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We consider the problem of inferring the operational status of a reactor facility using measurements from a radiation sensor network deployed around the facility's ventilation off-gas stack. The intensity of stack emissions decays with distance, and the sensor counts or measurements are inherently random with parameters determined by the intensity at the sensor's location. We utilize the measurements...
This work proposes an ANN based method for fetal heart rate monitoring. Various measurements are taken and given as input to the ANN based classifier to detect fetal health such as ‘Normal’, ‘Suspect’ and ‘Pathologic’. All the design and simulation works are carried out with MATLAB software. ANN based classifier is trained with data from various recordings of cardiotocography. After the network is...
Energy forecast is essential for a good planning of the electricity consumption as well as for the implementation of decision support systems which can lead the decision making process of energy system. Energy consumption time series prediction problems represent a difficult type of predictive modelling problem due to the existence of complex linear and non-linear patterns. This paper presents two...
This paper considers architecture and functionality of the embedded data acquisition system for automated beehive monitoring. A description of constructed sensor subsystems is given. Proposed solution acquires hive temperature, humidity and weight referring this data to the mobile application via wireless network. The system also performs an analysis of collected bee noises with artificial neural...
The paper presents some models based on artificial neural networks for particulate matter concentration forecasting. A methodology framework is proposed for selecting the best forecasting model from a set of neural networks models. First, two artificial neural network types (feed forward and radial basis) are analyzed for concentration forecasting of the particulate matter with diameter less than...
The article deals with the application of remote sensing of agricultural plantations for assessment of their nitrogen fertilizer provision. The basic technologies of remote sensing used today, their advantages and disadvantages are described. A new calibration method for images obtained from sensors placed on the platform of UAV in unstable illumination based on EXIFF data file, such as size Light...
Electrophysiological approach of stimulation of surgical wound tissues for recurrent laryngeal nerve (RLN) localization is considered. It is proposed to use neural network (NN) that identifying the distance from stimulation point to RLN for this purpose. Method of NN learning based on interval data analysis is proposed.
Virtual flow metering (VFM) is an attractive and cost-effective solution to meet the rising multiphase flow monitoring demands in the petroleum industry. It can also augment and backup physical multiphase flow metering. In this study, a heterogeneous ensemble of neural networks and regression trees is proposed to develop a VFM model utilizing bootstrapping and parameter perturbation to generate diversity...
The performance conditions of steam turbine regenerative system have important influence on the safety and economy of the units. It is of great significance to doing the research on the performance monitoring of the regenerative system to ensure the safe and economical operation of the whole coal-fired power plants. In view of the shortcomings of the complexity of traditional performance monitoring...
This paper is using artificial neural network (ANN) to predict oxygen content in the water for the fish farm, so that decrease times of starts of oxygen suppliers. In Southern Taiwan, aquaculture is one of major economic industries. Especially, the important issue is how to effectively monitor the oxygen content in the water, so that the fish will not die and start the oxygen suppliers for the minimum...
The critical requirements for devices connected in Internet of Things (IoT) are long battery life, long coverage range, and low deployment cost. In our previous work, we developed cognitive controller for controlling the HVAC of non-domestic building using short range communication in an unlicensed spectrum (915 MHz). In this work, we have upgraded our cognitive controller with recently developed...
In this paper, a neural network-based method for leakage detection of a gas pipeline by using gas flow pattern is proposed. The pipe is divided in several segments and each segment is modeled by considering input/output pressure of the gas flow. The idea is to use a computer network based on Internet of Things (IOT) phenomena to gather all the required information for detection of the leakage point...
This article concern to systems that support the manage economical use of electricity. An advisory and monitoring system equipped with artificial intelligence for non-invasive on-line identification of electrical devices was proposed. Research has been done on the basic element of the system, which is the classifier module. As data describing the objects, the electrical quantities obtained from the...
A smart wearable electrocardiographic (ECG) processor is presented for secure ECG-based biometric authentication and cardiac monitoring, including arrhythmia and anomaly detection. Data-driven Lasso regression and low-precision techniques are developed to compress the neural networks by 24.4X. The prototype chip fabricated in 65 nm LP CMOS consumes 1.06 μW at 0.55 V for real-time ECG authentication...
Wearable smart sensing is a promising technology to enhance user experience that has already been exploited in sport/fitness, as well as health and human monitoring. Wearable sensing systems not only provide continuous data monitoring and acquisition, but are also expected to process, and make sense of the acquired data by classification in similar ways as human experts do. Supporting continuous operation...
Level control is one of the most used processes in industries. However, it can present nonlinearities, which can make difficult its project. The PID controller is still a commonly used topology due to the non-necessity to know the full system dynamics, only the modelling that well describes the system behavior. The objective of this work is to identify, control and audit a level tank system from a...
An adaptive neuro-fuzzy inference system-based partial least squares (ANFIS-PLS) method was proposed for monitoring nonlinear processes. The ANFIS was used as a predictor to represent the nonlinear relationship between input and output score variables in each inner loop of PLS, and fuzzy c-means clustering was employed to determine the number of fuzzy rules. Moreover, the hybrid learning algorithm...
As a fetal surveillance technique, cardiotocography (CTG) involves fetal heart rate (FHR), uterine contraction activities, and fetal movements. CTG is practiced as a primary diagnostic test throughout the world to identify events that may pose a risk to the fetus during pregnancy and delivery. In this work, FHR signals carrying vital information on fetus were analyzed by using Haar (haar), Daubechies...
In today's world, structural development with reliability and integrity is an ever demanding process. Fault detection is the identification of normal healthy behavior of a system or process and recognition of any deviation from such normal behavior. Fault detection in structural systems provides important liability and financial advantages since it gives the decision-makers lead-time and flexibility...
Software Networks built by combining Software Defined Networks (SDN), Network Function Virtualization (NFV) and Cloud principles call for agile and dynamic automation of management operations to ensure continuous provisioning and deployment of networked resources and services. In this context, efficient Service Level Agreements (SLA) management and anticipation of Service Level Objectives (SLO) breaches...
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