Evaluation of four supervised learning methods for benthic habitat mapping using backscatter from multi-beam sonar

An understanding of the distribution and extent of marine habitats is essential for the implementation of ecosystem-based management strategies. Historically this had been difficult in marine environments until the advancement of acoustic sensors. This study demonstrates the applicability of supervised learning techniques for benthic habitat characterization using angular backscatter response data. With the advancement of multibeam echo-sounder (MBES) technology, full coverage datasets of physical structure over vast regions of the seafloor are now achievable. Supervised learning methods typically applied to terrestrial remote sensing provide a cost-effective approach for habitat characterization in marine systems. However the comparison of the relative performance of different classifiers using acoustic data is limited. Characterization of acoustic backscatter data from MBES using four different supervised learning methods to generate benthic habitat maps is presented. Maximum Likelihood Classifier (MLC), Quick, Unbiased, Efficient Statistical Tree (QUEST), Random Forest (RF) and Support Vector Machine (SVM) were evaluated to classify angular backscatter response into habitat classes using training data acquired from underwater video observations. Results for biota classifications indicated that SVM and RF produced the highest accuracies, followed by QUEST and MLC, respectively. The most important backscatter data were from the moderate incidence angles between 30° and 50°. This study presents initial results for understanding how acoustic backscatter from MBES can be optimized for the characterization of marine benthic biological habitats. © 2012 by the authors.

Comparative evaluation of multi-label classification methods

This paper presents a comparative evaluation of popular multi-label classification methods on several multi-label problems from different domains. The methods include multi-label k-nearest neighbor, binary relevance, label power set, random k-label set ensemble learning, calibrated label ranking, hierarchy of multi-label classifiers and triple random ensemble multi-label classification algorithms. These multi-label learning algorithms are evaluated using several widely used MLC evaluation metrics. The evaluation results show that for each multi-label classification problem a particular MLC method can be recommended. The multi-label evaluation datasets used in this study are related to scene images, multimedia video frames, diagnostic medical report, email messages, emotional music data, biological genes and multi-structural proteins categorization.

The safety and effectiveness of different methods of ear wax removal: a systematic review and economic evaluation

Build-up of earwax is a common reason for attendance in primary care. Current practice for earwax removal generally involves the use of a softening agent, followed by irrigation of the ear if required. However, the safety and benefits of the different methods of removal are not known for certain.

Evaluation of neck muscle size: long-term reliability and comparison of methods

Although it is important for prospective studies, the reliability of quantitative measures of cervical muscle size on magnetic resonance imaging is not well established. The aim of the current work was to assess the long-term reliability of measurements of cervical muscle size. In addition, we examined the utility of selecting specific sub-regions of muscles at each vertebral level, averaging between sides of the body, and pooling muscles into larger groups. Axial scans from the base of skull to the third thoracic vertebra were performed in 20 healthy male subjects at baseline and 1.5 years later. We evaluated the semi-spinalis capitis, splenius capitis, spinalis cervicis, longus capitis, longus colli, levator scapulae, sternocleidomastoid, anterior scalenes and middle with posterior scalenes. Bland-Altman analysis showed all measurements to be repeatable between testing-days. Reliability was typically best when entire muscle volume was measured (co-efficients of variation (CVs): 3.3-8.1% depending on muscle). However, when the size of the muscle was assessed at specific vertebral levels, similar measurement precision was achieved (CVs: 2.7-7.6%). A median of 4-6 images were measured at the specific vertebral levels versus 18-37 images for entire muscle volume. This would represent considerable time saving. Based on the findings we also recommend measuring both sides of the body and calculating an average value. Pooling specific muscles into the deep neck flexors (CV: 3.5%) and neck extensors (CV: 2.7%) can serve to reduce variability further. The results of the current study help to establish outcome measures for interventional studies and for sample size estimation.

Evaluation of lumbar disc and spine morphology: long-term repeatability and comparison of methods

Establishing the long-term repeatability of quantitative measures of lumbar intervertebral disc and spinal morphology is important for planning interventional studies. We aimed to examine this issue and to determine to what extent a smaller number of measurements per disc or vertebral level could be used to save operator time without compromising measurement precision. Twenty-one healthy male subjects were scanned at baseline and 1.5 years later. On sagittal MR-scans intervertebral disc cross-sectional area, anterior disc height, posterior disc height, intervertebral angle and intervertebral length were measured. The repeatability of the average value from all sagittal images or from 1, 3, 5 or 7 images centred at the spinous process was evaluated. Bland-Altman analysis showed all measurements to be repeatable between testing days. Intervertebral length was the most precise measurement (coefficients of variation [CVs] between 1.2% and 1.5%), followed by disc cross-sectional area (CVs between 2.9% and 3.6%). Variance component analysis showed that using 7 images, but not 1, 3 or 5 images, resulted in a similar level of measurement error as when measurements from all images were included.

