TC-II Short Courses
TCII offers industry based short causes, in the areas of applying a set of technologies to turn industrial problems into solutions powered by data meaningful information. It addresses industrial processes and productivity, compliance and standards, data quality and governance, customer services and market positions. TCII is widely considered as outstanding experts in the field, with research, projects and awards to prove it. We share our wealth of expertise on the topic of industrial informatics with you by series of short courses and workshops. The course is offered by our leading researchers, professors and industrial experts from the around of world. TCII short Courses are as following:
1) Data Mining for Big Data Intelligence
Data mining is the act of detecting patterns from existing data repositories. Depending on the underlying data mining algorithms, the underlying or ‘hidden patterns’ the data could be detected. These underlying patterns provide useful insight to business analysts, business managers and senior business executives is forming business strategies for strategic decision-making in organizations. The aim of this course is to provide audiences with the theoretical and practical knowledge, tools and techniques of data mining, and their applications in enterprises.
After the completion of the course audiences should have gained the necessary theoretical and practical knowledge in data mining techniques. It is highly recommended & suitable for persons who would like to make or leverage the use of data mining in their organization to gain business insight.
Topic 1 – Introduction (Knowledge Discovery and Data Mining)
Topic 2 – Data understanding (Introduce the problems that commonly occur with data in the real world. It introduces the current techniques used for data analysis.)
Topic 3 – Data Preparation (The need for different kinds of data pre-processing, and the possible techniques used for each kind are discussed. In particular, the importance and the reason for using a particular technique are given)
Topic 4 – Association Rule Mining (Introduce association rule mining and ‘Apriori’ algorithm for association rule mining is introduced)
Topic 5 – Decision Trees (Decision tree learning is described together with an overview of the existing algorithms. Advantages and disadvantages of decision tree learning and the purpose and method of decision tree pruning are discussed)
Topic 6 – Bayesian inference (Bayesian inference & the background for its use in data mining. Naive Bayes classifier and Bayesian Belief Networks (BBN’s)
Topic 7 – Neural Networks (Symbolic rule extraction, Network pruning, Generalization and learning in general).
Topic 8 – Clustering and other methods (Different clustering techniques, Algorithms used in data mining)
Topic 9 – Review of the whole data mining process (Re-establish the links within the material learned and thereby increase the understanding of the knowledge discovery process as a whole)
Topic10– Applications and case studies (Real world applications of data mining)
2) Cloud Computing and Services
Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources. Cloud services are software, platforms, infrastructure delivered by cloud computing. There has been a lot of attention in business and industry on “cloud computing and services” as a means for addressing business needs. It is widely believed that in the next decade, “cloud” will reshape the technology landscape in business. Obama stated that all US government services will be moved to the cloud. Australian government has indicated that all its public services will be available from the cloud. The aim of this course is present to audience about cloud computing and how businesses could leverage the use of cloud to address their needs.
This workshop will provide a guide to understand and use cloud services for mission-critical business units as well as daily routines business logics. This workshop also provides design, development and deployment of cloud applications in business.
Topic 1 – Cloud computing and cloud services
Topic 2 – The differences between Service Oriented Computing, Grid and Cloud
Topic 3 – The use of cloud computing for your organization
Topic 4 – Refine business cases, drivers, strategies, and business processes for cloud
Topic 5 – Deployment models and cloud virtualization
Topic 6 – Design and develop your cloud with GoogleTM
Topic 7 – Design and develop your cloud with AmazonTM
Topic 8 – Cloud interoperability and standards
Topic 9 – Cloud security and privacy
Topic 10 – Conclusion, feedback, and future directions
3) Cyber-Physical Systems – The new Frontier
The very recent development of Cyber-Physical Systems (CPS) provides a smart infrastructure connecting abstract computational artifacts with the physical world. The solution to CPS must transcend the boundary between the cyber world and the physical world by providing integrated models addressing issues from both worlds simultaneously. This needs new theories, conceptual frameworks and engineering practice. In this paper, we set out the key requirements that must be met by CPS systems, and review and evaluate the progress that has been made in the development of theory, conceptual frameworks and practical applications. A case study of using CPS for enabling smart electricity grids within the industrial informatics field is then presented. Grand challenges to informatics posed by CPS are raised at the end.
