HipMCL: a high-performance parallel implementation of the Markov clustering algorithm for
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ABSTRACT Biological networks capture structural or functional properties of relevant entities such as molecules, proteins or genes. Characteristic examples are gene expression networks or protein protein interaction networks, which hold information about functional

Calibration and Validation of Swat Model for Kunthipuzha Basin Using SUFI-2 Algorithm
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Model calibration is a process in which a generalized model is adjusted to represent the site specific process and conditions more realistically. Validation is the process of running a model with the parameters that were determined during calibration process with a data set

Minimizing the cost of two-tier cellular network with queuing handoff calls in microcell using genetic algorithm
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ABSTRACT Call dropping probability is less desirable rather than call blocking probability for modeling of two tier cellular network design. To reduce call dropping probability queuing for handoff calls in microcell may be the one solution. Determining number of cells in each tier

Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning
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ABSTRACT The correct use of model evaluation, model selection, and algorithm selection techniques is vital in academic machine learning research as well as in many industrial settings. This article reviews different techniques that can be used for each of these three

Cloud Droplet Size and Cloud Optical Depth Retrieval Algorithm Theoretical Basis
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1.1 PURPOSE The AirMSPI Cloud Droplet Size and Cloud Optical Depth Retrieval Algorithm Theoretical Basis (ATB) documents the algorithm for determining cloud-top droplet size distribution and 1D radiative transfer (RT) based cloud optical depth from AirMSPI

in searches for new heavy resonances decaying into boosted top-quarks with the ATLAS detector and a development of an improved b -tagging algorithm
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ABSTRACT This thesis describes the performance of the common ATLAS b-tagging algorithms in the context of the dense environments that can be found in the decay of boosted top quarks into jets and addresses the problems related to such conditions. The results of these

Modeling and Analyzing Neural Networks Using Reproducing Kernel Hilbert Space Algorithm
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ABSTRACT : In this paper, we present a new method for solving some certain differential systems in the artificial neural networks field. The analytic and approximate solutions are given with series form in the spaces W [a, b] and H [a, b]. The method used in this thesis has

A branch-and-price algorithm for the Minimum Latency Problem
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ABSTRACT This paper deals with the Minimum Latency Problem (MLP), a variant of the well- known Traveling Salesman Problem in which the objective is to minimize the sum of waiting times of customers. This problem arises in many applications where customer satisfaction is

A Study on IOT Approach for Monitoring Water Quality Using MQTT Algorithm
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ABSTRACT Degradation of water resources has become a common problem. The conventional methods of water quality monitoring involves the manual collection of water sample from different locations. These water samples were tested in the laboratory using rigorous skills

A Branch-and-Bound based Algorithm for Nonconvex Multiobjective Optimization
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ABSTRACT A new branch-and-bound based algorithm for smooth nonconvex multiobjective optimization problems with convex constraints is presented. The algorithm computes an (ε, )-approximation of all globally optimal solutions. We introduce the algorithm which uses

Survey on Different Method to Improve Performance of The Round Robin Scheduling Algorithm
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ABSTRACT Round Robin (RR) scheduling algorithm is the widely used scheduling algorithm in multitasking and real time environment. Its performance highly depends on a Time Quantum, which is a predefined amount of time assigned by CPU to every task to be

Prediction of surface roughness in the ball-end milling process using response surface methodology, genetic algorithms, and grey wolf optimizer algorithm
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The primary objective of machining operations modeling is developing a predictive capability for machining performance in order to facilitate effective planning of machining operations to achieve optimum productivity, quality, and cost. Modeling of output

Query Driven Algorithm Selection in Early Stage Retrieval
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ABSTRACT Large scale retrieval systems often employ cascaded ranking architectures, in which an initial set of candidate documents is iteratively refined and re-ranked by increasingly sophisticated and expensive ranking models. In this paper, we propose a

A Trust Region Algorithm for Heterogeneous Multiobjective Optimization
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ABSTRACT This paper presents a new trust region method for multiobjective heterogeneous optimization problems. One of the objective functions is an expensive black-box function, for example given by a time-consuming simulation. For this function derivative information

