EMG biofeedback in the treatment of tinnitus : an experimental evaluation

26 tinnitus patients received either electromyogram (EMG) biofeedback with counterdemand instructions, EMG biofeedback with neutral demand instructions, or no treatment. Assessment was conducted on self-report measures of the distress associated with tinnitus, the loudness, annoyance and awareness of tinnitus, sleep-onset difficulties, depression, and anxiety. Audiological assessment of tinnitus was also conducted and EMG levels were measured (the latter only in the 2 treatment groups). No significant treatment effects were found on any of the measures. There was a significant decrease in the ratings of tinnitus awareness over the assessment occasions, but the degree of change was equivalent for treated and untreated groups. Results do not support the assertion that EMG biofeedback is an effective treatment for tinnitus.

An evaluation framework for educational reform projects for teacher quality improvements in developing countries : a case study of Egyptian education reform

The role of the evaluation for Official Development Assistance (ODA) enterprises including educational development has become critical after increasing “aid fatigue” experienced by the international community in the 1990s. To date, however, monitoring and evaluating outcomes of the projects has been limited to the project life. Consequently these have been mainly through the international aid agencies. Furthermore, the monitoring and evaluation led by international aid agencies have paid little attention to aspects of the sustainability of technical cooperation in educational development. To sustain the impact of technical cooperation, the reinforcement of evaluation has drawn increasing attention in light of the emerging modalities in international development. Therefore this research was inspired to investigate alternative evaluation frameworks for an educational reform project for teacher quality improvement that may increase possibilities for long term sustainability. Importantly, the new modalities in international development and educational issues provide new options. In addition, the research reviewed theoretical and practical issues surrounding evaluation in general, and highlighted the evaluation of education reform projects. The research reported explored via case studies, the evaluation processes employed by the Egyptian education reform projects implemented by the Japan International Cooperation Agency (JICA) and the United Nations Children’s Fund (UNICEF). The case studies used three data sources (archival and relevant documents, a survey questionnaire and interviews) to illuminate the contextually-embedded evaluation processes. The research found that process evaluation is a potential alternative method since it is likely to be locally institutionalised, which may yield long-term sustainability of the projects.

Fast searching algorithm for candidate satellite-node set in NLMG

The Node-based Local Mesh Generation (NLMG) algorithm, which is free of mesh inconsistency, is one of core algorithms in the Node-based Local Finite Element Method (NLFEM) to achieve the seamless link between mesh generation and stiffness matrix calculation, and the seamless link helps to improve the parallel efficiency of FEM. Furthermore, the key to ensure the efficiency and reliability of NLMG is to determine the candidate satellite-node set of a central node quickly and accurately. This paper develops a Fast Local Search Method based on Uniform Bucket (FLSMUB) and a Fast Local Search Method based on Multilayer Bucket (FLSMMB), and applies them successfully to the decisive problems, i.e. presenting the candidate satellite-node set of any central node in NLMG algorithm. Using FLSMUB or FLSMMB, the NLMG algorithm becomes a practical tool to reduce the parallel computation cost of FEM. Parallel numerical experiments validate that either FLSMUB or FLSMMB is fast, reliable and efficient for their suitable problems and that they are especially effective for computing the large-scale parallel problems.

An evaluation of how well undergraduate property students are prepared for commencing their careers

The evolution of property education to adapt to the changing business environment requires changes to course content, methods of delivery and assessment. Many universities have a special interest in understanding how successfully students transition in and transition out of property programs. This study sought the views of final year students engaged in professional employment, employer representatives and representatives from professional associations to assess the preparedness of students to commence professional employment. The study showed that generally students possessed an appropriate level of technical and ‘soft skills’ to enter the professional realm with development required in some areas. All stakeholders agreed that the transition out of university was made more seamless through greater engagement with industry through field work and work experience from the intermediate stages of the property course.

An evaluation of viability of public private partnerships in social infrastructure procurement projects in Queensland, Australia

Public private partnerships (PPP) have been widely used as a method for public infrastructure project delivery not only locally and internationally, however the adoption of PPPs in social infrastructure procurement has still been very limited. The objective of this paper is to investigate the potential of implementation of current PPP framework in social affordable housing projects in South East Queensland. Data were collected from 22 interviewees with rich experiences in the industry. The findings of this study show that affordable housing investment have been considered by the industry practitioners as a risky business in comparison to other private rental housing investment. The main determents of the adoption of PPPs in social infrastructure project are the tenant-related factors, such as the inability of paying rent and the inability of caring the property. The study also suggests the importance of seeking strategic partnership with community-based organisation that has experiences in managing similar tenants’ profiles. Current PPP guideline is also viewed as inappropriate for the affordable housing projects, but the principle of VFM framework and risk allocation in PPPs still be applied to the affordable housing projects. This study helps to understand the viability of PPP in social housing procurement projects, and point out the importance of developing guideline for multi-stakeholder partnership and the expansion of the current VFM and PPPs guidelines.

