Ultrasonic-based Sensor Fusion Approach to Measure Flow Rate in Partially Filled Pipes

Flow rate measurement in pipes is essential for many applications. Thus, there have been a variety of flow meters developed that incorporate different technologies. However, a typical limitation in flow meters is that the pipe must be full in order to get an accurate flow reading. In many cases, this is not possible for practical reasons. When the pipe is full, ultrasonic flow meters can calculate the flow rate using known properties of the pipe and fluid, namely the cross-section, propagation path and fluid sound velocity. However, when the pipe is only partially filled, the propagation path is unknown which leads to an inability to calculate the correct flow rate. This paper presents a cost-effective sensor fusion approach to extend the capabilities of transit time ultrasonic flow meters to handle such scenarios. The approach determines the propagation path using capacitance-based level sensing, combined with fluid velocities ascertained via an ultrasonic sensor, leading to a significantly more accurate estimation of flow rates. Experiments in low flow rate situations validated the efficacy of the proposed model, with a 92% reduction of mean error in the lowest water height when compared to a conventional ultrasonic flow meter

Feasibility of valuing credit risk in the financial market in Sri Lanka: a case study

The Sri Lankan financial market uses non analytical techniques to quantify credit risk. Credit derivatives are not used to transfer credit risk. A Credit Default Swap (CDS) is the most widely used credit derivative to manage credit risk. To evaluate the price of CDS, various sophisticated methods are used. This research paper focuses on techniques to hedge credit risk in the Sri Lankan financial market, the behaviours of CDS in derivative markets, calculating a fair value of CDS, the main advantages of using credit derivatives, and major imperfections to use the pricing process of CDS in the Sri Lankan marke

3-D Printed Strain Sensor for Structural Health Monitoring

Additive manufacturing, or 3D printing, is evolving from a technology that can only aid rapid prototyping, to one that can be used to directly manufacture large-scale, real-world equipment. Gravity Separation Spirals (GSS) are vital to the mining industry for separating mineral-rich slurry into its different density components. In order to overcome inherent drawbacks of the traditional mould base manufacturing methods, including significant tooling costs, limited customisation and worker exposure to hazardous materials, a 3D printer is under development to directly print spirals. By embedding small Internet of Things (IoT) sensors inside the GSS, it is possible to remotely determine the operation conditions, predict faults, and use collected data to optimise production output. This work presents a 3D printed strain sensor, which can be directly printed into the GSS. This approach uses a carbon-based conductive filament to print a strain gauge on top of a Polylactic Acid (PLA) base material. Printed sensors have been tested using an Instron E10000 testing machine with an optical extensometer to improve accuracy. Testing was conducted by both loading and unloading conditions to understand the effect of hysteresis. Test results show a near-linear relationship between strain and measured resistance, and show a 6.05% increase in resistance after the test, which indicates minor hysteresis. Moreover, the impact of viscoelastic behaviour is identified, where the resistance response lags the strain. Results from both conductive and non-conductive material show the impact of the conductive carbon upon the tensile strength, which will help to inform future decisions about sensor placement

Integrated 3-D Printable Temperature Sensor for Advanced Manufacturing

As technology continues to develop at a rapid pace, the world progresses towards the fourth industrial revolution, Industry 4.0, with advancements in automation and machine intelligence, as well as manufacturing breakthroughs leading to more efficient and advanced methods. Additive manufacturing (AM), also known as 3D printing, is a type of manufacturing method that has experienced great development and has revolutionised end-product manufacturing. The authors are involved in a project to develop a large-scale industrial 3D printer to print equipment called a Gravity Separation Spiral (GSS), and in an effort to make the equipment "smart", sensors need to be embedded inside to monitor the operating conditions remotely. This paper presents a temperature sensor able to be printed by a multi-material 3D printer, into 3D printed equipment. In this method, a conductive carbon-based filament has been used to print temperature-sensitive traces inside a Polylactic Acid (PLA) base. The printed sensor was temperature tested in a controlled environment using a programmable heat pad, and the change in resistance has been measured as a voltage change using a data acquisition device. Tests were conducted within in the expected operating range, between 25 °C and 36 °C , and the absolute temperature error was found to be less than ±2°C

