The delinquent behaviour among adolescents is growing among school children everywhere in the world today. Although efforts have been taken to understand the reasons for this trend and to find a mechanism to control this situation, the number of bullying and intimidation among school children is increasing significantly. Although many researches indicated high rate of violent behaviour in urban than suburbs, low rate of violent in Shah Alam, a metropolitan city close by Kuala Lumpur encouraged the researchers to explore the causes of this situation. This research found the religiosity as an imperative reason for decreasing anti-social behaviour among adolescents in Shah Alam. The correlation between religiosity and law rate of violence was tested in this research based on theory of spiritual therapy for different type of addiction. An instrument consists of 103 questions prepared based on the Muslim Religiosity- Personality Inventory (MRPI) was used to collect the data. 107 secondary school Muslim students (58 boys, 49 girls) aged 13 to 14 years in Shah Alam participated in the data collection. The SPSS version 20.0. was used to analyse the data. High rate of religiosity among students in Shah Alam was found as controlling mechanism in the presence of potential reasons that encourage anti-social behaviour. The researchers, therefore, concluded invasive relationship between religiosity and delinquent behaviour. The researchers recommend introducing moderate religiosity to control anti-social behaviour among young people

The article is focused on the problem of teaching bilingual children. To solve this issue, the authors use the vast experience in addressing it in the Russian and British pedagogical thought in the late 20th and early 21st centuries. The authors believe that the comparison of diverse approaches makes it possible to use the ideas of various researchers for resolving the current issues of teaching bilinguals. Besides, the authors of the article try to present the key recommendations and learning approaches for teaching a second language to preschool children. The article stresses the importance of foreign language learning. The authors consider that it is very important to pay attention to the peculiarities of mastering foreign languages and the influence of the bilingual environment on the mental, speech, and personal development of the child. The article further analyses the main approaches to language learning and gives practical recommendations to bilingual children’s parents for teaching a second language. Finally, the article touches upon the problem of learning content. In the authors’ opinion, the latter should be as close as possible to children\'s understanding. It should be noted that early learning of a foreign language has many advantages in the modern multicultural world. More and more parents want to raise their children as bilinguals, to allow them to communicate in several languages. The authors hope that the recommendations given in the article will help parents of bilingual children and teachers find their approach to teaching a child a second language.

The aim of this research is to build up a regression model of solar irradiation using the Multivariate Adaptive Regression Splines (MARS) technique at Kulluk local region of Turkey.This research has explored a convenient prediction model for continuous response variables (Ed, Em, Hd and Hm) through a well-known data mining algorithm (MARS). In order to estimate Ed, Em, Hd and Hm,fourcontinuous predictors namely ESLOTEM, ESLOANGREF, OTHERSLOSS and COMPVSLOSS are involved. Four prediction models constructed by MARS algorithm are obtained with respect to the smallest Generalized Cross-Validation (GCV) where means of penalty are defined as 1 and the backward pruning method for the package “earth” of R software is used.

This paper reviews extant literature and political and technical discourses on the role played by financial reporting (and broadly the accounting system) on periods of economic and financial crises. Previous literature, both theoretical and empirical, shows that financial reporting should have low importance in causing an economic crisis. Accounting is probably just a secondary causal factor that amplifies (or mitigates) a crisis. Still, the body of knowledge of how this comes to be is extremely limited. Likely we may have not been asking the full set of relevant questions. In Addition, opportunities for future research on the role of accounting during periods of crisis are presented and framed under a setting that combines economic intuition and accounting theory and history.

This study aims at identifying the level of application of al-Zarnuji\'s ethical concepts among the students in Pondok Pasentren institutions in East Java Indonesia. This quantitative study utilizes the survey research design of stratified random sampling, which included a number of 391 Pondok Pesantren students from all districts in Gresik, Indonesia. The instrument that was applied for survey was developed through a literature review and three experts later validated the content. The findings indicated that the application level of al-Zarnuji\'s ethical concept is at high level (mean = 3.99; SD = 0.10) while implication shows that the ethical application should be given particular attention by all related parties in Pondok Pesantren as well as other educational institutions as emphasized by the Islamic education main goals. It is also seen that teachers need to put effort on finding new ways in developing ethical application to a maximum level.

In the work, on the basis of results of XRD, IR spectroscopy, and SEM/EDS investigations, the process of phase transformations proceeding during temperature treatment of wastes of plaster molds from the ceramic industry has been considered. It has been established that the dehydration process of secondary CaSO4·2H2O occurs in the direction of the formation of secondary CaSO4·0.5H2O and CaSO4 at a higher temperature than the dehydration of primary CaSO4·2H2O. The shift of the dehydration temperature is ~100-150 °C. Treatment at 900–1000 °C is not accompanied by the formation of estrich gypsum and is characterized by defect formation in the lattice of CaSO4. On the basis of secondary a soft-burned (200–300 °C) and a hard–burned (1000 °C) gypsum binders, and their mixtures, new gypsum materials possessing good strength properties are obtained without using primary gypsum binders.

