The open discovery initiative & promoting transparency in discovery

NISO recently updated the Open Discovery Initiative Recommended Practice (https://www.niso.org/publications/rp-19-2020-odi), which outlines best practices for working with library discovery services. It defines ways for libraries to assess the level of content provider participation; streamlines the process by which libraries, content providers and discovery service providers work together; defines models for “fair” linking; and suggests usage statistics that should be collected for libraries and for content providers. The recommendations in this document, created by members of the Open Discovery Initiative Standing Committee, enable libraries, discovery service providers, and content providers to work together to the full extent of their abilities - providing the most effective and rich experience to end users.

A solution to profiling for mobile computation cloud offloading

In this thesis, we develop a Generic Profiler which is a solution to profiling for mobile computation cloud offloading. Profiling refers to the process of examining and collecting statistics and information about data. The Generic Profiler uses resection in many cases to reduce redundant code and allow developers to easily incorporate new profilers to their offloading solutions. Third party developers can include the Generic Profiler into their solutions with ease and without having to worry about the underlying processes of storing data using a Content Provider. The Generic Profiler also contains a set of default profilers, which include a Location Profiler, Software Profiler, Wi-Fi Profiler, Telephony Profiler, and a Battery Profiler. Using the Software Profiler, we have shown that the performance, in terms of inclusive invocation time, of the profilers which are designed by implementing the Generic Profiler adequately store data.

A solution to profiling for mobile computation cloud offloading

In this thesis, we develop a Generic Profiler which is a solution to profiling for mobile computation cloud offloading. Profiling refers to the process of examining and collecting statistics and information about data. The Generic Profiler uses resection in many cases to reduce redundant code and allow developers to easily incorporate new profilers to their offloading solutions. Third party developers can include the Generic Profiler into their solutions with ease and without having to worry about the underlying processes of storing data using a Content Provider. The Generic Profiler also contains a set of default profilers, which include a Location Profiler, Software Profiler, Wi-Fi Profiler, Telephony Profiler, and a Battery Profiler. Using the Software Profiler, we have shown that the performance, in terms of inclusive invocation time, of the profilers which are designed by implementing the Generic Profiler adequately store data.

A solution to profiling for mobile computation cloud offloading

In this thesis, we develop a Generic Profiler which is a solution to profiling for mobile computation cloud offloading. Profiling refers to the process of examining and collecting statistics and information about data. The Generic Profiler uses reflection in many cases to reduce redundant code and allow developers to easily incorporate new profilers to their offloading solutions. Third party developers can include the Generic Profiler into their solutions with ease and without having to worry about the underlying processes of storing data using a Content Provider. The Generic Profiler also contains a set of default profilers, which include a Location Profiler, Software Profiler, Wi-Fi Profiler, Telephony Profiler, and a Battery Profiler. Using the Software Profiler, we have shown that the performance, in terms of inclusive invocation time, of the profilers which are designed by implementing the Generic Profiler adequately store data.

A solution to profiling for mobile computation cloud offloading

In this thesis, we develop a Generic Profiler which is a solution to profiling for mobile computation cloud offloading. Profiling refers to the process of examining and collecting statistics and information about data. The Generic Profiler uses reflection in many cases to reduce redundant code and allow developers to easily incorporate new profilers to their offloading solutions. Third party developers can include the Generic Profiler into their solutions with ease and without having to worry about the underlying processes of storing data using a Content Provider. The Generic Profiler also contains a set of default profilers, which include a Location Profiler, Software Profiler, Wi-Fi Profiler, Telephony Profiler, and a Battery Profiler. Using the Software Profiler, we have shown that the performance, in terms of inclusive invocation time, of the profilers which are designed by implementing the Generic Profiler adequately store data.

OPEN AND DISTANT LEARNING (ODL) STUDENTS ARE NO MORE JUST LEARNERS

The presence of diverse online resources in different delivery modes and the introduction of blended learning have posed new challenge for educational institutions to choose the method of learning which is not only effective but also a synchronized one. Changing a-synchronized contents into synchronized require an integrated effort from all members of e-learning system in the form of learning ecosystem. Learning ecosystem includes all components (content provider, infrastructure and consultant) that are necessary for the e-learning. In a learning system teacher are considered as content provider while students are acting as learners. A learning ecosystem aims to involve all stakeholders for the benefit of each other and does not restrict the role of students as learners only. Professional students enrolled in different degree programs have professional experience and are the source of asynchronous contents that can be synchronized through involving them as content vendors in learning ecosystem. This paper aims to introduce role of students as content vendors in the form of their professional experience from different industries. Their experiences will act as resources of educational institutions that can be assembled and used for awareness about business community among students. In order to integrate this valuable experiential knowledge, this paper will propose a model for institutions. Model proposed by this study will change the existing role of students solely as leaner to the knowledge providers. This attained knowledge will also cover the existing gap between theory and application of knowledge.

Executing a business model change: identifying key characteristics to succeed in volatile markets

The world is changing, and with it comes the requirement that enterprises change to survive in today's volatile markets. However, the change does not just include launching a new product on the market but also changing the business model of the whole organisation. To sustain in today's fast-changing markets, companies have to detect new market opportunities on time, assess them and find a way to incorporate the most beneficial opportunities into their business. Without this awareness that a company must change with the changing market, it risks losing its significance in the market. Both the change of the business model and the change of the organisation are needed to succeed in the market. An outstanding example of such a company is Netflix. They have successfully changed their business model twice: first, from an online-DVD-rental service to a streaming provider and then, to a content provider. They were aware of upcoming new technologies on-time, evaluated them and planned the implementation in the market while the old technology was still profitable. The present work outlines the major changes in Netflix's business model and how they managed the change process successfully.