scholarly journals HyOASAM: A Hybrid Open API Selection Approach for Mashup Development

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Bo Jiang ◽  
Pengxiang Liu ◽  
Ye Wang ◽  
Yezhi Chen
Keyword(s):  
Information Matrix ◽  
Experimental Comparison ◽  
Agile Development ◽  
User Requirement ◽  
Machine Model ◽  
User Stories ◽  
Selection Approach ◽  
The Matrix ◽  
Open Api ◽  
Basic Approaches

At present, Mashup development has attracted much attention in the field of software engineering. It is the focus of this article to use existing open APIs to meet the needs of Mashup developers. Therefore, how to select the most appropriate open API for a specific user requirement is a crucial problem to be solved. We propose a Hybrid Open API Selection Approach for Mashup development (HyOASAM), which consists of two basic approaches: one is a user-story-driven open API discovery approach, and the other is multidimensional-information-matrix- (MIM-) based open API recommendation approach. The open API discovery approach introduces user stories in agile development to capture Mashup requirements. First, it extracts three components from user stories, and then, it extracts three corresponding properties from open API descriptions. Next, the similarity calculation is performed on two sets of data. The open API recommendation approach first uses MIM to store open APIs, Mashups, and the invoking relationship between them. Second, it enters the matrix obtained in the previous step into a factorization machine model to calculate the association scores between the Mashups and the open APIs, and TOP-N open API lists for creating the Mashup are obtained. Finally, experimental comparison and analysis are carried out on the PWeb dataset. The experimental results show that our approach has improved significantly.

scholarly journals D-Optimal Slope Design for Second Degree Kronecker Model Mixture Experiment With Three Ingredients

2020 ◽  
Vol 9 (2) ◽  
pp. 30
Author(s):  
Ngigi Peter Kung’u ◽  
J. K. Arap Koske ◽  
Josphat K. Kinyanjui
Keyword(s):  
Information Matrix ◽  
Coefficient Matrix ◽  
Three Dimensions ◽  
Matrix Means ◽  
The Matrix ◽  
Optimal Values ◽  
The Moment ◽  
Product Algebra ◽  
Slope Design ◽  
Second Degree

This study presents an investigation of an optimal slope design in the second degree Kronecker model for mixture experiments in three dimensions. The study is restricted to weighted centroid designs, with the second degree Kronecker model. A well-defined coefficient matrix is used to select a maximal parameter subsystem for the model since its full parameter space is inestimable. The information matrix of the design is obtained using a linear function of the moment matrices for the centroids and directly linked to the slope matrix. The discussion is based on Kronecker product algebra which clearly reflects the symmetries of the simplex experimental region. Eventually the matrix means are used in determining optimal values of the efficient developed design.

scholarly journals Multi-Stage Optimization of Induction Machines Using Methods for Model and Parameter Selection

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5537
Author(s):  
Martin Nell ◽  
Alexander Kubin ◽  
Kay Hameyer
Keyword(s):  
Induction Machine ◽  
Optimization Methods ◽  
Induction Machines ◽  
Parameter Selection ◽  
Pattern Search ◽  
Machine Model ◽  
Multi Stage ◽  
Selection Approach ◽  
Optimization Parameters ◽  
Selection Of

Optimization methods are increasingly used for the design process of electrical machines. The quality of the optimization result and the necessary simulation effort depend on the optimization methods, machine models and optimization parameters used. This paper presents a multi-stage optimization environment for the design optimization of induction machines. It uses the strategies of simulated annealing, evolution strategy and pattern search. Artificial neural networks are used to reduce the solution effort of the optimization. The selection of the electromagnetic machine model is made in each optimization stage using a methodical model selection approach. The selection of the optimization parameters is realized by a methodical parameter selection approach. The optimization environment is applied on the basis of an optimization for the design of an electric traction machine using the example of an induction machine and its suitability for the design of a machine is verified by a comparison with a reference machine.

scholarly journals On Optimality of Designs with Three Distinct Eigenvalues

10.37236/2709 ◽  
2013 ◽  
Vol 20 (2) ◽  
Author(s):  
M. R. Faghihi ◽  
E. Ghorbani ◽  
G. B. Khosrovshahi ◽  
S. Tat
Keyword(s):  
Nonlinear Programming ◽  
Optimal Design ◽  
Design Theory ◽  
Incidence Matrix ◽  
Information Matrix ◽  
Block Designs ◽  
Nonzero Eigenvalue ◽  
Group Divisible ◽  
The Family ◽  
The Matrix

