Improving the efficiency of high power piezoelectric transducers for industrial applications

Most high-power ultrasound applications are driven by two-level inverters. However, the broad spectral content of the two-level pulse results in undesired harmonics that can decrease the performance of the system significantly. On the other hand, it is crucial to excite the piezoelectric devices at their main resonant frequency in order to have maximum energy conversion. Therefore a high-quality, low-distorted power signal is needed to excite the high-power piezoelectric transducer at its resonant frequency. This study proposes an efficient approach to develop the performance of high-power ultrasonic applications using multilevel inverters along with a frequency estimation algorithm. In this method, the resonant frequencies are estimated based on relative minimums of the piezoelectric impedance frequency response. The algorithm follows the resonant frequency variation and adapts the multilevel inverter reference frequency to drive an ultrasound transducer at high power. Extensive simulation and experimental results indicate the effectiveness of the proposed approach.

Using static analysis for automatic assessment and mitigation of unwanted and malicious activities within Android applications

In the last decade, smartphones have gained widespread usage. Since the advent of online application stores, hundreds of thousands of applications have become instantly available to millions of smart-phone users. Within the Android ecosystem, application security is governed by digital signatures and a list of coarse-grained permissions. However, this mechanism is not fine-grained enough to provide the user with a sufficient means of control of the applications' activities. Abuse of highly sensible private information such as phone numbers without users' notice is the result. We show that there is a high frequency of privacy leaks even among widely popular applications. Together with the fact that the majority of the users are not proficient in computer security, this presents a challenge to the engineers developing security solutions for the platform. Our contribution is twofold: first, we propose a service which is able to assess Android Market applications via static analysis and provide detailed, but readable reports to the user. Second, we describe a means to mitigate security and privacy threats by automated reverse-engineering and refactoring binary application packages according to the users' security preferences.

A simulation framework for smart meter security evaluation

The evolution of classic power grids to smart grids creates chances for most participants in the energy sector. Customers can save money by reducing energy consumption, energy providers can better predict energy demand and environment benefits since lower energy consumption implies lower energy production including a decrease of emissions from plants. But information and communication systems supporting smart grids can also be subject to classical or new network attacks. Attacks can result in serious damage such as harming privacy of customers, creating economical loss and even disturb the power supply/demand balance of large regions and countries. In this paper, we give an overview about the German smart measuring architecture, protocols and security. Afterwards, we present a simulation framework which enables researchers to analyze security aspects of smart measuring scenarios.

High-sensitivity fiber Bragg grating temperature sensor at high temperature [一种高温下高灵敏光纤光栅温度传感器的制作方法]

A method of making full use of the durable strain which fiber Bragg grating (FBG) can undertake is presented, which hugely improves the sensitivities of FBG temperature sensors at high temperature. When a sensor is manufactured at room temperature, its FBG should be given a pre-relaxing length according to the temperature it is asked to measure; once the temperature rise to the asked one, its FBG starts to be stretched and it starts to work with high sensitivity. The relationship between the pre-relaxing length and the working temperature is analyzed. In experiments, when the pre-relaxing lengths are 0.2mm、0.5mm、0.6mm, the working temperatures rise 25℃、50℃、61℃, respectively, and the sensitivities are almost the same (675pm/℃). The facts that the experimental results agree well with the theoretical analyses verify this method’s validity.

The application of fiber Bragg grating sensor to high precision temperature measurement [基于光纤光栅的高精度测温传感器研究]

Basing on the character that Fiber Bragg Grating (FBG) is sensitive to both temperature and strain, by using Al and Fe-Ni alloy’s bimetal structure, we successfully design and manufacture a high accuracy FBG temperature sensor for earthquake premonition. Furthermore, we analyze the accuracy of the FBG sensors with enhanced sensitivity for the first time, and get its accuracy is up to ±0.05℃ with highest resolution ever in all FBG temperature sensors (0.0014℃/pm). This work experimentally proves the feasibility of using FBG in the earthquake premonition monitoring, and builds the foundation for the application of optic technology in earthquake premonition monitoring.