Robust video stabilisation algorithm using feature point selection and delta optical flow

In this study, the authors propose a novel video stabilisation algorithm for mobile platforms with moving objects in the scene. The quality of videos obtained from mobile platforms, such as unmanned airborne vehicles, suffers from jitter caused by several factors. In order to remove this undesired jitter, the accurate estimation of global motion is essential. However it is difficult to estimate global motions accurately from mobile platforms due to increased estimation errors and noises. Additionally, large moving objects in the video scenes contribute to the estimation errors. Currently, only very few motion estimation algorithms have been developed for video scenes collected from mobile platforms, and this paper shows that these algorithms fail when there are large moving objects in the scene. In this study, a theoretical proof is provided which demonstrates that the use of delta optical flow can improve the robustness of video stabilisation in the presence of large moving objects in the scene. The authors also propose to use sorted arrays of local motions and the selection of feature points to separate outliers from inliers. The proposed algorithm is tested over six video sequences, collected from one fixed platform, four mobile platforms and one synthetic video, of which three contain large moving objects. Experiments show our proposed algorithm performs well to all these video sequences.

Empirical evaluation of a service analysis and design methodology

Service-orientation has gained widespread acceptance and is increasingly being employed as a paradigm for structuring both business and IT architectures. An earlier study of extant service analysis and design methodologies discovered a need for holistic approaches that equally account for both business and software services, which motivated the design of a new, consolidated service analysis and design methodology. A challenge in design-oriented research is to evaluate the utility of the newly created artefacts (here: the methodology), as they are often intended to become part of complex socio-technical systems. Therefore, after presenting a brief overview of the consolidated methodology, the paper discusses possible approaches for the “evaluate” phase of this design-science research process and presents the results of an empirical evaluation conducted in an Action Research study at one of Australia’s largest financial services providers.

Enhancing an Incremental Clustering Algorithm for Web Page Collections

With the size and state of the Internet today, a good quality approach to organizing this mass of information is of great importance. Clustering web pages into groups of similar documents is one approach, but relies heavily on good feature extraction and document representation as well as a good clustering approach and algorithm. Due to the changing nature of the Internet, resulting in a dynamic dataset, an incremental approach is preferred. In this work we propose an enhanced incremental clustering approach to develop a better clustering algorithm that can help to better organize the information available on the Internet in an incremental fashion. Experiments show that the enhanced algorithm outperforms the original histogram based algorithm by up to 7.5%.

Elliptic curve algorithm integration in the secure shell transport layer

This document describes algorithms based on Elliptic Cryptography (ECC) for use within the Secure Shell (SSH) transport protocol. In particular, it specifies Elliptic Curve Diffie-Hellman (ECDH) key agreement, Elliptic Curve Menezes-Qu-Vanstone (ECMQV) key agreement, and Elliptic Curve Digital Signature Algorithm (ECDSA) for use in the SSH Transport Layer protocol.

Population Monte Carlo Algorithm in High Dimensions

The population Monte Carlo algorithm is an iterative importance sampling scheme for solving static problems. We examine the population Monte Carlo algorithm in a simplified setting, a single step of the general algorithm, and study a fundamental problem that occurs in applying importance sampling to high-dimensional problem. The precision of the computed estimate from the simplified setting is measured by the asymptotic variance of estimate under conditions on the importance function. We demonstrate the exponential growth of the asymptotic variance with the dimension and show that the optimal covariance matrix for the importance function can be estimated in special cases.

Enhancing digital road map with lane details extracted from large-scale stereo aerial imagery using object-oriented image analysis

Precise, up-to-date and increasingly detailed road maps are crucial for various advanced road applications, such as lane-level vehicle navigation, and advanced driver assistant systems. With the very high resolution (VHR) imagery from digital airborne sources, it will greatly facilitate the data acquisition, data collection and updates if the road details can be automatically extracted from the aerial images. In this paper, we proposed an effective approach to detect road lane information from aerial images with employment of the object-oriented image analysis method. Our proposed algorithm starts with constructing the DSM and true orthophotos from the stereo images. The road lane details are detected using an object-oriented rule based image classification approach. Due to the affection of other objects with similar spectral and geometrical attributes, the extracted road lanes are filtered with the road surface obtained by a progressive two-class decision classifier. The generated road network is evaluated using the datasets provided by Queensland department of Main Roads. The evaluation shows completeness values that range between 76% and 98% and correctness values that range between 82% and 97%.

Towards an automatic road lane marks extraction based on ISODATA segmentation and shadow detection from large-scale aerial images

The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.

QoS-based web service composition accommodating inter-service dependencies using minimal-conflict , hill-climbing repair genetic algorithm

In the field of semantic grid, QoS-based Web service composition is an important problem. In semantic and service rich environment like semantic grid, the emergence of context constraints on Web services is very common making the composition consider not only QoS properties of Web services, but also inter service dependencies and conflicts which are formed due to the context constraints imposed on Web services. In this paper, we present a repair genetic algorithm, namely minimal-conflict hill-climbing repair genetic algorithm, to address the Web service composition optimization problem in the presence of domain constraints and inter service dependencies and conflicts. Experimental results demonstrate the scalability and effectiveness of the genetic algorithm.