Do the best scholars attract the highest speaking fees? An exploration of internal and external influence

This study investigates whether academics can capitalize on their external prominence (measured by the number of pages indexed on Google, TED talk invitations or New York Times bestselling book successes) and internal success within academia (measured by publication and citation performance) in the speakers’ market. The results indicate that the larger the number of web pages indexing a particular scholar, the higher the minimum speaking fee. Invitations to speak at a TED event, or making the New York Times Best Seller list is also positively correlated with speaking fees. Scholars with a stronger internal impact or success also achieve higher speaking fees. However, once external impact is controlled, most metrics used to measure internal impact are no longer statistically significant.

A case study of utilising concept knowledge in a topic specific document collection

The use of ‘topic’ concepts has shown improved search performance, given a query, by bringing together relevant documents which use different terms to describe a higher level concept. In this paper, we propose a method for discovering and utilizing concepts in indexing and search for a domain specific document collection being utilized in industry. This approach differs from others in that we only collect focused concepts to build the concept space and that instead of turning a user’s query into a concept based query, we experiment with different techniques of combining the original query with a concept query. We apply the proposed approach to a real-world document collection and the results show that in this scenario the use of concept knowledge at index and search can improve the relevancy of results.

Ecological approaches in planning for sustainable cities : a review of the literature

Rapid urbanization has brought environmentally, socially, and economically great challenges to cities and societies. To build a sustainable city, these challenges need to be faced efficiently and successfully. This paper focuses on the environmental issues and investigates the ecological approaches for planning sustainable cities through a comprehensive review of the relevant literature. The review focuses on several differing aspects of sustainable city formation. The paper provides insights on the interaction between the natural environment and human activities by identifying environmental effects resulting from this interaction; provides an introduction to the concept of sustainable urban development by underlining the important role of ecological planning in achieving sustainable cities; introduces the notion of urban ecosystems by establishing principles for the management of their sustainability; describes urban ecosystem sustainability assessment by introducing a review of current assessment methods, and; offers an outline of indexing urban environmental sustainability. The paper concludes with a summary of the findings.

Towards robust automatic affective classification of images using facial expressions for practical applications

Affect is an important feature of multimedia content and conveys valuable information for multimedia indexing and retrieval. Most existing studies for affective content analysis are limited to low-level features or mid-level representations, and are generally criticized for their incapacity to address the gap between low-level features and high-level human affective perception. The facial expressions of subjects in images carry important semantic information that can substantially influence human affective perception, but have been seldom investigated for affective classification of facial images towards practical applications. This paper presents an automatic image emotion detector (IED) for affective classification of practical (or non-laboratory) data using facial expressions, where a lot of “real-world” challenges are present, including pose, illumination, and size variations etc. The proposed method is novel, with its framework designed specifically to overcome these challenges using multi-view versions of face and fiducial point detectors, and a combination of point-based texture and geometry. Performance comparisons of several key parameters of relevant algorithms are conducted to explore the optimum parameters for high accuracy and fast computation speed. A comprehensive set of experiments with existing and new datasets, shows that the method is effective despite pose variations, fast, and appropriate for large-scale data, and as accurate as the method with state-of-the-art performance on laboratory-based data. The proposed method was also applied to affective classification of images from the British Broadcast Corporation (BBC) in a task typical for a practical application providing some valuable insights.

Incorporating visual information for spoken term detection

Spoken term detection (STD) is the task of looking up a spoken term in a large volume of speech segments. In order to provide fast search, speech segments are first indexed into an intermediate representation using speech recognition engines which provide multiple hypotheses for each speech segment. Approximate matching techniques are usually applied at the search stage to compensate the poor performance of automatic speech recognition engines during indexing. Recently, using visual information in addition to audio information has been shown to improve phone recognition performance, particularly in noisy environments. In this paper, we will make use of visual information in the form of lip movements of the speaker in indexing stage and will investigate its effect on STD performance. Particularly, we will investigate if gains in phone recognition accuracy will carry through the approximate matching stage to provide similar gains in the final audio-visual STD system over a traditional audio only approach. We will also investigate the effect of using visual information on STD performance in different noise environments.

Generalised features for bird vocalisation retrieval in acoustic recordings

Bioacoustic monitoring has become a significant research topic for species diversity conservation. Due to the development of sensing techniques, acoustic sensors are widely deployed in the field to record animal sounds over a large spatial and temporal scale. With large volumes of collected audio data, it is essential to develop semi-automatic or automatic techniques to analyse the data. This can help ecologists make decisions on how to protect and promote the species diversity. This paper presents generic features to characterize a range of bird species for vocalisation retrieval. In the implementation, audio recordings are first converted to spectrograms using short-time Fourier transform, then a ridge detection method is applied to the spectrogram for detecting points of interest. Based on the detected points, a new region representation are explored for describing various bird vocalisations and a local descriptor including temporal entropy, frequency bin entropy and histogram of counts of four ridge directions is calculated for each sub-region. To speed up the retrieval process, indexing is carried out and the retrieved results are ranked according to similarity scores. The experiment results show that our proposed feature set can achieve 0.71 in term of retrieval success rate which outperforms spectral ridge features alone (0.55) and Mel frequency cepstral coefficients (0.36).

