The field of context awareness is ever increasing due to the proliferation and omnipresent nature of mobile computing devices. Not only is learning becoming ubiquitous, but the sensors in mobile devices are permitting learning systems to adapt to the context of the learners. This paper provides a classification framework for the field of context-aware mobile learning, which is applied to papers published within selected journals from January 2009 to December 2015 inclusive. Obtained from the combined fields of context awareness and educational technology, a total of 2,968 papers are reviewed, resulting in 41 papers being selected for inclusion in this study. The classification framework consists of three layers: hardware architecture layer, context architecture layer and an evaluation layer. The framework will allow researchers and practitioners to quickly and accurately summarize the status of the current field of context-aware mobile learning. Furthermore, it has the potential to aid in future system development and decision making processes by showing the direction of the field as well as viable existing methods of system design and implementation.

Owing to a big deal of benefits that Agile process models offer to the software industry, they have been the center of attention for a couple of decades for researchers. Scrum has emerged as one of the most prevalent contemporary Agile approaches. It's adaptive and versatile nature makes it appropriate for adoption. Experts have been experimenting and tweaking the practices for last many years to enrich the Scrum. This paper is intended to provide the latest insightful understanding of how the Agile Scrum tailored and adapted in different areas for software process improvement that in turn lead to increased productivity and product quality. A research strategy has been designed to extract the literature since 2016, based on pragmatic transformations of Scrum, subsequently gaining the in-depth perception that is presented in the paper as a comprehensive review and the outcomes are discussed. This work will contribute a state-of-the-art objective summary from which advance research activities can be planned and carried out.

This paper presents the model analysis of ball-on-sphere system by considering the effect of friction. The ball-on-sphere system is modelled using bond graph technique. In the bond graph modelling procedures of the system, the various subsystems, storage elements, junction structures, transformer elements, dissipating element with appropriate causality assignments and energy exchange that make up the ball-on-sphere system were identified and modelled. In the model analysis of the ball-on-sphere system, the developed model with effect of friction had time of angular position response of the ball ( ) achieved at 0.5253s while in the system model without effect of friction, time of 0.5408s was achieved for the angular position response of the ball ( ). This shows 2.9% improvement of the angular position response of the ball considering frictional effect in the developed bond graph model of the system.

Image division refers to the way toward dividing an advanced picture into various portions. Image division says to a parcel of an image into various divisions that are homogeneous or comparable. The objective of the division is to Simplify or potentially changes the portrayal of an image into something that is more important and simpler to dissect. Advancement of precise image division different image division strategies is utilized to take care of a particular issue. The motivation behind this survey is to give an overview of various image division methods. These methods are sorted into four sorts: an) Edge based division b) Threshold Segmentation c) Clustering-based division D) Region-based division. This survey tended to different image division methods, their correlation and presents the issues identified with those procedures.

Purpose – Achieving organizational excellence requires high-levels of commitment and coordination of multiple dimensions throughout an organization. One dimension that most organizational excellence frameworks highlight is the necessity of having a comprehensive learning system, which focuses on knowledge and training. Therefore, a proper understanding of knowledge management is important to identify the factors that drive the achievement of high organizational performance and excellence.
Design/methodology/approach – A case study approach has been used, which utilized in-depth interviews with key personnel to obtain valuable insights into the use of strategic knowledge management to drive operational excellence. While the survey was conducted to assist in analyzing certain perspectives related to knowledge management within the organization.
Findings – The main findings highlight how the emerging enterprise social network systems have played a major role in institutionalizing collaboration and corporate socializing within the organization, which are both important factors for strategic knowledge management to be successful. Based on the study, a framework has been proposed to assist in the successful implementation of strategic knowledge management for the achievement of organizational excellence.
Research limitations/implications – Due to the research approach used some of the findings may include varying degrees of bias in the responses obtained. In addition, due to the lack of time available the proposed framework was not evaluated.
Originality/value – Investigating the link and relationship between strategic knowledge management and organizational performance that lead to higher levels of organizational excellence.

Topic modeling techniques have been primarily being used to mine the topics from text corpora. These techniques reveal the hidden thematic structure in a collection of documents and facilitate to build up new ways to browse, search and summarize large archive of texts. A topic is a group of words that frequently occur together. A topic modeling can connect words with similar meanings and make a distinction between uses of words with several meanings. Here we present a survey on journey of topic modeling techniques comprising Latent Dirichlet Allocation (LDA) and non-LDA based techniques and the reason for classify the techniques into LDA and non-LDA is that LDA has ruled the topic modeling techniques since its inception. We have used the three hierarchical classification criteria’s for classifying topic models that include LDA and non-LDA based, bag-of-words or sequence-of-words approach and unsupervised or supervised learning for our survey. Purpose of this survey is to explore the topic modeling techniques since Singular Value Decomposition (SVD) topic model to the latest topic models in deep learning. Also, provide the brief summary of current probabilistic topic models as well as a motivation for future research.

Ontology is one of the central area in natural language processing (NLP), artificial intelligence (AI) information retrieval (IR) and semantic web (SW). If you are working on ontology project, this paper will give you the relevant information about ontology related terms and best ontology development editor. In this paper five ontology development editors are reviewed and compared with their updated versions. They are Apollo1.0, SWOOP 2.3Beta4, Protégé 5.0, Graffoo 1.0 and Neon 2.5.2. Comparison of two main data models ontology and RDBMS is also done. This paper also present the classification of ontology languages from those reported in the Literature, with a special attention accorded to the interoperability between them. Additionally, this paper presents the important terms related to ontology. The main criterion for comparison of these tools and languages was the user interest and their application in different kind of real world tasks. The primary goal of this study is to introduce these important tools, languages and data models to ensure more understanding from their use.