Remote monitoring of objects or technological processes is used in many industries and service-oriented companies to obtain up-to-date information about the state of things or technical processes. The article is devot...
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Feature models are the de facto standard for modelling variabilities and commonalities. Concrete models in different domains exist;however, many are in private or sparse repositories or belong to discontinued projects...
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Fog computing extends the capabilities of cloud computing by enabling computing at the edge of the network, involving devices such as mobile collaborative devices or fixed nodes with integrated storage, computing, and...
Fog computing extends the capabilities of cloud computing by enabling computing at the edge of the network, involving devices such as mobile collaborative devices or fixed nodes with integrated storage, computing, and communication capabilities. Fog computing offers benefits such as improved efficiency, increased security, savings in network bandwidth, and increased flexibility. In order to provide a complete understanding of Fog computing, this paper presents its salient features and highlights the differences from cloud computing research. Cloud computing is an emerging technology that offers computing resources on a pay-per-use basis. It provides three service models, and the cloud offers cost-effective centrally managed resources for reliable computing for specific tasks. This document presents a comparison between Fog computing and cloud computing, highlighting the differences in design, deployment, services, and tools available to organizations and users. By explicating the distinctiveness of fog computing and its contrast to cloud computing, we contribute to the field by shedding light on the unparalleled potential of fog computing in conserving resources while delivering robust computational solutions at the network periphery. Our study offers a new perspective that challenges the prevailing practices and extends the discourse on optimizing distributed computing architectures.
In the present article, we have considered the issue of selection of potential locations of trade objects as a multi-factor decision-making in the conditions of uncertainty by applying the theory of fuzzy sets. Exampl...
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Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems lik...
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Graph colouring is the system of assigning a colour to each vertex of a *** is done in such a way that adjacent vertices do not have equal *** is fundamental in graph *** is often used to solve real-world problems like traffic light signalling,map colouring,scheduling,***,social networks are prevalent systems in our ***,the users are considered as vertices,and their connections/interactions are taken as *** users follow other popular users’profiles in these networks,and some don’t,but those non-followers are connected directly to the popular *** means,along with traditional relationship(information flowing),there is another relation among *** depends on the domination of the relationship between the *** type of situation can be modelled as a directed fuzzy *** the colouring of fuzzy graph theory,edge membership plays a vital *** membership is a representation of flowing information between end nodes of the *** from the communication relationship,there may be some other factors like domination in *** influence of power is captured *** this article,the colouring of directed fuzzy graphs is defined based on the influence of *** with this,the chromatic number and strong chromatic number are provided,and related properties are *** application regarding COVID-19 infection is presented using the colouring of directed fuzzy graphs.
As educators aim to evaluate students' knowledge, the design and quality of their assessment instruments play a vital role. Focusing on test difficulty, as well as comparing real and set results to determine knowl...
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ISBN:
(数字)9798350358100
ISBN:
(纸本)9798350358117
As educators aim to evaluate students' knowledge, the design and quality of their assessment instruments play a vital role. Focusing on test difficulty, as well as comparing real and set results to determine knowledge levels ensure that tests adequately challenge students without overwhelming them. There are various methods incorporating these concepts, such as item response theory and classical test theory. Recognizing the patterns of student performance, thus highlighting areas requiring further attention, can foster targeted interventions to enhance learning outcomes.
Because of the increased market opening and massive data collection brought about by globalization, the need of maintaining control over customs procedures has increased. However, the integration and processing of cus...
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ISBN:
(数字)9798350391183
ISBN:
(纸本)9798350391190
Because of the increased market opening and massive data collection brought about by globalization, the need of maintaining control over customs procedures has increased. However, the integration and processing of customs data are complicated by its extreme imbalance. Finding autonomous, computationally sophisticated solutions for customs handling is therefore crucial. The study described in this paper aims to propose an artificial intelligence-based method for customs fraud detection through data analytics. A machine learning-based approach for detecting customs fraud is proposed. The research methodology includes data preprocessing, data analytics, combining results, and deriving precise solutions from results obtained. The aim is to extract meaningful information from a dataset. For the purpose of classifying customs fraud, seven algorithms for machine-learning-kNN, SGD, Constant, Logistic Regression, Random Forest, Neural Network, and Naive Bayes-are chosen and empirically assessed.
A digital image is usually stored as a two-dimensional matrix consisting of numerical values of the intensity of each color;for example, Red-Green-Blue (RGB). This fact allows a possibility of manipulation of the imag...
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Machine learning technique is full-fledged as a boosting sector to develop modeling and forecasting of complex time series observations in the present environment. This study made an attempt to inspect the future perf...
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The process of unsteady flow of a single-phase liquid in a cylindrical reservoir arising under the elastic mode of reservoir development is considered. To describe this process, a power law of filtration is proposed f...
The process of unsteady flow of a single-phase liquid in a cylindrical reservoir arising under the elastic mode of reservoir development is considered. To describe this process, a power law of filtration is proposed for a single-phase flow in a porous medium. Within the framework of the proposed model, the task of identifying one parameter of the model characterizing the simulated reservoir system is set. To construct a discrete analog of the inverse problem, the finite difference method is used using an explicit–implicit approximation in time. To solve the resulting system of nonlinear equations, a special representation is proposed that allows reducing the nonlinear system to two independent systems of linear equations. As a result, an explicit formula is obtained for determining the approximate value of the desired reservoir parameter. Based on the proposed method, numerical experiments were carried out for model problems.
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