Guide to on-site wastewater management for industrial and commercial establishments and other institutions: guide for hotel and restaurant owners and managers in Kurunegala, Sri Lanka

Wastewater treatmentWater conservation

Guide to on-site wastewater management for industrial and commercial establishments and other institutions: guide for vehicle service station owners and managers

Wastewater treatmentEnvironmental managementOrganizations

Optimal Allocation of Land for Conservation: A General Equilibrium Analysis

This paper was replaced with a revised version on 7/26/10Conservation, General Equilibrium Modeling, Optimal Land Allocation, Conservation Tax, Environmental Economics and Policy, Land Economics/Use, Q57, C68,

The Mediating Mechanism of Consumer Ethical Beliefs in Determining the Influence of Cynicism and Empathy on Green Buying Intention

Green buying intention can help society and companies to achieve sustainability while balancing their marketing objectives. Although there have been many studies done in relation to green buying intention, there are still calls for research to specifically study the impact of individual factors and the impact of ethical beliefs on green buying intention. The objective of this research is to examine the influence of empathy and cynicism on green buying intention and the mediating mechanism of consumer ethical beliefs. A structured questionnaire was administered using the online platform, and 345 valid responses were collected. Partial least squares-Structural equation modeling (PLS-SEM) was performed to test the hypotheses using the SmartPLS 3.0 program. The results reveal that empathy and cynicism predict consumer intention to buy green products directly and indirectly through ethical beliefs. This study contributes to both literature and business practice, and may be the first research study to investigate the relationship between empathy and cynicism and green buying intention. In addition, the study helps managers to articulate marketing strategies such as empathetic and ethical focused advertising to promote green buying intentions of customers. This research will be particularly important for developing countries like Sri Lanka in promoting sustainable consumption which enhances environmental, social and future generations’ well-being. Sri Lankan business firms can improve their global presence by focusing on green consumerism as now many global firms have already begun sustainable business practices. Keywords: Green buying intention, Empathy, Cynicism, Consumer ethical beliefs, Green consumerism&nbsp

Development of a Chain Climbing Robot and an Automated Ultrasound Inspection System for Mooring Chain Integrity Assessment

Mooring chains used to stabilise offshore floating platforms are often subjected to harsh environmental conditions on a daily basis, i.e. high tidal waves, storms etc. Chain breakage can lead to vessel drift and serious damage such as riser rupture, production shutdown and hydrocarbon release. Therefore, integrity assessment of chain links is vital, and regular inspection is mandatory for offshore structures. Currently, structural health monitoring of chain links is conducted using either remotely operated vehicles (ROVs), which are associated with high costs, or by manual means, which increases the risk to human operators. The development of climbing robots for mooring chain applications is still in its infancy due to the operational complexity and geometrical features of the chain. This thesis presents a Cartesian legged magnetic adhesion tracked-wheel crawler robot developed for mooring chain inspection. The crawler robot presented in this study is suitable for mooring chain climbing in air and the technique can be adapted for underwater use. The proposed robot addresses straight mooring chain climbing and a misaligned scenario that is commonly evident in in-situ conditions. The robot can be used as a platform to convey equipment, i.e. tools for non-destructive testing/evaluation applications. The application of ultrasound for in-service mooring chain inspection is still in the early stages due to lack of accessibility, in-field operational complexity and the geometrical features of mooring systems. With the advancement of robotic/automated systems (i.e. chain-climbing robotic mechanisms), interest in in-situ ultrasound inspection has increased. Currently, ultrasound inspection is confined to the weld area of the chain links. However, according to recent studies on fatigue and residual stresses, ultrasound inspection of the chain crown should be further investigated. A new automated application for ultrasonic phased-array full-matrix capture is discussed in this thesis for investigation of the chain crown. The concept of the chain-climbing robot and the inspection technique are validated with laboratory-based climbing experiments and presented in this thesis

Sri Lanka Malaria Maps

BACKGROUND: Despite a relatively good national case reporting system in Sri Lanka, detailed maps of malaria distribution have not been publicly available. METHODS: In this study, monthly records over the period 1995 – 2000 of microscopically confirmed malaria parasite positive blood film readings, at sub-district spatial resolution, were used to produce maps of malaria distribution across the island. Also, annual malaria trends at district resolution were displayed for the period 1995 – 2002. RESULTS: The maps show that Plasmodium vivax malaria incidence has a marked variation in distribution over the island. The incidence of Plasmodium falciparum malaria follows a similar spatial pattern but is generally much lower than that of P. vivax. In the north, malaria shows one seasonal peak in the beginning of the year, whereas towards the south a second peak around June is more pronounced. CONCLUSION: This paper provides the first publicly available maps of both P. vivax and P. falciparum malaria incidence distribution on the island of Sri Lanka at sub-district resolution, which may be useful to health professionals, travellers and travel medicine professionals in their assessment of malaria risk in Sri Lanka. As incidence of malaria changes over time, regular updates of these maps are necessary

A statistical approach for uncertain stability analysis of mobile robots

Stability prediction is an important concern for mobile robots operating in rough environments. Having the capacity to predict areas of instability means pro-actively being able to plan safer traversable paths. The most influential tip-over stability measures are based on two criteria, the robot's center of mass (CM) and the supporting polygon (SP) defined by the convex area spanned between the ground contact-points. However, there is significant uncertainty associated with many parameters in the planning pipe-line: the actual robot kino-dynamic model, its localisation in the ground, and the terrain models, particularly in uneven terrain. This article proposes a statistical analysis of stability prediction to account for some of the uncertainties. This is accomplished using the force angle (FA) stability measure for a reconfigurable multi-tracked vehicle fitted with flippers, a manipulator arm and a sensor head. Probability density function (PDF) of contact-points, CM and the FA stability measure are numerically estimated, with simulation results performed on the open dynamics engine (ODE) simulator based on uncertain parameters. Two techniques are presented: a conventional Monte Carlo scheme, and a structured unscented transform (UT) which results in significant improvement in computational efficiency. Experimental results on maps obtained from a range camera fitted on the sensor head while the robot traverses over a ramp and a series of steps are presented that confirms the validity of the proposed probabilistic stability prediction method. © 2013 IEEE

A probabilistic approach to learn activities of daily living of a mobility aid device user

© 2014 IEEE. The problem of inferring human behaviour is naturally complex: people interact with the environment and each other in many different ways, and dealing with the often incomplete and uncertain sensed data by which the actions are perceived only compounds the difficulty of the problem. In this paper, we propose a framework whereby these elaborate behaviours can be naturally simplified by decomposing them into smaller activities, whose temporal dependencies can be more efficiently represented via probabilistic hierarchical learning models. In this regard, patterns of a number of activities typically carried out by users of an ambulatory aid device have been identified with the aid of a Hierarchical Hidden Markov Model (HHMM) framework. By decomposing the complex behaviours into multiple layers of abstraction the approach is shown capable of modelling and learning these tightly coupled human-machine interactions. The inference accuracy of the proposed model is proven to compare favourably against more traditional discriminative models, as well as other compatible generative strategies to provide a complete picture that highlights the benefits of the proposed approach, and opens the door to more intelligent assistance with a robotic mobility aid