Evaluation of electrochemical methods for determination of the seebeck coefficient of redox electrolytes

Recent advances in thermoelectrochemical cells, which are being developed for harvesting low grade waste heat, have shown the promise of cobalt bipyridyl salts as the active redox couple. The Seebeck coefficient, Se, of a redox couple determines the open circuit voltage achievable, for a given temperature gradient, across the thermoelectrochemical cell. Thus, the accurate determination of this thermodynamic parameter is key to the development and study of new redox electrolytes. Further, techniques for accurate determination of Se using only one half of the redox couple reduces the synthetic requirements. Here, we compare three different experimental techniques for measuring Se of a cobalt tris(bipyridyl) redox couple in ionic liquid electrolytes. The use of temperature dependent cyclic voltammetry (CV) in isothermal and non-isothermal cells was investigated in depth, and the Se values compared to those from thermo-electromotive force measurements. Within experimental error, the Se values derived from CV methods were found to be in accordance with those obtained from electromotive force (emf) measurements. The applicability of cyclic voltammetry techniques for determining Se when employing only one part of the redox couple was demonstrated.

A systematic evaluation of field-based screening methods for the assessment of anterior cruciate ligament (ACL) injury risk

BACKGROUND: Laboratory-based measures provide an accurate method to identify risk factors for anterior cruciate ligament (ACL) injury; however, these methods are generally prohibitive to the wider community. Screening methods that can be completed in a field or clinical setting may be more applicable for wider community use. Examination of field-based screening methods for ACL injury risk can aid in identifying the most applicable method(s) for use in these settings. OBJECTIVE: The objective of this systematic review was to evaluate and compare field-based screening methods for ACL injury risk to determine their efficacy of use in wider community settings. DATA SOURCES: An electronic database search was conducted on the SPORTDiscus™, MEDLINE, AMED and CINAHL databases (January 1990-July 2015) using a combination of relevant keywords. A secondary search of the same databases, using relevant keywords from identified screening methods, was also undertaken. STUDY SELECTION: Studies identified as potentially relevant were independently examined by two reviewers for inclusion. Where consensus could not be reached, a third reviewer was consulted. Original research articles that examined screening methods for ACL injury risk that could be undertaken outside of a laboratory setting were included for review. STUDY APPRAISAL AND SYNTHESIS METHODS: Two reviewers independently assessed the quality of included studies. Included studies were categorized according to the screening method they examined. A description of each screening method, and data pertaining to the ability to prospectively identify ACL injuries, validity and reliability, recommendations for identifying 'at-risk' athletes, equipment and training required to complete screening, time taken to screen athletes, and applicability of the screening method across sports and athletes were extracted from relevant studies. RESULTS: Of 1077 citations from the initial search, a total of 25 articles were identified as potentially relevant, with 12 meeting all inclusion/exclusion criteria. From the secondary search, eight further studies met all criteria, resulting in 20 studies being included for review. Five ACL-screening methods-the Landing Error Scoring System (LESS), Clinic-Based Algorithm, Observational Screening of Dynamic Knee Valgus (OSDKV), 2D-Cam Method, and Tuck Jump Assessment-were identified. There was limited evidence supporting the use of field-based screening methods in predicting ACL injuries across a range of populations. Differences relating to the equipment and time required to complete screening methods were identified. LIMITATIONS: Only screening methods for ACL injury risk were included for review. Field-based screening methods developed for lower-limb injury risk in general may also incorporate, and be useful in, screening for ACL injury risk. CONCLUSIONS: Limited studies were available relating to the OSDKV and 2D-Cam Method. The LESS showed predictive validity in identifying ACL injuries, however only in a youth athlete population. The LESS also appears practical for community-wide use due to the minimal equipment and set-up/analysis time required. The Clinic-Based Algorithm may have predictive value for ACL injury risk as it identifies athletes who exhibit high frontal plane knee loads during a landing task, but requires extensive additional equipment and time, which may limit its application to wider community settings.

Evaluation and comparison of 3D intervertebral disc localization and segmentation methods for 3D T2 MR data: A grand challenge.

The evaluation of changes in Intervertebral Discs (IVDs) with 3D Magnetic Resonance (MR) Imaging (MRI) can be of interest for many clinical applications. This paper presents the evaluation of both IVD localization and IVD segmentation methods submitted to the Automatic 3D MRI IVD Localization and Segmentation challenge, held at the 2015 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI2015) with an on-site competition. With the construction of a manually annotated reference data set composed of 25 3D T2-weighted MR images acquired from two different studies and the establishment of a standard validation framework, quantitative evaluation was performed to compare the results of methods submitted to the challenge. Experimental results show that overall the best localization method achieves a mean localization distance of 0.8 mm and the best segmentation method achieves a mean Dice of 91.8%, a mean average absolute distance of 1.1 mm and a mean Hausdorff distance of 4.3 mm, respectively. The strengths and drawbacks of each method are discussed, which provides insights into the performance of different IVD localization and segmentation methods.

