جستجوی مقالات مرتبط با کلیدواژه « 1 » در نشریات گروه « ریاضی »

In this paper, we consider a networked fractional SIR model. After proving the existence and uniqueness of the solution, we obtain the basic reproduction number, the disease-free equilibrium point and the endemic equilibrium point. By constructing the Lyapunov function, we show that the endemic equilibrium is globally asymptotically stable when the basic reproduction number is greater than 1, and the disease-free equilibrium is globally asymptotically stable when the basic reproduction number is less than 1. Finally, numerical simulations are carried out to verify these theoretical results. Thus, the stability theory of Laplacian diffusion is extended to the graph Laplacian model.

Various methods have recently been proposed to predict essential economic and non-economic variables. Each forecasting method has its own advantages and disadvantages based on the nature of the input data. Box-Jenkins and Halt-Winters methods are among the new approaches for increasing the accuracy of forecasting results. Therefore, this research aimed to predict OPEC average oil price data for June 2022 to May 2024 based on the data from 2003 to 2022 using Box-Jenkins and Holt-Winters methodology with a single variable. The errors of Box-Jenkins methodology, among the time series, processes ARIMA 5.1.5, ARIMA 4.1.5, ARIMA 3.1.5, and ARIMA 5.1.3 have the best accuracy with MSE of 61.86, 63.21, 63.29, and 63.62, respectively. The accuracy of the Holt-Winters method was not appropriately compared to the time series method due to the nature of the data.

Buildings have a significant impact on climate change through their resource and energy consumption. This paper focuses on the importance of building energy simulation in reducing energy consumption and enhancing building sustainability. The study followed a systematic research plan, which involved extracting, preprocessing, and categorizing citation data from Scopus covering the period from 1982 to 2022. Utilizing the PRISMA Algorithm, a total of 3,049 studies were analyzed. The research objectives included descriptive, network, and quantitative content analysis. The study successfully identified influential documents, authors, journals, organizations, and countries. Additionally, scientific maps were created to visualize the research landscape and identify gaps in the field. The analysis of studies identifies emerging research areas like artificial neural networks, NZEB, genetic algorithms, machine learning, and retrofitting, which hold potential for future research.

This paper investigates the possible effects of the implementation of value-added tax on Iran's inflation in companies listed on the Tehran Stock Exchange. The time domain of the collected data includes the financial statements of manufacturing companies accepted in the Tehran Stock Exchange in 6 years from the spring of 2014 to the spring of 2019. The obtained data includes manufacturing, service companies and institutions. Moreover, leasing companies, financial institutions, insurance and banks are not included with their data uploaded based on the Kodal site. The liquidity growth has been obtained from 2013 as the base year. This paper evaluates the collected data in two descriptive and inferential statistics sections. The descriptive analysis includes the indicators of descriptive statistics of frequency, percentage of relative frequency, mean, standard deviation, and inferential section art investigates research hypotheses using independent variables over dependent variables. In the following, efforts were made to investigate the direct and indirect effects of statistical equations and Eviews10, Excel software. the modified model results show the estimated coefficient of $(\beta= 368.1346)$. Also, the value (T=3.803553) of the critical point (2) and the probability level of Prob=0002, show that the estimated coefficient obtained is significant. The $R^{2}$ value indicates that the variable of inflation, which is known as an independent variable, has been able to affect the dependent variable of value-added tax by 0.89\%. The value of AR(1) is the amount of residual or residual based on the time pattern. According to the correction of the model, Durbin-Watson's value ranges from 1.80 to 10.2 for the optimal fit model.

The chattering phenomenon has been one of the most important controlling challenges in recent years, and efforts have been made to eliminate or control this phenomenon effectively, with various control strategies. In this article, a new super-twisting back-stepping sliding mode controller is proposed and to validate the performance of this controller, the outcomes of some well-known techniques are compared, in two aspects reducing tracking error and removing the chattering phenomenon. Also, a comparative analysis between control methods such as sliding mode,  feedback linearization and back-stepping control has been done in the sense of stability and convergence. The model discussed in this article is a non-linear, highly unstable system of the inverted pendulum. The results of applying the proposed controller on an inverted pendulum are compared in terms of the tracking speed, convergence time, error and chattering reduction. In addition, the stability analysis of the closed-loop system is presented according to the Lyapunov theorem. The results clearly show the efficiency of the proposed method not only in terms of stability and convergence improvement but also in reducing unwanted chattering.

