Multiple distribution static synchronous compensators for distribution feeder voltage support

The potential of multiple distribution static synchronous compensators (DSTATCOMs) to improve the voltage profile of radial distribution networks has been reported in the literature by few authors. However, the operation of multiple DSTATCOMs across a distribution feeder may introduce control interactions and/or voltage instability. This study proposes a control scheme that alleviates interactions among controllers and enhances proper reactive power sharing among DSTATCOMs. A generalised mathematical model is presented to analyse the interactions among any number of DSTATCOMs in the network. The criterion for controller design is developed by conducting eigenvalue analysis on this mathematical model. The proposed control scheme is tested in time domain on a sample radial distribution feeder installed with multiple DSTATCOMs and test results are presented.

A capability framework visualisation for multiple heterogeneous UAVs : from a mission commander's perspective

There is an increased interested in Uninhabited Aerial Vehicle (UAV) operations and research into advanced methods for commanding and controlling multiple heterogeneous UAVs. Research into areas of supervisory control has rapidly increased. Past research has investigated various approaches of autonomous control and operator limitation to improve mission commanders' Situation Awareness (SA) and cognitive workload. The aim of this paper is to address this challenge through a visualisation framework of UAV information constructed from Information Abstraction (IA). This paper presents the concept and process of IA, and the visualisation framework (constructed using IA), the concept associated with the Level Of Detail (LOD) indexing method, the visualisation of an example of the framework. Experiments will test the hypothesis that, the operator will be able to achieve increased SA and reduced cognitive load with the proposed framework.

Multiple cameras for audio-visual speech recognition in an automotive environment

Audio-visualspeechrecognition, or the combination of visual lip-reading with traditional acoustic speechrecognition, has been previously shown to provide a considerable improvement over acoustic-only approaches in noisy environments, such as that present in an automotive cabin. The research presented in this paper will extend upon the established audio-visualspeechrecognition literature to show that further improvements in speechrecognition accuracy can be obtained when multiple frontal or near-frontal views of a speaker's face are available. A series of visualspeechrecognition experiments using a four-stream visual synchronous hidden Markov model (SHMM) are conducted on the four-camera AVICAR automotiveaudio-visualspeech database. We study the relative contribution between the side and central orientated cameras in improving visualspeechrecognition accuracy. Finally combination of the four visual streams with a single audio stream in a five-stream SHMM demonstrates a relative improvement of over 56% in word recognition accuracy when compared to the acoustic-only approach in the noisiest conditions of the AVICAR database.

Piecing together an integrative taxonomic puzzle: microsatellite, wing shape and aedeagus length analyses of Bactrocera dorsalis s.l. (Diptera: Tephritidae) find no evidence of multiple lineages in a proposed contact zone along the Thai/Malay Peninsula

Bactrocera dorsalis (Hendel) and B. papayae Drew & Hancock represent a closely related sibling species pair for which the biological species limits are unclear; i.e., it is uncertain if they are truely two biological species, or one biological species which has been incorrectly taxonomically split. The geographic ranges of the two taxa are thought to abut or overlap on or around the Isthmus of Kra, a recognised biogeographic barrier located on the narrowest portion of the Thai Peninsula. We collected fresh material of B. dorsalis sensu lato (i.e., B. dorsalis sensu stricto + B. papayae) in a north-south transect down the Thai Peninsula, from areas regarded as being exclusively B. dorsalis s.s., across the Kra Isthmus, and into regions regarded as exclusively B. papayae. We carried out microsatellite analyses and took measurements of male genitalia and wing shape. Both the latter morphological tests have been used previously to separate these two taxa. No significant population structuring was found in the microsatellite analysis and results were consistent with an interpretation of one, predominantly panmictic population. Both morphological datasets showed consistent, clinal variation along the transect, with no evidence for disjunction. No evidence in any tests supported historical vicariance driven by the Isthmus of Kra, and none of the three datasets supported the current taxonomy of two species. Rather, within and across the area of range overlap or abutment between the two species, only continuous morphological and genetic variation was recorded. Recognition that morphological traits previously used to separate these taxa are continuous, and that there is no genetic evidence for population segregation in the region of suspected species overlap, is consistent with a growing body of literature that reports no evidence of biological differentiation between these taxa.

Forecasting success on large projects : developing reliable scales to predict multiple perspectives by multiple stakeholders over multiple time frames

Our aim is to develop a set of leading performance indicators to enable managers of large projects to forecast during project execution how various stakeholders will perceive success months or even years into the operation of the output. Large projects have many stakeholders who have different objectives for the project, its output, and the business objectives they will deliver. The output of a large project may have a lifetime that lasts for years, or even decades, and ultimate impacts that go beyond its immediate operation. How different stakeholders perceive success can change with time, and so the project manager needs leading performance indicators that go beyond the traditional triple constraint to forecast how key stakeholders will perceive success months or even years later. In this article, we develop a model for project success that identifies how project stakeholders might perceive success in the months and years following a project. We identify success or failure factors that will facilitate or mitigate against achievement of those success criteria, and a set of potential leading performance indicators that forecast how stakeholders will perceive success during the life of the project's output. We conducted a scale development study with 152 managers of large projects and identified two project success factor scales and seven stakeholder satisfaction scales that can be used by project managers to predict stakeholder satisfaction on projects and so may be used by the managers of large projects for the basis of project control.

