Skyline Method Research Articles

Three-dimensional wind fields of tropical cyclones for wind turbine structures

An efficient unsteady turbulent wind model is developed to simulate the wind field of tropical cyclones for wind turbines. The method first establishes frequency-domain wind fields, which are then changed to time-domain wind fields using the inverse Fast Fourier Transfer. Finally, interpolation is used to determine the full field unsteady turbulent wind speed. The OpenMP scheme for parallel computing and the skyline method for efficient matrix decomposition sped up 34 times faster than that without these schemes using an eight-core computer. Then, offshore wind turbine (OWT) support structure analyses and designs under International Electrotechnical Commission (IEC) 61400-3 and realistic tropical cyclone loads were performed for three cases. The results indicate that IEC 61400-3 Design Load Cases (DLCs) 2.2, 6.1, and 7.1 control the steel design for the case without tropical cyclone loads, but with such loads, IEC 61400-3 DLC I.2 dominates almost all the steel designs, which was attributed to yaw misalignment. However, actual tropical cyclones may cause worse conditions, especially for the yaw always on the X axis. Nevertheless, this actual tropical cyclone condition does not excessively increase the weight of the steel design, so IEC 61400-3 DLCs I.1 and I.2 are sufficient to ensure the safety of the OWT steel design.

Dynamic sorting and average skyline method for query processing in spatial-temporal data

With the continuous advancement in mobile computing and development of positioning in devices, querying of moving objects on road networking is an important task in the internet world. As a result ...

Dynamic sorting and average skyline method for query processing in spatial-temporal data

Dynamic sorting and average skyline method for query processing in spatial-temporal data

Cloud services security-driven evaluation for multiple tenants

Cloud Computing has become a reliable solution for outsourcing business data and operation with its cost-effective and resource-efficient services. A key part of the success of the cloud is the multi-tenancy architecture, where a single instance of a service can be shared between a large number of users, also known as tenants. Service selection for multiple tenants presents a real challenge that has not been properly addressed in the literature so far. Most of the existing cloud services selection approaches are designed for a single-user, and hence are inefficient when applied to the case of a large group of users with different, and often, conflicting requirements. In this paper, we propose a multi-tenant cloud services evaluation framework, whereby service selection is carried out per group of tenants that can belong to different service classes, rather than per a single user. We formulate the cloud services selection for multi-tenants as a complex multi-attribute large-group decision-making (CMALGDM) problem. Skyline method is initially applied to reduce the search space by eliminating the dominated services regardless of tenants’ requirements. Tenants are clustered based on their profiles characterized by different personal, service, and environmental features. Each tenant is assigned a weight to reflect its importance in the decision-making. The weight of a tenant is determined locally based on its closeness to the group decision and globally by combining its local weight with its corresponding cluster weight to reflect its total contribution to the overall decision-making. The final ranking of the alternatives is guided by a dynamic consensus process to reach a final solution with the highest level of agreement. The proposed framework supports multiple types of information, including deterministic data, interval numbers, and fuzzy numbers, to realistically represent the heterogeneity and uncertainty of security information.

Early phylogenetic estimate of the effective reproduction number of SARS-CoV-2.

To reconstruct the evolutionary dynamics of the 2019 novel‐coronavirus recently causing an outbreak in Wuhan, China, 52 SARS‐CoV‐2 genomes available on 4 February 2020 at Global Initiative on Sharing All Influenza Data were analyzed. The two models used to estimate the reproduction number (coalescent‐based exponential growth and a birth‐death skyline method) indicated an estimated mean evolutionary rate of 7.8 × 10−4 subs/site/year (range, 1.1 × 10−4‐15 × 10−4) and a mean tMRCA of the tree root of 73 days. The estimated R value was 2.6 (range, 2.1‐5.1), and increased from 0.8 to 2.4 in December 2019. The estimated mean doubling time of the epidemic was between 3.6 and 4.1 days. This study proves the usefulness of phylogeny in supporting the surveillance of emerging new infections even as the epidemic is growing.

Jointly Inferring the Dynamics of Population Size and Sampling Intensity from Molecular Sequences.

