International Journal Of Nonlinear Analysis And Applications
Volume:15 Issue: 1, Jan 2024

In this paper, we mainly investigate the finite order transcendental meromorphic solutions of Fermat-type equations and also we consider here the linear difference operator of meromorphic function. In addition, we extend some recent results obtained in [1]. The example is exhibited to validate certain claims of the main result.

In this paper, we introduce and study a new class of centralizers which are called triple θ-centralizers. We will see that the notions of triple θ-centralizers and θ-centralizers are different. Some observations concerning triple θ-centralizers and approximate triple θ-centralizers are given.

Breast cancer is known to be among the most prevalent cause of mortality among women. Since early breast cancer diagnosis increases survival chances, the development of a system with a highly accurate output to detect suspicious masses in mammographic images is of great significance. Thus, many studies have focused on the development of methods with favorable performance and acceptable accuracy to detect cancerous masses, proposed various techniques to diagnose breast cancer, and compared their accuracies. Most previous studies have used composite selection and feature reduction techniques to detect breast cancer and accelerate its treatment; however, most have failed to reach the desired accuracy due to the selection of ineffective features and the lack of a proper analytical method for the features. The present study reviews the methods proposed to detect breast cancer so far and analyzes the process of feature vector optimization techniques as well as the normal/abnormal and benign/malignant mass classification.

The purpose of this study is to examine financing with a focus on optimizing working capital with structural equations. The statistical population of the present study consists of all the financial managers and senior managers of the dairy industry sector of Golestan province. The sample size of the research was considered to be 73 people, and the questionnaire was distributed among them. And for this purpose, nine hypotheses were formed, which were analyzed using pls. The results of the data analysis showed that investment factors have an effect on business factors. Facilitation factors do not affect business factors. Production factors do not affect commercial factors. Economic factors affect commercial factors. Performance has an impact on business factors. Business factors affect market factors. Business factors affect organizational factors. Investment factors influence market factors through commercial factors and investment factors influence organizational factors through commercial factors.

In this article, we extend some recently fixed point theorems in the setting of G−fuzzy metric spaces. We introduce some new concepts of contractions called γ-contractions and γ-weak contractions. We prove some fixed point theorems for mappings providing γ-contractions and γ-weak contractions. On the other hand, we consider a more general class of auxiliary functions in the contractivity condition.

In the present paper, the impacts of viscous dampers on controlling the vibrations imposed on seismic vibrations are evaluated using descriptive methods. To this end, the library method and other research related to viscous dampers and their impacts on controlling external excitation such as earthquakes have been used. ETABS software was used for modelling the structures. Also, nonlinear dynamic analysis was used for seismic analysis of the structures. Based on the findings, using viscous dampers are effective to improve seismic parameters of structure and to decrease displacement, speed, base shear, and velocity. On the other hand, viscous fluid dampers can strengthen the structure and its performance during severe earthquakes and can be applied in newly constructed structures. The impact of a passive viscous damper on reducing the seismic response of the structures is found significant at the confidence level of 90%. Reduction of energy of structure hysteresis because of the nonlinear behaviour of members using dampers is proved to be significant at the confidence level of 80%. The results reveal that the lateral resistance of an EBF with a short joint can be 4/5 to 9 times more than the lateral resistance of an MRF, that the behaviour coefficient of fifteen-story EBF considered 6/5-7/75, concluded that the length of the bray does not have an impact on the behaviour coefficient of these frames.

Nowadays, the number of road accidents in Iran is on the increase. Therefore, the financial loss by such accidents which are imposed on households and the government is very high. Since the financial, psychological, and social harms are sometimes irreparable, it is required to think of effective solutions. This study was applied and quantitative in terms of objective with a survey approach to validate the identification and control model of factors affecting strategic crisis management in road accidents. Data collection was conducted using a 50-item questionnaire based on the model developed by the researchers and a survey of 100 employees of the General Directorate of Roads in Kerman province. The results indicated that causal factors affect the main category at 0.705, the main category affects strategies at 0.379, intervening factors affect strategies at 0.129, underlying factors affect strategies at 0.457 and finally, strategies affect consequences at 0.849 all with a 95% confidence level.

