Cloud computing is an innovative technology which is based on the internet to preserve large applications. It is warehoused as a shared data over one platform. In addition, it offers better services to clients who belong to different organizations. In spite of the maximum utilization of computational resources provided by the cloud computing with lower cost, it suffers from specific restrictions. These restrictions are encountered through the load balancing of data in the cloud data centers. These restrictions are represented in the less bandwidth utilization, resource limitations, fault tolerance and security etc. In order to overcome these limitations, new computing model called Fog Computing is presented. It aims to offer the required service of the sensitive data to end users without delaying. The function of the fog computing is similar to the cloud computing with two preferred advantages. The first one is that it is placed more near to the end users to introduce its service in less time. Secondly, it is more valuable for streaming the real time applications, sensor networks, IOT which need high speed and reliable internet connection.
In this paper, a novel load balancing algorithm has been proposed over a novel architectural model in the Fog Computing environment. The proposed model aims to serve the real-time tasks within their deadline. In addition, it serves the different soft tasks without starving. The soft tasks are classified according to the execution time and the priority levels. In addition, they are served according to their waiting time and priority-level. Furthermore, the proposed algorithm is employed to maximize the throughput, the resources and the network utilization and preserving the data consistency with less complexity to accomplish the end users demand.

The senior project stage in bachelor’s degrees represents an essential milestone in the learning process of a Computer Science (CS) student. The Senior Project Management System (SPMS) plays an important role in refining the quality of the resulting product and improving the learning experience of students. The CS department at King Abdulaziz University (KAU) has followed a well-defined system for managing senior projects since 2012. Systems evolve through time in response to encounters that unfold when the system is put to use. The administration of CS senior projects is no exception. In this paper, we present some incremental changes that have been introduced as refinements to the original system. This paper focuses on analyzing the data of the projects conducted during 2015 and 2016 in the Computer Science Department, Girls Main Campus (GMC) branch from the following perspectives: the project plan and deliverables at each milestone, and the provision of constructive mature collective feedback by the evaluating committee. These refinements are called addendums as they are additional steps to the SPMS and each step is monitored by using forms. This paper also describes some practices that support the SPMS along with the rationale behind their application. Evidence for the two addendums have been collected from analysis of the relevant forms. The analysis showed that the students benefited from the flexibility introduced by the milestone addendum as they made use of the new options. In addition, analysis of the forms of the feedback addendum showed that this documentation served as a means to gather the overall collective opinion of the committee members as opposed to the individual assessment of each member. Additional evidence was collected from evaluation committee members, by conducting a questionnaire. It showed that participants do benefit from the discussion promoted by the feedback addendum.

Research studies and attitudes towards ICT use in education management are shifting, and often significantly. This is likely to have a major impact upon ICT and education management. However, the real significance of the impact for educational management has yet to be seen within this research study. The focus of the research study is to investigate and analyses the ICT usage in Education Management. ICT in teaching has an important role and its impact on the advancement of educational processes related to effective teaching and learning, and modern research in this field is almost irreplaceable. Another important element is the use of different software platforms that facilitate learning visible and make it more concrete, more practical and applicable to everyday life. In order to analyze the data a combination of qualitative and quantitative methodology has been used. In order to analyze this, Case study analysis of high schools in city of Skopje, Macedonia is realized. Insights and recommendations are provided.

Big Data is an accumulation of data sets which are abundant and intricate in character. They comprise both structured and unstructured data that evolve abundant, so speedy they are not convenient by classical relational database systems or current analytical tools. Big Data Analytics is not linearly able to expand. It is a predefined schema. Now big data is very helpful for backup of data not for everything else. There is always a data introducing. It also helps to solve India’s big problems. It also helps to fill the data gap. Health care is the conservation or advancement of health along the avoidance, interpretation and medical care of disorder, bad health, abuse, and other substantial and spiritual deterioration in mortal. Health care is expressed by health experts in united health experts, specialists, physician associates, mid-wife, nursing, antibiotic, pharmacy, psychology and other health. This paper focuses on providing information in the area of big data analytics and its application in medical domain. Further it includes introduction, Challenging aspects and concerns, Big Data Analytics in use, Technical Specification, Research application, Industry application and Future applications.

Be it indigenous or foreign language, languages are core for communicating messages from one person to another or group of persons. Primarily, it is learnt at home, schools, through the media like television and radio programmes. However, most of these language-teaching approaches do not measure the percentage growth of people who have gained the knowledge of the language over the years; they also lack the capacity to foretell the range of people that will acquire the knowledge of the language in the latest future. This is because several of the language teaching aids do not have the required dataset to describe and effectively predict the state of the language (a category of people who can speak and write the language) now, and against the future. Here, the research proposed an analytic game based model for Yoruba language evaluation. The essence is first to ascertain the user’s initial knowledge of a language, train users through difference fun filled game stages and levels, evaluate the user at the end of every level and analyse the clustered dataset of users game points to describe and predict the state of the language by using a dual level predictive analytics technique.

The picture noise is an irregular variation of brightness and color information in pictures. It decreases picture quality and permeability of specific elements inside the picture. The most surely understood noise that corrupts the photo with impulse noise. In this work, an effective algorithm is intended to identify and remove noise from a picture. An improved de-noising calculation in view of the median filter is exhibited for greyscale and colored images. The algorithm incorporates two cases: I) if the chose window contains all pixel values "0" to "255" at that point center preparing pixel supplanted by the mean of qualities. II) If the chosen window does not contain all components "0" and "255" then eliminate "0" and "255" and central preparing pixel is replaced by the median of remaining pixels values. The performance is checked off the purposed algorithm by comparing it with corresponding filters. The experiment checked at various noise proportion 5% to 80% for greyscale and color pictures. Results are checked as far as MSE and PSNR and even at high noise proportion; it gives better outcomes over other existing techniques.

The cloud computing is the rapidly growing technology in the IT world. A vital aim of the cloud is to provide the services or resources where they are needed. From the user’s prospective convenient computing resources are limitless thatswhy the client does not worry that how many numbers of servers positioned at one site so it is the liability of the cloud service holder to have large number of resources. In cloud data-centers, huge bulk of power exhausted by different computing devices.Energy conservancy is a major concern in the cloud computing systems. From the last several years, the different number of techniques was implemented to minimize that problem but the expected results are not achieved. Now, in the proposed research work, a technique called Enhanced - ACO that is developed to achieve better offloading decisions among virtual machines when the reliability and proper utilization of resources will also be considered and will use ACO algorithm to balance load and energy consumption in cloud environment. The proposed technique also minimizes energy consumption and cost of computing resources that are used by different processes for execution in cloud. The earliest finish time and fault tolerance is evaluated to achieve the objectives of proposed work. The experimental outcomes show the better achievement of prospective model with comparison of existing one. Meanwhile, energy-awake scheduling approach with Ant colony optimization method is an assuring method to accomplish that objective.