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.

Internet of Things (IoT) referred to interconnected the world of things like physical devices, cars, sensors, home appliances, actuators and machines embedded with software at any time, any location. The increasing number of IoT devices facing challenges which are registration, integration, describing sensor, interoperability, semantics, security, discovery and searching. The current systems are suitable for limited number of devices. Our ecosystem change day by day which means we have billions and trillions of devices connecting to the Internet in future. One major challenge in current system is searching of suitable Smart Things from a millions or even billions number of devices in IoT. For the purpose of searching and indexing, some discovery methods and techniques are discussed and compared. Those techniques and methods are studied and find out the limitations and issued of the current system. Another challenge to searching the Smart Things is a variety of description models for describing the Smart Things. In this piece of work, a novel search engine is proposed to search the Smart Things with variety of description models. A web interface is implemented in this research with HTML, JSON and XML formats. The description models of Smart Things SensorML, SensorThings API and W3C JSON-LD are implemented in the current proposed system.

In cloud computing, requirements engineering is a greatly under-researched topic. Requirement elicitation is a key activity that helps in assemble the requirements of a system from different users, customers and stakeholders. Cloud services providers need methods to correctly elicit requirements from consumers, as the consumers of cloud services are more diverse and there occur some conflictions in the non-functional requirement of some kinds of consumers. Sometimes eliciting security requirements is an important task, because the cloud services are acquired by potential cloud consumers are secure for them to use. Both literature and market surveys are performed on different elicitation approaches that are followed by CSPs to fetch consumer requirements, recommendations and data from cloud service providers and from consumers of cloud computing services. This study aims to discuss the elicitation methods being used by cloud providers in Pakistan IT industry, and the resulting feedback of the consumers by these methods. This would lead to determine current elicitation methods are sufficient or there is a need to design a new elicitation method that can sufficiently provide with more customer satisfaction. We have used semi-structured interviews and questionnaires to gather information about the elicitation techniques that are used by cloud providers to elicit consumer requirements. This study is conducted in Pakistan IT industry. Somehow, this research enlightens the trend and scope of cloud computing in Pakistan. This study would be beneficial for cloud providers adequately gather their consumer requirements and enhance the knowledge of elicitation techniques that are used by cloud providers.

Agent Based modelling is widely used for presenting and evaluating a social phenomenon. Agent based modelling helps the researcher to analyze and evaluate a social model and its related hypothetical theories by simulating a real situation. This research presents a model for showing the behavior of an offender that is greatly influenced by volunteering of people on the offending tendencies. It is observed that how the offending behavior of someone urges others to do the same criminal act or violation of norms. And how can volunteering make the offender feel shameful of his doings and motivate others to volunteer in likewise situation in future. An agent based Model is presented and simulated to evaluate and validate the conceptualization of presented social dilemma. This model is simulated by asking some questions with exacting focus on the offending behavior of an agent. This study evaluates all the simulated results from the presented model to describe theoretical foundation spreading of offending or criminal behavior. Moreover, it validates the role of volunteering in the decrement of offending tendencies of the people as it presents an understandable situation in which offending of someone increases the offending tendencies of audience. Moreover the results of this research show that the volunteering decreases the offending tendencies of not just offender but also of the audience.

Tenuous community detection in social networks is becoming an interesting area of research and its various important applications are emerging. Existing research has focused on the identification of a dense community. However, finding the tenuous community has posed a different kinds of challenges and existing solutions are not viable for this research problem. In this paper, a novel approach called the least linked community (LLC) is proposed to find a tenuous community from online social networks. The concept of k-links with the shortest path distance between two nodes is proposed and utilized to find a community with the least interaction and weak relationships.The experiment demonstrated significant results in terms of accuracy, effectiveness, and efficiency compared to other existing techniques. Although the proposed algorithm presents significant results it may require further evaluation with different data sets.