Let ${\cal D}_{v,b,k}$ denote the family of all connected block designs with $v$ treatments and $b$ blocks of size $k$. Let $d\in{\cal D}_{v,b,k}$. The replication of a treatment is the number of times it appears in the blocks of $d$. The matrix $C(d)=R(d)-\frac{1}{k}N(d)N(d)^\top$ is called the information matrix of $d$ where $N(d)$ is the incidence matrix of $d$ and $R(d)$ is a diagonal matrix of the replications. Since $d$ is connected, $C(d)$ has $v-1$ nonzero eigenvalues $\mu_1(d),\ldots,\mu_{v-1}(d)$.Let ${\cal D}$ be the class of all binary designs of ${\cal D}_{v,b,k}$. We prove that if there is a design $d^*\in{\cal D}$ such that (i) $C(d^*)$ has three distinct eigenvalues, (ii) $d^*$ minimizes trace of $C(d)^2$ over $d\in{\cal D}$, (iii) $d^*$ maximizes the smallest nonzero eigenvalue and the product of the nonzero eigenvalues of $C(d)$ over $d\in{\cal D}$, then for all $p>0$, $d^*$ minimizes $\left(\sum_{i=1}^{v-1}\mu_i(d)^{-p}\right)^{1/p}$ over $d\in{\cal D}$. In the context of optimal design theory, this means that if there is a design $d^*\in{\cal D}$ such that its information matrix has three distinct eigenvalues satisfying the condition (ii) above and that $d^*$ is E- and D-optimal in ${\cal D}$, then $d^*$ is $\Phi_p$-optimal in ${\cal D}$ for all $p>0$. As an application, we demonstrate the $\Phi_p$-optimality of certain group divisible designs. Our proof is based on the method of KKT conditions in nonlinear programming.

scholarly journals How to Write Ethical User Stories? Impacts of the ECCOLA Method

2021 ◽  
pp. 36-52
Author(s):  
Erika Halme ◽  
Ville Vakkuri ◽  
Joni Kultanen ◽  
Marianna Jantunen ◽  
Kai-Kristian Kemell ◽  
...  
Keyword(s):  
Web Applications ◽  
Ethical Issues ◽  
Agile Development ◽  
Control Group ◽  
Ethical Guidelines ◽  
User Stories ◽  
Ai Ethics ◽  
High Level ◽  
Agile Software ◽  
Student Projects

AbstractArtificial Intelligence (AI) systems are increasing in significance within software services. Unfortunately, these systems are not flawless. Their faults, failures and other systemic issues have emphasized the urgency for consideration of ethical standards and practices in AI engineering. Despite the growing number of studies in AI ethics, comparatively little attention has been placed on how ethical issues can be mitigated in software engineering (SE) practice. Currently understanding is lacking regarding the provision of useful tools that can help companies transform high-level ethical guidelines for AI ethics into the actual workflow of developers. In this paper, we explore the idea of using user stories to transform abstract ethical requirements into tangible outcomes in Agile software development. We tested this idea by studying master’s level student projects (15 teams) developing web applications for a real industrial client over the course of five iterations. These projects resulted in 250+ user stories that were analyzed for the purposes of this paper. The teams were divided into two groups: half of the teams worked using the ECCOLA method for AI ethics in SE, while the other half, a control group, was used to compare the effectiveness of ECCOLA. Both teams were tasked with writing user stories to formulate customer needs into system requirements. Based on the data, we discuss the effectiveness of ECCOLA, and Primary Empirical Contributions (PECs) from formulating ethical user stories in Agile development.

Improved Vertical Covariance Estimates for Ensemble-Filter Assimilation of Near-Surface Observations

2007 ◽  
Vol 135 (3) ◽  
pp. 1021-1036 ◽  
Author(s):  
Joshua P. Hacker ◽  
Jeffrey L. Anderson ◽  
Mariusz Pagowski
Keyword(s):  
Rational Function ◽  
Land Surface ◽  
Time Of Day ◽  
Covariance Matrices ◽  
Near Surface ◽  
State Variable ◽  
The Matrix ◽  
Filter Approach ◽  
Basic Approaches ◽  
Surface Observations

Abstract Strategies to improve covariance estimates for ensemble-based assimilation of near-surface observations in atmospheric models are explored. It is known that localization of covariance estimates can improve conditioning of covariance matrices in the assimilation process by removing spurious elements and increasing the rank of the matrix. Vertical covariance localization is the focus of this work, and two basic approaches are compared: 1) a recently proposed hierarchical filter approach based on sampling theory and 2) a more commonly used fifth-order piecewise rational function. The hierarchical filter allows for dynamic estimates of localization functions and does not place any restrictions on their form. The rational function is optimized for every analysis time of day and for every possible observation and state variable combination. The methods are tested with a column model containing PBL and land surface parameterization schemes that are available in current mesoscale modeling systems. The results are expected to provide context for assimilation of near-surface observations in mesoscale models, which will benefit short-range mesoscale NWP applications. Results show that both the hierarchical and rational function approaches effectively improve covariance estimates from small ensembles. The hierarchical approach provides localization functions that are irregular and more closely related to PBL structure. Analysis of eigenvalue spectra show that both approaches improve the rank of the covariance matrices, but the amount of improvement is not always directly related to the assimilation performance. Results also show that specifying different localization functions for different observation and state variable combinations is more important than including time dependence.