Estimating past population dynamics from molecular sequences that have been sampled longitudinally through time is an important problem in infectious disease epidemiology, molecular ecology, and macroevolution. Popular solutions, such as the skyline and skygrid methods, infer past effective population sizes from the coalescent event times of phylogenies reconstructed from sampled sequences but assume that sequence sampling times are uninformative about population size changes. Recent work has started to question this assumption by exploring how sampling time information can aid coalescent inference. Here, we develop, investigate, and implement a new skyline method, termed the epoch sampling skyline plot (ESP), to jointly estimate the dynamics of population size and sampling rate through time. The ESP is inspired by real-world data collection practices and comprises a flexible model in which the sequence sampling rate is proportional to the population size within an epoch but can change discontinuously between epochs. We show that the ESP is accurate under several realistic sampling protocols and we prove analytically that it can at least double the best precision achievable by standard approaches. We generalize the ESP to incorporate phylogenetic uncertainty in a new Bayesian package (BESP) in BEAST2. We re-examine two well-studied empirical data sets from virus epidemiology and molecular evolution and find that the BESP improves upon previous coalescent estimators and generates new, biologically useful insights into the sampling protocols underpinning these data sets. Sequence sampling times provide a rich source of information for coalescent inference that will become increasingly important as sequence collection intensifies and becomes more formalized.

Dynamic Traffic Assignment under Multiple Vehicle Classes

This paper proposes a convergence point progression based arrangement abnormality figuring out for the multi-class dynamic traffic undertaking (DTA) difficulty which includes bodily traces using the plausibility of technique diploma. An extragradient framework that requires just pseudomonotonicity and Lipschitz improvement for get collectively is made to control the problem. We likewise gift a automobile truck association question, which imparts that enticing vans to travel or broadening the truck stream in a shape can enhance organize execution for cars the diploma that the immovable car journey time. Numerical fashions are set up to layout the centrality of considering specific vehicle sorts and their joint endeavors in a DTA model, the influences of various parameters at the occasion of the function, and the presentation of the course of movement figuring.Existing thoughts blowing site visitors project definitions necessarily assume the time-subordinate O-D excursion arrange and the time-subordinate structure route of motion to be known from the before for the whole finding out skyline. Notwithstanding, there's moreover a need to provide enduring manner statistics to organize clients below ATIS/ATMS whilst unexpected groupings in O-D desires in addition as structure attributes (for example most distant point decay on unequivocal relationship in attitude on occasions) take place. This paper demonstrates a transferring skyline device for preserving an eye out for the perpetual traffic project trouble, in which an ATIS/ATMS controller is needed to have O-D needs up to the existing time and area amongst time, and present moment and medium-time period assessments of destiny O-D needs. The mission issue is explained in semi predictable for a close by time period destiny period (or degree) to select a great manner embraced plot for customers coming into the shape sensibly for the brief move time variety. The next model is jumbled due to unfold everyday conditions portraying this issue. Two nuances are mentioned problem to whether an ability to reroute automobiles in tour exists. A moving skyline method approach benevolent to a semi steady usage of an change customer classes (MUC) time-subordinate traffic errand game-plan calculation created beforehand of time with the aid of the manufacturers is portrayed. Use issues are talked about from the point of view of ATIS/ATMS applications.

Scene-Awareness Based Single Image Dehazing Technique via Automatic Estimation of Sky Area

The occurrence of fog, mist, smog, or haze significantly reduces the visibility of the scenes and images, resulting in limited recognition of computer vision and computer graphics. So, removing haze from images is a must. In this paper, we regard image dehazing as a mathematical inversion process and image restoration based on atmospheric scattering models. The atmospheric light can be accurately estimated by combining the gray threshold segmentation and the skyline method. The improved least squares filtering method is used to optimize the transmittance map so that the edge details can be highlighted and the halo effect can be alleviated. A large number of test images show that our algorithm can achieve better experimental results than the other seven most advanced dehazing strategies.

Semantic Constraint and QoS-Aware Large-Scale Web Service Composition

Service-oriented architecture facilitates the running time of interactions by using business integration on the networks. Currently, web services are considered as the best option to provide Internet services. Due to an increasing number of Web users and the complexity of users’ queries, simple and atomic services are not able to meet the needs of users; and to provide complex services, it requires service composition. Web service composition as an effective approach to the integration of business institutions’ plans has taken significant acceleration. Nowadays, web services are created and updated in a moment. Therefore, in the real world, there are many services which may not have composability according to the conditions and constraints of the user's preferred choice. In the proposed method for automatic service composition, the main requirements of users including available inputs, expected outputs, quality of service, and the priority are initially and explicitly specified by the user and service composition is done with this information. In the proposed approach, due to a large number of services with the same functionality, at first, the candidate services are reduced by the quality of service-based Skyline method, and moreover, by using an algorithm based on graph search, all possible solutions will be produced. Finally, the user’s semantic constraints are applied on service composition, and the best composition is offered according to user’s requests. The result of this study shows that the proposed method is more scalable and efficient, and it offers a better solution by considering the user’s semantic constraints.