Infill drilling is the first choice to increase the recovery factor, but the mission of selecting the best well location is considered a major challenge with the huge area of the reservoir and the time consumption to conducting the simulation runs that may reach hundreds to thousands. This paper adopted the design of an experiment plus a proxy optimization technique to solve this problem. Where the Latin Hypercube represents the DoE while the radial basis function network represents the artificial intelligence proxy model. The proxy model mimics the reservoir model to reduce the computation time and speed up the well-placement optimization process. The Latin Hypercube approach is used to generate data to train the proxy model to construct a reliable artificial intelligence model to predict the best wells locations. The results are very optimistic and encouraging to rely on using the art-of-state to construct a proxy model to conduct the infill wells drilling optimization. Where the increase in cumulative oil production for the optimized case is more than the un-optimized case by 6.45% and the decrease in the field cumulative water production for the optimized case is less than the un-optimized case by 16.11% from 2020 to 2040.

Supply chain members are interdependent through financial, material and information flows. In addition to conferring benefits for the chain, this dependence brings uncertainty and risks. The extent of such challenges makes collaborative interactions and improvement of supply chain performance confront significant problems. Therefore, managers are encouraged to embrace new technologies to settle these problems. The new blockchain technology offers advantages such as traceability, decentralization, encryption, immutability and transparency of data transfer. In this way, the things that are necessary to create trust and integrity in a supply chain are provided by a blockchain. The purpose of this study is to systematically analyze how blockchain technology is placed in the supply chain network of the food industry and present the potential challenges of its implementation. In this research, the qualitative data foundation method and MAXQDA20 software are applied to determine the antecedents and processes of blockchain deployment. In the following, the resulting paradigm model is validated using the partial least squares technique (PLS), and SMART PLS software. The results of this study indicate that the drafting of the law and the support of the government create an impact on the establishment of blockchain in the food supply chain. Moreover, with the development of technological infrastructure, the chain will be improved and ultimately gain a competitive advantage and economic development of the country even with the imposition of sanctions.

This work studies the existence and the uniqueness of the solution to a kind of high-order nonlinear fractional integro-differential equations involving Rieman-Liouville fractional derivative. The boundary condition is of integral type which entangles ending point of the domain. First, the unique exact solution is extracted in terms of Green's function for the linear fractional differential equation and then Banach contraction mapping theorem is applied to prove the main result in the case of general nonlinear source term. Furthermore, our main result is demonstrated by an illustrative example to show its legitimacy and applicability.

The database management system (DBMS) for any application is crucial for developers because each application needs high performance to run efficiently. Therefore, database Benchmarking is the process of performing several Defined tests on those databases to evaluate their performance. The electronic benchmarking System (EBS) facilitates and improves human resource management (HRM) in all aspects of real life. EBS designed by four different database backends and three different web technology. This paper presents a comparative evaluation of the performance of the top DBMS systems namely (MySQL, SQL Server, Oracle, and MS Access). The middleware is designed using three dynamic web technologies (PHP, ASP, and PYTHON). In order to evaluate the backend performance for the four mentioned databases system by using two Parameters Response Time (RT) and Throughput (TT) over different Tire Architectures namely: One-Tier Architecture (1TA), Two-Tier Architecture (2TA). This paper will show which of the database has a better Response time (RT) and Throughput (TT).

This paper determines the weights of the key factors for evaluating the performance of the banking system in Iran using the Balanced Scorecard (BSC) and Fuzzy Analytic Network Process (FANP) approaches. This paper first identifies key factors for the performance evaluation and then determines the cause-and-effect relationship between using the DEMATEL approach. The key factors were included in the BSC framework using the experts' opinions and following principles, including the need for all communication to lead to profitability, not considering the causal relationship from more tangible dimensions to intangible dimensions, and eliminating feedback causal relationships. The calculated weights show the maximum importance of the learning and growth dimensions and the minimum importance of the financial dimension. Among the key factors, on-time service is the maximum important, with customer retention being the minimum important. The extracted key factors can evaluate the performance of the country's banking system descriptively and based on the data obtained from declarations or official reports provided by different evaluators.

The purpose of this research is to investigate the current state of budgeting and accounting in Iraqi public organizations and develop a conceptual framework and model for the implementation of performance-based budgeting and accrual accounting in these organizations. The required data were collected through an open-ended questionnaire and the Delphi technique, and qualitative content analysis was used to identify the requirements for the implementation of performance-based budgeting and accrual accounting in Iraq. The population consisted of faculty members, senior managers, financial managers, and financial and budget experts in Iraqi public organizations over the period 2021-2022. Using purposive sampling, 65 individuals were selected as the sample. Descriptive data were analyzed using measures of central tendency and dispersion, and the validity and reliability of the instrument were assessed through face validity and Cronbach's alpha. The results indicated the absence of performance-based budgeting and accrual accounting in Iraqi public organizations, and conceptual frameworks and models are proposed for the implementation of these systems.

