Provide a method to diagnose and optimize diabetes using data mining methods and firefly algorithm by Reza Molaee Fard

“…The results of this study indicate that the DBSCAN algorithm is more efficient than other clustering algorithms. …”
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A Proposed Harmony Search Algorithm for Honeyword Generation by Yasser A. Yasser, Ahmed T. Sadiq, Wasim AlHamdani

“…The harmony search algorithm (HSA), a metaheuristic intelligence algorithm inspired by music, is used in this article to offer a novel method for generating honeyword. …”
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AN ALGORITHM FOR ASSEMBLING A COMMON IMAGE OF VLSI LAYOUT by Y. Y. Lankevich

“…Employing graphics processing units enables acceleration of computations. We realize algorithms and programs for assembling a common image of VLSI layout. …”
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A New Algorithm for Positive Semidefinite Matrix Completion by Fangfang Xu, Peng Pan

“…Recovery results show that our algorithm is helpful.…”
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Modified Projection Algorithms for Solving the Split Equality Problems by Qiao-Li Dong, Songnian He

“…The split equality problem (SEP) has extraordinary utility and broad applicability in many areas of applied mathematics. Recently, Byrne and Moudafi (2013) proposed a CQ algorithm for solving it. …”
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Algorithms for estimating modular numbers in floating-point arithmetic by Konstantin Sergeevich Isupov

“…Therefore, RNS is used for reaching the maximum performance in many high-speed computer arithmetic applications. …”
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A ranking hashing algorithm based on listwise supervision by Anbang YANG, Jiangbo QIAN, Yihong DONG, Huahui CHEN

“…Recently,learning to hash technology has been used for the similarity search of large-scale data.It can simultaneous increase the search speed and reduce the storage cost through transforming the data into binary codes.At present,most ranking hashing algorithms compare the consistency of data in the Euclidean space and the Hamming space to construct the loss function.However,because the Hamming distance is a discrete integer value,there may be many data points sharing the same Hamming distance result in the exact ranking cannot be performed.To address this challenging issue,the encoded data was divided into several subspaces with the same length.Each subspace was set with different weights.The Hamming distance was calculated according to different subspace weights.The experimental results show that this algorithm can effectively sort the data in the Hamming space and improve the accuracy of the query compared with other learning to hash algorithms.…”
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Modern warfarin- dosing algorithms in patients with atrial fibrillation by M. Yu. Kolesnyk, Ya. M. Mykhaylovskyi

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Hierarchical Models and Tuning of Random Walk Metropolis Algorithms by Mylène Bédard

“…We obtain weak convergence and optimal scaling results for the random walk Metropolis algorithm with a Gaussian proposal distribution. The sampler is applied to hierarchical target distributions, which form the building block of many Bayesian analyses. …”
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Using genetic Algorithm in Task scheduling for Multiprocessing System by Asmaa Hammo, Ghosun Basheer, Muna Jawhar

“…In this work we use Genetic Algorithm for best section to implement many independent tasks on multiprocessor systems. …”
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AdaBoost algorithm based on fitted weak classifier by Pengfeng SONG, Qingwei YE, Zhihua LU, Yu ZHOU

“…AdaBoost algorithm was proposed to minimize the accuracy caused by weak classifiers by minimizing the training error rate,and the single threshold was weaker and difficult to converge.The AdaBoost algorithm based on the fitted weak classifier was proposed.Firstly,the mapping relationship between eigenvalues and marker values was established.The least squares method was introduced to solve the fitting polynomial function,and the continuous fitting values were converted into discrete categorical values,thereby obtaining a weak classifier.From the many classifiers obtained,the classifier with smaller fitting error was selected as the weak classifier to form a new AdaBoost strong classifier.The UCI dataset and the MIT face image database were selected for experimental verification.Compared with the traditional Discrete-AdaBoost algorithm,the training speed of the improved algorithm was increased by an order of magnitude.And the face detection rate can reach 96.59%.…”
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Systemic therapy of psoriasis and psoriatic arthritis: assignment algorithms by Marianna M. Khobeysh, Evgeny V. Sokolovskiy

“…Therapy of patients with psoriasis requires solving the complex issue of drug selection, which depends on many factors. The choice of systemic therapy algorithm is an important issue that determines the effectiveness and safety of treatment, influences the prognosis of the disease and the patient’s quality of life.…”
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Study of a new fast adaptive filtering algorithm by WANG Zhen-li, ZHANG Xiong-wei, YANG Ji-bin, CHEN Gong

“…A new fast adaptive filtering algorithm was presented by using the correlations between the signal’s former and latter sampling times. …”
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Algorithmic Maps and the Political Geography of Early-modern Japan by Mark Ravina

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An overview of Cuckoo Optimization Algorithm based Image Processing by Baydaa sulaiman

“…The CS algorithm has been used in many applications to solve optimization problems. …”
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Compact quantum algorithms for time-dependent differential equations by Sachin S. Bharadwaj, Katepalli R. Sreenivasan

“…Here, we present algorithms for solving time-dependent PDEs, with particular reference to fluid equations. …”
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Quantum algorithms for cooling: A simple case study by Daniel Molpeceres, Sirui Lu, J. Ignacio Cirac, Barbara Kraus

“…Preparation of low-energy quantum many-body states has a wide range of applications in quantum information processing and condensed-matter physics. …”
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LMS Algorithm Step Size Adjustment for Fast Convergence by Dariusz BISMOR

“…This is probabely the cause of its main drawback: the need of a careful choice of the step size – which is the reason why so many variable step size flavors of the LMS algorithm has been developed. …”
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IMPROVEMENT OF CUCKOO ALGORITHM FOR ASSOCIATION RULE HIDING PROBLEM by Đoàn Minh Khuê, Lê Hoài Bắc

“…Recently, a meta-heuristic algorithm is relatively effective for this purpose, which is cuckoo optimization algorithm (COA4ARH). …”
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A Recommendation Algorithm Based on Restricted Boltzmann Machine by WANG Weibing, ZHANG Lichao, XU Qian

“…In the case where the amount of data is too large, the recommended results output by the RBM model will be broader Besides, many collaborative filtering algorithms currently do not handle large data sets better So, we try to use the deep learning technology to strengthen the personalized recommendation model We propose a hybrid recommendation model combining the bound Boltzmann model and the hidden factor model First, we use the RBM algorithm to generate candidate sets, and score the sparse matrix of the candidate set Then we use the LFM model to sort the candidate results and select the optimal solution for recommendation The hybrid model is validated using used large public datasets It can be seen from the verification that compared with the traditional recommendation model, the proposed method can improve the accuracy of the score prediction…”
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