scholarly journals Fitting directed graphical Gaussian models with one hidden variable

2004 ◽  
Vol 1 (1) ◽  
pp. 119-130
Author(s):  
Fulvia Pennoni
Keyword(s):  
Directed Acyclic Graph ◽  
Information Matrix ◽  
Continuous Variables ◽  
Gaussian Models ◽  
Second Derivatives ◽  
The Em Algorithm ◽  
The Matrix ◽  
Graphical Gaussian Models ◽  
Independence Structure ◽  
Graphical Gaussian

We discuss directed acyclic graph (DAG) models to represent the independence structure of linear Gaussian systems with continuous variables: such models can be interpreted as a set of recursive univariate regressions. Then we consider Gaussian models in which one of the variables is not observed and we show how the incomplete log-likelihood of the observed data can be maximized using the EM. As the EM algorithm does not provide the matrix of the second derivatives we show how to get an explicit formula for the observed information matrix. We illustrate the utility of the models with two examples.

scholarly journals X−1-balance of some partially balanced experimental designs with particular emphasis on block and row-column designs

2015 ◽  
Vol 52 (1) ◽  
pp. 1-12
Author(s):  
Ryszard Walkowiak
Keyword(s):  
Information Matrix ◽  
Positive Definite Matrix ◽  
Positive Definite ◽  
The Other ◽  
Experimental Designs ◽  
Block Designs ◽  
The Matrix

SummaryThis paper considers block designs and row-column designs where the information matrix C has two different nonzero eigenvalues, one of multiplicity 1 and the other of multiplicity h−1, where h is the rank of the matrix C. It was found that for each such design there exists a diagonal positive definite matrix X such that the design is X −1-balanced.

Tensile behavior of aloe vera fiber reinforced epoxy and polyester resin matrix composites

2018 ◽  
Vol 47 (5) ◽  
pp. 440-443 ◽  
Author(s):  
M.P. Jenarthanan ◽  
Karthikeyan Marappan
Keyword(s):  
Testing Machine ◽  
Aloe Vera ◽  
Tensile Behavior ◽  
Resin Matrix ◽  
Minor Effect ◽  
Matrix Composites ◽  
Machine Model ◽  
Content Type ◽  
The Matrix ◽  
Polyester Matrix

Purpose This paper aims to investigate the tensile behavior of epoxy and polyester matrix composites reinforced with continuous and aligned aloe vera fibers. Design/methodology/approach Composites with different volume fractions (30, 40 and 50 Vol. %) were fabricated by laying the fibers in a steel mould and pouring liquid resin, either DEGEBA/TETA epoxy or methyl-ethyl ketone hardened orthophthalic polyester, under pressure of 3 MPa. The specimens were cured for 24 h at room temperature and then tested in a universal Instron testing machine, model 5582, at 298 K (25°C). Findings The fracture surface was analyzed by scanning electron microscopy (SEM) under an acceleration voltage of 15 kV. SEM fractography revealed a poor adhesion between both the epoxy and polyester matrices with the aloe vera fiber. The results showed that in both cases the introduction of aloe vera fibers had a minor effect on the matrix reinforcement. Originality/value Investigation and comparison of tensile behavior of epoxy and polyester matrix composites reinforced with continuous and aligned aloe vera fibers have not been attempted so far.

scholarly journals A Hybrid Effort Estimation Technique for Agile Software Development (HEETAD)

2019 ◽  
Vol 9 (1) ◽  
Keyword(s):  
Software Development ◽  
Agile Development ◽  
Software Project ◽  
Hybrid Technique ◽  
Effort Estimation ◽  
Software Effort Estimation ◽  
User Stories ◽  
Development Costs ◽  
Time Required ◽  
Agile Software

Software development becomes a complex process when the software grows in size or complexity making it difficult to estimate usage of resources or development costs. Software effort estimation is that part of development which helps in assessing resource prior to development. An estimate is a quantified evaluation of the effort necessary to carry out a given development task and most often expressed in terms of durations. Effort estimation is done with an intent to aggregate individual estimates and obtain the overall duration, effort or cost of a software project. The workforce is measured as effort and the total time required is defined for a task in effort estimations which is usually expressed in units (Man-day, Man-month, and Man-year). Most other factors like cost or total time required to developed software are dependent on these estimations. Further, Algorithms used for estimating software developments efforts, may also be imprecise. Thus, Effort estimations plays an important part of software development in planning and monitoring projects. Agile methodology is relatively a new set of practices in software development. Agile estimations are based on many factors. Improperly recorded information from Agile methods can result in erratic estimations thus creating an impending need for precise effort estimations. It is difficult to find a single technique which can suit all conditions. Hence, this paper attempts to estimate agile development efforts by using a hybrid technique based on function points and user stories. Results of the proposed technique demonstrate that the arrived effort estimations based on user stories are efficient.

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