Modeling and multiway analysis of chatroom tensors

This work identifies the limitations of n-way data analysis techniques in multidimensional stream data, such as Internet chat room communications data, and establishes a link between data collection and performance of these techniques. Its contributions are twofold. First, it extends data analysis to multiple dimensions by constructing n-way data arrays known as high order tensors. Chat room tensors are generated by a simulator which collects and models actual communication data. The accuracy of the model is determined by the Kolmogorov-Smirnov goodness-of-fit test which compares the simulation data with the observed (real) data. Second, a detailed computational comparison is performed to test several data analysis techniques including svd [1], and multi-way techniques including Tucker1, Tucker3 [2], and Parafac [3].

Using ‘think aloud’ as a strategy for improving clinical reasoning in high fidelity case-based simulation for undergraduate nursing students.

Theme Paper for Curriculum innovation and enhancement theme AIM: This paper reports on a research project that trialled an educational strategy implemented in an undergraduate nursing curriculum. The project aimed to explore the effectiveness of ‘think aloud’ as a strategy for improving clinical reasoning for students in simulated clinical settings. BACKGROUND: Nurses are required to apply and utilise critical thinking skills to enable clinical reasoning and problem solving in the clinical setting (Lasater, 2007). Nursing students are expected to develop and display clinical reasoning skills in practice, but may struggle articulating reasons behind decisions about patient care. The ‘think aloud’ approach is an innovative learning/teaching method which can create an environment suitable for developing clinical reasoning skills in students (Banning, 2008, Lee and Ryan-Wenger, 1997). This project used the ‘think aloud’ strategy within a simulation context to provide a safe learning environment in which third year students were assisted to uncover cognitive approaches to assist in making effective patient care decisions, and improve their confidence, clinical reasoning and active critical reflection about their practice. MEHODS: In semester 2 2011 at QUT, third year nursing students undertook high fidelity simulation (some for the first time), commencing in September of 2011. There were two cohorts for strategy implementation (group 1= used think aloud as a strategy within the simulation, group 2= no specific strategy outside of nursing assessment frameworks used by all students) in relation to problem solving patient needs. The think aloud strategy was described to students in their pre-simulation briefing and allowed time for clarification of this strategy. All other aspects of the simulations remained the same, (resources, suggested nursing assessment frameworks, simulation session duration, size of simulation teams, preparatory materials). Ethics approval has been obtained for this project. RESULTS: Results of a qualitative analysis (in progress- will be completed by March 2012) of student and facilitator reports on students’ ability to meet the learning objectives of solving patient problems using clinical reasoning and experience with the ‘think aloud’ method will be presented. A comparison of clinical reasoning learning outcomes between the two groups will determine the effect on clinical reasoning for students responding to patient problems. CONCLUSIONS: In an environment of increasingly constrained clinical placement opportunities, exploration of alternate strategies to improve critical thinking skills and develop clinical reasoning and problem solving for nursing students is imperative in preparing nurses to respond to changing patient needs.

Non-intrusive continuous user behaviour analysis using computerized systems

There are different ways to authenticate humans, which is an essential prerequisite for access control. The authentication process can be subdivided into three categories that rely on something someone i) knows (e.g. password), and/or ii) has (e.g. smart card), and/or iii) is (biometric features). Besides classical attacks on password solutions and the risk that identity-related objects can be stolen, traditional biometric solutions have their own disadvantages such as the requirement of expensive devices, risk of stolen bio-templates etc. Moreover, existing approaches provide the authentication process usually performed only once initially. Non-intrusive and continuous monitoring of user activities emerges as promising solution in hardening authentication process: iii-2) how so. behaves. In recent years various keystroke dynamic behavior-based approaches were published that are able to authenticate humans based on their typing behavior. The majority focuses on so-called static text approaches, where users are requested to type a previously defined text. Relatively few techniques are based on free text approaches that allow a transparent monitoring of user activities and provide continuous verification. Unfortunately only few solutions are deployable in application environments under realistic conditions. Unsolved problems are for instance scalability problems, high response times and error rates. The aim of this work is the development of behavioral-based verification solutions. Our main requirement is to deploy these solutions under realistic conditions within existing environments in order to enable a transparent and free text based continuous verification of active users with low error rates and response times.

