مطالب

A recommendation system is a system that, based on a limited amount of information provided by users as well as the feedback given to goods, persons, and locations by other users, provides appropriate suggestions to the user. Today, with the large number of physicians and specialists, it seems necessary to have a system for identifying the right specialist and experienced physician for the patient. We present in this study a system for medical recommendations that analyzes physicians and specialists. It uses collaborative filtering and scores provided by other users to suggest physician recommendations according to the area of expertise of the physician. Research conducted and evaluation of results show that this system can successfully recommend a specialist doctor to the user in 90% of cases.

Social network research analyzes the relationships between interactions, people, organizations, and entities. With the developing reputation of social media, community detection is drawing the attention of researchers. The purpose of community detection is to divide social networks into groups. These communities are made of entities that are very closely related. Communities are defined as groups of nodes or summits that have strong relationships among themselves rather than between themselves. The clustering of social networks is important for revealing the basic structures of social networks and discovering the hyperlink of systems on human beings and their interactions. Social networks can be represented by graphs where users are shown with the nodes of the graph and the relationships between the users are shown with the edges. Communities are detected through clustering algorithms. In this paper, we proposed a new clustering algorithm that takes into account the extent of relationships among people. Outcomes from particular data suggest that taking into account the profundity of people-to-people relationships increases the correctness of the aggregation methods.

In recent years, we have seen an increase in the production of films in a variety of categories and genres. Many of these products contain concepts that are inappropriate for children and adolescents. Hence, parents are concerned that their children may be exposed to these products. As a result, a smart recommendation system that provides appropriate movies based on the user's age range could be a useful tool for parents. Existing movie recommender systems use quantitative factors and metadata that lead to less attention being paid to the content of the movies. This research is motivated by the need to extract movie features using information retrieval methods in order to provide effective suggestions. The goal of this study is to propose a movie recommender system based on topic modeling and text-based age ratings. The proposed method uses latent Dirichlet allocation (LDA) modelling to identify hidden associations between words, document topics, and the levels of expression of each topic in each document. Machine learning models are then used to recommend age-appropriate movies. It has been demonstrated that the proposed method can determine the user's age and recommend movies based on the user's age with 93% accuracy, which is highly satisfactory.

In computer networks, introducing an intrusion detection system with high precision and accuracy is considered vital. In this article, a proposed model using a deep learning algorithm is presented and its results are analyzed. To evaluate the performance of this algorithm, NSL-KDD, CIC-IDS 2018, UNSW-NB15 and MQTT datasets have been used. The evaluation criteria include precision, accuracy, F1 score, and, readability. The new approach uses a hybrid algorithm that includes a convolutional neural network (CNN) to extract general features and long-short-term memory (LSTM) to extract periodic features that are in the form of a layer. are cross-connected, it is introduced to detect penetration. This algorithm showed the highest known accuracy of 99% on the NSL-KDD dataset.  It has reached 97% in all criteria in UNSW-NB15, 96% in all criteria in CIC-IDS 2018, and also, in MQTT for three abstraction levels of features, i.e. packet-based flow features, unidirectional flow, and The two-way flow has reached above 97%, which shows the superiority of this algorithm.

SUBJECT AND OBJECTIVES : The source of sovereignty and obedience is Allah, the Almighty. Any obedience to others but Allah is rejected and considered as oppression unless it be along with His sovereignty and through His permission, such as the Guardianship (wilayah) of prophets and Divine Authorities (wali). The question arises here that what are the reasons for the compulsion of obedience or forbidding opposition to the Prophets. METHOD AND FINDING : This paper, was conducted with the method of qualitative research and documentary review. Accordingly, the author has examined the most important proofs of the obligation to follow the commands and instructions of the prophets based on the Quranic sources of narration and the covenants. CONCLUSION : This study argues that its evidences are based on both Sharia (Divine Law) and intellect; because if everyone acts according to his own ideas, as wherever the words of the Prophets agreed with his carnal desires, he would act according to them and if the words of the Prophets were not in accordance with his intentions and desires, he would not pay attention to them and so oppose him, surely such a person is not a follower of the Law of Religious, even though he seems to be a believer. In fact, he is really a hypocrite or ignorant of the truth of religion, which in both cases lacks faith.

SUBJECT AND OBJECTIVES : Due to the outbreak of a virus from the corona family called Covid-19, which has infected millions of people around the world, the subject of the possibility or impossibility of Government responsibility for infectious diseases is a global issue. It is the Government's duty to act in order to improve human life, and this is in accordance with its existential philosophy. This debate originates from the capabilities and powers that are monopolized by Government. It is believed that, by resorting to the authority and discretions of a conventional Government, it can prevent the spread of many infectious diseases to a large extent and in case of negligence in performing tasks, must be liable. This is the initial question: Why should the Government be liable for infectious disease which it had no role in creating it? METHOD AND FINDING : In this paper, by descriptive and analytical method and by collecting library resources, the continuity and relation between the responsibility of the Government and infectious diseases will be discussed. The Right to Life and the Right to Health are the basis of legal authority to intervene in the field of infectious diseases. CONCLUSION : Public Law and Human Rights has a special view of infectious diseases and some statutes provide for Emergency Situations. Governments are committed to taking the most effective measures possible to prevent spread of infectious diseases. According to the findings of this study, during Corona, these liabilities for the Government can be enumerated: Identification, Determining the liable authorities and institution, Education, Responsibility for prevention and treatment, Establish and expand insurance protections, Compensation for victims, Judicial and political Responsibility. In Iran, it is necessary to design a comprehensive system for exceptional situations such as pandemics.