Driver behavior is the main cause of road crashes; it is the key element that insures a better understanding and improves predictions of car accidents. The main goal of our study is to determine the set of driver behavior features that are the most encountered in literature; we were based on behavioral questionnaires as a source for these features. We selected the questionnaires that are most cited in literature and therefore proved their efficiency through many studies they were employed in. Then we extracted the features considered in their items and classified them by rate of appearance according to the Pareto & ABC principle. In the second part of our study we collaborated with the National Committee for Circulation Accident Prevention (CNPAC) of the Ministry of Transportation of Morocco in order to compare the findings we gathered from literature with the researches they administer. We prepared a questionnaire that contains the final set of features and we transmitted it to experts working in the road safety field to rate it according to their knowledge and experience. Data analysis showed significant differences in some features, which demonstrates the gap between theoretical results and field research.

The type of information systems used to recommend items to the users are called Recommendation systems. The concept of recommendations was seen among cavemen, ants and other creatures too. Users often rely on opinion of their peers when looking for selecting something, this usual behavior of the humans, led to the development of recommendation systems. There exist various recommender systems for various areas. The existing recommendation systems use different approaches. The applications of recommendation systems are increasing with increased use of web based search for users’ specific requirements. Recommendation techniques are employed by general purpose websites such as google and yahoo based on browsing history and other information like user’s geographical locations, interests, behavior in the web, history of purchase and the way they entered the website.
Document recommendation systems recommend documents depending on the similar search done previously by other users. Clickstream data which provides information like user behavior and the path the users take are captured and given as input to document recommendation system. Movie recommendation systems and music recommendation systems are other areas in use and being researched to improve. Social recommendation is gaining the momentum because of huge volume of data generated and diverse requirements of the users. Current web usage trends are forcing companies to continuously research for best ways to provide the users with the suitable information as per the need depending on the search and preferences.
This paper throws light on common strategies being followed for building recommendation systems. The study compares existing techniques and highlights the opportunities available for research in this area.

Today, many business transactions are done online, especially in the financial sector or banking [1]. But as companies grow, many problems occur such as the inability to manage data consistency, especially when data is associated with more than one database. Replication is one of the most commonly used way of syncing data. However, to ensure data remains consistent, it is not enough just to take advantage of the replication process. The problem that often happens is connection failure or offline host. The Binary Log approach is one of the alternative methods that can be used to develop database synchronization. Generally, binary log is used for data recovery or backup purposes. Binary log in the DBMS (Database Management System) record all changes that occur in the database both at the data and structure level, as well as the duration of time used. This information can be used as a reference in updating data, while the ZeroMQ socket used as data exchange medium so data in all system locations will be synchronized and integrated in real time. This research will discuss how to develop a synchronization system by utilizing Binary Log from MySQL to recognize data changes, inherit changes, send changes, and hopefully can contribute new alternative method in developing real time database synchronization.

Code reviews and inspections have the purpose to ensure that the code has sufficient quality to be released. It is generally seen as an economical way of finding errors, increase team productivity and sharing technical and product knowledge among team members. This approach is traditionally adopted in software development companies, but their practices may be useful in other contexts, such as in the process of learning software engineering. In this sense, this study proposes an innovative framework for conducting code reviews in a Computer Science course. The proposed framework can be applied in any object-oriented program language, and it is sufficiently concise to be applied in the classroom, namely in a 90-minute session in which all students are invited to collaborate in this process. The findings suggest that code reviews in an academic context can help students to strategically reflect about the performed work, enhance their soft skills, and increase their ability to work in groups. On the other hand, as the main challenges, the findings reveal that students typically don’t have previous experience in performing inspections and it can become difficult to perform a complete inspection in a classroom session.

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.

Association rule hiding an important issue in recent years due to the development of privacy preserving data mining techniques for hiding the association rules. One of the mostly used techniques to hide association rules is the sanitization of the database. In this paper, a novel algorithm MPSO2DT has been proposed based on the Particle Swarm Optimization (PSO) in order to reduce the side effects. The aim is to reduce the side effects such as Sensitive item-set hiding failure, Non-sensitive misses, extra item-set generations and Database dissimilarities along with the reduction of running time and complexities through transaction deletion.