Lateral displacements of commonly found gravity retaining walls in Sri Lanka due to seismic action

Gravity type retaining walls have been widely used to retain soil in Sri Lanka. However, it was reported that the performance of gravity type retaining walls during earthquake is poor. In view of the above, it was attempted in this study to develop a methodology to estimate the possible displacements of commonly found gravity retaining walls in Sri Lanka due to expected earthquakes. In addition, it was attempted to recommend an optimum shape for gravity retaining walls to minimize the possible displacements. This work was backed by Mononobe-Okabe theory and Newmark‟s sliding wedge analysis. Using Mononobe-Okabe analysis, threshold acceleration that would cause a relative displacement between retaining wall and soil, was found for different types of retaining walls. Using Newmark‟s method, an analytical model was developed to predict lateral displacements during seismic loadings. Then different acceleration-time histories of earthquakes, which are similar to those observed near Sri Lanka recently, were fed to the developed analytical model and the lateral displacements were found. Gravity retaining walls with a sloping back is found to give the least displacements, compared to the other types such as vertical and battered type gravity retaining walls for same acceleration-time history and to the same ground slope behind the retaining wall

IoTNetSim:A Modelling and Simulation Platform for End-to-End IoT Services and Networking

Internet-of-Things (IoT) systems are becoming increasingly complex, heterogeneous and pervasive, integrating a variety of physical devices and virtual services that are spread across architecture layers (cloud, fog, edge) using different connection types. As such, research and design of such systems have proven to be challenging. Despite the influx in IoT research and the significant benefits of simulation-based approaches in supporting research, there is a general lack of appropriate modelling and simulation platforms to create a detailed representation of end-to-end IoT services, i.e. from the underlying IoT nodes to the application layer in the cloud along with the underlying networking infrastructure. To aid researchers and practitioners in overcoming these challenges, we propose IoTNetSim, a novel self-contained extendable platform for modelling and simulation of end-to-end IoT services. The platform supports modelling heterogeneous IoT nodes (sensors, actuators, gateways, etc.) with their fine-grained details (mobility, energy profile, etc.), as well as different models of application logic and network connectivity. The proposed work is distinct from the current literature, being an all-in-one tool for end-to-end IoT services with a multi-layered architecture that allows modelling IoT systems with different structures. We experimentally validate and evaluate our IoTNetSim implementation using two very large-scale real-world cases from the natural environment and disaster monitoring IoT domains

RELATIONSHIP BETWEEN SOIL CONDITIONS AND OCCURRENCE OF ROOT ROT DISEASE IN A FOREST NURSERY AT KUBALPOLA.

Soil conditions influence the seasonal development and geographical distribution of soil-borne fungi and development of root diseases. Diseased seedlings and soil samples were collected from Kumbalpola nursery which is one of the largest teak nurseries in Sri Lanka. The results of the survey showed that almost 17% of seedling were affected by root rot. Rhizoctonia species, one of the soil inhabitants, was identified as the causal organism of root rot of teak. The fungal populations of infested and non-infested soils of the nursery were studied.The environmental factors which influence the severity of the disease, including soil moisture, soil pH, soil temperature, organic carbon, organic matter and nitrogen contents, were compared in both soils

A model-driven engineering approach for the service integration of IoT systems

With the development of IoT devices and web services, the objects of the real world are more interconnected, which allows applications to extend their characteristics in different fields, including industrial or home environments, among other possible examples such as health, trade, transport, or agriculture. However, this development highlights the challenge of interoperability, because devices are heterogeneous and use different communication protocols and different data formats. For this reason, we propose a model for point-to-point integration in three-layer IoT applications: (a) hardware, which corresponds to the physical objects (controller, sensor and actuator), (b) communication, which is the bridge that allows the exchange of data between a MQTT queue and REST web services, and (c) integration, which establishes a sequence of transactions to coordinate the components of the system. For this purpose, a metamodel, a graphic editor and a code generator have been developed that allow the developer to design IoT systems formed by heterogeneous components without having in-depth knowledge of every hardware and software platform. In order to validate our proposal, a smart home scenario has been developed, with a series of sensors and actuators that combined show a complex behavior

Investigation of obstructive sleep apnea using nonlinear mode interations in nonstationary snore signals

Acoustic studies on snoring sounds have recently drawn attention as a potential alternative to polysomnography in the diagnosis of obstructive sleep apnea (OSA). This paper investigates the feasibility of using nonlinear coupling between frequency modes in snore signals via wavelet bicoherence (WBC) analysis for screening of OSA. Two novel markers (PF1 and PSF), which are frequency modes with high nonlinear coupling strength in their respective WBC spectrum, are proposed to differentiate between apneic and benign snores in same- or both-gender snorers. Snoring sounds were recorded from 40 subjects (30 apneic and 10 benign) by a hanging microphone, and subsequently preprocessed within a wavelet transform domain. Forty inspiratory snores (30 as training and 10 as test data) from each subject were examined. Results demonstrate that nonlinear mode interactions in apneic snores are less self-coupled and usually occupy higher and wider frequency ranges than that of benign snores. PF1 and PSF are indicative of apneic and benign snores (p < 0.0001), with optimal thresholds of PF1 = 285 Hz and PSF = 492 Hz (for both genders combined), as well as sensitivity and specificity values between 85.0 and 90.7%, respectively, outperforming the conventional diagnostic indicator (spectral peak frequency, PF = 243-275 Hz, sensitivity = 77.7-79.7%, specificity = 72.0-78.0%, p < 0.0001). Relationships between apnea-hypopnea index and the proposed markers could likely take the functional form of exponential or power. Perspectives on nonlinear dynamics analysis of snore signals are promising for further research and development of a reliable and inexpensive diagnostic tool for OSA