scholarly journals Recommendation-Based Component Selection for Component-Based Systems

2019 ◽  
Vol 8 (3) ◽  
pp. 6605-6611
Keyword(s):  
Business Processes ◽  
Focal Point ◽  
Search Space ◽  
Data Mining Algorithm ◽  
Software Components ◽  
Reusable Components ◽  
Reusable Component ◽  
Component Selection ◽  
And Performance ◽  
Selection Of

Selection of reusable software components in software repositories to facilitate quality software development has always been a focal point and a big concern for software researchers. One of the most time-consuming tasks in software reusability is tracing and retrieving software components from a large repository. The selection of inapt software package can result in high cost and ultimately becomes a prime source of adverse outcome in business processes and performance of the organization. Creation of quality software depends upon the selection of the best set of components among all the alternatives present in the reusable component repository. Frequently used sets of components can be obtained by using mining algorithms. This paper proposes a component selection methodology and a method for retrieval of the optimal set of reusable components from the repository. Case-based retrieval is applied for initial filtering of components to narrow down the search space. A data mining algorithm is applied to extract the candidate set of components for a given case. Most frequent set of components aid the decision-maker to select the finest component set and also assist in suggesting the supplementary components for the case to match with the latest updates.

scholarly journals The Dataset of the Experimental Evaluation of Software Components for Application Design Selection Directed by the Artificial Bee Colony Algorithm

Data ◽  
2020 ◽  
Vol 5 (3) ◽  
pp. 59
Author(s):  
Alexander Gusev ◽  
Dmitry Ilin ◽  
Evgeny Nikulchev
Keyword(s):  
Swarm Intelligence ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Operating Conditions ◽  
Software Components ◽  
Bee Colony ◽  
Component Selection ◽  
Effective Selection ◽  
Intelligence Approach ◽  
Selection Of

The paper presents the swarm intelligence approach to the selection of a set of software components based on computational experiments simulating the desired operating conditions of the software system being developed. A mathematical model is constructed, aimed at the effective selection of components from the available alternative options using the artificial bee colony algorithm. The model and process of component selection are introduced and applied to the case of selecting Node.js components for the development of a digital platform. The aim of the development of the platform is to facilitate countrywide simultaneous online psychological surveys in schools in the conditions of unstable internet connection and the large variety of desktop and mobile client devices, running different operating systems and browsers. The module whose development is considered in the paper should provide functionality for the archiving and checksum verification of the survey forms and graphical data. With the swarm intelligence approach proposed in the paper, the effective set of components was identified through a directional search based on fuzzy assessment of the three experimental quality indicators. To simulate the desired operating conditions and to guarantee the reproducibility of the experiments, the virtual infrastructure was configured. The application of swarm intelligence led to reproducible results for component selection after 312 experiments instead of the 1080 experiments needed by the exhaustive search algorithm. The suggested approach can be widely used for the effective selection of software components for distributed systems operating in the given conditions at this stage of their development.

Research on Data Mining Algorithm Based on Rough Set

2012 ◽  
Vol 433-440 ◽  
pp. 3340-3346 ◽  
Author(s):  
Yong Bin Yang
Keyword(s):  
Data Mining ◽  
Rough Set ◽  
Search Space ◽  
Data Mining Algorithm ◽  
Data Mining Algorithms ◽  
Starting Point ◽  
Depth Study ◽  
Mining Algorithms ◽  
Selection Of ◽  
Improved Algorithm

Through in-depth study on the existing rough set and data mining technologies, for the shortcomings of the existing data mining algorithms based on rough set, this paper presents an improved algorithm. This algorithm has the attribute nuclear as the starting point of reduction calculation, filtering distinguishable matrix as the basis for selection of candidate attributes, and condition attribute, decision attribute information entropy as heuristic information, to find the smallest reduction of the decision information system. The improved algorithm well solves the defects of the heuristic algorithm based on distinguish matrix, reducing the property search space, so as to improve the reduction speed.

Business processes in the insurance company: The method of operation through separating the key areas of activities

2020 ◽  
Vol 23 (11) ◽  
pp. 1269-1290
Author(s):  
A.A. Turgaeva
Keyword(s):  
Business Process ◽  
Business Processes ◽  
Systems Approach ◽  
Insurance Company ◽  
Entry And Exit ◽  
Control Procedures ◽  
Selection Of

Subject. This article analyzes the business processes in the insurance company, using the method of their operation with the selection of key areas of activity. Objectives. The article aims to describe certain business processes in insurance, highlighting participants, lines of activity, and the sequence of procedures. It analyzes the business process Settlement of Losses, which is one of the significant business processes in the insurance company. Methods. For the study, I used the methods of induction and deduction, analogy, and the systems approach. Results. Based on the analysis and description of business processes in the insurance company and the identification of key elements and steps in terms of the effectiveness of decisions, the article identifies the checkpoints of Entry and Exit, activity direction, and resources of the Settlement of Losses process. Conclusions. The application of the categories that split business processes makes it possible to develop step regulation for all processes and acceptable control procedures for different operations. The presented checkpoints at different steps of the business process will help identify weaknesses and eliminate them by re-checking the point.

