Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks. From last few decades, there seen explosive increase in the average person's interest for stock market. In a financially explosive market, as the stock market, it is important to have a very accurate prediction of a future trend. Because of the financial crisis and recording profits, it is compulsory to have a secure prediction of the values of the stocks. Predicting a non-linear signal requires progressive algorithms of machine learning with help of Artificial Intelligence (AI). In our research, we are going to use Machine Learning Algorithm specially focus on Linear Regression (LR), Three month Moving Average(3MMA), Exponential Smoothing (ES) and Time Series Forecasting using MS Excel as best statistical tool for graph and tabular representation of prediction results. We obtained data from Yahoo Finance for Amazon (AMZN) stock, AAPL stock and GOOGLE stock after implementation LR we successfully predicted stock market trend for next month and also measured accuracy according to measurements.

Game development industry spreading it roots at wider level. With the advancements in gaming technologies industries adopted latest trends for developing modern games. Artificial intelligence (AI) with programming provided countless support for latest technology adoption in game industry. This paper aims to highlight some major points of our research "Creation of third person shooter game in unreal engine 4". We discussed how we can use one of the most powerful current generation game engines in an attempt to create our own game "Hysteria". Endeavoring used to replicate the process of the major game production cycle .It is used by modern gaming industries. We attempted it to create an action adventure shooting game by creating its own original storyline. The game Hysteriaisplayedfromathirdperson perspective in which the player must go through multipleenvironmentsfightinghordesof enemies and try to reach the end of level. Depending on the difficulty level that the player sets, there will be the number of enemies and their fighting intensity. The game has been developed but running at initial stages; further enhancement will be required to give it a much professional impression so that in near future it could be successfully commercialized.

Re-engineering (RE) of existing educational institutions (EI) with adoption of latest technology trends (LTT) in form of artificial intelligence (AI) can be great effective in term of quality systems. Increase in student's strength in class and terrorist attacks on EI urged us to introduce such approach that can assure education quality. Class monitoring with heavy strength always remain major issue for teacher during lecture delivery. In this paper, we implemented reengineering using artificial intelligence based two theories of 1) Multi-face recognition (MFR) system 2) Facial expression recognition (FER) system. Both of these theories supported by intelligent techniques as principal component analysis (PCA), discrete wavelet transform (DWT) and k-nearest neighbor (KNN). After implementation of these intelligent techniques student's attentiveness will increase. Our developed system can detect expressions like happiness, repulsion, fear, anger, and confusion. Student's attentiveness score will be displayed on screen. Teacher can interpret on the basis of attentiveness %age. System decision making can be helpful for class continuity or short break. This system is also an application of an expert system (ES) and knowledge base system (KBS) for educational quality assurance. A similar monitoring system was imposed in china with Hikvision Digital Technology. Predations results proved monitoring can be best way for education quality.

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Muhammad Muzammul and Dr. M. AwaisAn empirical approach for software reengineering process with relation to quality assurance mechanism ADCAIJSoftware development advances focus on productivity of existing software systems and quality is basic demand of every engineering product. In this paper we will discuss complete reengineering process with aspects of forward, reverse and quality assurance mechanism. As we know the software development life cycle (SDLC) follows a complete mechanism of engineering process. In forward engineering we tried to follow selective main phases of software engineering (data,requirements,design,development,implementation). Inreverse engineering we move backward from the last phase of developing product as it gather requirements from implemented product (implementation, coding, design,requirements,data).During reengineering we add up more quality features on customer demands, but the actual demand is to fulfill quality needs that can be assured by external as well as internal quality attributes such as reliability, efficiency, flexibility, reusability and robustness in any software system. We discussed a methodological approach to move from reengineering to the journey of quality assurance. More than 50 studies come into discussion and throughput results proposed by graph and tabular form. We can say if the reengineering process produce quality attributes, then it can be said by old software system refactoring as code refactoring, data refactoring and architectural refactoring we obtained a quality products at lower cost instead of new software system development, which causes decrease in quality attributes as cost, time etc. In future work testing methodology can be proposed for quality assurance.Muhammad Muzammul and Dr. M. Awais An empirical approach for software reengineering process with relation to quality assurance mechanism ADCAIJAn empirical approach for software reengineering process with relation to quality assurance mechanism ADCAIJ