Multiple founders and firm value

In this paper, we highlight the existence of multi-founder firms, which were founded by multiple individuals (with no family connections) who are still actively involved in the firm as directors and/or managers. These firms provide a unique setting to shed further light on the net valuation effects of founder involvement. In particular, multi-founder firms provide us with the opportunity to examine the benefits and costs to shareholders of multiple founders involved as directors, CEOs and managers in the same firm. Our analysis indicates that multi-founder firms are more valuable than all other types of firms, including single-founder firms and family firms, with the valuation premium positively related to the number of founders involved in the firm. Further analysis confirms that this valuation premium is linked to the direct involvement of the multiple founders as directors and CEOs. However, further founder involvement in vice president positions has a negative relationship with firm value.

Antibiotics overuse in children with upper respiratory tract infections in Saudi Arabia : risk factors and potential interventions

Background: Antibiotics misuse is currently one of the major public health issues worldwide. This misuse can lead to the development of bacterial resistance, increasing the burden of chronic diseases, rising costs of health services, and the development of side effects. Several factors may influence this pattern of overuse. Objectives:This article will review the pertinent factors contributing to the overuse of antibiotics worldwide, and to assess the intervention strategies to limit this overuse. Methods: studies about antibiotics use in children were reviewed from several electronic databases, such as MEDLINE and Pubmed. Results: Factors contributing to the overuse of antibiotics could include psychosocial factors, such as behaviors and attitudes (e.g. self-medication, over-the-counter medication, or patients/parents pressure), and demographic factors, such as socio-economic status and education level. Several intervention strategies were reported to be effective in reducing the overuse of antibiotics, such as health education, doctor-patient communication, and policies change. Multifaceted interventions were found to be the most effective in reducing the antibiotics overuse.

A penalty-based grouping genetic algorithm for multiple composite SaaS components clustering in Cloud

Software as a Service (SaaS) in Cloud is getting more and more significant among software users and providers recently. A SaaS that is delivered as composite application has many benefits including reduced delivery costs, flexible offers of the SaaS functions and decreased subscription cost for users. However, this approach has introduced a new problem in managing the resources allocated to the composite SaaS. The resource allocation that has been done at the initial stage may be overloaded or wasted due to the dynamic environment of a Cloud. A typical data center resource management usually triggers a placement reconfiguration for the SaaS in order to maintain its performance as well as to minimize the resource used. Existing approaches for this problem often ignore the underlying dependencies between SaaS components. In addition, the reconfiguration also has to comply with SaaS constraints in terms of its resource requirements, placement requirement as well as its SLA. To tackle the problem, this paper proposes a penalty-based Grouping Genetic Algorithm for multiple composite SaaS components clustering in Cloud. The main objective is to minimize the resource used by the SaaS by clustering its component without violating any constraint. Experimental results demonstrate the feasibility and the scalability of the proposed algorithm.

Numerical solution of stress intensity factors of multiple cracks in great number with eigen COD boundary integral equations

Based on the eigen crack opening displacement (COD) boundary integral equations, a newly developed computational approach is proposed for the analysis of multiple crack problems. The eigen COD particularly refers to a crack in an infinite domain under fictitious traction acting on the crack surface. With the concept of eigen COD, the multiple cracks in great number can be solved by using the conventional displacement discontinuity boundary integral equations in an iterative fashion with a small size of system matrix. The interactions among cracks are dealt with by two parts according to the distances of cracks to the current crack. The strong effects of cracks in adjacent group are treated with the aid of the local Eshelby matrix derived from the traction BIEs in discrete form. While the relatively week effects of cracks in far-field group are treated in the iteration procedures. Numerical examples are provided for the stress intensity factors of multiple cracks, up to several thousands in number, with the proposed approach. By comparing with the analytical solutions in the literature as well as solutions of the dual boundary integral equations, the effectiveness and the efficiencies of the proposed approach are verified.

Online multiple profile manager for eHealth information sharing

Online social networks connect millions of people around the globe. These electronic bonds make individuals comfortable with their behaviours. Such positive signs of sharing information is useful phenomena requires consideration to establish a socio-scientific effect. Recently, many web users have more than one social networking account. This means a user may hold multiple profiles which are stored in different Social Network Sites (SNNs). Maintaining these multiple online social network profiles is cumbersome and time-consuming [1]. In this paper we will propose a framework for the management of a user's multiple profiles. A demonstrator, called Multiple Profile Manager (MPM), will be showcased to illustrate how effective the framework will be.