Combinatorial design of key distribution mechanisms for wireless sensor networks

Key distribution is one of the most challenging security issues in wireless sensor networks where sensor nodes are randomly scattered over a hostile territory. In such a sensor deployment scenario, there will be no prior knowledge of post deployment configuration. For security solutions requiring pair wise keys, it is impossible to decide how to distribute key pairs to sensor nodes before the deployment. Existing approaches to this problem are to assign more than one key, namely a key-chain, to each node. Key-chains are randomly drawn from a key-pool. Either two neighbouring nodes have a key in common in their key-chains, or there is a path, called key-path, among these two nodes where each pair of neighbouring nodes on this path has a key in common. Problem in such a solution is to decide on the key-chain size and key-pool size so that every pair of nodes can establish a session key directly or through a path with high probability. The size of the key-path is the key factor for the efficiency of the design. This paper presents novel, deterministic and hybrid approaches based on Combinatorial Design for key distribution. In particular, several block design techniques are considered for generating the key-chains and the key-pools. Comparison to probabilistic schemes shows that our combinatorial approach produces better connectivity with smaller key-chain sizes.

Solving inherent problems of anomaly detection by cooperation

Anomaly detection compensates shortcomings of signature-based detection such as protecting against Zero-Day exploits. However, Anomaly Detection can be resource-intensive and is plagued by a high false-positive rate. In this work, we address these problems by presenting a Cooperative Intrusion Detection approach for the AIS, the Artificial Immune System, as an example for an anomaly detection approach. In particular we show, how the cooperative approach reduces the false-positive rate of the detection and how the overall detection process can be organized to account for the resource constraints of the participating devices. Evaluations are carried out with the novel network simulation environment NeSSi as well as formally with an extension to the epidemic spread model SIR

An extensible simulation framework for critical infrastructure security

We introduce the Network Security Simulator (NeSSi2), an open source discrete event-based network simulator. It incorporates a variety of features relevant to network security distinguishing it from general-purpose network simulators. Compared to the predecessor NeSSi, it was extended with a three-tier plugin architecture and a generic network model to shift its focus towards simulation framework for critical infrastructures. We demonstrate the gained adaptability by different use cases

Kerberos based security system for session initiation protocol

Session Initiation Protocol (SIP) is developed to provide advanced voice services over IP networks. SIP unites telephony and data world, permitting telephone calls to be transmitted over Intranets and Internet. Increase in network performance and new mechanisms for guaranteed quality of service encourage this consolidation to provide toll cost savings. Security comes up as one of the most important issues when voice communication and critical voice applications are considered. Not only the security methods provided by traditional telephony systems, but also additional methods are required to overcome security risks introduced by the public IP networks. SIP considers security problems of such a consolidation and provides a security framework. There are several security methods defined within SIP specifications and extensions. But, suggested methods can not solve all the security problems of SIP systems with various system requirements. In this thesis, a Kerberos based solution is proposed for SIP security problems, including SIP authentication and privacy. The proposed solution tries to establish flexible and scalable SIP system that will provide desired level of security for voice communications and critical telephony applications.

Militarism and International Relations : Political economy, security, theory, edited by Anna Stavrianakis and Jan Selby, Abingdon, Routledge, 2012, 212 pp., £80.00 (hardback), ISBN 978-0-415-61491-7

An engaging narrative is maintained throughout this edited collection of articles that address the issue of militarism in international relations. The book seamlessly integrates historical and contemporary perspectives on militarism with theory and relevant international case studies, resulting in a very informative read. The work is comprised of three parts. Part 1 deals with the theorisation of militarism and includes chapters by Anna Stavrianakis and Jan Selby, Martin Shaw, Simon Dalby, and Nicola Short. It covers a range of topics relating to historical and contemporary theories of militarism, geopolitical threat construction, political economy, and the US military’s ‘cultural turn’.

Fast exact nearest neighbour matching in high dimensions using d-D Sort

Data structures such as k-D trees and hierarchical k-means trees perform very well in approximate k nearest neighbour matching, but are only marginally more effective than linear search when performing exact matching in high-dimensional image descriptor data. This paper presents several improvements to linear search that allows it to outperform existing methods and recommends two approaches to exact matching. The first method reduces the number of operations by evaluating the distance measure in order of significance of the query dimensions and terminating when the partial distance exceeds the search threshold. This method does not require preprocessing and significantly outperforms existing methods. The second method improves query speed further by presorting the data using a data structure called d-D sort. The order information is used as a priority queue to reduce the time taken to find the exact match and to restrict the range of data searched. Construction of the d-D sort structure is very simple to implement, does not require any parameter tuning, and requires significantly less time than the best-performing tree structure, and data can be added to the structure relatively efficiently.