Optimal voltage support mechanism in distribution networks

Optimal scheduling of voltage regulators (VRs), fixed and switched capacitors and voltage on customer side of transformer (VCT) along with the optimal allocaton of VRs and capacitors are performed using a hybrid optimisation method based on discrete particle swarm optimisation and genetic algorithm. Direct optimisation of the tap position is not appropriate since in general the high voltage (HV) side voltage is not known. Therefore, the tap setting can be determined give the optimal VCT once the HV side voltage is known. The objective function is composed of the distribution line loss cost, the peak power loss cost and capacitors' and VRs' capital, operation and maintenance costs. The constraints are limits on bus voltage and feeder current along with VR taps. The bus voltage should be maintained within the standard level and the feeder current should not exceed the feeder-rated current. The taps are to adjust the output voltage of VRs between 90 and 110% of their input voltages. For validation of the proposed method, the 18-bus IEEE system is used. The results are compared with prior publications to illustrate the benefit of the employed technique. The results also show that the lowest cost planning for voltage profile will be achieved if a combination of capacitors, VRs and VCTs is considered.

Sharing with Creative Commons : a business model for content creators

Creative Commons (CC) is often seen as a social movement, dismissed by critics as a tool for hobbyists or academics who do not sell their creations to make a living. However, this paper argues that the licensing of creative copyright works under a CC licence does not preclude commercial gain. If used wisely, CC licences can be a useful tool for creators in their quest for commercial success. In particular, this paper argues that the sharing of creative works online under a CC licence allows creators to circumvent traditional distribution channels dominated by content intermediaries, whilst maintaining a level of control over their copyright works (i.e. explicitly reserving some rights but not all rights). This will be illustrated by case studies on how CC is being used by content creators and intermediaries respectively, and how successful their respective methods are in harnessing this tool.

Clone detection in repositories of business process models

As organizations reach to higher levels of business process management maturity, they often find themselves maintaining repositories of hundreds or even thousands of process models, representing valuable knowledge about their operations. Over time, process model repositories tend to accumulate duplicate fragments (also called clones) as new process models are created or extended by copying and merging fragments from other models. This calls for methods to detect clones in process models, so that these clones can be refactored as separate subprocesses in order to improve maintainability. This paper presents an indexing structure to support the fast detection of clones in large process model repositories. The proposed index is based on a novel combination of a method for process model decomposition (specifically the Refined Process Structure Tree), with established graph canonization and string matching techniques. Experiments show that the algorithm scales to repositories with hundreds of models. The experimental results also show that a significant number of non-trivial clones can be found in process model repositories taken from industrial practice.

Automated error correction of business process models

As order dependencies between process tasks can get complex, it is easy to make mistakes in process model design, especially behavioral ones such as deadlocks. Notions such as soundness formalize behavioral errors and tools exist that can identify such errors. However these tools do not provide assistance with the correction of the process models. Error correction can be very challenging as the intentions of the process modeler are not known and there may be many ways in which an error can be corrected. We present a novel technique for automatic error correction in process models based on simulated annealing. Via this technique a number of process model alternatives are identified that resolve one or more errors in the original model. The technique is implemented and validated on a sample of industrial process models. The tests show that at least one sound solution can be found for each input model and that the response times are short.

Global Business Today 2nd edition

Global Business Today is focused on the fundamentals of international business. Not only does this text provide coverage of the strategic imperatives of operating IB out of a small, dependent economy but it also builds a thorough worldwide orientation. In this edition, international business Graduate Attributes have been integrated throughout and there is topical discussion of issues such as the Doha round of trade negotiation, climate change and the rise of China and India. The authors recognise that case studies reinforce relevance and have therefore included either entirely new or significantly revised cases in every chapter. With a concise treatment of the crucial elements of an IB course, Global Business Today is the ideal text for a first subject in international busines

Configurable multi-perspective business process models

A configurable process model provides a consolidated view of a family of business processes. It promotes the reuse of proven practices by providing analysts with a generic modelling artifact from which to derive individual process models. Unfortunately, the scope of existing notations for configurable process modelling is restricted, thus hindering their applicability. Specifically, these notations focus on capturing tasks and control-flow dependencies, neglecting equally important ingredients of business processes such as data and resources. This research fills this gap by proposing a configurable process modelling notation incorporating features for capturing resources, data and physical objects involved in the performance of tasks. The proposal has been implemented in a toolset that assists analysts during the configuration phase and guarantees the correctness of the resulting process models. The approach has been validated by means of a case study from the film industry.

