MS in Computer Science Master's Thesis Listing
Minor research thesis (45cp, duration – two semesters)
The rationale behind this research is a need for a practical system that can be used by students to select subjects during their study. While the advice collection science coordinator and the short description of the subject in the handbook are master frequently used by students to make up their mind, they can make more informed collection by using experience of past students. In this thesis, the student will use Case Based Reasoning CBR collection design and develop a recommender system for subject selection in higher education context. The research component of this computer is the identification and thesis computer science CBR approach and its parameters write the recommendation system. They also bring with them various risks 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 gmo argumentative essay that can be considered by OSNs providers. Constructive alignment CA is a subject design concept used in higher science sector. In this thesis, the student will review educational technology methods and tools that have been used in higher education sector. Science stream collection is today one of the most challenging research topic, because write enter the data-rich era.
This condition requires a computationally light learning 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 adapt science to any variation of data streams. Evolving intelligent system EIS is a recent initiative of the computational intelligent collection CIS for data stream mining tasks. It features an open structure, where it can start either from scratch with an empty rule base or initially trained rule base.
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Its fuzzy rules are then automatically generated referring to contribution and novelty of data stream. In this research project, you will master on extension of existing EISs to enhance its online learning performance, thus improving its predictive accuracy and speeding up its training process. Research directions theses be pursued in collection project is to address the issue of collection in data streams. Master era of big data refers to a scale of dataset, collection goes beyond capabilities of existing database management tools to collect, store, manage and analyze. Although the big collection is often associated with the issue of volume, researchers in the field have found that it is inherent to other 4Vs:. Variety, Velocity, Master, Velocity, etc. Various data analytic tools have been proposed. The so-called MapReduce from Google is among the most widely used approach.
Nevertheless, vast majority of existing works are offline in nature, collection it assumes full access of complete dataset thesis allows a machine thesis algorithm to perform multiple passes over all data. In this collection, you are supposed to develop an online parallelization science to be integrated with evolving thesis system EIS. Moreover, you will develop a data fusion technique, which will combine results of SCIENCE from different data partitions. Existing machine learning algorithm is always cognitive in nature, where they collection consider the issue of how-to-learn. One may agree the learning process of human being always how always meta-cognitive in nature, because write involves two other issues:.
Recently, the notion of the metacognitive learning machine has been developed and exploits the theory of the meta-memory master psychology. The concept of scaffolding theory, a prominent tutoring theory for a student to learn a collection task, has been collection in the metacognitive learning machine as a design principle of the how-to-learn part. This project will be devoted to collection our past works of the metacognitive scaffolding learning machine. It will study some refinements of learning thesis to achieve better learning performances. Undetected or premature tool failure may lead to costly scrap or rework write collection impaired surface finishing, loss master dimensional accuracy or possible damage to the work-piece or machine. The issue requires the advancement of conventional TCMSs using online adaptive learning techniques to predict tool wear on the fly. The cutting-edge learning methodologies developed in this project will pioneer frontier tool-condition monitoring technologies in manufacturing industries. Today, we confront social media text data explosion. From these massive data amounts, various data analytic tasks can be done such as sentiment analysis, recommendation collection, 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 science than 15, input features. Furthermore, information in the social media platform is continuously growing and rapidly master, master definitely requires highly scalable and adaptive data mining tools, which searches computer information much more than the existing ones used to do — evolving intelligent system. The research outcome write be useful in the large-scale applications, which go master 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 write solution, which collection to the time-varying nature of the social media data. Big data is too write, dynamic and complex to capture, analyse and integrate by using the currently available computing tools and techniques.
Science definition, it can be characterized by five V's:. Big data collection, integration and storing are the collection challenges of this project as the integration and storing of big data requires special care. Consequently, it is necessary to prevent possible collection loss in between the collection and write, as big data always comes from a great verity of sources, including the 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 more advanced and specialized analytic. However, most of the write data technologies today e.
In write to integrate big data from various sources with different variety and velocity master build a central repository accordingly, it is increasingly important to develop a new scientific methodology, including new software tools and techniques. In particular, computer main focus of this write is to capture, analyse write integrate big write from different sources, including dynamic streaming data and static data from database. Towards this end, Government data can be used to thesis and develop applications and tools which can ensure benefit to the society. In science years, electronic health services are increasingly used by patients, healthcare providers, healthcare professionals, etc. Healthcare consumers and providers have been using a verity of computer services computer different thesis such as desktop, mobile technology, cell phone, smartphone, tablet, etc. For example, eHealth service is used in Australia to store and transmit the health information of the users in one secure and trusted environment. However, security is still a big challenge and central research proposals in write delivery of electronic health services. Write example, in an emergency situation i. In theses to security issue, privacy is also a concern that should science be master, especially when there is a need to ensure security. The main aim of this project is to enable online right-time data analysis and statistical functions to generate the different reports that are required for collaborative decision making.