Optimizing Skyline Query Processing in Incomplete Data

Given the significance of skyline queries, they are incorporated in various modern applications including personalized recommendation systems as well as decision-making and decision-support systems. Skyline queries are used to identify superior data items in the database. Most of the previously proposed skyline algorithms work on a complete database where the data are always present (non-missing). However, in many contemporary real-world databases, particularly those databases with large cardinality and high dimensionality, such assumption is not necessarily valid. Hence, missing data pose new challenges if the processing skyline queries cannot easily apply those methods that are designed for complete data. This is due to the fact that imperfect data cause the loss of the transitivity property of the skyline method and cyclic dominance . This paper presents a framework called Optimized Incomplete Skyline (OIS) which utilizes a technique that simplifies the skyline process on a database with missing data and helps prune the data items before performing the skyline process. The proposed strategy assures that the number of the domination tests is significantly reduced. A set of experiments has been accomplished using both real and synthetic datasets aimed at validating the performance of the framework. The experiment results confirm that the OIS framework is indeed superior and steadily outperforms the current approaches in terms of the number of domination tests required to retrieve the skylines.

S-DenseNet: A DenseNet Compression Model Based on Convolution Grouping Strategy Using Skyline Method

DenseNet has strong expressiveness in many computer vision tasks, but the complexity of its model makes it difficult to deploy to devices with limited computing resources. In this paper, we propose S-DenseNet, a compact model of DenseNet which makes the extracting features of DenseNet more comprehensively and reduces the parameter redundancy at the same time. Firstly, we investigate the parameter redundancy of DenseNet and show the possibility of compressing DenseNet. For example, we reduced its parameters by 10% as keeping in the same accuracy. Secondly, we propose an algorithm based on the Skyline method for converting standard convolution into group convolution automatically. It can choose the filter weights automatically and restore the standard convolution filter with a high sparsity one called S-Conv. Finally, we combine S-Conv with dense connections and formed a more effective network architecture, that is S-DenseNet. Experiments show that in Cifar10, Cifar100 and SVHN datasets, we use only 40% parameters and 20% FLOPs of DenseNet, and the accuracy is improved by 1%. Compared with the compression models of DenseNet and other CNNs, we use less complexity in the model and achieve higher or similar accuracy. On ImageNet dataset, compared with lightweight CNN models, traditional CNNs and their compression models, we achieve the higher or similar Top-1 accuracy with less complexity.

SEFAP: an efficient approach for ranking skyline web services

With the increasing number of Web services published on the Web, many of services provide the same functionality with different quality of service. Ranking similar web services based on QoS is then an important issue. This paper proposes a hybrid approach to rank-order Skyline Web services, which mixes several methods borrowed from Multi-Criteria Decision Making field. The Skyline method is used to reduce the decision space and focusing only on interesting Web services that are not dominated by any other service. For weighting QoS criteria, we aggregate objective and subjective weights. The objective Entropy weights are extracted directly from invocation history data, however, the subjective weights are calculated using Fuzzy AHP from user opinions. Promethee method is leveraged to rank Skyline Web services, by taking advantage of the outranking relationships between Skyline Web services and generating positive, negative and Net flows. An efficient algorithm to rank-order Skyline Web services on the basis of Net flow is developed. A case study is presented to illustrate the different steps of our approach. The experimental evaluation conducted on real-world datasets demonstrates that our approach can better capture the user preferences and retrieve the best ranked Skyline Web services.