Optimal adaptive inspection and maintenance for redundant systems

2021 ◽  
pp. 1748006X2110201
Author(s):  
Chaochao Lin ◽  
Matteo Pozzi
Keyword(s):  
Engineering Systems ◽  
Discounted Cost ◽  
Markov Decision ◽  
Inspection And Maintenance ◽  
And Performance ◽  
Partially Observable ◽  
Series Systems ◽  
Selection Of ◽  
Redundant Systems

Optimal exploration of engineering systems can be guided by the principle of Value of Information (VoI), which accounts for the topological important of components, their reliability and the management costs. For series systems, in most cases higher inspection priority should be given to unreliable components. For redundant systems such as parallel systems, analysis of one-shot decision problems shows that higher inspection priority should be given to more reliable components. This paper investigates the optimal exploration of redundant systems in long-term decision making with sequential inspection and repairing. When the expected, cumulated, discounted cost is considered, it may become more efficient to give higher inspection priority to less reliable components, in order to preserve system redundancy. To investigate this problem, we develop a Partially Observable Markov Decision Process (POMDP) framework for sequential inspection and maintenance of redundant systems, where the VoI analysis is embedded in the optimal selection of exploratory actions. We investigate the use of alternative approximate POMDP solvers for parallel and more general systems, compare their computation complexities and performance, and show how the inspection priorities depend on the economic discount factor, the degradation rate, the inspection precision, and the repair cost.

scholarly journals A Multiple Criteria Decision Making Method to Weight the Sustainability Criteria of System Selection for Surface Mining

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3066
Author(s):  
Michał Patyk ◽  
Przemysław Bodziony ◽  
Zbigniew Krysa
Keyword(s):  
Decision Making ◽  
Performance Assessment ◽  
Multiple Criteria Decision Making ◽  
Surface Mining ◽  
Open Pit ◽  
Mining Equipment ◽  
Surface Mines ◽  
Mining Conditions ◽  
And Performance ◽  
Selection Of

Selection and assessment of mining equipment used in open pit rock mines relies chiefly on estimates of overall exploitation cost. The rational arrangement of mining equipment and systems comprising loading machines, haul trucks and crushing plants should be preceded by a thorough analysis of technical and economic aspects, such as investment outlays and the costs of further exploitation, which largely determine the costs of mining operations and the deposit value. Additionally, the operational parameters of the mining equipment ought to be considered. In this study, a universal set of evaluation criteria has been developed, and an evaluation method has been applied for the selection of surface mining equipment and the processing system to be operated in specific mining conditions, defined by the user. The objective of this study is to develop and apply the new methodology of multi-criteria selection of open pit rock mining equipment based on multiple criteria decision-making (MCDM) procedures, to enable the optimization of loading, handling and crushing processes. The methodology, underpinned by the principles of MCDM, provides the dedicated ranking procedures, including the ELECTRE III. The applied methodology allows the alternative options (variants) to be ranked accordingly. Ultimately, a more universal methodology is developed, applicable in other surface mines where geological and mining conditions are similar. It may prove particularly useful in selection and performance assessment of mining equipment and process line configurations in mining of low-quality rock deposits. Therefore, we undertook to develop universal criteria and applications for the selection and performance assessment of process machines for surface mines, taking into account environmental aspects as well as deposit quality.

scholarly journals Measuring Software Maintainability with Naïve Bayes Classifier

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 136
Author(s):  
Nayyar Iqbal ◽  
Jun Sang ◽  
Jing Chen ◽  
Xiaofeng Xia
Keyword(s):  
Business Processes ◽  
Naive Bayes ◽  
Naïve Bayes ◽  
Business Value ◽  
Software Components ◽  
Naive Bayes Classifier ◽  
Bayes Classifier ◽  
Naïve Bayes Classifier ◽  
Error Type ◽  
Software Maintainability

Software products in the market are changing due to changes in business processes, technology, or new requirements from the customers. Maintainability of legacy systems has always been an inspiring task for the software companies. In order to determine whether the software requires maintainability by reverse engineering or by forward engineering approach, a system assessment was done from diverse perspectives: quality, business value, type of errors, etc. In this research, the changes required in the existing software components of the legacy system were identified using a supervised learning approach. New interfaces for the software components were redesigned according to the new requirements and/or type of errors. Software maintainability was measured by applying a machine learning technique, i.e., Naïve Bayes classifier. The dataset was designed based on the observations such as component state, successful or error type in the component, line of code of error that exists in the component, component business value, and changes required for the component or not. The results generated by the Waikato Environment for Knowledge Analysis (WEKA) software confirm the effectiveness of the introduced methodology with an accuracy of 97.18%.