This research was carried out quantitatively to analyze the management of road transport of cargo and goods in Isfahan province with an emphasis on the political and security dimensions. Through semi-structured interviews with 8 subject matter experts, the management components of the road transport industry were identified. In the next step, the data extracted by the survey method was used as the basis for compiling a researcher-made questionnaire in the dimensions of environmental, economic, technical, process, operational, legal and human resource damages. The statistical sample in this phase was estimated to be 269 people through Cochran's sampling formula and was selected by the available random method. The validity of the data was confirmed through formal, content, and construct validity, as well as its reliability through Cronbach's alpha greater than 0.7. The results show that the average of all identified dimensions is higher than average (3); The results also show that the highest influence coefficient in process damages is (0.147) and the highest predictive power belongs to technical damages (0.245). The model fit criterion shows that the influence and predictor coefficients of the model are reliable.

Glaucoma stands out as a prevalent ocular ailment in the elderly population, causing substantial harm to the optic nerves and eventual vision impairment. Fundus photography plays a pivotal role in the clinical assessment of glaucoma, facilitating the exploration of associated morphological alterations. Computational algorithms, capable of processing fundus images, have emerged as indispensable tools in this diagnostic domain. Hence, the imperative development of an automated diagnostic system leveraging image processing techniques is underscored. In this study, a novel approach to the segmentation and classification of retinal optic nerve head images is introduced. This method concurrently executes both tasks through a deep learning framework, thereby enhancing the learning speed within the network. The proposed network encompasses approximately 29 million parameters and demonstrates an efficiency of 2.5 seconds for segmenting and classifying retinal images. Central to this strategy is a multi-task deep learning network, harmonizing segmentation and classification processes, and leveraging information from both tasks to optimize learning efficacy. Validation of the proposed method is conducted using the publicly available ORIGA dataset. The attained performance metrics for accuracy, sensitivity, specificity, and F1-score are 99.461, 93.46, 100, and 98.7006, respectively. These results collectively affirm the substantial advancement achieved by the proposed method in comparison to existing methodologies.

The present research is aimed at verifying the operational budget of foreign oil companies (case study: National Iranian Oil Company). The statistical population of the present study is the National Iran Oil Company, and subject to lack of samples the population of the study is conducted with all national Iranian oil company's subsidiaries that operate abroad are studied. To collect the necessary information and statistics, a questionnaire method was used for hard data, as well as a sample of the conducted studies, also competent authorities references were used for soft data. To carry out this research, at first, the significance of the variables was checked using the generalized Dickey-Fuller test, and after determining the degree of significance of the variables, the ARFIMA method was used to determine the model of operational budgeting. To estimate the research model, Eviews 10 software was used. The results of the research analysis showed that political risk and inflation have a negative and significant impact on the operating budget of the company and reduce the efficiency of resources. Also, the increase in environmental and organizational variables causes budgeting based on the intrinsic price of crude oil. Finally, the results of the research showed that variables such as the behaviour of competing companies and financial support as variables of structural failure in the operational budgeting model have a significant impact.

This research aims to design a Grounded Theory-based model for talent management for future Iran. Moving from the present to the future, the lack of human resources will become a serious problem for Iran. Therefore, to overcome the coming difficult days, it is necessary to identify and nurture the existing talent well, and since the best time to identify and develop talent is childhood, adolescence, and youth ages, and people are in school and university, at this age, so the education cycle is the best cycle for talent management. This research was conducted to compensate for the lack of human resources through optimal control of talent. The research method is sequential mixed (the qualitative section is preferred to the quantitative section). In the quantitative section, 10 expert professors were interviewed, and the results were analyzed through the Grounded Theory method and 122 codes were obtained as 6 axial categories. Then, the model was designed. The designed model was tested using a sample including 400 people and finally, suggestions were presented.

The study aims to present a customer relationship management (CRM) model focusing on customer knowledge management in the banking industry. It employs a qualitative, applied research approach using systematic grounded theory. Data was collected through semi-structured interviews with 18 experts from Pasargad Bank, utilizing snowball and purposeful sampling methods. The proposed model includes Causal factors, Contextual factors, and Intervening factors. Our strategies include: improving management structure, enhancing marketing strategies, human resource management, market orientation, and improving service delivery methods. Then 3 categories of factors ``banking services marketing" in the three core codes of ``greater and established presence in the market", ``improving the bank structure for better service delivery" and ``realizing internal marketing" were identified as consequences in the customer relationship management model with an emphasis on customer knowledge management in the banking industry. Moreover, the model's validation confirmed construct validity across all dimensions.

Within this paper, we study the initial growth of interfaces and asymptotic locally weak solutions by the construction of its self-similar solution to the Cauchy Problem for a parabolic p-Laplacian type diffusion-convection equation with the effect of absorption source. The significant methods are applied in this work, techniques of blowing up, rescaling, and comparison principles in non-smooth domains. The importance of this model came through its applications in a variety of fields such as chemical process design, biophysics, plasma physics, quantum physics, and others.