Finite Element Analysis (FEA), with its rapidly growing computer capabilities, is the most powerful instrument to solve thermal mechanisms. The system was originally used in applications where safety aspects of aerospace and nuclear power plants are particularly critical, then generalized to other heavy sectors, such as the construction of boats, automobiles, and aeronautical sectors. The FE methodology is consistently developed, enabling researchers to analyze the welding process in depth. In the model, the closely connected heat transmission, the development of micro-structures and the mechanical performance. This study depicts the analysis of Wire arc Additive Manufacturing on a simple cuboidal plank using welding and behavior of heat patterns emerging along the welded path. Since WAAM product needs post processing due to resulting residual stresses, various ways to diminish the residual stresses and distortion are also discussed after running the simulation and understanding heat affected regions along the welded path.

Digital textile printing technology has been considered the preferred textile printing technology since 2003, when production digital textile printers were first introduced at ITMA (International Exhibition of Textile Machinery) in Birmingham, UK. However, in 2021, 18 years later, this technology is utilized in fewer than 10% of the entire textile printing industry. In this document, we aim to summarize the state-of-the-art of the digital textile printing industry and to predict its future trajectory.

In the current scenario, high accuracy and quality are not only expected but also a minimum of production time. To do this, process parameters must be varied as required and requires knowledge of the optimal input parameter values for optimizing the objective. Electro-Discharge Machining (EDM) is a non-conventional electro-thermic process, where electric power is utilized to create an electric spark. The thermal erosion of the workpiece due to the spark discharge results in the material being removed. EDM\'s mechanism includes electric dissipation, plasma generation, very high-temperature creation in a very short period (μs), high pressure, severe thermal disruption, etc. It is incredibly hard to understand because of the complexity of the process. Therefore, it is vital to model the process to understand the process and determine the impact of different process parameters. In this study, the modelling of the EDM process using the Finite Element Method (FEM) software ANSYS 19.2 was attempted.

Knee osteoarthritis severity grading from plain radiographs and magnetic resonance (MR) images is of great significance in the diagnosis of osteoarthritis (OA). Recently, deep learning had a great impact on improving the Kellgren and Lawrence (KL) grading scheme of Knee osteoarthritis KOA using models that acquire the contextual features spontaneously without the need for any conventional high computational spatial configuration modeling. In this study, we review the state-of-the-art deep learning methods that enhanced the knee osteoarthritis severity KL grading. Pre-trained models such as ResNet18, VGG, DenseNet, Convolutional Siamese neural network, ResNet34, Squeeze-and-excitation ResNet (SE-ResNet) were found to be employed to extract valuable data for clinical images in the surveyed papers. The survey concludes that some very significant sophisticated deep learning methods were employed in some studies to grade KOA, which may also work on grading other diseases.

The paper deals with the development of education in Montenegro from its very beginnings until 1918, the year that saw the creation of the Kingdom of Serbs, Croats and Slovenes, which also included the Montenegrin state. By analysing the development of education chronologically, the study provides an overview of such development over the course of several periods in history: the Middle Ages, Renaissance humanism, the struggle for liberation from the Ottoman rule and the creation of the state (principality and kingdom) during the Petrović dynasty, followed by a review of the state of education at the time of the Austro-Hungarian occupation of Montenegro during the First World War. Using the historiographical method, the method of theoretical analysis and evaluation of available sources, the aim of this paper was to look at the schooling system of Montenegro in the specified period as credibly and realistically as possible, as well as to show how school and literacy played an important and irreplaceable role in development and enlightenment of the entire Montenegrin population.

The speed of technology development demands digital skills from each member of society. 10% of citizens in the EU lack such skills. Exactly as many (or 10%) are adult citizens of Latvia that have limited digital skills . That means - the digital climate has forced pensioners to learn to pay with money digitally and to adapt to new forms of media communication that take place via the use of a screen.\nThe purpose of the paper is to investigate whether seniors in Latvia have adapted to the digital environment. To determine this, we used qualitative survey research. As a control area of this study 68 participants of the survey were interviewed – all seniors – to investigate their experience with digital money transactions and in situations of media use.

Recently, Convolutional neural networks (CNN) have shown a growth due to their ability of learning different level image representations that helps in image classification in different fields. These networks have been trained on millions of images, so they gained a powerful ability of obtaining the rightful features from the inputted images, which results in accurate classification. In this paper, we explore the feasibility of transfer learning based convolutional neural networks for the diagnosis of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Features are transferred from a CNN trained on a source task, i.e., ImageNet, to a target task, i.e. chest X-rays datasets. We transfer features learned from two AlexNet and VGG-16 that are trained on ImageNet, to classify 3 different chest pathologies including SARS-CoV-2, Normal chests, and Viral Pneumonia. The employed pre-trained models are modified by replacing their feedforward neural network classifier, Softmax, by a support vector machine (SVM) that is expected to slightly boost their performance (AlexNet-SVM and VGG16-SVM). All employed models are trained (fine-tuned) on a 60% of the available large dataset of chest X-rays in turn to investigate its power of generality while trained using large amount of data. The networks are also tested on 40% of the data. The optimum performance was attained by the VGG16-SVM which scored a high accuracy of 96.27% and strong features extraction capability as compared to the other models. Experimentally, it is proposed that our COVID-19 diagnosis system can be used in conjunction with other tests for facilitating the screening and early detection of such disease.