An recurrent neural network application to forecasting the quality of water diversion in the water source of Lake Taihu

2011 ◽  
Author(s):  
Heyi Wang ◽  
Yi Gao ◽  
Zhaoan Xu ◽  
Weidong Xu
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Lake Taihu ◽  
Water Source ◽  
Water Diversion ◽  
Quality Of Water ◽  
Network Application

A Robust False Spam Review Detection Using Deep Long Short-Term Memory (LSTM) Based Recurrent Neural Network

2020 ◽  
Vol 17 (8) ◽  
pp. 3421-3426
Author(s):  
D. Deva Hema ◽  
J. Tharun ◽  
G. Arun Dev ◽  
N. Sateesh
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Short Term Memory ◽  
Online Reviews ◽  
Physical Contact ◽  
Proposed Model ◽  
Deep Recurrent Neural Network ◽  
Bayes Algorithm ◽  
Fake Reviews

Our day-to-day activity is highly influenced by development of Internet. One of the rapid growing area in Internet is E-commerce. People are eager to buy products from online sites like Amazon, embay, Flipkart etc. Customers can write reviews about the products purchased online. The purchasing of good through online has been increasing exponentially since last few years. As there is no physical contact with goods before purchasing through online, people totally rely on reviews about the product before purchasing it. Hence review plays an important role in deciding the quality of the product. There are many customers who give online reviews about the product after using it. Hence the quality of the product is decided by the reviews of the customers. Thus, detection of fake reviews has become one of the important task. The proposed system will help in finding such fake reviews about the product, so that the fake reviews can be eliminated. Therefore, the purchasing of the products will be totally based on the genuine reviews. The proposed system uses Deep Recurrent Neural Network (DRNN) to predict the fake reviews and the performance of the proposed method has compared with Naïve Bayes Algorithm. The proposed model shows good accuracy and can handle huge amount of data over the existing system.

Contributions Regarding the Possibility of Increasing the Milling Process Efficiency

2013 ◽  
Vol 436 ◽  
pp. 219-224
Author(s):  
Cristian Gelmereanu ◽  
Stefan Bogdan ◽  
Liviu Morar
Keyword(s):  
Neural Network ◽  
Execution Time ◽  
Milling Process ◽  
Cutting Process ◽  
Process Efficiency ◽  
Workpiece Vibration ◽  
Network Application ◽  
Increase Efficiency

The main purpose of the paper is to develop a neural network application that could predict the tool-workpiece vibration. Increase efficiency by decreasing vibrations has been imposed by the cutting progresses theory and the fields related directly to the cutting process. Thus, this procedure aims to an increasing efficiency, lowering costs and execution time and also improving the quality of parts.

scholarly journals Water quality and management in the Australian pig industry

2021 ◽  
Vol 61 (7) ◽  
pp. 637
Author(s):  
Louise Edwards ◽  
Helen Crabb
Keyword(s):  
Water Quality ◽  
Management Practices ◽  
Production Systems ◽  
Water Source ◽  
Quality Parameters ◽  
Quality Of Water ◽  
Standard Quality ◽  
Pig Performance ◽  
The Impact

Context Water is the first nutrient and an essential component of all agricultural production systems. Despite its importance there has been limited research on water, and in particular, the impact of its availability, management and quality on production systems. Aims This research sought to describe the management and quality of water used within the Australian pig industry. Specifically, the water sources utilised, how water was managed and to evaluate water quality at both the source and the point of delivery to the pig. Methods Fifty-seven commercial piggeries across Australia participated in this study by completing a written survey on water management. In addition, survey participants undertook physical farm parameter measurements including collecting water samples. Each water sample was tested for standard quality parameters including pH, hardness, heavy metals and microbiological status. Key results Responses were received from 57 farms, estimated to represent at least 22% of ‘large’ pig herds. Bore water was the most common water source being utilised within the farms surveyed. Management practices and infrastructure delivering water from the source to the point of consumption were found to differ across the farms surveyed. Furthermore, water was regularly used as a delivery mechanism for soluble additives such as antibiotics. The quality of water at the source and point of consumption was found to be highly variable with many parameters, particularly pH, hardness, salinity, iron, manganese and microbiological levels, exceeding the acceptable standard. Conclusions In general, water quality did not appear to be routinely monitored or managed. As a result, farm managers had poor visibility of the potential negative impacts that inferior water quality or management may be having on pig production and in turn the economics of their business. Indeed, inferior water quality may impact the delivery of antibiotics and in turn undermine the industry’s antimicrobial stewardship efforts. Implications The study findings suggest that water quality represents a significant challenge to the Australian pig industry. Access to drinking water of an acceptable quality is essential for optimal pig performance, health and welfare but also to ensure farm to fork supply chain integrity, traceability and food safety.

