The benefits of crowdsourcing are enabled by open environments where multiple external stakeholders contribute to a firm's outcomes. In recent years, crowdsourcing has emerged as a distributed model of problem-solving and market development. Here, model assignments are assigned to networked individuals to complete so that the manufacturing expense of a business can be minimized considerably. The main objective of this research is to develop a methodology which will capture the value generation process in the presence of uncertainties (Risk factors) in crowdsourcing context. This study is designed to make an important contribution to the field of practice and knowledge. Value-Risk Analysis of crowd souring is one of the under studies Worldwide, especially in Pakistan. Provided the need, we have discussed the crowdsourcing as business process and presented an understanding of the risks associated with crowdsourcing use and possible strategies that can be used to maximize the value and minimize the identified risks.
For the better understanding of crowdsourcing practices in Pakistan, three case studies were conducted based on three well reputed organizations of Pakistan and results gathered to help understand its practices, some of the risks associated with it and how they manage those risks.

In this paper, the importance of blockchain technology have been discussed and the generations of blockchain (Bitcoin and Ethereum) have been compared provided different aspects. The blockchain is a technology which allows direct transaction without involving third party. Also, it offers many facilities like high translucency, high safety and security, improved trace-ability, greater proficient and transactions’ speed, and reduced costs. Moreover, the cryptocurrencies provide advance security level. The basic purpose of this study is to highlight different aspects of Blockchain, Bitcoin and Ethereum and to show which cryptocurrency is better approach. The research contributes to show the impact of this technology in different fields and a comparison of bitcoin and ethereum is presented to analyze and furnish a decision regarding the best among them.
The use of blochchain technology in government applications can bring a drastic change in the world because it is safer and faster. Also, the comparison shows that ethereum is better than bitcoin as it is efficient and has more applications as compared to bitcoin. It offers more advanced services such as smart contracts. All in all, the analysis has concluded with Ethereum as faster and securer approach.

In the domain of knowledge, there is a rising demand for such a System to provide learning support via a platform which can generate any sort of questions automatically from provided source either (PDF) books or simply any keyword against a user needs to perform a test where STMS serves the purpose. Regarding Keyword operation, the System scraps all the text from Wikipedia and converts it into multiple choice questions. Moreover, it summarizes raw text from Wikipedia and parse the text from provided content to generate Multiple-Choice Questions(MCQs). The System also finds all the Named Entities and POS (Parts of speech tags) in the content to create relevant questions. The questions include Multiple-Choice Questions(MCQs), Cloze based questions and WH- questions (why, where, when etc.).
In addition, when users score standard points in the test then they qualify for earning zone where they can earn money ($ Dollars) for scoring points in each test. The Income comes from AdSense applied on the website and other Local ads, Affiliating marketing and advertisements. All in all, the System would help in educational learning by providing helping material in the lacking knowledge areas after analyzing the tests users have performed while the Web-Traffic is the key to Success for monetary benefits.

Disaster recovery is a continuous dilemma in cloud platform. Though sudden scaling up and scaling down of user’s resource requests is available, the problem of servers down still persists getting users locked at vendor’s end. This requires such a monitoring agent which will reduce the chances of disaster occurrence and server downtime. To come up with an efficient approach, previous researchers’ techniques are analyzed and compared regarding prediction and monitoring of outages in cloud computing. A dual functionality Prediction and Monitoring Agent is proposed to intelligently monitor users’ resources requests and to predict coming surges in web traffic using Linear Regression algorithm. This solution will help to predict the user’s future requests’ behavior, to monitor current progress of resources’ usage, server virtualization and to improve overall disaster recovery process in Cloud Computing.