Supplement of A fire model with distinct crop, pasture, and non-agricultural burning: use of new data and a model-fitting algorithm for FINAL.
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Figure S2. Performance change in gridcells chosen for optimization (Optimization 3).(a b): Sum of squared errors from model output with initial (a) and final (b) parameter sets.(c): Difference in sum of squared errors (identical to Fig. 4d, but with non-optimized gridcells

Adapting a kidney exchange algorithm to align with human values
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ABSTRACT The efficient allocation of limited resources is a classical problem in economics and computer science. In kidney exchanges, a central market maker allocates living kidney donors to patients in need of an organ. Patients and donors in kidney exchanges are

Prediction of Iberian lynx road mortality in southern Spain: a new approach using the MaxEnt algorithm G. Garrote, J. Fernández López, G. López
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G Ruiz, MA Simón 2018 ABSTRACT Prediction of Iberian lynx road mortality in southern Spain: a new approach using the MaxEnt algorithm . In recent years, the Iberian lynx (Lynx pardinus) has experienced a significant increase in the size of its population and in its distribution. The species currently

Study of Biometric Classification Using Speed-Constrained Multi-Objective Particle Swarm Optimization Algorithm
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ABSTRACT In biometric identification area, many useful model-based techniques are executed such as neural networks and support vector machines. The proposed descriptor is tested on standard benchmark databases related to user biometric identification like UCI/Statlog and

Analysis on Medical Data sets using Apriori Algorithm Based on Association Rules
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ABSTRACT During the process of mining frequent item sets, when minimum support is little, the production of candidate sets is a kind of time-consuming and frequent operation in the mining algorithm . The APRIORI algorithm does not need to produce the candidate sets, the

An Adaptive Filon Algorithm for Highly Oscillatory Integrals
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ABSTRACT Based on the error analysis of Extended Filon Method (EFM), we present an adaptive Filon method to calculate highly oscillatory integrals. The main idea is to allow interpolation points depend upon underlying frequency in order to minimize the error

Global Convergence of an Extended Descent Algorithm without Line Search for Unconstrained Optimization
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ABSTRACT In this paper, we extend a descent algorithm without line search for solving unconstrained optimization problems. Under mild conditions, its global convergence is established. Further, we generalize the search direction to more general form, and also

Short comment: Algorithm Theoretical Baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project by De Smedt et al., AMTD 2017
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1.[Chance and Orphal, 2011] used the cross-section by [Meller and Moortgat, 2000] to rescale the higher resolved cross-section by [Cantrell et al., 1990], basically combining the advantages of both publications. Is there a specific reason why to use [Meller and Moortgat

A Charge System Search based DV Hop Algorithm for Wireless Sensor Networks
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ABSTRACT In Wireless Sensor Networks (WSNs), Localization is one of important issue that can affect the performance of networks. To design an accurate localization algorithm is a challenging task among researchers. It is noticed that DV Hop algorithm gets more attention Catheter ablation in patients suffering from persistent atrial fibrillation (PERS) is challenging and associated with only moderate success. The underlying substrates as well as mechanisms to initiate and to maintain atrial fibrillation (AF) are still not completely

Conservation by Algorithm
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Digital devices are spreading rapidly in conservation as costs shrink and capabilities grow. They are changing the way conservation operates (Arts et al., 2015). To take just one example, the website of a wildlife concession in Tanzania recently described the use of a

Impact of Gradient Ascent and Boosting Algorithm in Classification
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ABSTRACT : Boosting is the method used to improve the accuracy of any learning algorithm which often suffers from over fitting problem, because of inappropriate coefficient associated to the data points. The objective of our research is to train the data, such that the weighing

O-GlcNAcPRED-II: an integrated classification algorithm for identifying O-GlcNAcylation sites based on fuzzy undersampling and a K-means PCA oversampling
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ABSTRACT Motivation: Protein O-GlcNAcylation (O-GlcNAc) is an important post-translational modification of serine (S)/threonine (T) residues that involves multiple molecular and cellular processes. Recent studies have suggested that abnormal O-G1cNAcylation causes many