This paper seeks to prove the pathwise uniqueness of an abstract stochastic partial differential equation in Hilbert spaces driven by both Poisson random measure and the Wiener process with Hölder continuous drift. The main idea is based on the corresponding infinite-dimensional Kolmogorov equation. In addition, the main result is further supported by the help of an example.

Small area estimation methods have been considered in various fields, especially medicine, agriculture, economics, social sciences, and political Science. These methods have many applications in providing reliable statistics for small-sample or non-sample statistical areas. In estimating the small area, there are two approaches: the basic design and the basic model. In this paper, a model-based approach to labor force indicators is considered using a multinomial mixed Logit model. The practical application of the method proposed in this article is to estimate the total number of employees, unemployed and unemployment rate using household income and expenditure data for Semnan province by cities; Semnan, Shahroud, Damghan and Garmsar concerning the period 2011-2016. Finally, we have found the estimates of unemployment rate for Garmsar (9.14), Semnan (9.84), Damghan (11.29), and Shahroud (12.40) in 2016. The more distance from Tehran (the Iranian Capital), the more is the unemployment rate!

Financial fraud detection is a challenging problem due to four primary reasons: the constantly changing fraudulent behavior, the lack of a mechanism to track fraud data, the specific limitations of available detection techniques (such as machine learning algorithms), and the highly dispersed financial fraud dataset. Thus, it can be declared that teaching algorithms are complex. The current study used machine learning techniques, including support vector machine regression and boosted regression tree, to detect financial fraud in the Iranian stock market. The findings indicated that the boosted regression tree machine model has the lowest RMSE. Furthermore, concerned with the sensitivity value of the models, the boosted regression tree model has the highest sensitivity in the sense that they had correctly detected the absence of financial fraud Tehran Stock Exchange market the Tehran Stock Exchange market. The boosted regression tree has the highest kappa coefficient indicating the appropriate performance of this model compared to other models used in the research.

The population of fish stocks is constantly exposed to threats and invasion and finally, the problem of extinction due to some reasons. In this study, in order to estimate the technical efficiency of the Kilka fishing industry, the activities of 30 fishing fleets were investigated by the random border production function method and with the proposed maximum likelihood model of Battese and Coelli. Four independent variables used in this research are the number of vessels, the number of manpower, the fishing capital, and the number of nets. The factors selected as affecting the inefficiency are the fishermen’s age, the fishermen’s education level, the fishermen’s second job, the catch manager’s working record, the catch manager’s education level, the number of stormy days and The number of fishing hours. Error terms (deviations from the efficient boundary) have been divided into two elements as disturbance and inefficiency. The estimation of the technical efficiency is based on the final model at different levels based on which the highest technical efficiency in this group is 0/97 and the lowest is0/46. The mean technical efficiency of the exploiters is 0/87. The range between the minimum and maximum efficiency has been calculated as0/41. The results showed that efficiency decreased by decreasing stormy days and increasing fishing hours. In contrast, efficiency decreases with the increasing number of stormy days and decreasing fishing hours. It was also found that increasing the level of education of fishermen increases efficiency. The Kilka fishing industry was exposed to various risks, thus in this study, we get to analyze the types of risks such as the effects of the comb jelly (Mnemiopsis leidyi) and weather changes in the Kilka fishing industry.

In this paper, we consider the tangent bundle TM of a Riemannian manifold (M, g) with the Sasaki metric G and using the Cauchy-Kowalevski Theorem, we answer the question of how many analytic statistical structures are there on (TM, G). Also, we study the Ricci tensor of linear affine connections on the tangent bundle TM. In addition, we answer the question of how many Ricci flat affine connections with and without torsion are there on the tangent bundle.

Our work proposes a new numerical method for finding the solution of three-dimensional Volterra-Hammerstein integral equations by using three-dimensional hybrid block-pulse functions and Legendre polynomials. Our integral equation is converted to a system of nonlinear equations. An error bound for the suggested method is established. Eventually, some numerical examples illustrate that our method is feasible and efficient.

