A new distributed control strategy to coordinate multiple dstatcoms in LV network

Voltage rise is the main issue which limits the capacity of Low Voltage (LV) network to accommodate more Renewable Energy (RE) sources. In addition, voltage drop at peak load period is a significant power quality concern. This paper proposes a new robust voltage support strategy based on distributed coordination of multiple distribution static synchronous compensators (DSTATCOMs). The study focuses on LV networks with PV as the RE source for customers. The proposed approach applied to a typical LV network and its advantages are shown comparing with other voltage control strategies.

Soluble laminin and arginine-glycine-aspartic acid containing peptides differentially regulate type IV collagenase messenger RNA, activation, and localization in testicular cell culture

Rat testicular cells in culture produce several metalloproteinases including type IV collagenases (Sang et al. Biol Reprod 1990; 43:946-955, 956-964). We have now investigated the regulation of testicular cell type IV collagenase and other metalloprotemases in vitro. Soluble laminin stimulated Sertoli cell type IV collagenase mRNA levels. However, three peptides corresponding to different domains of the laminin molecule (CSRAKQAASIKVASADR, FALRGDNP, CLQDGDVRV) did not influence type IV collagenase mENA levels. Zyniographic analysis of medium collected from these cultures revealed that neither soluble laminin nor any of the peptides influenced 72-Wa type IV collagenase protein levels. However, peptide FALRGDNP resulted in both, a selective increase in two higher molecular-weight metalloprotemnases (83 kDa and 110 Wa and in an activation of the 72-Wa rat type IV collagenase. Interleukin-1, phorbol ester, testosterone, and FSH did not affect collagenase activation, lmmunocytochemical studies demonstrated that the addition of soluble laminin resulted in a redistribution of type IV collagenase from intracellular vesicles to the cell-substrate region beneath the cells. Peptide FALRGDNP induced a change from a vesicular to peripheral plasma membrane type of staining pattern. Zymography of plasma membrane preparations demonstrated triton-soluble gelatinases of 76 Wa, 83 Wa, and 110 Wa and a triton-insoluble gelatinase of 225 Wa, These results indicate that testicular cell type IV collagenase mRNA levels, enzyme activation, and distribution are influenced by laminin and RGD-containing peptides.

Tensor-based item recommendation using probabilistic ranking in social tagging systems

A common problem with the use of tensor modeling in generating quality recommendations for large datasets is scalability. In this paper, we propose the Tensor-based Recommendation using Probabilistic Ranking method that generates the reconstructed tensor using block-striped parallel matrix multiplication and then probabilistically calculates the preferences of user to rank the recommended items. Empirical analysis on two real-world datasets shows that the proposed method is scalable for large tensor datasets and is able to outperform the benchmarking methods in terms of accuracy.

Towards the development of 1-to-n human machine interfaces for unmanned aerial vehicles

Multi-touch interfaces across a wide range of hardware platforms are becoming pervasive. This is due to the adoption of smart phones and tablets in both the consumer and corporate market place. This paper proposes a human-machine interface to interact with unmanned aerial systems based on the philosophy of multi-touch hardware-independent high-level interaction with multiple systems simultaneously. Our approach incorporates emerging development methods for multi-touch interfaces on mobile platforms. A framework is defined for supporting multiple protocols. An open source solution is presented that demonstrates: architecture supporting different communications hardware; an extensible approach for supporting multiple protocols; and the ability to monitor and interact with multiple UAVs from multiple clients simultaneously. Validation tests were conducted to assess the performance, scalability and impact on packet latency under different client configurations.

Classifying natural aerial scenery for autonomous aircraft emergency landing

In this paper, we present an approach for image-based surface classification using multi-class Support Vector Machine (SVM). Classifying surfaces in aerial images is an important step towards an increased aircraft autonomy in emergency landing situations. We design a one-vs-all SVM classifier and conduct experiments on five data sets. Results demonstrate consistent overall performance figures over 88% and approximately 8% more accurate to those published on multi-class SVM on the KTH TIPS data set. We also show per-class performance values by using normalised confusion matrices. Our approach is designed to be executed online using a minimum set of feature attributes representing a feasible and ready-to-deploy system for onboard execution.