In this study, we examine the inverse problem for the differential equation of the Sturm-Liouville type with the spectral boundary condition in the finite interval. Using Lieberman-Hochstadt's method, we show that if $p(x)$ is prescribed on the half interval  $\left(\frac{\pi}{2},\pi\right)$  then a single spectrum suffices to determine $p(x)$ on $(0,\pi)$. Moreover, applying Gesztesy-Simon's method, we demonstrate that if $p(x)$  is assumed over the given segment $[\pi/2(1 - \theta), \pi]$ where $\theta \in (0, 1),$ a finite number of the spectrum is enough to give $p(x)$ on $(0, \pi)$.

With the expansion of Internet of Things (IoT) services and the use of satellite communications, according to the regional or continental extent of these services, the need for lightweight encryption has increased. In satellite communications, security cannot be fully implemented given the long transmission distances, rendering heavy encryption algorithms, such as RSA, unreliable. ECC using mathematical solutions and elliptic curve discrete logarithm problems (ECDLP) can be considered a lightweight algorithm in telecommunications. Here, we propose a new strategy for secure IOT data communication between a satellite link and a terrestrial link that uses the principles of ECC elliptic curve cryptography and the NIST P-256 standard for key agreement and encryption for transmitting messages over the satellite communication platform.

Construction projects are frequently associated with a high incidence of cost overruns. To address this issue, the present study adopts a descriptive and survey-based approach to identify and rank the factors that contribute to construction costs. The study's statistical population comprises ten expert specialists, and the fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) with Analytical Network Process (ANP) (DANP) technique is utilized to evaluate the research factors. Additionally, the fuzzy DANP and Delphi methods are employed to rank the essential dimensions and criteria of the research. The study's findings reveal that environmental factors are the primary cause of construction cost overruns, followed by managerial factors and legal and administrative factors, respectively. Dynamic conditions often result in unpredictable challenges for environmental factors, making them a critical driver of construction cost overruns. Therefore, environmental factors play a significant role in contributing to construction cost overruns.

The rapid advancements in healthcare and the increasing demand for high-quality healthcare services have placed significant pressure on hospital facilities. The complexity of healthcare systems requires continuous innovation to meet the ever-changing needs of patients and healthcare providers. A comprehensive model grounded in the Grounded Theory is proposed to address the challenges and complexities of innovation in hospital design. This model aims to facilitate innovation in hospital design and operations while ensuring sustainability. In this study, qualitative data were collected through interviews with key stakeholders in hospital design and management. The data were analyzed using grounded theory methodology to develop a model for innovation in hospital design. The process of data collection and analysis was not two consecutive processes but was carried out in a zigzag and simultaneous manner, which is the nature of theoretical sampling. By analyzing the interviews line by line, open coding was done. Based on the identified open codes, central codes were formed and a theoretical model was developed with the help of selective coding. Finally, the paradigm model was approved by the opinion of experts. The results indicate that in the context of innovation in hospital design, key factors include leadership and management, interdisciplinary collaboration, stakeholder engagement, and the integration of technology and evidence-based practices. These factors, along with a focus on patient-centred care, lead to the emergence of innovative solutions and sustainable practices in hospital design.

This paper proposes an observation-driven finite mixture model for clustering high-dimension data. A simple algorithm using static hidden variables statically clusters the data into separate model components. The model accommodates normal and skew-normal distributed mixtures with time-varying component means, covariance matrices and skewness coefficient. These parameters are estimated using the EM algorithm and updated with the Generalized Autoregressive Scale (GAS) approach. Our proposed model is preferably clustered using a skew-normal distribution rather than a normal distribution when dealing with real data that may be skewed and asymmetrical. Finally, our proposed model will be evaluated using a simulation study and the results will be discussed using a real data set.

Using the Pohozaev-type arguments, we prove the nonexistence results for sub-elliptic problems with critical Sobolev-Hardy exponents and Hardy-type potentials on the Carnot group.

A $b$-coloring of a graph\ $G$ is a proper coloring of its vertices such that each color class contains a vertex that has a neighbor in every other color classes. The $b$-chromatic number of a graph $G$, denoted by $b(G)$, is the largest integer $k$ such that $G$ admits a $b$-coloring with $k$ colors. Let $G_{e}$ be the graph obtained from $G$ by subdividing the edge $e $. A graph $G$ is $sd_{b}$-critical if $b(G_{e})<b(G)$ holds for any edge $e$ of $G$. In this paper, we first present \ several basic properties of $sd_{b} $-critical graphs and then we give a characterization of $sd_{b}$-critical $P_{4}$-sparse graphs and $sd_{b}$-critical quasi-line graphs.

We introduce a fast method of computing the topological charge indices of simple graphs (molecules) which does not require matrices of large sizes. For the case of trees, we give a compact formula and in the general case we obtain upper and lower bounds for the charge indices. We give concrete examples of trees and molecules with their charge indices computed using our method.

We give a purely combinatorial proof for the infinitary van der Waerden's theorem.