Wealth management and financial management behaviors often show emotional needs such as security, acceptance, and success. On the other hand, financial issues change people's knowledge, behavior, emotions, and social relationships. People's behavior differs in how they interact with the cognitive-behavioral factors affecting their wealth management level. In this regard, the present study seeks to explain the role of cognitive-behavioral factors in wealth management by predicting the causal relationships among the constructs of these factors on the wealth management of investors. The research population is active investors in the capital market, and a standardized questionnaire was used to collect data. After conducting the reliability and validity tests of the sample data, the structural modeling approach was used. The results of the structural modeling unraveled that the cognitive-behavioral constructs (financial collage, financial genogram, financial discipline, and financial self-efficacy) have a significant impact on investors' wealth management. In addition, financial knowledge and mental accounting through financial data mining significantly influence investors' wealth management.

The main purpose of this study is to predict the future yield of saffron contracts using a modified quadratic model, which is a library documentary research from the aspect of data collection, and from the aspect of results, it is applied and quantitative research. The time period of the quantitative part is a 5-year period from 2019/03/20 to 2023/03/20 in the form of daily frequency of the Ministry of Jihad, Agriculture and Customs of Iran from the website of the Iran Commodity Exchange, which was collected and the modified second-order model in terms of complexity, from The type of nonlinear polynomial problems that the proposed methods are modelled by coding in Matlab software environment with normal data. Overall, the results indicate that the neural network model has a higher reliance on power compared to the adjusted quadratic model in predicting the saffron contract yield, and the calculation results show that price fluctuations, cash price, transaction volume, and liquidity are the most important in order They have the contractual yield of saffron.

One of the most important challenges facing the evolution of smart cities over the last decade has been the optimization of energy use. Also, artificial intelligence and its algorithms, such as reinforcement learning, have appeared as a catalyst in the process of designing and optimizing smart services in the urban space, and in this issue, the generation and use of energy are critical factors. Using a technique based on reinforcement learning, the authors of this research successfully decreased and optimised smart city energy use. The suggested reinforcement learning method uses a collection of agents to cooperate together to achieve a shared objective using an optimum energy distribution policy (value action function). Agents' ability to cooperate to optimise energy use and save expenses is only one example of the many advantages that will accrue from their concerted efforts. To determine the worth of each option, the suggested technique looks at energy consumption data and the degree to which the option has been implemented in the past. This architecture ensures the device achieves an optimal balance between its energy footprint and the dependability of its communications. The simulation findings reveal that the yearly energy consumption in the smart city may be reduced by more than 35%-40% via the optimization of energy consumption using the proposed reinforcement learning approach.

Profit forecasting by management is one of the mechanisms through which management provides information about the company's future profitability status. This research has been conducted with the aim of providing a model to identify factors affecting the accuracy of management profit forecasts in Iranian companies on the Tehran Stock Exchange.his research is applied in terms of purpose and correlational in terms of nature. In order to achieve the goal of the research, 131 companies were selected from among the companies admitted to the Tehran Stock Exchange during the years 2010 to 2019 by systematic elimination and considered as the main sample. Bayesian averaging and dynamic averaging approaches have been used to determine the optimal model. Based on the results of BMA, TVP-DMA, TVP-DMS, BVAR and OLS models to identify the most important influencing variables on the accuracy of management profit forecast, the BMA model had the highest efficiency. Based on this, 50 identified variables affecting the accuracy of management profit forecasting were entered in the Bayesian averaging model (in 5 audit categories; financial ratios; macroeconomic variables; corporate and managerial governance indicators) and based on previous probabilities, 13 variables were identified as important variables. These variables include management profit forecasts of the past period; Profit or loss of the company; discretionary accruals; type of industry; the existence of the audit committee; Financial Leverage; operational debt leverage ratio; return on equity; economic uncertainty; economic growth fluctuations; swelling; Accrued profit management and management ability. According to the results of the research, several factors influence the management profit forecast, and this indicated the multi-dimensionality of the management profit forecast, and this indicates the fact that managers need to have a systemic perspective in order to reduce the management profit forecast error.