Enabling safe autonomous driving in real-world city traffic using multiple criteria decision making

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.

Bluetooth vehicle trajectory by fusing Bluetooth and loops : motorway travel time statistics

Loop detectors are widely used on the motorway networks where they provide point speed and traffic volumes. Models have been proposed for temporal and spatial generalization of speed for average travel time estimation. Advancement in technology provides complementary data sources such as Bluetooth MAC Scanner (BMS), detecting the MAC ID of the Bluetooth devices transported by the traveller. Matching the data from two BMS stations provides individual vehicle travel time. Generally, on the motorways loops are closely spaced, whereas BMS are placed few kilometres apart. In this research, we fuse BMSs and loops data to define the trajectories of the Bluetooth vehicles. The trajectories are utilised to estimate the travel time statistics between any two points along the motorway. The proposed model is tested using simulation and validated with real data from Pacific motorway, Brisbane. Comparing the model with the linear interpolation based trajectory provides significant improvements.

An object-oriented design of a World Model for autonomous city vehicles

This paper presents an object-oriented world model for the road traffic environment of autonomous (driver-less) city vehicles. The developed World Model is a software component of the autonomous vehicle's control system, which represents the vehicle's view of its road environment. Regardless whether the information is a priori known, obtained through on-board sensors, or through communication, the World Model stores and updates information in real-time, notifies the decision making subsystem about relevant events, and provides access to its stored information. The design is based on software design patterns, and its application programming interface provides both asynchronous and synchronous access to its information. Experimental results of both a 3D simulation and real-world experiments show that the approach is applicable and real-time capable.

Frizzled-7 receptor ectodomain expression in a colon cancer cell line induces morphological change and attenuates tumor growth

Frizzled (FZD) receptors have a conserved N-terminal extracellular cysteine-rich domain that interacts with Wnts and co-expression of the receptor ectodomain can antagonize FZD-mediated signalling. Using the ectodomain as an antagonist we have modulated endogenous FZD7 signalling in the moderately differentiated colon adenocarcinoma cell line, SK-CO-1. Unlike the parental cell line, which grows as tightly associated adherent cell clusters, the FZD7 ectodomain expressing cells display a spread out morphology and grow as a monolayer in tissue culture. This transition in morphology was associated with decreased levels of plasma membrane-associated E-cadherin and β-catenin, localized increased levels of vimentin and redistribution of α6 integrin to cellular processes in the FZD7 ectodomain expressing cells. The morphological and phenotype changes induced by FZD7 ectodomain expression in SK-CO-1 cells is thus consistent with the cells undergoing an epithelial-to-mesenchymal-like transition. Furthermore, initiation of tumor formation in a xenograft tumor growth assay was attenuated in the FZD7 ectodomain expressing cells. Our results indicate a pivotal role for endogenous FZD7 in morphology transitions that are associated with colon tumor initiation and progression.

eHealth-as-a-Service (eHaaS) : towards universal stakeholder engagement

With the introduction of the Personally Controlled Health Record (PCEHR), the Australian public is being asked to accept greater responsibility for their healthcare by taking an active role in the management of personal health information. Although well designed, constructed and intentioned, policy and privacy concerns have resulted in an eHealth model that may impact future health sharing requirements. Hence, as a case study for a consumer eHealth initative in the Australian context, eHealth-as-a-Service (eHaaS) serves as a disruptive step in in the aggregation and transformation of health information for use as real-world knowledge. The strategic value of extending the community Health Record Bank (HRB) model lies in the ability to automatically draw on a multitude of relevant data repositories and sources to create a single source of the truth and to engage market forces to create financial sustainability. The opportunity to transform the beleaguered Australian PCEHR into a realisable and sustainable technology consumption model for patient safety is explored. Moreover, the current clerical focus of healthcare practitioners acting in the role of de facto record keepers is renegotiated to establish a shared knowledge creation landscape of action for safer patient interventions. To achieve this potential however requires a platform that will facilitate efficient and trusted unification of all health information available in real-time across the continuum of care. eHaaS provides a sustainable environment and encouragement to realise this potential.