Improved Particle Swarm Optimizer with Dynamically Adjusted Search Space and Velocity Limits for Global Optimization

2015 ◽  
Vol 24 (05) ◽  
pp. 1550017 ◽  
Author(s):  
Aderemi Oluyinka Adewumi ◽  
Akugbe Martins Arasomwan
Keyword(s):  
Global Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Search Space ◽  
Particle Swarm Optimizer ◽  
Search Range ◽  
Original Algorithm ◽  
Inertia Weight ◽  
And Performance

This paper presents an improved particle swarm optimization (PSO) technique for global optimization. Many variants of the technique have been proposed in literature. However, two major things characterize many of these variants namely, static search space and velocity limits, which bound their flexibilities in obtaining optimal solutions for many optimization problems. Furthermore, the problem of premature convergence persists in many variants despite the introduction of additional parameters such as inertia weight and extra computation ability. This paper proposes an improved PSO algorithm without inertia weight. The proposed algorithm dynamically adjusts the search space and velocity limits for the swarm in each iteration by picking the highest and lowest values among all the dimensions of the particles, calculates their absolute values and then uses the higher of the two values to define a new search range and velocity limits for next iteration. The efficiency and performance of the proposed algorithm was shown using popular benchmark global optimization problems with low and high dimensions. Results obtained demonstrate better convergence speed and precision, stability, robustness with better global search ability when compared with six recent variants of the original algorithm.

scholarly journals GENETIC DIVERGENCE AND MORPHO-AGRONOMIC PERFORMANCE OF JATROPHA CURCAS L. CLONES FOR SELECTION OF CLONAL VARIETIES

2016 ◽  
Vol 29 (4) ◽  
pp. 841-849
Author(s):  
ADRIANA QUEIROZ DE ALMEIDA ◽  
SIMONE ALVES SILVA ◽  
VANESSA DE OLIVEIRA ALMEIDA ◽  
DEOCLIDES RICARDO DE SOUZA ◽  
GILMARA DE MELO ARAÚJO
Keyword(s):  
Genetic Diversity ◽  
Multivariate Analysis ◽  
Plant Height ◽  
Genetic Divergence ◽  
Morphological Characterization ◽  
Stem Diameter ◽  
Agronomic Performance ◽  
And Performance ◽  
Lower Contribution ◽  
Selection Of

ABSTRACT The knowledge about genetic diversity of jatropha crop is important for genetic conservation resources and breeding of this species. The aim of this study was to evaluate the genetic diversity and performance of jatropha clones through morphological characterization to selection of clonal varieties for biofuels production. The clones were obtained through shoot cuttings from previous selection in a population of half-sibs progenies. The morphoagronomic analyses of clones was carried out at 180 days after transplantation and were evaluated plant height, stem diameter, number of primary branches and number of secondary branches, number of bunches and number of fruits per plant. Evaluating clones performance, significant results were found for the number of secondary branches. About analysis of genetic diversity, the measures of dissimilarity genetic varied from 0.62 to 13.11, this way, the UFRBPR14 and UFRBPR15 clones were more divergent. The Tocher method was efficient to verify formation of four groups. The characteristics that most contributed to the divergence among clones were branches number, height and number of bunches, and, stem diameter had lower contribution. The jatropha clones differed only in the secondary branches number and multivariate analysis showed divergence among the jatropha clones with formation of four groups. Also, branches number, plant height and number of bunches were characteristic that contributed to genetic divergence.

Digging deep? Digging more? A research on the influence of corporate CSR theme consistency strategy

2018 ◽  
Vol 1 (1) ◽  
pp. 76-93 ◽  
Author(s):  
Yang Zhang ◽  
Xuhui Wang ◽  
Yingying Shen
Keyword(s):  
Communication Channel ◽  
Information Dissemination ◽  
Focal Point ◽  
Social Programs ◽  
Business Practices ◽  
Content Type ◽  
Moderation Effect ◽  
Corporate Social ◽  
And Behavior ◽  
Selection Of

PurposeAs the focal point of both academic studies and business practices, the theme strategy of corporate social responsibility (CSR) arouses wide attention. However, extant studies concentrate more on the selection of the theme of CSR activities, such as the fitness between CSR activities and the core business, thus largely neglecting the consistency of the theme. The purpose of this paper is to determine whether the enterprise should adopt a consistent theme strategy or should participate in different social programs, and how do customers response to the lack of studies in different theme-consistent strategies.Design/methodology/approachIn this paper, two progressive experiments are performed. The purpose of study 1 is to examine the influence of theme consistency on consumers’ CSR association and how consumers’ attribution to corporation motivation mediates such impacts. The purpose for study 2 is to examine whether information dissemination channels and cooperation with public organization could affect the influence of theme consistency strategy.FindingsThe significant influences of theme consistency on consumer CSR association was demonstrated, and consumer’s perceived motivation of CSR was found to play the mediation role. Moreover, the moderation effect of the communication channel of CSR information was found to be important to strengthen the influence of the theme-consistent strategy.Originality/valueThis paper not only demonstrates the influence of theme consistency, but also explains how theme consistency influences consumers’ attitude and behavior. It enriches the study on the antecedent variables of consumers’ attribution to corporate motivation.

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