However, building CPS is not a trivial task. It requires a new ground-breaking theory that models cyber and physical resources in a unified framework. This is a huge challenge that none of the current state-of-the-art methods are able to overcome due to the fact that computer science and control theory are independently developed based on overly-simplified assumptions of each other. For example, many key requirements (e.g. uncertainty, inaccuracy, etc.) crucial to physical systems are not captured and fully dealt with in the computer science research agenda. In a similar vein, computational complexity, system evolution and software failure are often ignored from the physical control theory viewpoint, which treats computation as a precise, error-free, static 'black-box'. The solution to CPS must transcend the boundary between the cyber world and the physical world by providing a unified infrastructure that permits integrated models addressing issues from both worlds simultaneously. This paper begins by setting out the requirements and then evaluates the progress that has been made in addressing these. This paper will show that CPS calls for new theories and some fundamental changes to the existing computing paradigm.
This short course will provide a introduction on the foundamental of Cyber Physical Systems (CPS), including CPS requirements, referencial architectures, Cyber physical system design and implementation, and plenty industrial applications.
Topic 1 – CPS Foundation, Systems of Systems, compare with Cloud and Grid
Topic 2 – CPS, IoT and WoT, standards and architecture requirements, babric and nodes
Topic 3 – Computation, networking and physical processes
Topic 4 – Enbedded computers and networks software systems
Topic 5 – Computation and Feedback Loops
Topic 6 – Software embeeded in devices, stockastic processes
Topic 7 – Dynamic integration of the physical processes and processes of transforming data
Topic 8 – Conjoin abstractions, modelling, design and analysis
Topic 9 – CPS, IoT and WoT, standards and requirement
Topic 10– CPS in Health care, Transporation and smart energy
4) Ontology Modeling, Engineering and Evolution
Ontologies are widely used in knowledge engineering, artificial intelligence and computer science, in applications related to knowledge management, natural language processing, e-commerce, intelligent information, information retrieval, database design and integration, bio?informatics, education, software development, and in new emerging fields like the semantic web. Ontologies include richer relations between terms. These rich relations enable the expression of domain?specific knowledge, without the need to include domain?specific terms. Therefore, a true ontology should contain not only a hierarchy of concepts organised by the subsumption relation but also other ‘semantic relations’ that specify how one concept is related to another. It is important to remember that the ontologies are organised by concepts, not words. This can be helpful in recognising and avoiding potential logical ambiguities. Ontologies developed independently for different purposes will often differ greatly from each other. The main purpose of an ontology is to enable communication between computer systems to perform certain types of computations and communication. The key ingredient that makes up an ontology is a vocabulary of basic terms and a precise specification of what those terms mean.
After this course you will grasp the principal concepts of ontologies and how ontologies and knowledge bases are related, and have gained experience in designing and developing an ontology.
Topic 1 – Ontology Definition
Topic 2 – Ontology Editor Protégé OWL
Topic 3 – Components of OWL Ontologies
Topic 4 – Ontology Fundamentals
Topic 5 – Ontology Engineering
Topic 6 – Ontology Implementation
Topic 7 – Ontology Reasoning Tools
Topic 8 – Ontology with Knowledge Base
Topic 9 – Ontology Maintenance
Topic 10– Cases studies
5) Wireless Sensor Networks for Environmental Sustainability
Wireless Sensor Networks (WSNs) has gathered a lot of interest recently, since it has opened new challenges with the development of interesting applications like surveillance, environment monitoring etc. The development of efficient protocols for WSNs communication as well as development of WSNs, motes itself has presented numerous challenges for the research community. Energy is the biggest concern for such networks and achieving high energy efficiency is of paramount importance for the longevity of the network. In order to combat this energy challenge energy efficient hardware and communication protocol design for such devices has gathered the intentions of the research community recently.
The workshop provides an ideal opportunity for industry and academic to gain in-depth understanding of WSN and its applications.
Topic 1 – Introduction and Overview of WSNs
Topic 2 – Commercial and Scientific Applications of WSNs like vehicular emission measurement etc.