Evaluation of deterministic and complex analytical hierarchy process methods for agricultural land suitability analysis in a changing climate

Land suitability analysis is employed to evaluate the appropriateness of land for a particular purpose whilst integrating both qualitative and quantitative inputs, which can be continuous in nature. However, in agricultural modelling there is often a disregard of this contiguous aspect. Therefore, some parametric procedures for suitability analysis compartmentalise units into defined membership classes. This imposition of crisp boundaries neglects the continuous formations found throughout nature and overlooks differences and inherent uncertainties found in the modelling. This research will compare two approaches to suitability analysis over three differing methods. The primary approach will use an Analytical Hierarchy Process (AHP), while the other approach will use a Fuzzy AHP over two methods; Fitted Fuzzy AHP and Nested Fuzzy AHP. Secondary to this, each method will be assessed into how it behaves in a climate change scenario to understand and highlight the role of uncertainties in model conceptualisation and structure. Outputs and comparisons between each method, in relation to area, proportion of membership classes and spatial representation, showed that fuzzy modelling techniques detailed a more robust and continuous output. In particular the Nested Fuzzy AHP was concluded to be more pertinent, as it incorporated complex modelling techniques, as well as the initial AHP framework. Through this comparison and assessment of model behaviour, an evaluation of each methods predictive capacity and relevance for decision-making purposes in agricultural applications is gained.

Modelling solute transport in structured soils: performance evaluation of the ADR and TRM models

The movement of chemicals through the soil to the groundwater or discharged to surface waters represents a degradation of these resources. In many cases, serious human and stock health implications are associated with this form of pollution. The chemicals of interest include nutrients, pesticides, salts, and industrial wastes. Recent studies have shown that current models and methods do not adequately describe the leaching of nutrients through soil, often underestimating the risk of groundwater contamination by surface-applied chemicals and overestimating the concentration of resident solutes. This inaccuracy results primarily from ignoring soil structure and nonequilibrium between soil constituents, water, and solutes. A multiple sample percolation system (MSPS), consisting of 25 individual collection wells, was constructed to study the effects of localized soil heterogeneities on the transport of nutrients (NO−3, Cl−, PO3−4) in the vadose zone of an agricultural soil predominantly dominated by clay. Very significant variations in drainage patterns across a small spatial scale were observed (one-way ANOVA, p < 0.001 indicating considerable heterogeneity in water flow patterns and nutrient leaching. Using data collected from the multiple sample percolation experiments, this paper compares the performance of two mathematical models for predicting solute transport, the advective-dispersion model with a reaction term (ADR), and a two-region preferential flow model (TRM) suitable for modelling nonequilibrium transport. These results have implications for modelling solute transport and predicting nutrient loading on a larger scale.

Evaluation of interventions for gay men: two desiderata

This paper was presented in a session at the AIDS Impact conference devoted to a debate on the methods that should be used to evaluate educational interventions. The paper highlights two desiderata for evaluation of interventions directed at gay men. First, the view is presented that there is no acceptable substitute for assessing the effect of an intervention on gay men's sexual behaviour (rather than, for example, their AIDS-related attitudes or beliefs). This view is justified in terms of (a) the differences that exist between AIDS-related thinking in the cold light of day and during actual sexual encounters; and (b) the often faulty nature of intuitions about the factors that contribute to sexual risk-taking and the ways in which it might be reduced. Second, it is argued that the randomized control study design represents the best means for ensuring that interventions will be as effective as possible. Criticisms which have been made of this design are discussed and the conclusion drawn that they do not amount to a strong case against it.

Accounting narrative evaluation: using texture as a measure of quality

This paper applies a texture-based approach to evaluating accounting narratives. We employ the texture index created by Sydserff and Weetman (1999) as it is purported to evaluate narratives more accurately than previous methods. Not enough emphasis has been placed on the utilisation of linguistic tools in the accounting context. We see that a rigorous test serves the accountability function and may contribute positively to investor protection and confidence. We support the contention that improving narrative evaluation will help increase the quality of accounting narratives as they are presented in corporate annual reports. Quality for purpose of this paper is defined as a function of readability and understandability. These characteristics are considered essential for informed investment decision-making. We focus on the usefulness of the texture index in determining an appropriate measure of both readability and understandability by applying the texture index to a sample of corporate annual reports. Our results show conditional support for the use of the texture index as a viable alternative to readability tests.