In this manuscript, we introduce $LG^{c}$-fuzzy Euclidean topological space in which $L$ denotes a completely distributive lattice with a countable subset dense in it. We use the structure of $LG$-fuzzy topological space $(X,\ \mathfrak{T})$, which $X$ is an $L$-fuzzy subset of the crisp set $M$ and $\mathfrak{T}: L^M_X \to L $, is an $L$-gradation of openness on $X$ to define the fundamental concepts of $LG$-fuzzy analysis such as $LG$-locally compactness and $LG$-paracompactness and prove several theorems. In consequence, we show that any second countable Hausdorff $LG$-fuzzy topological space that is $LG$-locally compact is $LG$-paracompact. Also from any given metric $\rho$ on a crisp set $M$ and $L$-fuzzy subset $X$ of it, we construct an $L$-gradation of openness $\mathfrak{T}_{\rho}$ on $X$ and obtain $LG$-fuzzy topological metric space $(X,\mathfrak{T}_{\rho} )$. Finally, we prove an interesting theorem: Every $LG$-fuzzy topological metric space, is $LG$-paracompact.

Reliability analysis is crucial for understanding the performance and failure characteristics of lifetime systems. This paper presents a comprehensive study on the reliability analysis of lifetime systems using the Weibull distribution. The Weibull distribution, known for its flexibility in modeling failure times, provides a versatile framework for capturing diverse failure behaviors. A useful model for redundancy systems is proposed in this paper. The model consists of $(n+1)$ components, where n components serve as spare parts for the main component. The failure rate of the working component is time-dependent, denoted as $\lambda (t)$, while the failure rates of the non-working components are assumed to be zero. Whenever a component fails, one of the spare parts immediately takes over its role. The failed components in this model are considered non-repairable. To analyze this model, we establish the differential equations that describe the system states. By solving these equations, we calculate important parameters such as system reliability and mean time to failure (MTTF) in real-time scenarios. These parameters provide valuable insights into the performance and behavior of the system under study. By employing the Weibull distribution and the proposed model, this paper contributes to enhancing the understanding of reliability analysis in lifetime systems and enables the estimation of important reliability parameters for practical applications.

This study aimed to explain the pattern of user trust in social network-based marketing. This research is applied in terms of purpose, and exploratory in terms of approach. Social network users in the city of Tabriz were considered as a community and among them, 400 people were selected as a statistical sample based on a simple random sampling method. The main data collection tool was a closed and researcher-made questionnaire consisting of 42 items that were designed based on the initial conceptual model. SPSS, LISREL and smart-PLS software were used for descriptive and inferential analysis. Finally, the research results led to the explanation of the pattern of user trust in social network-based marketing (based on the paradigm model structure) and the model hypothetical relationships in a large community were tested and confirmed.

The purpose of this research is to investigate the effectiveness of audit firm rotation on audit quality in companies listed on the Tehran Stock Exchange using Pearson's linear torque model. In order to achieve the purpose of the study, using the method of screening or systematic removal of the number of 90 companies admitted to the Tehran Stock Exchange, during the period of 2016 to 2021, selection and panel or combined data related to 630 companies-years from the database of the organization The stock market and securities were collected. This research is categorized as descriptive-correlation research in terms of its practical purpose, and historical or post-event-field research in terms of time. The results of the statistical analysis show that there is a direct relationship between the mandatory rotation of auditors and audit quality. In addition, the study shows that the companies that have changed their external auditors during the research period have a higher average "audit quality" and a lower dispersion coefficient of "audit quality" compared to the competing group or companies subject to the retention of independent auditors. They were. The conducted research showed that the coefficient of variance of the "audit quality" factor was higher for the business owners whose independent auditors were subject to mandatory rotation compared to their competitor group or the business owners whose independent auditors were not subject to mandatory rotation.

A continuous operator $T$ between two Banach lattices $E$ and     $F$ is called almost order-weakly compact, whenever for each almost order bounded subset $A$ of $E$,  $T(A)$ is a relatively weakly compact subset of $F$. We show that the positive operator $T$ from  $E$ into a  Dedekind complete Banach lattice $F$  is almost order-weakly compact iff  $T(x_n) \xrightarrow{\|.\|}0$ in $F$ for each disjoint almost order bounded sequence $\{x_n\}$ in $E$. In this manuscript, we study some properties of this class of operators and its relationships with the others known classes of operators.

It is well known that the solution of fractional models proved to be a powerful tool in studying various problems which appear in the sciences of real life. In view of the fact that economic applications are accelerating at an amazing pace, and the large number of modeling in this speciality, it has expanded the number of problems. So, our contribution is based on finding generalized solutions of a fractional differential equation known for their applications in microeconomics and finance and creating an algorithm which allows us to estimate the coefficients of this type of equation. And to really illustrate our results we will choose a model known in the stochastic literature by COGARCH but with fractional derivative, to demonstrate the asymptotic behavior of the estimators, including the impact of fractional order on the space of stochastic differential equations.