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Number of results: 8
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Abstract

Water is widely used in the mining industry, particularly in mineral enrichment processes. In the process of magnetic separation or flotation of crushed ore, a concentrate (an enriched product), and tailings (a product with a low content of a useful component) are obtained. One of the main tasks of enrichment processes is the efficient use of water resources. This is achieved by reclaiming and subsequent reusing water contained in ore beneficiation products by extracting it in industrial thickeners. Optimizing this process makes it possible to reduce water usage in the mining industry, reduce costs of mineral enrichment processes, and address extremely urgent environmental protection problems. To evaluate the process of sedimentation of the solid phase in the pulp within the thickener, measurements of parameters of longitudinal ultrasonic oscillations and Lamb waves that have traveled a fixed distance in the pulp and along the measuring surface in contact with it are used. The proposed approach allows for the consideration of pulp density, particle size of the solid phase in the ore material and the dynamics of changes in these parameters in the thickener at the initial stage of the sedimentation process. Based on the obtained values, adjustments can be made to the characteristics of its initial product, leading to reduced water usage and minimized loss of a useful component.
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Authors and Affiliations

Vladimir Morkun
1
Natalia Morkun
1
Vitaliy Tron
1
Oleksandra Serdiuk
1
Alona Haponenko
1

  1. Kryvyi Rih National University, Kryvyi Rih, Ukraine
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Abstract

Energy based approach was used in the study to formulate a set of functions approximating the magnetic flux linkages versus independent currents. The simplest power series that approximates field co-energy and linked fluxes for a two winding core of an induction machine are described by a set of common unknown coefficients. The authors tested three algorithms for the coefficient estimation using Weighted Least-Squared Method for two different positions of the coils. The comparison of the approximation accuracy was accomplished in the specified area of the currents. All proposed algorithms of the coefficient estimation have been found to be effective. The algorithm based solely on the magnetic field co-energy values is significantly simpler than the method based on the magnetic flux linkages estimation concept. The algorithm based on the field co-energy and linked fluxes seems to be the most suitable for determining simultaneously the coefficients of power series approximating linked fluxes and field co-energy.

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Authors and Affiliations

Tadeusz J. Sobczyk
Adam Warzecha
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Abstract

Abstract. The paper introduces a neuromorphic computational approach for breathing rate monitoring of a single person observed using a Frequency-Modulated Continuous Wave radar. The architecture, aimed at implementation in analog hardware to ensure high energy efficiency and to provide system operation longevity, comprises two main functional modules. The first one is a data preprocessing unit aimed at the extraction of information relevant to the analysis objective, whereas the second one is a pre-trained recurrent neural regressor, which analyzes sequences of incoming samples and estimates the breathing rate. To ensure compatibility with neural processing and to achieve simplicity of underlying resources, several solutions were proposed for the data preprocessing module, which provides range-wise space segmentation, selection of a bin of interest (comprising the dominant motion activity), and delivery of data to regressor inputs. To implement these functions, we introduce an appropriate chirp frequency modulation scheme, apply a neuromorphic filtering procedure and use a Winner-Takes-All network for extracting information from the bin of interest. The architecture has been experimentally verified using a dataset of indoor recordings supplied with reference data from a Zephyr BioHarness device. We show that the proposed architecture is capable of making correct breathing rate estimates while being feasible for analog implementation. The mean squared regression error with respect to the Zephyr-produced reference values is approximately 3.3 breaths per minute (with a deviation of ±0:27 in the 95% confidence interval) and the estimates are produced by a recurrent, GRU-based neural regressor, with a total of only 147 parameters.
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Authors and Affiliations

Krzysztof Ślot
1
ORCID: ORCID
Piotr Łuczak
1
ORCID: ORCID
Sławomir Hausman
2
ORCID: ORCID

  1. Institute of Applied Computer Science, Lodz University of Technology
  2. Institute of Electronics, Lodz University of Technology
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Abstract

A new approach to solve the inverse problem in electrical capacitance tomography is presented. The proposed method is based on an artificial neural network to estimate three different parameters of a circular object present inside a pipeline, i.e. radius and 2D position coordinates. This information allows the estimation of the distribution of material inside a pipe and determination of the characteristic parameters of a range of flows, which are characterised by a circular objects emerging within a cross section such as funnel flow in a silo gravitational discharging process. The main advantages of the proposed approach are explicitly: the desired characteristic flow parameters are estimated directly from the measured capacitances and rapidity, which in turn is crucial for online flow monitoring. In a classic approach in order to obtain these parameters in the first step the image is reconstructed and then the parameters are estimated with the use of image processing methods. The obtained results showed significant reduction of computations time in comparison to the iterative LBP or Levenberg-Marquard algorithms.

