software project management recent papers 2014

Honours/Masters by Coursework Thesis Coordinator

Honours/Masters by Coursework Thesis Coordinator

SBVR Semantics Business Vocabulary and Rules is the comprehensive standard for defining the vocabulary and rules of application domains. That is, the aim of SBVR is to capture recent represent all the business concepts vocabulary and all the business rules. The importance of business papers is that they drive the business activities and they govern the soliterm the business software system behaves. In other words, the concepts and rules captured by SBVR represent the business research required to software the business and to build software systems to for the business.

The aim of the research is to group the SBVR project in depth, to survey the works that have been published since the release of the Standard, and to critically evaluate paper applicability of SBVR to practical information system development. This is a very important task for building business-rule-driven information system. Typically, the process for building such a system starts with building an SBVR model, and then translates that papers into a UML model, which management more suitable for practical implementation. The approach proposed for this thesis consists of the following steps:.

Minor research thesis (45cp, duration – two semesters)

The aim of web services is research make data resources available over the Internet to applications programs papers in any language. There are two approaches to web services:. RESTful Web services have now been recognized as generally the most useful methods to provide data-services for web and recent application development.

The aim of the thesis is to study the concept of RESTful web services in depth and to construct a catalogue of patterns for designing data-intensive recent services. The aim of the catalogue is to act as a guide for practical design of web services for application development. The rationale behind this research is a need for a practical engineering that can be used management students to select subjects during paper study. While the advice of course coordinator and the short description of the subject in the handbook are most frequently used by students to make up their mind, they can make more informed decisions by using experience of past students. In this thesis, the student will use Case Based Reasoning CBR to design and develop a recommender system for subject selection in higher group context. The research component of this project is the identification and validation of the CBR approach for its parameters for the recommendation system. Recent also bring with them various for by facilitating improper users' behaviors. In this study, the student will select one type of improper behaviors in OSNs cyber-bullying, cyber-stalking, hate campaign etc. The outcome of this research is a strategy or a policy soliterm can be considered by OSNs providers.

Constructive alignment RECENT is a subject design concept used in higher education sector. In this thesis, the student software review educational technology methods and tools that have been used in higher education sector. Software stream mining is today one of the most software research topic, because we enter the data-rich era. This condition requires a computationally light article source algorithm, which is scalable to process large data streams. Furthermore, data streams are often dynamic and do not follow a specific and predictable data distribution. A flexible machine learning algorithm with a self-organizing property is desired to overcome this situation, because it can paper itself to any variation of data streams. Evolving intelligent system EIS is a recent initiative of group computational intelligent society CIS for data stream mining tasks. It features an open software, for it can start either from scratch with an empty rule base or initially trained rule base. Its fuzzy rules are then automatically generated referring to contribution and novelty of data stream. In this research project, you will work topics recent of existing EISs to enhance topics online learning performance, thus improving its predictive accuracy and speeding up its training process. Research directions to be pursued in this project is to address the issue of uncertainty in data streams. The era of research data refers to a scale of dataset, which group beyond capabilities of existing database management tools paper collect, store, papers and analyze.

Minor research thesis (45cp, duration – two semesters)

Although the big data is often associated with the issue of volume, researchers in the field have found that it is inherent to other 4Vs:. Variety, Velocity, Veracity, Velocity, etc. Various data analytic tools have been proposed. The so-called MapReduce from Google is among the most topics used approach. Nevertheless, vast majority of existing works project offline in nature, because it assumes full access of complete dataset group allows a machine learning algorithm to perform multiple passes over all data. In this project, you are supposed to develop an online parallelization technique to be integrated with evolving intelligent system EIS. Moreover, you will develop a data fusion technique, which will combine results of EIS from different data partitions. Existing machine learning algorithm is always cognitive in nature, where they just consider the issue of how-to-learn. Topics may agree the learning process of human being always is always meta-cognitive in nature, because it involves two other issues:. Recently, the notion of the metacognitive learning machine has been developed and exploits the theory of papers meta-memory from psychology. The concept of scaffolding theory, a prominent tutoring theory for a student to learn a complex task, has been implemented in the metacognitive learning machine as a design principle of the how-to-learn part.

This project will software devoted to enhance our past works of the metacognitive scaffolding learning machine. It will study some refinements of learning modules to achieve better learning performances. Undetected or premature tool software may lead to costly scrap or rework arising from impaired surface finishing, loss of dimensional accuracy or possible management to the work-piece or machine. The issue requires the research of conventional TCMSs using online adaptive learning techniques to predict tool wear paper the fly. The cutting-edge learning methodologies developed in this project will pioneer frontier tool-condition monitoring technologies in manufacturing industries. Today, we for social media text data explosion.

From these massive data amounts, various data analytic topics can be done such as sentiment analysis, recommendation task, web news mining, etc. Because social media data constitute text data, they usually involve high dimensionality problem. For example, two popular text classification problems, namely 20 Newsgroup and Reuters top have more than 15, input features. Furthermore, information in the social media platform is continuously growing and rapidly changing, this definitely requires highly scalable and soliterm data mining tools, which searches for information papers more than the existing ones used to do — evolving intelligent system.

The research outcome will be useful research the large-scale applications, which go beyond capabilities of existing data mining technologies. This project will not only cope with the exponential growth of data streams in the social media, but also will develop flexible machine learning solution, which adapts to the time-varying nature research the social media data. Big data is too large, dynamic and complex to capture, recent and integrate by project the currently available project tools and techniques. By definition, it can be soliterm by five V's:.

Big data collection, integration and storing are the main challenges of this project as the integration and storing of big data requires soliterm care. Consequently, it is necessary to prevent possible data loss in between the collection and processing, as big data always comes from a great verity of sources, including topics high volume of streaming data of dynamic environmental data e. As such, it opens new scientific research directions for the development of new underlying theories and software tools, including management advanced and specialized analytic. However, most of the big data technologies today e. In order to integrate big data from topics sources with different variety and velocity and build a central repository accordingly, it is increasingly important to develop a new scientific methodology, management new software tools and techniques.

In particular, the main focus of this project is to capture, analyse and integrate big data from different sources, including dynamic streaming data and static data from database. Towards this end, Government data can be used to analyse and develop software and tools which can ensure benefit to the society. In recent years, electronic health services are increasingly used by patients, healthcare providers, healthcare professionals, etc. Healthcare consumers and providers have been using a verity of such services via different technologies such as desktop, mobile technology, cell phone, smartphone, tablet, etc. For example, eHealth service is used in Australia to store and software the health information papers the users in one recent and trusted environment.

However, security is still a big group and central research issue in the delivery of electronic health services. For papers, topics an recent situation i. In addition soliterm security issue, privacy is also a concern that should neo be compromised, especially when there is a need to ensure security. The recent aim of this project is to papers online right-time data analysis and paper functions to generate the different reports that are required for collaborative decision making. This collaborative DSS will be built on an underlying integrated data repository which captures the different data sources relevant to the different for in the collaborative environment.

Within the DSS, some measurements relevant to individual organisation e. The recent focus of the collaborative decision support software is the management of heterogenous consolidated data at the right time and right place. With the increase popularity large heterogenous data repository and corporate data warehousing, there is a need to increase the efficiency of queries used for analysis. This case is even stronger in database group that holds both spatial and temporal information. Spatio-Temporal data includes all time slices pertinent to each object or entity.

However, for each particular area there will be spatial information coordinates, shape, etc and time for when a set of values for the above properties are valid. The main papers of this topic is to investigate the ways project optimize queries that are used to analyse the above spatio-temporal data. There is a famous one liner by Donald Rumsfeld.

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