This research intends to shed some light on the influence of culture on the learners understanding of culture specific jokes. For this purpose, the responses of the volunteer students of first year master of English at Constantine University have been collected. The research work is mainly concerned with finding whether the high exposure to the foreign language culture has anything to do with the learner’s level of understanding of jokes. Both the quantitative and qualitative analysis indicated that there is an association between the learners’ level of understanding of the jokes and their exposure to culture. Despite the limited scope of this study, the research findings revealed interesting implications on research to the teaching of the foreign culture to students at university level.

People's Democratic Republic of Algeria Ministry of Higher Education and Scientific Research

Business Intelligence and Analytics in Small and Medium-sized Enterprises

Disclosed is an approach for allowing an entity to perform semantic analysis upon data associated with an entity, and to automatically perform categorization of that data and to generate alerts based on a set of predefined rules. A topic is created based on which to categorize a set of semantically analyzed messages. A set of rules is defined, wherein an alert is generated when the set of rules is satisfied for the semantically analyzed messages.

Method and system for implementing alerts in semantic analysis technology

Smart use of business intelligence (BI) can allow organizations to leverage the huge amounts of transactional data at their disposal and turn it into a powerful decision support mechanism that gives them competitive advantage. Despite the potential benefits of an effective BI system, the adoption and use of BI systems within the enterprise remains low, especially among smaller companies with resource constraints. This can partly be explained by the predominant deployment approach available today in which a firm needs to procure, install, configure and operate a BI system in-house. Barriers of high cost, complexity and lack of in-house expertise discourage many firms from adopting BI systems. This paper argues that adopting a cloud computing model, where BI is offered as a service over the Internet can lower these barriers and accelerate the pace of BI adoption. However, migrating BI systems from traditional on-premise environments to the cloud presents huge challenges. There are technical, economic, organizational and regulatory hurdles to overcome. Further, BI systems are multi-component (ETL, Data warehouse, data marts, OLAP, reporting, data mining etc.) and deciding which component(s) to move to the cloud, and which ones to leave on-premise needs careful consideration. In addition, the fact that cloud computing is still in its infancy means there is a general lack of conceptual and architectural frameworks to guide companies considering migrating enterprise systems to the cloud. This paper takes a closer look into traditional BI and proposes a conceptual framework that companies can use to chart an adoption path for cloud BI. The framework combines attributes of IT outsourcing, traditional BI, cloud computing as well as decision theory to present a consolidated view of cloud BI. The domain of South African Higher Education was chosen as the target in which the framework will be tested.

A conceptual framework for delivering cost effective business intelligence solutions as a service

Context: Cloud computing has gained significant attention of researchers and practitioners. This emerging paradigm is being used to provide solutions in multiple domains without huge upfront investment because of its on demand recourseprovisioning model. However, the information about how software systems are constructed for cloud based systems and what architecture approaches are used to build these systems in not available in synthesized form, which makes it hard to find common architecture solutions for building applications for cloud and identify research gaps. Object: The main objective of this study is to systematically identify and analyze the currently published research on the topics related to software architectures for cloudbased systems in order to identify architecture solutions for achieving quality requirements. Method: We decided to carry out a systematic mapping study to find as much peerreviewed literature on the topics related to software architectures for cloud-based systems as possible. This study has been carried out by following the guidelines for conducting systematic literature reviews and systematic mapping studies as reported in the literature. Based on our paper selection criteria defined by the requirements of the study’s objectives and research questions, we have found 86 papers to be included in this study out of initial set of 1491 papers. Results: We have grouped selected papers into different categories of themes including: quality attributes (15%), multi-tenancy (3%), frameworks (3%), workflow based systems (4%), support for hybrid devices (7%), middleware infrastructure for managing services and resources (10%), architecture refactoring considerations for migrating applications to cloud (4%), generic architecture solution (12%), emerging research areas (3%) and cloud application domains (39%). We have described problems being addressed in each category, which architecture solutions have been proposed to solve these problems and technologies that have been used. Conclusions: The selected studies reports challenges and potential solutions related to maintaining underlying infrastructure for supporting large number of users, utilizing cloud computing for making applications available for devices with limited resource, performing sensitive data processing on cloud and achieving service level agreements at different levels or abstractions. Energy optimization, service adaptability, reliability, resource provisioning and service integration are most commonly addressed quality attributes in cloud bases system. Work reported in this study focuses on architectural constructs of cloud-enabled systems reported in literature. We have synthesized architecture approaches proposed in paper into architecture styles

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A Systematic Mapping Study of Software Architectures for Cloud Based Systems

With the rapid development of web technology, an increasing number of enterprises having been seeking for a method to facilitate business decision making process, power the bottom line, and achieve a fully coordinated organization, called business intelligence (BI). Unfortunately, traditional BI tends to be unmanageable, risky and prohibitively expensive, especially for Small and Medium Enterprises (SMEs). The emergence of cloud computing and Software as a Service (SaaS) provides a cost effective solution. Recently, business intelligence applications delivered via SaaS, termed as Business Intelligence as a Service (SaaS BI), has proved to be the next generation in BI market. However, since SaaS BI just comes in its infant stage, a general framework maybe poorly considered. Therefore, in this paper we proposed a general conceptual framework for SaaS BI, and presented several possible future directions of SaaS BI.

Wu Zhangjun

Papers

A Conceptual Framework for Business Intelligence as a Service (SaaS BI)