Socioeconomic and geographic correlates of intimate partner violence in Sri Lanka: Analysis of the 2016 Demographic and Health Survey

Intimate partner violence (IPV) is a serious public health issue and violation of human rights. The prevalence of IPV in South Asia is especially pronounced. We examined the associations between socioeconomic position (SEP), geographical factors and IPV in Sri Lanka using nationally representative data. Data collected from Sri Lanka’s 2016 Demographic and Health Survey were analysed using multilevel logistic regression techniques. A total of 16,390 eligible ever-partnered women aged 15-49 years were included in the analysis. Analyses were also stratified by ethnicity, type of violence, neighbourhood poverty and post-conflict residential status for selected variables. No schooling/primary educational attainment among women (OR 2.46 95% CI 1.83-3.30) and their partners (OR 2.87 95% CI 2.06-4.00), financial insecurity (OR 2.17 95% CI 1.92-2.45) and poor household wealth (OR 2.64 95% CI 2.22-3.13) were the socioeconomic factors that showed the strongest association with any IPV, after adjusting for age and religion. These associations predominately related to physical and/or sexual violence, with weak associations for psychological violence. Women living in a post-conflict environment had a higher risk (OR 2.96 95% CI 2.51-3.49) of IPV compared to other areas. Ethnic minority women (Tamil and Moor) were more likely to reside in post-conflict areas and experience poverty more acutely compared to the majority Sinhala women, which may explain the stronger associations for low SEP, post-conflict residence and IPV found among Tamil and Moor women. Policies and programs to alleviate poverty, as well as community mobilisation and school-based education programs addressing harmful gender norms may be beneficial. Trauma informed approaches are needed in post-conflict settings. Further exploratory studies investigating the complex interplay of individual, household and contextual factors occurring in this setting is required

Impacts of streamflow alteration on benthic macroinvertebrates by mini‑hydro diversion in Sri Lanka

Our study focused on quantifying the alterations of streamflow at a weir site due to the construction of a mini-hydropower plant in the Gurugoda Oya (Sri Lanka), and evaluating the spatial responses of benthic macroinvertebrates to altered flow regime. The HEC-HMS 3.5 model was applied to the Gurugoda Oya sub-catchment to generate streamflows for the time period 1991-2013. Pre-weir flows were compared to post-weir flows with 32 Indicators of Hydrologic Alteration using the range of variability approach (RVA). Concurrently, six study sites were established upstream and downstream of the weir, and benthic macroinvertebrates were sampled monthly from May to November 2013 (during the wet season). The key water physico-chemical parameters were also determined. RVA analysis showed that environmental flow was not maintained below the weir. The mean rate of non-attainment was similar to 45% suggesting a moderate level of hydrologic alteration. Benthic macroinvertebrate communities significantly differed between the study sites located above and below the weir, with a richness reduction due to water diversion. The spatial distribution of zoobenthic fauna was governed by water depth, dissolved oxygen content and volume flow rate. Our work provides first evidence on the effects of small hydropower on river ecosystem in a largely understudied region. Studies like this are important to setting-up adequate e-flows

UAV Remote Sensing for delineation of Urban Vegetation using Object Based Image Analysis

