optimal parameters needed to achieve the control objective and this method has better stability and higher accuracy. Originality/value The innovative PIO algorithm is used to calculate the optimal parameters, and the cascade saturation control law is used to control the actuator. Compared with the traditional algorithm, the regulation time is shortened and the steady-state error is reduced.

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Choi, Jaeyoung. "Inferring the Hidden Cascade Infection over Erdös-Rényi (ER) Random Graph." Electronics 10, no. 16 (August 6, 2021): 1894. http://dx.doi.org/10.3390/electronics10161894.

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Finding hidden infected nodes is extremely important when information or diseases spread rapidly in a network because hints regarding the global properties of the diffusion dynamics can be provided, and effective control strategies for mitigating such spread can be derived. In this study, to understand the impact of the structure of the underlying network, a cascade infection-recovery problem is considered over an Erdös-Rényi (ER) random graph when a subset of infected nodes is partially observed. The goal is to reconstruct the underlying cascade that is likely to generate these observations. To address this, two algorithms are proposed: (i) a Neighbor-based recovery algorithm (NBRA(α)), where 0≤α≤1 is a control parameter, and (ii) a BFS tree-source-based recovery algorithm (BSRA). The first one simply counts the number of infected neighbors for candidate hidden cascade nodes and computes the possibility of infection from the neighbors by controlling the parameter α. The latter estimates the cascade sources first and computes the infection probability from the sources. A BFS tree approximation is used for the underlying ER random graph with respect to the sources for computing the infection probability because of the computational complexity in general loopy graphs. We then conducted various simulations to obtain the recovery performance of the two proposed algorithms. As a result, although the NBRA(α) uses only local information of the neighboring infection status, it recovers the hidden cascade infection well and is not significantly affected by the average degree of the ER random graph, whereas the BSRA works well on a local tree-like structure.

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Urías, Jesús, and Diego A. Quiñones. "Householder methods for quantum circuit design." Canadian Journal of Physics 94, no. 2 (February 2016): 150–57. http://dx.doi.org/10.1139/cjp-2015-0490.

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Algorithms to resolve multiple-qubit unitary transformations into a sequence of simple operations on one-qubit subsystems are central to the methods of quantum-circuit simulators. We adapt Householder’s theorem to the tensor-product character of multi-qubit state vectors and translate it to a combinatorial procedure to assemble cascades of quantum gates that recreate any unitary operation U acting on n-qubit systems. U may be recreated by any cascade from a set of combinatorial options that, in number, are not lesser than super-factorial of 2n, [Formula: see text]. Cascades are assembled with one-qubit controlled-gates of a single type. We complement the assembly procedure with a new algorithm to generate Gray codes that reduce the combinatorial options to cascades with the least number of CNOT gates. The combined procedure —factorization, gate assembling, and Gray ordering — is illustrated on an array of three qubits.

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Xie, Hong, Yongkun Li, and John C. S. Lui. "Understanding Persuasion Cascades in Online Product Rating Systems." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5490–97. http://dx.doi.org/10.1609/aaai.v33i01.33015490.

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Online product rating systems have become an indispensable component for numerous web services such as Amazon, eBay, Google play store and TripAdvisor. One functionality of such systems is to uncover the product quality via product ratings (or reviews) contributed by consumers. However, a well-known psychological phenomenon called “messagebased persuasion” lead to “biased” product ratings in a cascading manner (we call this the persuasion cascade). This paper investigates: (1) How does the persuasion cascade influence the product quality estimation accuracy? (2) Given a real-world product rating dataset, how to infer the persuasion cascade and analyze it to draw practical insights? We first develop a mathematical model to capture key factors of a persuasion cascade. We formulate a high-order Markov chain to characterize the opinion dynamics of a persuasion cascade and prove the convergence of opinions. We further bound the product quality estimation error for a class of rating aggregation rules including the averaging scoring rule, via the matrix perturbation theory and the Chernoff bound. We also design a maximum likelihood algorithm to infer parameters of the persuasion cascade. We conduct experiments on the data from Amazon and TripAdvisor, and show that persuasion cascades notably exist, but the average scoring rule has a small product quality estimation error under practical scenarios.

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Ivanova, Donka, Nikolay Valov, and Martin Deyanov. "Application of the genetic algorithm for cascade control of a HVAC system." MATEC Web of Conferences 292 (2019): 01064. http://dx.doi.org/10.1051/matecconf/201929201064.

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In this article the application of genetic algorithm for tuning of HVAC cascade system is proposed. The tuning procedure for a cascade system is very time-consuming and practice shows that additional controller tuning is needed when classical method is used. The main problem in classical method is the interconnection between the parameters of the two controllers. The proposed optimal tuning procedure overcomes the disadvantages. It is based on the following criteria: minimum integral square error, minimum settling time and minimum overshoot. The best process quality is achieved with PI controller in the inner loop and a PID controller in the outer loop of the cascade HVAC system. The proposed method for simultaneous tuning of controller parameters in a cascade control system can be applied in different control systems.

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Sujecki, Sławomir. "An Efficient Algorithm for Steady State Analysis of Fibre Lasers Operating under Cascade Pumping Scheme." International Journal of Electronics and Telecommunications 60, no. 2 (June 1, 2014): 143–49. http://dx.doi.org/10.2478/eletel-2014-0017.

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Abstract We derive an efficient algorithm for the steady state analysis of fibre lasers operating under cascade pumping scheme by combining the shooting method with the Newton-Raphson method. We compare the proposed algorithm with the two standard algorithms that have been used so far in the available literature: the relaxation method and the coupled solution method. The results obtained show that the proposed shooting method based algorithm achieves much faster convergence rate at the expense of a moderate increase in the calculation time. It is found that a further improvement in the computational efficiency can be achieved by using few iterations of the relaxation method to calculate the initial guess for the proposed shooting method based algorithm

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Hashim, Ashwaq T., Ahmed M. Hasan, and Hayder M. Abbas. "Design and implementation of proposed 320 bit RC6-cascaded encryption/decryption cores on altera FPGA." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 6 (December 1, 2020): 6370. http://dx.doi.org/10.11591/ijece.v10i6.pp6370-6379.

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This paper attempts to build up a simple, strong and secure cryptographic algorithm. The result of such an attempt is “RC6-Cascade” which is 320-bits RC6 like block cipher. The key can be any length up to 256 bytes. It is a secret-key block cipher with precise characteristics of RC6 algorithm using another overall structure design. In RC6-Cascade, cascading of F-functions will be used instead of rounds. Moreover, the paper investigates a hardware design to efficiently implement the proposed RC6-Cascade block cipher core on field programmable gate array (FPGA). An efficient compact iterative architecture will be designed for the F-function of the above algorithm. The goal is to design a more secure algorithm and present a very fast encryption core for low cost and small size applications.

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Journal articles on the topic 'Cascade algorithm'

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