Profile and wavefront optimization by metaheuristic algorithms for efficient finite element analysis

For an efficient solution of the equations arising from finite element analysis, the stiffness matrix of the model should be structured. This can be done by reducing the profile or wavefront of the corresponding graph matrix of the structure depending on whether skyline or frontal method being used, respectively. One of the efficient methods to achieve this goal is the use of the method of King, extended by Sloan. In this paper the coefficients of the priority function utilized in the generalized Sloan’s method are optimized using the recently developed metaheuristic algorithm, so-called vibrating particles system. The results are compared to those of other metaheuristic algorithms consisting of the particle swarm optimization, colliding bodies optimization, enhanced colliding bodies optimization, and tug of war optimization. These metaheuristics, are used for optimum nodal numbering of the graph models of the finite element meshes to reduce the profile and wavefront of the corresponding sparse matrices. Comparison of the results achieved by these metaheuristic algorithms and those of the King and Sloan, demonstrates the efficiency of the new metaheuristic utilized for profile and wavefront optimization.

Towards an efficient and a more accurate web service selection using MCDM methods

Nowadays, due to the fast growth of the number of web services with the same functionalities, the selection of the best services becomes a tricky task. Therefore, to provide a more powerful selection tool, web services are now additionally distinguished with respect to their non-functional aspects, especially to Quality of Service (QoS) requirements. Indeed, using QoS perspective in web service selection can help to promote the best candidate web services among those holding the same functional requirements. Hitherto, various QoS based web service selection approaches have been explored in the literature. However, two main challenging and conflicting issues are still demanding a specific attention, namely how accurate is the selection and what is the cost of such a process? In this paper, we target Multi Criteria Decision Making (MCDM) methods to select web services. Within this context, we propose a hybrid method to select the optimal web services based on MCDM. First of all, we use the Skyline method to reduce the research space by removing the dominated web services. Then, the BWM (Best Worst Method) is applied to normalize the weights associated with the QoS parameters according to the user request requirements. To rank the non-dominated web services with respect to the weights normalization, we explore the use of four different MCDM approaches that enjoy an affordable complexity, which are: VIKOR, SAW, TOPSIS and COPRAS. For the sake of a comparison, each method is first tested separately in order to assess its ability to select the optimal elements. Then, in order to provide the best compromise between the different ranking methods, we apply the Borda voting method to determine the compromise solution. Hence, we are able to measure the accuracy of each technique relatively to the Borda solution by applying a similarity function. The implementation and the simulation of the different methods have permitted to assess their performances in terms of time execution and accuracy. The results show clearly that MCDM ranking methods are more likely to diverge in selecting the best elements when the number of web services is increased. This finding argues for the pertinence of computing the Borda solution in the context of MCDM based web service selection.

Sea-level variations have influenced the demographic history of estuarine and freshwater fishes of the coastal plain of Paraná, Brazil.

This study surveyed the mitochondrial haplotype diversity of nine freshwater fish species and two estuarine-marine species from the coastal basins and drainages of the highland plateaus of Paraná, Brazil. Portions of the cytochrome b gene or the control region were sequenced. The demographic history of each species was inferred using the Bayesian skyline method, mismatch distribution analysis and statistical neutrality tests. Demographic reconstruction analyses revealed a single pattern of variation in the effective population size (Ne ) among species. No dramatic changes in Ne were detected in upland species. By contrast, evidence of population expansion over the past 200 000 years was detected in all coastal plain and estuarine species. These findings correspond to periods of low sea-level (regressions) followed by a rapid increase in the sea-level by >100 m. The resulting reconnections and subsequent fragmentation and isolation between the estuarine and freshwater bodies were putatively relevant to the historical demography of the fish species in these areas.

Grid-PPPS: A Skyline Method for Efficiently Handling Top-kQueries in Internet of Things

A rapid development in wireless communication and radio frequency technology has enabled the Internet of Things (IoT) to enter every aspect of our life. However, as more and more sensors get connected to the Internet, they generate huge amounts of data. Thus, widespread deployment of IoT requires development of solutions for analyzing the potentially huge amounts of data they generate. A top-kquery processing can be applied to facilitate this task. The top-kqueries retrievektuples with the lowest or the highest scores among all of the tuples in the database. There are many methods to answer top-kqueries, where skyline methods are efficient when considering all attribute values of tuples. The representative skyline methods are soft-filter-skyline (SFS) algorithm, angle-based space partitioning (ABSP), and plane-project-parallel-skyline (PPPS). Among them, PPPS improves ABSP by partitioning data space into a number of spaces using hyperplane projection. However, PPPS has a high index building time in high-dimensional databases. In this paper, we propose a new skyline method (called Grid-PPPS) for efficiently handling top-kqueries in IoT applications. The proposed method first performs grid-based partitioning on data space and then partitions it once again using hyperplane projection. Experimental results show that our method improves the index building time compared to the existing state-of-the-art methods.

