Evaluation of pour-flush latrines and pit management in Honduras

In order to meet the Sustainable Development Goals criteria for sustainable sanitation, sanitation solutions must safely separate humans from waste and include safe disposal in situ or treatment off-site of excreta. In 2016, Water Mission conducted a cross-sectional evaluation assessing the function, use, and pit management of 15,644 pour-flush latrines installed in Colón, Honduras between 2007 and 2015. Continued function of 85% of latrines and continued use of 82% demonstrated viability of the latrines, at least up until the point of pit fill. Of the 15% of pits that had filled at the time of survey, nearly 77% of households had not taken any action to enable ongoing pit functionality, likely attributable to a lack of planning. Increased education and programming on pit management and the training of a local mason are now integrated into the employed approach in efforts to improve the longer-term viability of this sanitation solution

Numerical calculation of varistor model for sinusoidal signal

ZnO varistors are semiconductor devices with highly nonlinear current-voltage characteristic and are widely used as devices for overvoltage protection. Varistor applications range from the use of small varistors to protect electronic components to large varistors for protection of power systems. This paper presents proposed model of ZnO varistor and methodology of its mathematical analysis and simulation. The mathematical analysis of the proposed model makes it possible simulate the current trace on a nonlinear element

Neural networks for real-time estimation of parameters of signals in power systems

Fast determination of parameters of the fundamental waveform of voltages and currents is essential for the control and protection of electrical power systems. Most of the known digital algorithms are not fully parallel, so that the speed of processing is quite limited. New parallel algorithms, which can be implemented by analogue adaptive circuits employing some neural networks principles, are proposed. The problem of estimation is formulated as an optimization problem and solved by using the gradient descent method. Algorithms based on the least absolute value, the minimax, the least-squares and the robust leastsquares criteria are developed and compared. The networks process samples of observed noisy signals (voltages or currents) and give as a solution the desired parameters of signal components. Extensive computer simulations confirm the validity and performance of the proposed algorithms and neural network realizations. The proposed methods seem to be particularly useful for real-time, high-speed estimation of parameters of sinusoidal signals in electrical power systems

Neural networks for real-time estimation of parameters of signals in power systems

The purpose of this paper is to present new algorithms and along with them new architectures of analogue neuron-like adaptive processors for online estimation of parameters of sinusoidal signals, which are distorted by higher harmonics and corrupted by noise. For steady-state conditions we have developed neural networks which enable us to estimate the amplitudes and the frequency of the fundamental component of signals. When estimating the basic waveform of currents during short circuits the exponential DC component distorts the results. Assuming the known frequency, we have developed adaptive neural networks which enable us to estimate the amplitudes of the basic components as well as the amplitudes and the time constant of a DC component. The problem of estimation of signal parameters is formulated as an unconstrained optimization problem and solved by using the gradient descent continuous-time method. Basing on this approach we have developed systems of nonlinear differential equations that can be implemented by analog adaptive neural networks. The solution of the optimization problem bases on some principles given by Tank and Hopfield [ 4 ] as well as by Kennedy and Chua. The developed networks contain elements which are similar to the adaptive threshold elements of the perceptron presented by Widrow

Adaptive Neural Networks for Robust Estimation of parameters of Noisy Harmonic Signals

In many applications, very fast methods are required for estimating and measurement of parameters of harmonic signals distorted by noise. This follows from the fact that signals have often time varying amplitudes. Most of the known digital algorithms are not fully parallel, so that the speed of processing is quite limited. In this paper we propose new parallel algorithms, which can be implemented by analogue adaptive circuits employing some neural network principles. The problem of estimation is formulated as an optimization problem and solved by using the gradient descent method. Algorithms based on the least-squares (LS), the total least-squares (TLS) and the robust TLS criteria are developed and compared. The networks process samples of observed noisy signals and give as a solution the desired parameters of signal components. Extensive computer simulations confirm the validity and performance of the proposed algorithm

Investigation of Supra-Harmonics through Signal Processing Methods in Smart Grids