Plug and Play Distributed Model Predictive Control with Dynamic Coupling: A Randomized Primal-dual Proximal Algorithm
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ABSTRACT This paper proposes an algorithm for distributed model predictive control that is based on a primal-dual proximal algorithm developed recently by two of the authors. The proposed scheme does not require strong convexity, involves one round of communication

CoABind: a novel algorithm for Coenzyme A (CoA)-and CoA derivatives-binding residues prediction
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ABSTRACT Motivation: Coenzyme A (CoA)-protein binding plays an important role in various cellular functions and metabolic pathways. However, no computational methods can be employed for CoA-binding residues prediction. Results: We developed three methods for the

Personalised adaptive basal-bolus algorithm using SMBG/CGM data
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An essential component of the diabetes management plan is the glucose monitoring using either meters for self-monitoring of blood glucose (SMBG) or more recently continuous glucose monitors (CGM). The main objective of the study is the simultaneous ABSTRACT In this paper, we study the target tracking problem in a wireless sensor network. A sensor receives a measurement from an energy emitting target and employs binary quantization to the received measurement to generate its decision. A sinusoidal waveform

A Progressive Hedging Based Branch-and-Bound Algorithm for Mixed-Integer Stochastic Programs
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ABSTRACT . Progressive Hedging (PH) is a well-known algorithm for solving multi-stage stochastic convex optimization problems. Most previous extensions of PH for mixed-integer stochastic programs have been implemented without convergence guarantees. In this

A robust parallel algorithm for combinatorial compressed sensing
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ABSTRACT It was shown in previous work that a vector x∈ Rn with at most kn nonzeros can be recovered from an expander sketch Ax in O (nnz (A) log k) operations via the parallel-l0 decoding algorithm where nnz (A) denotes the number of nonzero entries in A∈ Rm n. In

Optimal Power Control algorithm for Multi-Radio Multi-Channel Wireless Mesh Network
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ABSTRACT Multi-Radio Multi-Channel Wireless mesh networks (MRMC WMNs) is the self- configuring backhaul providing internet access for last mile users through multi-hop forwarding. The increasing demand for low cost wireless networks coverage has motivated a

Trust Value based Algorithm to Identify and Defense Gray-Hole and Black-Hole attack present in MANET using Clustering Method
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ABSTRACT A Mobile ad hoc network (MANET) is infrastructure less network and has numbers of mobile nodes. Any node can work as a router that receives and sends packets and routes them. Networks are highly affected by various types of attacks so securities are a

A Unified Primal Dual Active Set Algorithm for Nonconvex Sparse Recovery
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ABSTRACT In this paper, we consider the problem of recovering a sparse signal based on penalized least squares. We develop an algorithm of primal-dual active set type for a class of nonconvex sparsitypromoting penalties, which includes l0, bridge, smoothly clipped

Comparison of Flocking Algorithm According to Number of Boids in Virtual Reality Environment
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ABSTRACT . Flocking algorithm in limited PC performance period was studied for efficient algorithm which could express large scale animation due to load performance, but since the 2000s, as the PC performance started to improve, studies focusing on efficient large scale

An Improved K-Means Clustering Algorithm
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ABSTRACT This Vast spread of computing technologies has led to abundance of large data sets. Thus, there is a need to find similarities and define groupings among the elements of these big data sets. One of the ways to find these similarities is data clustering. Currently

Research on a handwritten character recognition algorithm based on an extended nonlinear kernel residual network.
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ABSTRACT Although the accuracy of handwritten character recognition based on deep networks has been shown to be superior to that of the traditional method, the use of an overly deep network significantly increases time consumption during parameter training. For

Efficient Support Vector Machine Training Algorithm on GPUs
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ABSTRACT Support Vector Machines (SVMs) are popular for many machine learning tasks. With rapid growth of dataset size, the high cost of training limits the wide use of SVMs. Several SVM implementations on GPUs have been proposed to accelerate SVMs. However