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Authors and Affiliations

Hela Garbaa
Andrzej Romanowski
ORCID: ORCID
Lidia Jackowska-Strumiłło
Krzysztof Grudzień
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Abstract

There are reasons researchers may be interested in accounting for spatial heterogeneity of preferences, including avoiding model misspecification and the resulting bias, and deriving spatial maps of willingness-to-pay (WTP), which are relevant for policy-making and environmental management. We employ a Monte Carlo simulation of three econometric approaches to account for spatial preference heterogeneity in discrete choice models. The first is based on the analysis of individual-specific estimates of the mixed logit model. The second extends this model to explicitly account for spatial autocorrelation of random parameters, instead of simply conditioning individual-specific estimates on population-level distributions and individuals’ choices. The third is the geographically weighted multinomial logit model, which incorporates spatial dimensions using geographical weights to estimate location-specific choice models. We analyze the performance of these methods in recovering population-, region- and individual-level preference parameter estimates and implied WTP in the case of spatial preference heterogeneity. We find that, although ignoring spatial preference heterogeneity did not significantly bias population-level results of the simple mixed logit model, neither individual-specific estimates nor the geographically weighted multinomial logit model was able to reliably recover the true region- and individual-specific parameters. We show that the spatial mixed logit proposed in this study is promising and outline possibilities for future development.
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Bibliography

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Authors and Affiliations

Wiktor Budziński
1
ORCID: ORCID
Mikołaj Czajkowski
1
ORCID: ORCID

  1. University of Warsaw
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Abstract

Due to the nonlinear current-voltage (I-V) relationship of the photovoltaic (PV) module, building a precise mathematical model of the PV module is necessary for evaluating and optimizing the PV systems. This paper proposes a method of building PV parameter estimation models based on golden jackal optimization (GJO). GJO is a recently developed algorithm inspired by the idea of the hunting behavior of golden jackals. The explored and exploited searching strategies of GJO are built based on searching for prey as well as harassing and grabbing prey of golden jackals. The performance of GJO is considered on the commercial KC200GT module under various levels of irradiance and temperature. Its performance is compared to well-known particle swarm optimization (PSO), recent Henry gas solubility optimization (HGSO) and some previous methods. The obtained results show that GJO can estimate unknown PV parameters with high precision. Furthermore, GJO can also provide better efficiency than PSO and HGSO in terms of statistical results over several runs. Thus, GJO can be a reliable algorithm for the PV parameter estimation problem under different environmental conditions.
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Authors and Affiliations

Thuan Thanh Nguyen
1
ORCID: ORCID

  1. Faculty of Electrical Engineering Technology, Industrial University of Ho Chi Minh City, No. 12 Nguyen Van Bao, Ward 4, Go Vap District, Ho Chi Minh City, Vietnam
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Abstract

Specific requirements are designed and implemented in electronic and telecommunication systems for received signals, especially high-frequency ones, to examine and control the signal radiation. However, as a serious drawback, no special requirements are considered for the transmitted signals from a subsystem. Different industries have always been struggling with electromagnetic interferences affecting their electronic and telecommunication systems and imposing significant costs. It is thus necessary to specifically investigate this problem as every device is continuously exposed to interferences. Signal processing allows for the decomposition of a signal to its different components to simulate each component. Radiation control has its specific complexities in systems, requiring necessary measures from the very beginning of the design. This study attempted to determine the highest radiation from a subsystem by estimating the radiation fields. The study goal was to investigate the level of radiations received and transmitted from the adjacent systems, respectively, and present methods for control and eliminate the existing radiations.

The proposed approach employs an algorithm which is based on multi-component signals, defect, and the radiation shield used in the subsystem. The algorithm flowchart focuses on the separation and of signal components and electromagnetic interference reduction. In this algorithm, the detection process is carried out at the bounds of each component, after which the separation process is performed in the vicinity of the different bounds. The proposed method works based on the Fourier transform of impulse functions for signal components decomposition that was employed to develop an algorithm for separation of the components of the signals input to the subsystem.

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Authors and Affiliations

Milad Daneshvar
Naser Parhizgar
Homayoon Oraizi

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