Remote sensing technology has rapidly advanced during the last few decades and the number of remote sensing platforms has increased. The development of Unmanned Aerial Vehicles (UAV) image acquisition systems has radically changed the aerial Photogrammetric mapping due to its low cost, high spatial resolution and high accuracy and provide a great potential for vegetation mapping in urban areas. Urban environment planning becomes a challenging task for urban planners due to fast urbanization processes and growth of population. Urban land use is a crucial information for planning authorities and there is a growing demand for urban land cover maps for decision-making procedures in urban planning. In this article, we demonstrate a rule sets knowledge-based classification method, in object oriented classification which is a fully automated and highly accurate engineering approach for demarcation of urban vegetation with the use of eCognition software. DJI Phantom 4, consumer grade drone was used to acquire high resolution aerial photos as an input dataset in the study. In this study, vegetation mapping was done using the textural and contextual information acquired from the RGB image (Orthophoto) without using any Near Infrared (NIR) information and a Digital Surface Model (DSM) which was developed using Pix4D software, used as an ancillary data in the classification process in order to obtain the elevation information. The extraction of tree canopy and the buildings in a coastal urban environment has used to illustrate the analysis. The DSM was validated using ground control points observed by field measurements. The resultant urban vegetation map was validated with the digitized land use layer and an overall accuracy of 90.15% was obtained. This study indicates that low cost drones compared to the survey grade drones, also can provide high accurate and high resolution products suitable for many urban local area planning studies.Keywords: Photogrammetry, Object oriented classification, DSM, Orthophoto, Urban plannin

Nature of Prehistoric Archaeological Investigation and Research in Sri Lanka (1992 – 2019)

Sri Lankan prehistoric investigations can be divided into several phases. Identifying the nature of prehistoric archaeologicalinvestigation and research in Sri Lanka between 1992 – 2018 is the research problem of this paper. The main objective of theresearch is to collect data and information of Prehistoric Archaeological Investigation and Research (Exploration andExcavation) in Sri Lanka between 1992 – 2018 and arrange them in chronological order. In this process data and information werecollected using primary and secondary sources through library survey, Field study, web survey and interviews were conducted toobtain more quantitative data The key research findings of the research are based on the identified several extraordinaryfeatures of this period compared to the early research periods such as systematic excavations, chronological methods, multidisciplinary approach, researches in associated with new scientific methodologies and innovative scientific methodologies including genealogical experiments. DOI : http://doi.org/10.31357/fhss/vjhss.v06i01.1

Accurate Crop Spraying with RTK and Machine Learning on an Autonomous Field Robot

The agriculture sector requires a lot of labor and resources. Hence, farmers are constantly being pressed for technology and automation to be cost-effective. In this context, autonomous robots can play a very important role in carrying out agricultural tasks such as spraying, sowing, inspection, and even harvesting. This paper presents one such autonomous robot that is able to identify plants and spray agro-chemicals precisely. The robot uses machine vision technologies to find plants and RTK-GPS technology to navigate the robot along a predetermined path. The experiments were conducted in a field of potted plants in which successful results have been obtained.Comment: 7 pages, 12 figures, Journa

Human epidermal growth factor receptor-2 gene expression positivity determined by silver in situ hybridization/immunohistochemistry methods and associated factors in a cohort of Sri Lankan patients with gastric adenocarcinoma : a prospective study

Objective: Positive human epidermal growth factor 2 (HER2) expression and its predictive clinicopathological features remain unclear in Sri Lankan gastric cancer (GC) patients. Here, we aimed to determine GC HER2 status predictors by analyzing associations between clinicopathological features and HER2 expression using immunohistochemistry (IHC) and silver in situ hybridization (SISH). Methods: During this 4-year prospective study, clinicopathological data were collected from participants in the National Hospital of Sri Lanka. HER2 IHC and SISH were performed using commercial reagents. Using chi-square tests, associations of HER2-IHC/SISH with clinicopathological features were analyzed. Results: Overall, 145 GC patients were included, 69 had gastrectomies and 76 had biopsies. Positive HER2 expression by IHC was associated with age 5/high-power field, with additional perineural invasion and lymphovascular invasion in resections. These features, excluding lymphovascular invasion but including male sex, were associated with HER2 expression by SISH. Conclusions: Age <60 years, high nuclear grade, tumor necrosis, and perineural invasion are associated factors of HER2 status. These could be used to triage GC patients for HER2 status testing in limited resource settings where IHC/SISH analysis is costly