Nowadays supra-harmonic distortion studies are gaining attention day by day in power quality research area. When handling communication systems especially Power Line Carrier (PLC) systems in frequency range 2- 150 kHz, they are suitable for causing electromagnetic interference (EMI) to other systems. This study shows results of analysis employing advanced method called ensemble empirical mode decomposition (EEMD) to describe supra-harmonic distortion. Unlike the traditional method (short time fourier transform- STFT), EEMD gives extensive representation for supra-harmonic component

Techno-Economic Optimization of Grid-Connected Photovoltaic (PV) and Battery Systems Based on Maximum Demand Reduction (MDRed) Modelling in Malaysia

Under the present electricity tariff structure in Malaysia, electricity billing on a monthly basis for commercial and industrial consumers includes the net consumption charges together with maximum demand (MD) charges. The use of batteries in combination with photovoltaic (PV) systems is projected to become a viable solution for energy management, in terms of peak load shaving. Based on the latest studies, maximum demand (MD) reduction can be accomplished via a solar PV-battery system based on a few measures such as load pattern, techno-economic traits, and electricity scheme. Based on these measures, the Maximum Demand Reduction (MDRed) Model is developed as an optimization tool for the solar PV-battery system. This paper shows that energy savings on net consumption and maximum demand can be maximized via optimal sizing of the solar PV-battery system using the MATLAB genetic algorithm (GA) tool. GA optimization results revealed that the optimal sizing of solar PV-battery system gives monthly energy savings of up to 20% of net consumption via solar PV self-consumption, 3% of maximum demand (MD) via MD shaving and 2% of surplus power supplied to grid via net energy metering (NEM) in regards to Malaysian electricity tariff scheme and cost of the overall system

Water safety plans and climate change mitigation

[Excerpt] Definition Quality water at affordable prices for all is a key condition for the promotion of public health, environmental sustainability, and quality and safety of life. In a context of growing external uncertainties arising from changes in the climate and the environment, ensuring these conditions is an upward concern and is of utmost relevance to increase scientific research on the impacts of climate change on water quality modification and in minimization/mitigation strategies

Temporal and thematic trends in water, sanitation and hygiene (WaSH) research in Pacific Island Countries: a systematic review

Pacific Island Countries (PICs) lag behind global trends in water, sanitation and hygiene (WaSH) development. We conducted a systematic search of all English language papers (published before February 2015) about WaSH in PICs to evaluate the state of the peer-reviewed literature and explore thematic findings. A total of 121 papers met the criteria for full-text review following an initial search result of more than 6,000 papers. Two reviewers independently assessed the quality and relevance of each article and consolidated their findings according to four emergent themes: public health, environment, emergency response and interventions, and management and governance. Findings indicate a knowledge gap in evidence-guided WaSH management strategies that advocate for human health while concurrently protecting and preserving drinking water resources. Extreme weather events threaten the quantity and quality of limited freshwater resources, and cultural factors that are unique to PICs present challenges to hygiene and sanitation. This review highlights the strengths and weaknesses of the peer-reviewed literature on WaSH in PICs, addresses spatial and temporal publication trends, and suggests areas in need of further research to help PICs meet development goals

On-plot drinking water supplies and health: a systematic review

Many studies have found that household access to water supplies near to or on the household plot can reduce the probability of diarrhea, trachoma, and other water-related diseases, and it is generally accepted that on-plot water supplies produce health benefits for households. However, the collective body of research literature has not been analyzed to weigh the evidence supporting this. A systematic literature review was conducted to investigate the impacts of on-plot water supplies on diarrhea, trachoma, child growth, and water-related diseases, to further examine the relationship between household health and distance to water source and to assess whether on-plot water supplies generate health gains for households. Studies provide evidence that households with on-plot water supplies experience fewer diarrheal and helminth infections and greater child height. Findings suggest that water-washed diseases are more strongly impacted by on-plot water access than waterborne diseases. Few studies analyzed the effects of on-plot water access on quantity of domestic water used, hygiene behavior, and use of multiple water sources, and the lack of evidence for these relationships reveals an important gap in current literature. The review findings indicate that on-plot water access is a useful health indicator and benchmark for the progressive realization of the Sustainable Development Goal target of universal safe water access as well as the human right to safe water