Climbing Robot for Steel Bridge Inspection: Design Challenges

Inspection of bridges often requires high risk operations such as working at heights, in confined spaces, in hazardous environments; or sites inaccessible by humans. There is significant motivation for robotic solutions which can carry out these inspection tasks. When inspection robots are deployed in real world inspection scenarios, it is inevitable that unforeseen challenges will be encountered. Since 2011, the New South Wales Roads & Maritime Services and the Centre of Excellence for Autonomous Systems at the University of Technology, Sydney, have been working together to develop an innovative climbing robot to inspect high risk locations on the Sydney Harbour Bridge. Many engineering challenges have been faced throughout the development of several prototype climbing robots, and through field trials in the archways of the Sydney Harbour Bridge. This paper will highlight some of the key challenges faced in designing a climbing robot for inspection, and then present an inchworm inspired robot which addresses many of these challenges

Knowledge, attitude and practices related to leishmaniasis among healthcare workers in an endemic area in southern Sri Lanka

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Automatic Detection of Sleep Arousal Events from Polysomnographic Biosignals

Manual scoring of arousals is generally conducted by sleep experts in spite of being time-consuming and subjective. Our objective of this study was to develop an algorithm for automatic detection of sleep arousals without distinguishing between the types of arousal and sleep disorder groups. The processed and analysed data multiple overnight Polysomnography (PSG) recordings, consisting of 9 human subjects (6 male, 3 female), with age range of 34-69 and different conditions (4 patients with obstructive sleep apnoeas, 4 healthy and 1 patient with periodic limb movement disorder). PSG biosignals were processed to extract necessary features. Knearest neighbours (KNN) was used as the classifier and performance of algorithm were evaluated by Leave-One-Out Cross-Validation. The average sensitivity, specificity and accuracy of algorithm was 79%, 95.5% and 93%, respectively. These results demonstrate that our algorithm can automatically detect arousals with high accuracy. Furthermore, the algorithm is capable to be upgraded for classification of various types of arousals based upon their origin and characteristics

Application of Random Forest Classifier for Automatic Sleep Spindle Detection

Sleep spindle detection using supervised learning methods such as Artificial Neural Networks and Support Vector Machines had been researched in the past. Supervised learning methods such as the above are prone to overfitting problems. In this research paper, we explore the detection of sleep spindles using the Random Forest classifier which is known to over fit data to a much lower extent when compared to other supervised classifiers. The classifier was developed using data from 3 subjects and it was tested on data from 12 subjects from the MASS database. A sensitivity of 71.2% and a specificity of 96.73% was achieved using the random forest classifier

Linear and non-linear interdependence of EEG and HRV frequency bands in human sleep

The characterisation of functional interdependencies of the autonomic nervous system (ANS) stands an evergrowing interest to unveil electroencephalographic (EEG) and Heart Rate Variability (HRV) interactions. This paper presents a biosignal processing approach as a supportive computational resource in the estimation of sleep dynamics. The application of linear, non-linear methods and statistical tests upon 10 overnight polysomnographic (PSG) recordings, allowed the computation of wavelet coherence and phase locking values, in order to identify discerning features amongst the clinical healthy subjects. Our findings showed that neuronal oscillations θ, α and σ interact with cardiac power bands at mid-to-high rank of coherence and phase locking, particularly during NREM sleep stages

Sri Lankan Journal of Anaesthesiology 17(1) : 42 – 44 (2009) AUDIT AUDIT ON ORGANOPHOSPHATE POISONING REQUIRING INTENSIVE CARE UNIT ADMISSION

Organophosphates (OP) inhibits both cholinesterase and pseudo cholinesterase activities. The inhibition of acetyl cholinesterase causes accumulation of acetyl choline at synapses and over stimulation of muscarinic and cholinergic activities. The mortality rate is 3-25 % (2). Early diagnosis and appropriate treatment is life saving. The clinical course of OP is very severe and may require intensive care management. Materials and methods: A retrospective audit was performed of Intensive Care Unit (ICU) admissions at General Hospital Nuwara Eliya for a period of six months from 01 st of October 2007 to 31 st of March 2008. 31 patients were included. The diagnosis was made from th

Sensorial Quality and Physicochemical Properties of Newly Developed Ice-Cream, with Plant Originated Stabilizer; Modified Kithul (Caryota urens) Flour

Aims: Replacement of existing stabilizer in ice cream industry by using modified Kithul (Caryota urens) flour which helps to reduce usage of other ingredients which are used for improve the texture and creaminess of the product was examined. Kithul (Caryota urens) flour has better stabilizing ability than other flour and it can be used in product diversification in the food industry. The objective of this study was to use modified Kithul (Caryota urens) flour as a new plant origin stabilizer for the production of ice cream which can be easily applied for ice cream machines. Study Design: Three treatments were prepared as commercial stabilizer based (industrial mixture) as the control (A), and two samples with modified Kithul flour under two condition as without refrigerated (B) and 24 hours refrigerated (C) the modified Kithul flour with milk before preparing ice cream. Place and Duration of Study: Department of Biosystems Engineering, Faculty of Agriculture and Plantation Management, Wayamba University of Sri Lanka, between June 2019 and January 2020. Methodology: Three samples were evaluated for its sensory properties and selected ice cream sample from the sensory evaluation (Treatment B) was evaluated for proximate composition and evaluated for physicochemical properties vs industrial ice cream as a control. Results: The comparison revealed that modified Kithul flour-based ice cream (Treatment B) was better in terms of low cost of production, high overrun and high overall acceptability in the sensory analysis vs industrial ice cream (Treatment A). Conclusion: According to the results of the evaluation of quality attributes, without refrigerated milk-modified Kithul flour mixture before making ice cream is better than the industrial ice cream due to their low cost of production, high overrun and high overall acceptability in sensory analysis

Sleep Onset Detection with Multiple EEG Alpha-Band Features: Comparison Between Healthy, Insomniac and Schizophrenic Patients

In the past several studies have evaluated the human sleep onset (wake to sleep transition) using the electroencephalographic (EEG) measurements. This paper has evaluated the detection accuracy of sleep stages for multiple features based on the EEG alpha activity, during SO in healthy, insomniac and schizophrenic patients. The features include topographic features such as Directed Transfer Function, Full frequency DTF, Welch Coherence, Minimum Variance Distortionless Response Coherence and Partial Directed Coherence. Sleep stages Wake, NREM (Non-rapid Eye Movement) stages 1 and 2 were classified using Artificial Neural Networks (ANN) classifier and evaluated using classification accuracy. The results suggest that using topographic set of features yield an agreement of 81.3 % with the whole database classification of human expert

Variance of Arrowroot (Maranta arundinacea) Starch Granule Morphology among Five Different Provinces in Sri Lanka

Arrowroot (Maranta arundinacea) is an underutilized tuber crop in Sri Lanka that produces a gluten-free, easily digestible starch. This research aimed to determine the variance of arrowroot starch granular morphology among the plants grown in five different provinces (Western, North-Western, Southern, Sabaragamuwa, Uva). Arrowroot starch granules were observed using the light microscope and scanning electron microscope. Oval, irregular globular and spherical shapes were the predominant granule shapes for arrowroot. The mean percentage of oval shaped granules ranged between 48.46 % - 59.34 %.          The length and width of the granules were not significantly different among the five provinces. The length of the starch granules ranged between 42.91 - 45.86 µm while the width ranged between 30.81 – 32.32 µm. Arrowroot flour samples from five different provinces in Sri Lanka were not significantly different with regard to the starch granular morphology and therefore, arrowroot flour can be utilized in the local food industry without concerning their geographical locations