Universal codes from switching strategies

We discuss algorithms for combining sequential prediction strategies, a task which can be viewed as a natural generalisation of the concept of universal coding. We describe a graphical language based on Hidden Markov Models for defining prediction strategies, and we provide both existing and new models as examples. The models include efficient, parameterless models for switching between the input strategies over time, including a model for the case where switches tend to occur in clusters, and finally a new model for the scenario where the prediction strategies have a known relationship, and where jumps are typically between strongly related ones. This last model is relevant for coding time series data where parameter drift is expected. As theoretical contributions we introduce an interpolation construction that is useful in the development and analysis of new algorithms, and we establish a new sophisticated lemma for analysing the individual sequence regret of parameterised models.

Social engineering in social networking sites : the art of impersonation

Social networking sites (SNSs), with their large number of users and large information base, seem to be the perfect breeding ground for exploiting the vulnerabilities of people, who are considered the weakest link in security. Deceiving, persuading, or influencing people to provide information or to perform an action that will benefit the attacker is known as “social engineering.” Fraudulent and deceptive people use social engineering traps and tactics through SNSs to trick users into obeying them, accepting threats, and falling victim to various crimes such as phishing, sexual abuse, financial abuse, identity theft, and physical crime. Although organizations, researchers, and practitioners recognize the serious risks of social engineering, there is a severe lack of understanding and control of such threats. This may be partly due to the complexity of human behaviors in approaching, accepting, and failing to recognize social engineering tricks. This research aims to investigate the impact of source characteristics on users’ susceptibility to social engineering victimization in SNSs, particularly Facebook. Using grounded theory method, we develop a model that explains what and how source characteristics influence Facebook users to judge the attacker as credible.

Copper-capped carbon nanocones on silicon : plasma-enabled growth control

Controlled self-organized growth of vertically aligned carbon nanocone arrays in a radio frequency inductively coupled plasma-based process is studied. The experiments have demonstrated that the gaps between the nanocones, density of the nanocone array, and the shape of the nanocones can be effectively controlled by the process parameters such as gas composition (hydrogen content) and electrical bias applied to the substrate. Optical measurements have demonstrated lower reflectance of the nanocone array as compared with a bare Si wafer, thus evidencing their potential for the use in optical devices. The nanocone formation mechanism is explained in terms of redistribution of surface and volumetric fluxes of plasma-generated species in a developing nanocone array and passivation of carbon in narrow gaps where the access of plasma ions is hindered. Extensive numerical simulations were used to support the proposed growth mechanism.

Plasma-controlled adatom delivery and (re)distribution: Enabling uninterrupted, low-temperature growth of ultralong vertically aligned single walled carbon nanotubes

Large-scale (∼109 atoms) numerical simulations reveal that plasma-controlled dynamic delivery and redistribution of carbon atoms between the substrate and nanotube surfaces enable the growth of ultralong single walled carbon nanotubes (SWCNTs) and explain the common experimental observation of slower growth at advanced stages. It is shown that the plasma-based processes feature up to two orders of magnitude higher growth rates than equivalent neutral-gas systems and are better suited for the SWCNT synthesis at low nanodevice friendly temperatures. © 2008 American Institute of Physics.

Supporting process model validation through natural language generation

The design and development of process-aware information systems is often supported by specifying requirements as business process models. Although this approach is generally accepted as an effective strategy, it remains a fundamental challenge to adequately validate these models given the diverging skill set of domain experts and system analysts. As domain experts often do not feel confident in judging the correctness and completeness of process models that system analysts create, the validation often has to regress to a discourse using natural language. In order to support such a discourse appropriately, so-called verbalization techniques have been defined for different types of conceptual models. However, there is currently no sophisticated technique available that is capable of generating natural-looking text from process models. In this paper, we address this research gap and propose a technique for generating natural language texts from business process models. A comparison with manually created process descriptions demonstrates that the generated texts are superior in terms of completeness, structure, and linguistic complexity. An evaluation with users further demonstrates that the texts are very understandable and effectively allow the reader to infer the process model semantics. Hence, the generated texts represent a useful input for process model validation.