Today, most activities and important data are placed on Internet websites, so attempts to intrude into these websites have grown exponentially. Intrusion detection systems (IDS) of web attacks are an approach to protect users. But, these systems are suffering from such drawbacks as low accuracy in detecting new attacks. To tackle this problem, various machine learning methods have been developed in recent years. Since attack requests differ from normal requests slightly, these anomaly detection methods have failed to exhibit good accuracy in new attack detection. In web requests and responses, a great deal of interconnected data is usually moved, and anomaly detection attempts need to consider all these connections, but this is a very complicated task. Thus, some research works on attack detection are confined to the analysis of just URL and a part of the request. This paper presents a new method for web attack detection using seq2seq networks using attention. The method is shown to successfully classify the traffic by predicting the possible responses and calculating differences from real responses of the webserver. The higher accuracy of this method versus similar methods shows that the use of the attention mechanism can cope with the challenge of analyzing long web requests and responses to a great extent. The proposed model exhibited a high result in terms of the specificity criterion when it came to such attacks as SQL Injection and XSS whose success highly depends on the server’ s response. This can be attributed to the inclusion of the link between the request and response in identifying web attacks in the proposed method.

Background and Aim: Because Joint attention provides the basis for learning core skills such as language, social communication, playfulness, mind theory, and behavior theory, it has become a target for therapeutic intervention for children with autism spectrum disorder. Therefore, the purpose of this study is to identify and develop the components of a Joint attention education program with a synthesis research approach and based on the principles of timely intervention for children with autism spectrum disorder. Method: used in this research is qualitative and Synthesis Research. The statistical community of research synthesis in this research includes all articles, theses and studies on Joint attention training for children with autism spectrum disorder. that with that with the keywords of Joint attention training,Joint attention program and autism spectrum disorder through search engines and English-language scientific resource databases including Pup Med, Embase, PsycINFO, ProQuest, Google Scholar, Science Direct, Springer and the keywords in addition to the above keywords of Joint attention training and Joint attention program were searched through Magiran and SID Persian language databases. . Among these, there are 34 research articles in English and Persian, which were selected from among 60 published articles in the period from 2010 to 2021. Results: After analysis, coding and classification, the research results showed indicators. The components of Joint attention training for children with autism in the age range of 3 to 5 years have been extracted based on the components arising from the study of theoretical foundations and research background in the form of research synthesis. Accordingly, Joint attention training based on seven basic categories, including attention recognition, initiation of Joint attention,Response to shared attention,Initiation of behavioral requests,Response to social interaction,The beginning of social interaction and response to behavioral requests is solid, and Joint attention exercises and training activities can be designed, implemented and evaluated based on these components. The content validity of the program in the Waltz and Basel method is generally equal to 0. 84, which indicates the appropriate and acceptable content validity for this program.

Introduction: Autism spectrum disorder affects communication skills and a person's appropriate response to the outside environment. The present study was conducted with the aim of determining the effectiveness of the Identiplay method on improving Joint attention in autistic children. Method: The research method was a single case study with A-B design and follow-up. From the statistical population of children with autism spectrum disorder in the rehabilitation center of Tehran, three children were selected as the study sample using the purposeful sampling method. The tool for collecting information in this research was Gilliam's autism diagnosis test (2006) and the identity play protocol based on the approach of Phillips and Biwan (2007). To analyze the data, graph analysis methods, reliable change index, clinical significance, recovery percentage of POD, PND indices and calculation of stability of trend and median were used. Results: The results of the research showed that the Identiplay method was effective in improving Joint attention in autistic children. Identity Play significantly improves the Joint attention of children with autism spectrum disorder. Conclusion: Considering the effectiveness of the identity bridge method on autistic children, it is suggested that this method be used as a new and complementary approach in the field of education and rehabilitation of children with autism spectrum disorder along with other major therapies.

Robots, especially humanoid robot are going to be used in various fields, among them therapy fields. A new approach was emerged which utilized robots to improve the social skill, not physical skill. This approach was dealing with three challenges: firstly, autism creates a special condition that the patient dose not easily accept a therapist, so in the first step the researcher had to find a solution for interacting with autistic children, the second challenge was selecting appropriate algorithms and methods for eye tracking and head pose detection with these children who have inaccurate eye center localization as well. The third one included the treatment and research process which should not over stimulate the children. To overcome the mentioned challenges, a real time eye gaze tracking algorithm with high robustness as well as a fuzzy decision making tree for interacting the medial and engineering information were utilized during the treatment that were implemented on a humanoid robot. Whereas none of the commercial hardware used.

Aims: According to Extreme Male Brain (EMB) theory in autism, the strong and weak points of cognitive reactions of autistic people are milder in males. Joint attention, as a compromiser of subsequent opportunities for the development of social cognition, is disturbed in autistic people.This study aimed to investigate this cognitive function in male and females.Method: Fifty seven (32 female) students of Shahid Beheshti University, based on available sampling in year 2013-2014were recruited in the study. Using eye tracking, the behavior and fixation of eye movements as well as the results of computer tasks of Joint attention were measured.Results: The results of one and two ways variance indicated that gaze patterns of males and females are different.Also, duration time for looking at the target and face in males was longer than females.Conclusion: In conclusion, our evidence supported the theory of extreme male brain theory indicating lower performance of Joint attention in males than females.

Objectives: Joint attention is one of the most important prerequisite of language and social development. There are two types of Joint attention, Initiating Joint attention and Responding to Joint attention. This study examined the development of responding to Joint attention in typically developing children in 8-30 month.Methods: This study was cross-sectional.61 children (40 female and 21 male) were examined in age 9, 12, 15, 18, 24 and 30 month. Tasks of Joint attention scale of Early Social Communication Scales (ESCS) were used to assess children. Colmogrov-Smirinov and Kruskal-Wallis were used for data analysis and mean scores were computed for all groups.Results: Data analysis showed that there was significant difference between mean ranks of groups.Children scores had an increasing pattern across 9 to 30 month.Discussion: Results of this study indicated that responding to Joint attention is developing from 9 to 30 month by considering the individual differences between children in every group.

Alarm systems are essential in safe operation of industrial plants. Since many process variables are interacting with each other, so in this paper, an approximate method is introduced to design and analysis of a multivariate alarm system. In this method, the alarm system is designed base on Joint indices. The Joint FAR and Joint MAR are defined for a m-variable alarm system thanks to multivariate Markov scheme. In proposed method, the alarm Joint indices are defined by solving a Linear Programing (LP) optimization problem. By defining Joint indices, tuning of the alarm parameters (like, threshold and etc. ) can be done by these indices instead of correlation analysis. In this paper, penalty scenario and Genetic algorithm are used for alarm generation, and parameter optimization in Tennessee Eastman (TE) Process. The results of proposed method are compared with other methods.