Education is a continually developing activity, it shapes the way an individual develops their attitudes, thoughts and behavior. Education is not just about being literate but it is an overall development of the person in every aspect of their lives. A society's educational system can be greatly linked to its culture as the culture that one is in have an affect on the type of curriculum the institutions will develop in order to cater to every individual of that particular culture. Education moulds and shapes a society and it is influenced by the culture of the particular country or society. The educational system acts as a point of reference for the society's needs and demands. The principles that dominate this article is culture and education are interrelated and interconnected. Every educational paradigm is influenced by the culture of the society in which it operates. This essay underlines the extensive connection between culture and education. As a result, the goal of this essay is to depict these features from a Philosophical-Psychological approach.

Artifacts are ubiquitous and influential in our world, but their nature and existence are controversial. Several theories have been proposed to explain the ontology of artifacts. Drawing on Popper's theory of three worlds, this paper suggests a metaphysics for artifacts along the line of a critical rationalist (CR) approach. This theory distinguishes between three realms of reality: the physical world (World 1), the mental world (World 2), and the world of objective knowledge (World 3). The paper argues that artifacts have different ontological components that correspond to these three realms, and that each component is real and causal. The paper shows how this perspective can account for the intentional and functional aspects of artifacts, as well as their dependence on plans that influence different realms of reality. The paper explains how this pluralistic ontology, compared to the rival theories, enables one to explain the relevant ontological problems of artifacts. The paper also explores how this proposal can lead to a research program encompassing a broader range of technologies, such as social artifacts. In sum, the paper suggests that Popper's three worlds theory provides a rich and comprehensive framework for understanding the metaphysics of artifacts.

Queuing systems play important role on modeling and interpreting different issues such as information technology, transportation, supply change management, and traffic control at industrial and non-industrial systems in current world. One of more complex but applicable forms in queuing systems, is queue networks which are important in order to establish proper system and optimize them. So, available approaches deal with to analyze situations or decide optimal size ofsystem’s variables only base on one goal, while it is logical to consider various goals for determining optimal system, thus optimizing base on this, leads to system being more realistic. Therefore in this paper, we offer one multi-objective optimization approach base on desirability function in order to solve queue network’s problems. Another important intended concept in proposed approach, is making Robust process which refers to low sensitivity of goals to uncontrollable variables (noise factors). Features of proposed approaches were mapped through giving numerical examples.

One of the challenging issues in today’s competitive world for servicing companies is uncertainty in some factors or parameters that they often derive from fluctuations of market price and other reasons. With regard to this subject, it would be essential to provide Robust solutions in uncertain situations. This paper addresses an open vehicle routing problem with demand uncertainty and cost of vehicle uncertainty. Bertsimas and Sim’s method has been applied to deal with uncertainty in this paper. In addition, a deterministic model of open vehicle routing problem is developed to present a Robust counterpart model. The deterministic and the Robust model is solved by GAMS software. Then, the mean and standard deviations of obtained solutions were compared in different uncertainty levels in numerous numerical examples to investigate the performance of the developed Robust model and deterministic model. The computational results show that the Robust model has a better performance than the solutions obtained by the deterministic model.

Reviewing the literature, we observed that there is no mathematical model including Dual PBB Structure in University. The purpose of this paper is to construct a PBB model for university so that the budget is allocated not only to plans based on their priorities, but also to faculties based on approved student per Capita. Considering the various criteria in the university system and because of stochastic uncertainties in the problem parameters, led to designing a Goal Programming model of Robust PBB. A significant point, is to use performance Indicators-calculated based on data envelopment analysis approach (DEA) determined the importance coefficient for each educational groups in order to allocateing budget. In addition, the weights of Goals and the priority of each plan were determined using some paired comparison questionnaires completed by experts. The PBBGP model has 5 goals,  1627constraints and 1236 decision variables. The results of models solution- that are presented on two macro and Operational Levels- and simulation of models, Demonstrate high level capabilities of RPBB model in response to the uncertainty in the parameters of problem and also managing the level of decision risk. Because of Partial allocation of the approved budget for the University, by attention to the results from solving the model and simulation of Robust model, Decision makers can according to received budget has been allocated the budget to programs and faculties.

Federated Learning enables aggregating models trained over a large number of clients by sending these models to a central server, while data privacy is preserved since only the models are sent. Federated learning techniques are considerably vulnerable to poisoning attacks. In this paper, we explore the threat of poisoning attacks and introduce a game-based Robust federated averaging algorithm to detect and discard bad updates provided by the clients. We model the aggregating process with a mixed-strategy game that is played between the server and each client. The valid actions of the clients are to send good or bad updates while the server can accept or ignore these updates as its valid actions. By employing the Nash Equilibrium property, the server determines the probability of providing good updates by each client. The experimental results show that our proposed game-based aggregation algorithm is significantly more Robust to faulty and noisy clients in comparison with the most recently presented methods. According to these results, our algorithm converges after a maximum of 30 iterations and can detect 100% of the bad clients for all the investigated scenarios. In addition, the accuracy of the proposed algorithm is at least 15.8% and 2.3% better than state of the art for flipping and noisy scenarios, respectively.

In this paper, the specific trait of Persian signatures is applied to signature verification. Efficient features, which can discriminate among Persian signatures, are investigated in this approach. Persian signatures, in comparison with other languages signatures, have more curvature and end in a specific style. An experiment has been designed to determine the function indicating the most Robust features of Persian signatures. To improve the performance of verification, a combination of shape based and dynamic extracted features is applied to Persian signature verification. To classify these signatures, Support Vector Machine (SVM) is applied. The proposed method is examined on two common Persian datasets, the new proposed Persian dataset in this paper (Noshirvani Dynamic Signature Dataset) and an international dataset (SVC2004). For three Persian datasets EER value are equal to 3, 3.93, 4.79, while for SVC2004 the EER value is 4.43.These experiments led to identification of new features combinations that are more Robust. The results show the over performance of these features among all of the previous works on the Persian signature databases; however, it does not reach the best reported results in an international database. This can be deduced that language specific approaches may show better results.

In this study, a Robust two-stage risk-aversion optimization model is proposed for the multi-product relief network design problem. The comprehensive set of decisions for locating and reinforcing relief facilities, inventory planning, and distributing healthcare items has been considered in an integrated manner. Uncertainties of relief facility capacity, relief demand, and the node linkage capacity are considered. Moreover, the weighted average expected loss is considered in the proposed Robust planning model. The efficiency of the proposed model has been evaluated by examining numerical instances. The obtained results indicate the efficiency of the distributionally Robust model compared to the traditional two-stage stochastic model. In addition, the type of ambiguous set and levels of confidence, risk aversion, and adjustment parameters will affect network performance.