Mass types, element orders and solution schemes for the richards equation

The Richards equation for water movement in unsaturated soils is highly nonlinear and generally cannot be solved analytically. An alternative is to solve the equation numerically with finite-element methods. Conventionally, it has been accepted that the consistent mass scheme with higher-order elements is superior for solving complex nonlinear physical problems. However, results from other studies indicate that a finite-element model based on the consistent mass with higher-order elements would cause numerical oscillation problems. In this study, lumped mass, consistent mass, linear elements, and quadratic/cubic elements were evaluated to determine the most efficient method to solve the Richards equation with finite-element models. Results demonstrated that, when using consistent mass schemes or quadratic/cubic elements, the time step cannot be arbitrarily reduced to achieve the convergence; the mesh size must first be reduced in order to avoid numerical oscillations. In a time-dependent problem with large and complex domain, the minimum mesh size allowed is often unknown a priori . As a result, the intrinsic necessity of constantly adjusting the mesh size and hence rearranging the mesh structure is not efficient. On the other hand, in the lumped mass scheme with linear elements, one can arbitrarily reduce the time step at any time during the simulation to obtain a stable and consistent solution without changing the mesh structure. For nonlinear and time-dependent problems with large mesh domain, most of the computer time is used in algorithms to solve the linearized matrix equations. Results from this study indicate that, to solve the Richards equation, the conjugate-gradient methods are more efficient than the sky-line decomposition method. The three preconditioning schemes investigated do not have any significant difference in computer memory and time required.

TRANSIENT LAMINAR NATURAL CONVECTION IN AN ENCLOSURE FROM STEADY FLOW STATE TO STATIONARY STATE

The aim of this numerical study is to investigate the transient natural convection in a two-dimensional enclosure of which the upper and lower walls are adiabatic. Initially t = 0, the left wall is at a higher temperature than the right wall, and the fluid of the enclosure is at a steady flow state. At time t > 0, the temperature of the left wall descends to that of the right wall. This causes the flow of the fluid in the enclosure to change. As time increases, the flow decays. Finally, the flow ceases and the fluid becomes stationary. During the computing process, a penalty finite-element method with a Newton-Raphson iteration algorithm and a backward difference scheme dealing with the time term are adopted to solve the governing equations. A skyline method is used to reduce massive computer memory. The effect of Rayleigh number on the heat transfer mechanism during the transient process is examined by investigating the Ra = 104 case, in which conduction heat transfer is dominant, and the Ra = 106 case, in which convection is dominant. In both cases, only one cell exists at the initial steady flow state. Wren the boundary condition changes, another cell forms. As time increases, the two cells become symmetric to the vertical centerline. For the Ra = 104 case, only the right cell transfers heat to the left cell. However, for the Ra = 106 case, the two cells transfer heat to each other during the transient process. Besides the flow field, the temperature distribution and the local Nusselt number distributions along the left and right walls during the transient process are also examined in detail.

A penalty finite element method for natural convection heat transfer in a partially divided enclosure

Theoretical study of natural convection has been performed in a square enclosure partitioned by a single adiabatic baffle protruding from the ceiling. A penalty finite element method with 9-node quadrilateral element and Newton-Raphson scheme are adopted in this study to solve the heat transfer coefficients of three different baffle locations and two different baffle heights. During the calculating process, an out-of-core skyline method is utilized to reduce computer memory. The fluid in the enclosure is air; Rayleigh number of 10 4 and 10 5 are calculated. The results show that heat transfer coefficients are influenced by the baffle height and baffle location.

Finite element solution of three‐dimensional incompressible fluid flow problems by a preconditioned conjugate residual method

AbstractA new algorithm for the solution of the three‐dimensional Navier–Stokes equation using the mixed formulation and an incomplete factorization technique is presented. The linear system obtained at each modified Newton–Raphson iteration is solved by the preconditioned conjugate residual method (PCR) using an out‐of‐core incomplete LU factorization as preconditioning. This factorization is performed on a matrix stored by a new static storage method called the packed skyline method. The performance of the proposed algorithm is assessed for the wall‐driven cubic cavity problem using the Q −P1 enriched element.