The background of this research is how the application of the algorithm in traffic control systems, with the Greedy algorithm, the system will decide what action and what punishment will be given to traffic offenders on the highway, with the Greedy algorithm, the decisions taken will be based on data and facts. based on existing laws, so decisions made based on law and the human side cannot influence the decisions to be taken by the system based on the application of the Greedy algorithm. The research method used in this study uses literature reviews by reading many previous research journals, it will be able to add knowledge and deepen the research we are doing this time, with the literature review method, we will be able to find new problems and can be used as new research because The literature review is very helpful for our research this time. The system that is being used is using CCTV and can determine what decisions and punishments will be given to traffic offenders, through evidence based on images taken by cameras placed at red lights or corners of the capital's highway, the system this has been active effectively but with the implementation of the algorithm will increase. This research will produce a system proposal and be able to find out whether the application of the Greedy algorithm is correct and can help the current system by implementing the algorithm, so the existing system is more perfect. The main contribution of this research is that the use of the Greedy algorithm can help control the traffic system to enforce the law. 

In India, purchasing furniture online consistently faces a quandary regarding how one can comprehend whether the furniture is a solid match to purchase, regardless of whether it will fit in space without really contacting and looking at the furniture in detail. With such a dilemma there are chances for online stores to decline in their business. There is always a good certainty that technology can help to bridge the barrier and help one to overcome the dilemma. This study creates a unique light on how Augmented Reality can help to create and simulate buying furniture an online experience and enhancing customer experience provided uniqueness and mobility with the help of a mobile application. Our application allows users to simulate and experience furniture in 3D simulation using markerless augmented reality. Users can try a piece of furniture in their space supported by gestures and color furniture to try out diverse tints of the same. This research advances a new way of implementing markerless augmented reality for buying furniture products online provided by mobile applications and communicating with virtual objects in a real environment with an easy-to-use user interface.

Blended teaching strategy becomes an integral part of the 21st-century education system to meet the industry 4.0 needs. As not only the online system can create the best system from the points of view of effectiveness and expending cost, but also the traditional teaching style cannot meet the higher level of industry needs. Therefore, the combination of the advancement of technology and the effective design of teaching theory appears in different blended systems to promote education level. This system also proposes a new model to initiate the teaching style that can supplement the requirements of this education era based on FLIP learning terms. The system is built by blending the online and face-to-face strategies using communication technology and multimedia components at pre-class, online test, and in-class times based on stakeholders’ satisfaction with the system. The outcome intends to build an effective education system that facilitates the developing country, the Myanmar situation. Moreover, the research methodology goal includes improving the problem-solving ability and performance results of the university students and to increase the self-reflection of all participants.

The present age is the age of information. The globalization has affected every sphere of the life including education. In spite of availability of ICT infrastructure in schools, their potential is underutilized because of digital incompetence of the teachers.  New digital technologies are acting as a catalyst towards improvement of learning outcome and enhancing quality of education, but only introduction of such technologies in schools for producing change and innovation is not enough, it requires digitally competent teachers to facilitate the use of ICT in education. These teachers will act as facilitators and mentors to students to lead them towards problem solving and innovation to meet the new challenges of globalization. Teachers must be able to create learning environments which are student centric and foster creativity, Meta cognition, meta-literacy, collaboration and communication in learners. Mere superficial use of ICT in teaching will not yield the required learning outcome, but the integration of ICT in pedagogy is important to enhance teaching, learning process. This can be done only when teachers are competent enough to use ICT tools and facilitate ICT integrated education. In this paper, we tried to assess the teacher’s perspective about the ICT and investigate the factors responsible for resistance of teachers in using ICT in schools and suggestive measures for successful integration of ICT in the teaching process by the teachers of Rajouri district (J&K, India). The ICT skills are very important for teachers to support alternative modes of teaching, learning, i.e. e-learning, mobile learning in the present outbreak of pandemic disease caused by Coronavirus-COVID19. 

In the present situation, COVID-19 is a very common and dangerous issue in the whole world. Ensuring our healthy mental state is very essential at the period of COVID-19. But as a result of being in the home quarantine for a long time, people are going to notice a mental change such as stress, depression, mood swing. We proposed an RHMCD model which helps us to reach our required goal. This model contains machine learning algorithms. We examined our work with Naive Bayes classifiers, Support Vector Machine, and logistic regression. For gaining the report of mental conditions we used the sentiment analysis technique. For measuring the level of depression we also used a decision tree approach.