The phenomenon of business process management : practitioners’ emphasis

Since 2005, Business Process Management (BPM) has been one of the top 10 issues for CIO’s. However, while there is a general awareness what BPM is and what it relates to, one needs to ask ‘does everyone have the same understanding of the BPM phenomenon? And if not, is there a pattern to these conceptions and how do the ways of conceptualizing BPM differ?’ This paper presents the practitioner conceptions of BPM using a phenomenographic approach to detect variations in the BPM conceptions emphasised. 26 interviews were conducted with BPM practitioners with various scopes of work (namely program management, project management and execution levels) in this qualitative research. Distinct variations in how BPM is conceptualized among BPM practitioners are revealed, showing that emphasis is put depending on their scope of work either towards value generation, improvement or managing processes. This is of particular relevance to the Information Systems and BPM community in order to align the rigorous work done to date by the research community with the current understanding of BPM in the practitioner community.

Grounding action in visuo-haptic space using experience networks

Traditional approaches to the use of machine learning algorithms do not provide a method to learn multiple tasks in one-shot on an embodied robot. It is proposed that grounding actions within the sensory space leads to the development of action-state relationships which can be re-used despite a change in task. A novel approach called an Experience Network is developed and assessed on a real-world robot required to perform three separate tasks. After grounded representations were developed in the initial task, only minimal further learning was required to perform the second and third task.

Towards more complete satisfaction of customers in construction

In an environment where economic, political and technological change is the rule, a fundamental business strategy should be the defence of traditional markets and thoughtful entry into new markets, with an aim to increase market penetration and stimulate profit. The success of such a strategy will depend on the success of firms to do more and better for customers than their competitors. In other words, the firm’s primary competitive advantage will come from changes they implement to please their customers. In the construction industry, complexity of technical knowledge and construction processes have traditionally encouraged clients to play a largely passive role in the management of their project. However, today’s clients not only want to know about internal efficiency of their projects but also need to know how they and their contractors compare and compete against their competitors. Given the vulnerability of construction activities in the face of regional financial crisis, constructors need to be proactive in the search to improve their internal firm and project processes to ensure profitability and market responsiveness. In this context, reengineering is a radical design that emphasises customer satisfaction rather than cost reduction This paper discusses the crucial role of the client-project interface and how project networks could facilitate and improve information dissemination and sharing, collaborative efforts, decision-making and improved project climate. An intra-project network model is presented, and project managers’ roles and competencies in forming and coordinating project workgroups is discussed.

Distributed object tracking with robot and disjoint camera networks

We describe a novel two stage approach to object localization and tracking using a network of wireless cameras and a mobile robot. In the first stage, a robot travels through the camera network while updating its position in a global coordinate frame which it broadcasts to the cameras. The cameras use this information, along with image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to track the objects. We present results with a nine node indoor camera network to demonstrate that this approach is feasible and offers acceptable level of accuracy in terms of object locations.

Embedding information literacy in a first year business undergraduate course

This article reports on a project to embed information literacy skills development in a first-year undergraduate business course at an Australian university. In accordance with prior research suggesting that first-year students are over-confident about their skills, the project used an optional online quiz to allow students to pre-test their information literacy skills. The students' lower than expected results subsequently encouraged greater skill development. However, not all students elected to undertake the first quiz. A final assessable information literacy quiz increased the levels of student engagement, suggesting that skill development activities need to be made assessable. We found that undertaking the information literacy quizzes resulted in a statistically significant improvement in students' information literacy skills from the pre-test to the post-test. This research therefore extends previous research by providing an effective means of delivering information literacy skill development to large cohorts of first-year students.

A survey on the relationship between trust and interest similarity in online social networks

A remarkable growth in quantity and popularity of online social networks has been observed in recent years. There is a good number of online social networks exists which have over 100 million registered users. Many of these popular social networks offer automated recommendations to their users. This automated recommendations are normally generated using collaborative filtering systems based on the past ratings or opinions of the similar users. Alternatively, trust among the users in the network also can be used to find the neighbors while making recommendations. To obtain the optimum result, there must be a positive correlation exists between trust and interest similarity. Though the positive relations between trust and interest similarity are assumed and adopted by many researchers; no survey work on real life people’s opinion to support this hypothesis is found. In this paper, we have reviewed the state-of-the-art research work on trust in online social networks and have presented the result of the survey on the relationship between trust and interest similarity. Our result supports the assumed hypothesis of positive relationship between the trust and interest similarity of the users.

Developing trust networks based on user tagging information for recommendation making

Recommender systems are one of the recent inventions to deal with ever growing information overload. Collaborative filtering seems to be the most popular technique in recommender systems. With sufficient background information of item ratings, its performance is promising enough. But research shows that it performs very poor in a cold start situation where previous rating data is sparse. As an alternative, trust can be used for neighbor formation to generate automated recommendation. User assigned explicit trust rating such as how much they trust each other is used for this purpose. However, reliable explicit trust data is not always available. In this paper we propose a new method of developing trust networks based on user’s interest similarity in the absence of explicit trust data. To identify the interest similarity, we have used user’s personalized tagging information. This trust network can be used to find the neighbors to make automated recommendations. Our experiment result shows that the proposed trust based method outperforms the traditional collaborative filtering approach which uses users rating data. Its performance improves even further when we utilize trust propagation techniques to broaden the range of neighborhood.