Robust principal component analysis in water quality index development

Some statistical procedures already available in literature are employed in developing the water quality index, WQI. The nature of complexity and interdependency that occur in physical and chemical processes of water could be easier explained if statistical approaches were applied to water quality indexing. The most popular statistical method used in developing WQI is the principal component analysis (PCA). In literature, the WQI development based on the classical PCA mostly used water quality data that have been transformed and normalized. Outliers may be considered in or eliminated from the analysis. However, the classical mean and sample covariance matrix used in classical PCA methodology is not reliable if the outliers exist in the data. Since the presence of outliers may affect the computation of the principal component, robust principal component analysis, RPCA should be used. Focusing in Langat River, the RPCA-WQI was introduced for the first time in this study to re-calculate the DOE-WQI. Results show that the RPCA-WQI is capable to capture similar distribution in the existing DOE-WQI.

SPSA Based Feature Relevance Estimation For Video Retrieval

With the availability of a huge amount of video data on various sources, efficient video retrieval tools are increasingly in demand. Video being a multi-modal data, the perceptions of ``relevance'' between the user provided query video (in case of Query-By-Example type of video search) and retrieved video clips are subjective in nature. We present an efficient video retrieval method that takes user's feedback on the relevance of retrieved videos and iteratively reformulates the input query feature vectors (QFV) for improved video retrieval. The QFV reformulation is done by a simple, but powerful feature weight optimization method based on Simultaneous Perturbation Stochastic Approximation (SPSA) technique. A video retrieval system with video indexing, searching and relevance feedback (RF) phases is built for demonstrating the performance of the proposed method. The query and database videos are indexed using the conventional video features like color, texture, etc. However, we use the comprehensive and novel methods of feature representations, and a spatio-temporal distance measure to retrieve the top M videos that are similar to the query. In feedback phase, the user activated iterative on the previously retrieved videos is used to reformulate the QFV weights (measure of importance) that reflect the user's preference, automatically. It is our observation that a few iterations of such feedback are generally sufficient for retrieving the desired video clips. The novel application of SPSA based RF for user-oriented feature weights optimization makes the proposed method to be distinct from the existing ones. The experimental results show that the proposed RF based video retrieval exhibit good performance.

Improving spoken term detection using complementary information

This research has made contributions to the area of spoken term detection (STD), defined as the process of finding all occurrences of a specified search term in a large collection of speech segments. The use of visual information in the form of lip movements of the speaker in addition to audio and the use of topic of the speech segments, and the expected frequency of words in the target speech domain, are proposed. By using these complementary information, improvement in the performance of STD has been achieved which enables efficient search of key words in large collection of multimedia documents.

Inconsistent Transmission of Banana Bunchy Top Virus in Micropropagated Bananas and its Implication for Germplasm Screening

Banana bunchy top virus (BBTV) was readily transmitted through tissue culture in banana (Mum sp.) cv. Lady finger (AAB) and Cavendish cv. Williams (AAA). Lines derived from infected and healthy field plants had similar in vitro multiplication rates. BBTV infected in vitro cultures displayed symptoms of stunting, leaf curling, chlorotic and green flecks, and poor root growth. Symptoms became milder with time, and were often difficult to discern in older, rapidly multiplying cultures. A triple antibody sandwich ELISA using polyclonal and monoclonal antibodies was very efficient for detecting BBTV in vitro. Symptomless, ELISA-negative plants arose in 10 out of 11 lines derived from BBTV-infected field plants and first appeared after 9 months continuous in vitro culture at a constant 28OC. Meristem tip culture or heat therapy was not used. These plants remained symptomless and ELISA-negative after planting out in the glasshouse (individual plants checked for up to 16 months). The implications of this inconsistent transmission of BBTV for germplasm indexing and exchange are discussed.

GRDB: A general purpose relational database system

This article discusses the design and development of GRDB (General Purpose Relational Data Base System) which has been implemented on a DEC-1090 system in Pascal. GRDB is a general purpose database system designed to be completely independent of the nature of data to be handled, since it is not tailored to the specific requirements of any particular enterprise. It can handle different types of data such as variable length records and textual data. Apart from the usual database facilities such as data definition and data manipulation, GRDB supports User Definition Language (UDL) and Security definition language. These facilities are provided through a SEQUEL-like General Purpose Query Language (GQL). GRDB provides adequate protection facilities up to the relation level. The concept of “security matrix” has been made use of to provide database protection. The concept of Unique IDentification number (UID) and Password is made use of to ensure user identification and authentication. The concept of static integrity constraints has been used to ensure data integrity. Considerable efforts have been made to improve the response time through indexing on the data files and query optimisation. GRDB is designed for an interactive use but alternate provision has been made for its use through batch mode also. A typical Air Force application (consisting of data about personnel, inventory control, and maintenance planning) has been used to test GRDB and it has been found to perform satisfactorily.

