In this research, a method based on the classification and Prediction of the neural network to determine the location and orientation of cracks in pipes is presented. For this purpose, first, the finite element method is used to model wave propagation and crack modeling in different locations and orientations. In this regard, two types of longitudinal and torsional guided excitation waves have been used. The obtained signals are processed to calculate the appropriate characteristics. In the present study, reflection echoes were measured، and five features were extracted at six levels from discrete wavelet decomposition of raw signals. Selected properties of the signals are processed to limit the size of the neural network model without losing information. For this purpose, the firefly algorithm method was used and fed to an artificial neural network that predicts the location and orientation of the crack. In this study, conventional multilayer perceptron diffusion networks have been used. According to the obtained results, it is observed that the proposed method shows good accuracy in predicting the location and orientation of the crack, and the percentage of neural network errors is less than 7%.

Efficient distribution of service requests between fog and cloud nodes considering user mobility and fog nodes’ overload is an important issue of fog computing. This paper proposes a heuristic method for task placement considering the mobility of users, aiming to serve a higher number of requested services and minimize their response time. This method introduces a formula to overload Prediction based on the entry-exit ratio of users and the estimated time required to perform current requests that are waiting in the queue of a fog node. Then, it provides a solution to avoid the predicted overloading of fog nodes by sending all delay-tolerant requests in the overloaded fog node’s queue to the cloud to reduce the time required for servicing delay-sensitive requests and to increase their acceptance rate. In addition, to prevent requests from being rejected when the mobile user leaves the coverage area of the current fog node, the requests in the current fog node’s queue will be transferred to the destination fog node. Simulation results indicate that the proposed method is effective in avoiding the overloading of the fog nodes and outperforms the existing methods in terms of response time and acceptance rate.

Chromosomal Defects are one of the commonest congenital Defects responsible for fetal and neonatal death and handicap. The traditional method of screening for Down’s syndrome has been maternal age where amniocentesis or chorionic villous sampling is offered to women aged 35 years or more. This results in the need for an invasive test in 15-20% of pregnant women with a detection of less than half of the fetuses with Down’s syndrome, because the majority of affected fetuses come from the younger age group. A more effective method of screening is based in the combination of: maternal age, a maternal blood sample for the measurement of the placental products of free b-hCG and PAPP-A and an ultrasound scan at 11-13 weeks; to measure the collection of fluid behind the fetal neck (nuchal translucency), to examine the fetal nose and palate, to measure the fetal heart rate and to assess the flow of blood across the tricuspid valve of the fetal heart and the ductus venosus.This new method of screening reduces dramatically the number of women requiring an invasive test from about 20% to less than 3% and at the same time increases the detection rate of Down’s syndrome and other major chromosomal abnormalities from less than 50% to more than 95%.There are several other benefits of the 11–13 weeks scan as well including: accurate dating of the pregnancy, early diagnosis of many major fetal abnormalities, and the detection of multiple pregnancies with reliable diagnosis of chorionicity, which is the main determinant of the outcome in multiple pregnancies Although there are some markers at second trimester (sonographic and biochemical) to assess risk of chromosomal abnormalities but detection rate is less than first trimester and also early diagnosis ( in first trimester) and early termination is much better regarding patient’s preferences, less complications and less psychological stress.

A study of various deficiencies observed in the process of pile carpet weaving in the Province of Kashan has revealed that the most important Defects are: unevenness, crimpled sides and erroneous application of the cartoon. Improving weavers' skills will have a significant effect on reducing these Defects.Therefore, weavers should be given educational advice on recognizing the capabilities of looms and other rug weaving equipment, the quality of raw materials and their harmonious use, the correct way of weaving flatwoven rugs, the manner of interlacing the wefts, and daftin-zadan (pounding an iron comb on the weft).

One of the important issues in understanding hadith is to consider the defective traditions and distinguishing them from sounds traditions. Knowing defective traditions needs exact information and necessary expertise in the knowledge of hadith, and only the specialists in the science of hadith and scholars who are completely familiar with the documents and texts of traditions can distinguish the defective traditions. In this article the different kinds of the causes of hadith and the way of knowing them have been discussed, and some examples of defective traditions are given. The following issues are among the signs of defect in hadith:1. It is narrated only by one person.2. The tradition apparently has a linked chain of transmitters, but during the study it becomes clear some of the transmitters have been omitted.3. The tradition is apparently has connected chain of transmitters, but in fact it is unconnected and connected only in form.4. The text of the hadith is mixed with the text of another tradition or the document of one hadith comes within the document of another tradition.5. The narrator while relating the hadith errs and corrupts the hadith, for example he adds a word or a sentence to the tradition.6. Dividing the tradition in cases where the omitted part and the mentioned part share the same meaning.

In this paper, we have extended our literature survey with experimental implementation. Analyzing numerous Artificial Intelligence (AI) techniques in software engineering (SE) can help understand the field better, the outcomes will be more effective when used with it. Our manuscript shows various AI-based algorithms that include Machine learning techniques (ML), Artificial Neural Networks (ANN), Deep Neural Networks (DNN) and Convolutional Neural Networks (CNN), Natural Language Processing (NLP), Genetic Algorithms (GA) applications. Software testing using Ant Colony Optimization (ACO) approach, predicting software maintainability with Group Method of Data Handling (GMDH), Probabilistic Neural Network (PNN), and Software production with time series analysis technique. Furthermore, data is the fuel for AI-based model testing and validation techniques. We have also used NASA dataset promise repository in our script. There are various applications of AI in SE, and we have experimentally demonstrated one among them, i. e., software defect Prediction using AI-based techniques. Moreover, the expected future trends have also been mentioned, these are some significant contributions to the research