SUITABILITY OF LOW TEMPERATURE VACUUM PAN EVAPORATOR CONDENSATE FOR PLANT USES

1966 ◽  
Vol 29 (2) ◽  
pp. 40-44
Author(s):  
Daniel A. Stock
Keyword(s):  
Low Temperature ◽  
Skim Milk ◽  
Water Source ◽  
Additional Treatment ◽  
Pan Evaporation ◽  
Quality Of Water ◽  
Plant Uses ◽  
Preliminary Study ◽  
Exchange Medium

Summary A preliminary study to investigate the possibility of utilizing condensates and tailwater from the low temperature vacuum pan evaporation of skim milk for evaporating plant uses was made. The results indicated that the utilization of these condensates and tailwaters for various plant purposes is possible and should provide a readily available, safe and sanitary water source if adequate steps such as quality monitoring and treatment are taken to insure that the highest quality of water is retained and used. The use of tailwater as a heat exchange medium on a single pass basis should require only quality control monitoring. However, condensate or tailwater which is to be used for other purposes should be aerated and may need additional treatment to prevent the development of tastes, odors, growths, corrosion, and scale formation.

scholarly journals Nonlinear Autoregressive Recurrent Neural Network Model for Quality of Service Prediction

2020 ◽  
Vol 8 (6) ◽  
pp. 4762-4770
Keyword(s):  
Neural Network ◽  
Quality Of Service ◽  
Recurrent Neural Network ◽  
Prediction System ◽  
Qos Prediction ◽  
Proposed Model ◽  
Routing Monitoring ◽  
The Given ◽  
Nonlinear Autoregressive

Due to the advances in computer networks, Internet and multimedia communications, Quality of Service (QoS) monitoring and assessment become an increasingly important. The importance of assessing QoS stems from the fact it may reflect the resources availability of a network that may provide solutions for QoS provision, routing, monitoring, management … etc. In the literature, several monitoring and measurement approached and methods have been developed to quantify and predict the QoS of multimedia applications transmitted over such networks. In this research, a new QoS prediction system will be designed. The proposed system is based on using the Nonlinear Autoregressive with eXogenous input model (NARX) using recurrent neural network. This prediction system uses in addition to the QoS parameters; previous measured QoS values will used as inputs to this model. The expected output of this new model is the forecasted QoS. The proposed model will be trained, tested, validated and then optimized to provide a good estimate of the QoS provided by the given network. Simulation results are expected to show that the proposed model will have high accurate QoS prediction capabilities compared to other QoS assessment systems adopted in the literature.

scholarly journals Determinants of Water Source Use, Quality of Water, Sanitation and Hygiene Perceptions among Urban Households in North-West Ethiopia: A Cross-Sectional Study

2020 ◽  
Author(s):  
Shewayiref Geremew Gebremichael ◽  
Emebet Yismaw ◽  
Belete Dejen ◽  
Adeladilew Dires
Keyword(s):  
Drinking Water ◽  
Water Source ◽  
Cross Sectional Study ◽  
Water Sources ◽  
Cross Sectional ◽  
North West ◽  
Drinking Water Sources ◽  
Quality Of Water ◽  
North West Ethiopia

AbstractBackgroundClean water is an essential element for human health, wellbeing, and prosperity. Every human being has the right to access safe drinking water. But, in now day, due to rapid population growth, illiteracy, lack of sustainable development, and climate change; it still faces a global challenge for about one billion people in the developing nation. The discontinuity of drinking water supply puts in force households either to use unsafe water storage materials or to use water from unimproved sources. This study aimed to identify the determinants of water source types, use, quality of water, and sanitation perception of physical parameters among urban households in North-West Ethiopia.MethodsA community-based cross-sectional study was conducted among households from February to March 2019. An interview-based pre-tested and structured questionnaire was used to collect the data. Data collection samples were selected randomly and proportional to each kebeles’ households. MS Excel and R Version 3.6.2 was used to enter and analyze the data; respectively. Descriptive statistics using frequencies and percentages were used to explain the sample data concerning the predictor variable. Both bivariate and multivariate logistic regressions were used to assess the association between the independent and the response variables.ResultsFour hundred eighteen (418) households have participated. Based on the study undertaken, 78.95% of households used improved and 21.05% of households used unimproved drinking water sources. Households drinking water sources are significantly associated with age of participant (x2 = 20.392, df=3), educational status (x2 = 19.358, df=4), source of income (x2 = 21.777, df=3), monthly income (x2 = 13.322, df=3), availability of additional facilities (x2 = 98.144, df=7), cleanness status (x2 =42.979, df=4), scarcity of water (x2 = 5.1388, df=1) and family size (x2 = 9.934, df=2). The logistic regression analysis also indicated as those factors are significantly determined (p 0.05) the water source types used by households. Factors such as availability of toilet facility, household member type, and sex of head of the household are not significantly associated with the drinking water sources.ConclusionThe study showed that being an older age group of the head of the household, being government employer, merchant and self-employed, being a higher income group, the presence of all facilities in the area, lived in a clean surrounding and lower family size are the determinant factors of using drinking water from improved sources. Therefore; the local, regional, and national governments and other supporting organizations shall improve the accessibility and adequacy of drinking water from improved sources through short and long time plans for the well-being of the community in the area.

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