A visual profile of Queensland Indigenous children

Purpose Little is known about the prevalence of refractive error, binocular vision, and other visual conditions in Australian Indigenous children. This is important given the association of these visual conditions with reduced reading performance in the wider population, which may also contribute to the suboptimal reading performance reported in this population. The aim of this study was to develop a visual profile of Queensland Indigenous children. Methods Vision testing was performed on 595 primary schoolchildren in Queensland, Australia. Vision parameters measured included visual acuity, refractive error, color vision, nearpoint of convergence, horizontal heterophoria, fusional vergence range, accommodative facility, AC/A ratio, visual motor integration, and rapid automatized naming. Near heterophoria, nearpoint of convergence, and near fusional vergence range were used to classify convergence insufficiency (CI). Results Although refractive error (Indigenous, 10%; non-Indigenous, 16%; p = 0.04) and strabismus (Indigenous, 0%; non-Indigenous, 3%; p = 0.03) were significantly less common in Indigenous children, CI was twice as prevalent (Indigenous, 10%; non-Indigenous, 5%; p = 0.04). Reduced visual information processing skills were more common in Indigenous children (reduced visual motor integration [Indigenous, 28%; non-Indigenous, 16%; p < 0.01] and slower rapid automatized naming [Indigenous, 67%; non-Indigenous, 59%; p = 0.04]). The prevalence of visual impairment (reduced visual acuity) and color vision deficiency was similar between groups. Conclusions Indigenous children have less refractive error and strabismus than their non-Indigenous peers. However, CI and reduced visual information processing skills were more common in this group. Given that vision screenings primarily target visual acuity assessment and strabismus detection, this is an important finding as many Indigenous children with CI and reduced visual information processing may be missed. Emphasis should be placed on identifying children with CI and reduced visual information processing given the potential effect of these conditions on school performance

Cortical processing of musical pitch as reflected by behavioural and electrophysiological evidence

In a musical context, the pitch of sounds is encoded according to domain-general principles not confined to music or even to audition overall but common to other perceptual and cognitive processes (such as multiple pattern encoding and feature integration), and to domain-specific and culture-specific properties related to a particular musical system only (such as the pitch steps of the Western tonal system). The studies included in this thesis shed light on the processing stages during which pitch encoding occurs on the basis of both domain-general and music-specific properties, and elucidate the putative brain mechanisms underlying pitch-related music perception. Study I showed, in subjects without formal musical education, that the pitch and timbre of multiple sounds are integrated as unified object representations in sensory memory before attentional intervention. Similarly, multiple pattern pitches are simultaneously maintained in non-musicians' sensory memory (Study II). These findings demonstrate the degree of sophistication of pitch processing at the sensory memory stage, requiring neither attention nor any special expertise of the subjects. Furthermore, music- and culture-specific properties, such as the pitch steps of the equal-tempered musical scale, are automatically discriminated in sensory memory even by subjects without formal musical education (Studies III and IV). The cognitive processing of pitch according to culture-specific musical-scale schemata hence occurs as early as at the sensory-memory stage of pitch analysis. Exposure and cortical plasticity seem to be involved in musical pitch encoding. For instance, after only one hour of laboratory training, the neural representations of pitch in the auditory cortex are altered (Study V). However, faulty brain mechanisms for attentive processing of fine-grained pitch steps lead to inborn deficits in music perception and recognition such as those encountered in congenital amusia (Study VI). These findings suggest that predispositions for exact pitch-step discrimination together with long-term exposure to music govern the acquisition of the automatized schematic knowledge of the music of a particular culture that even non-musicians possess.

Development of a Multiplexed Bead-Based Suspension Array for the Detection and Discrimination of Pospiviroid Plant Pathogens

Efficient and reliable diagnostic tools for the routine indexing and certification of clean propagating material are essential for the management of pospiviroid diseases in horticultural crops. This study describes the development of a true multiplexed diagnostic method for the detection and identification of all nine currently recognized pospiviroid species in one assay using Luminex bead-based suspension array technology. In addition, a new data-driven, statistical method is presented for establishing thresholds for positivity for individual assays within multiplexed arrays. When applied to the multiplexed array data generated in this study, the new method was shown to have better control of false positives and false negative results than two other commonly used approaches for setting thresholds. The 11-plex Luminex MagPlex-TAG pospiviroid array described here has a unique hierarchical assay design, incorporating a near-universal assay in addition to nine species-specific assays, and a co-amplified plant internal control assay for quality assurance purposes. All assays of the multiplexed array were shown to be 100% specific, sensitive and reproducible. The multiplexed array described herein is robust, easy to use, displays unambiguous results and has strong potential for use in routine pospiviroid indexing to improve disease management strategies.