Topic 3 – WSN Architecture
Topic 4 – WSN Communication Protocol Stack
Topic 5 – WSN system requirements and challenges
Topic 6 – WSN simulation tool
Topic 7 – Quality-of-Service
Topic 8 – Cross-layer optimisation
6) Security, Trust, and Privacy
Security, trust, privacy and risk are some of the fundamentals of business from providers and consumers’ point of view. Imaging losing all of your company’s data! Worse still, imagine if your competitors got hold of your information, financials, new research and development information. Unfortunately, in today’s world we need consider high levels of protection for our information and data by securing it from predators, loss and destruction and reducing our data’s vulnerability. An organisation needs to identify its system’s strengths and weaknesses and measure its overall performance against ideals and best practice. Trust has played a central role in human relationships and has been the subject of study in many fields including business, law, social science, philosophy and psychology. It has been vital to people being able to form contracts, carry out business and work together cooperatively and underpins many forms of collaboration. Closely to this notion of trust is the concept of reputation within a community with other peers. This is frequently used as the basis for judgment as to whether to trust an individual or organisation particularly in the absence of previous direct contact. Privacy issues have been gaining attention from law makers, regulators and the media. As a result, businesses are under pressure to draft privacy policies and post them on their web sites, chief privacy officers are becoming essential members of many enterprises and companies are taking pro-active steps to avoid the potential reputation damage of a privacy mistake. As new technologies are developed, they increasingly raise privacy concerns – the World Wide Web, wireless location-based services, and RFIP chips are just a few examples.
Additionally, the recent focus on national security and fighting terrorism has brought with it new concerns about governmental intrusions on person privacy. As we all know almost each e-Commerce transaction has some undesired outcomes which the person doing it hopes they will not occur when he is undertaking that particular transaction. The quantification of undesired outcomes occurring can be termed as Risk. This also applies to the transactions in the field of e-commerce. One major characteristic of the transactions in e-Commerce is that they may be done in virtual environments. Hence the consumer generally has no opportunity to see and try the product before buying it, showing that there is a high level of Risk involved in these types of transactions according to the consumer’s point of view. In order to address these issues, this course will provide an in-depth look into security, trust, privacy and risk in the business environment, as well as related technologies and case studies.
Attendees will gain understanding in security, trust, privacy and risk from philosophical, historical, ethical and technical perspectives.
Topic 1 -Introduction of information and data security
Topic 2 -Information and data security technologies (data inspection, data protection, data detection, reaction, and reflection)
Topic 3 -Introduction of trust and reputation
Topic 4 -Trustworthiness and reputation measurement and prediction methodologies (CCCI Metrics etc.)
Topic 5 -Introduction of privacy
Topic 6 -Privacy protection technologies and applications (online privacy protection, P3P, anonymity, pseudo-anonymity, government surveillance, privacy survey, etc.)
Topic 7 -Introduction of risk
Topic 8 -Risk measurement, prediction and management methodologies (CCAS Metrics etc.) and case studies
Topic 9 -Conclusion, feedback and future directions
7) Data Quality and Data Warehousing for Corporate Governance and Responsibility
The data quality issue has caught on in recent years, and more and more companies are attempting to cleanse the data. It is reported that 53% of companies have suffered losses due to the poor data quality, and the data quality problem costs US economy at over US $600 billion per annum. Data cleansing is the act of detecting and correcting corrupt or inaccurate records from data repositories. Data warehouse technology is designed for providing multi-dimensional analysis for decision-making. The aim of this course is to provide audiences with the theoretical and practical knowledge, tools and techniques of data quality, data cleansing, and data warehouse, and their applications in enterprises.
- Gain the necessary theoretical and practical knowledge in initiating.
- Leading a data quality assessment, data cleansing and data warehouse project in their organisations.
- Organise to move to the next agile, mobile and global era.
- Learn how to organisations to move to the next era.
Topic 1 - Why data quality, data cleansing and data warehouse – causes, problems, and challenges for corporate governance
Topic 2 - Data quality rules
Topic 3 - Data quality assessment methods
Topic 4 - Data cleansing issues, processes, methods, and applications
Topic 5 - Data warehouse: an overview
Topic 6 - Planning and business requirement for a data warehouse project
Topic 7 - Application of data warehouse in corporations
Topic 8 - Conclusion, feedback, and future directions