scholarly journals Artificial intelligence method developed for classifying raw sugarcane in the presence of the solid impurity

2021 ◽  
Vol 46 (3) ◽  
pp. 49-54
Author(s):  
Lucas Janoni Dos Santos ◽  
�rica Regina Filletti ◽  
Fabiola Manhas Verbi Pereira
Keyword(s):  
High Frequency ◽  
Low Cost ◽  
Computational Cost ◽  
Industrial Sector ◽  
Solid Mixture ◽  
Promising Application ◽  
Artificial Neural Network Ann ◽  
Outstanding Result ◽  
Low Computational Cost ◽  
Acquisition Method

An investigation dedicated to evaluating a big issue in biorefineries, solid impurity in raw sugarcane, is presented. This relevant industrial sector requests a high-frequency, low-cost, and noninvasive method. Then, the developed method uses the averaged color values of ten color-scale descriptors: R (red), G (green), B (blue), their relative colors (r, g, and b), H (hue), S (saturation), V (value) and L (luminosity) from digital images acquired from 146 solid mixtures among sugarcane stalks and solid impurity � vegetal parts (green and dry leaves) and soil. The solid mixture of samples was prepared considering desirable and undesirable scenarios for the solid impurity amounts. The outstanding result was revealed by an artificial neural network (ANN), achieving 100% of accurate classifications for two ranges of raw sugarcane in the samples: from 90 to 100 wt% and from 41 to 87 wt%. Low-computational cost and a simple setup for image acquisition method could screen solid impurity in sugarcane shipments as a promising application.

scholarly journals Status Estimation and In-Process Connection of Kanbans Using BLE Beacons and LPWA Network to Implement Intra-Traceability for the Kanban System

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5038
Author(s):  
Kosuke Shima ◽  
Masahiro Yamaguchi ◽  
Takumi Yoshida ◽  
Takanobu Otsuka
Keyword(s):  
Inventory Management ◽  
Low Cost ◽  
Computational Cost ◽  
Low Energy ◽  
Manufacturing Strategy ◽  
Implementation Cost ◽  
Measurement Systems ◽  
Process Route ◽  
Kanban System ◽  
Low Computational Cost

IoT-based measurement systems for manufacturing have been widely implemented. As components that can be implemented at low cost, BLE beacons have been used in several systems developed in previous research. In this work, we focus on the Kanban system, which is a measure used in manufacturing strategy. The Kanban system emphasizes inventory management and is used to produce only required amounts. In the Kanban system, the Kanban cards are rotated through the factory along with the products, and when the products change to a different process route, the Kanban card is removed from the products and the products are assigned to another Kanban. For this reason, a single Kanban cannot trace products from plan to completion. In this work, we propose a system that uses a Bluetooth low energy (BLE) beacon to connect Kanbans in different routes but assigned to the same products. The proposed method estimates the beacon status of whether the Kanban is inside or outside a postbox, which can then be computed by a micro controller at low computational cost. In addition, the system connects the Kanbans using the beacons as paired connection targets. In an experiment, we confirmed that the system connected 70% of the beacons accurately. We also confirmed that the system could connect the Kanbans at a small implementation cost.

scholarly journals Software System Development to Diagnose Heart Diseases

2019 ◽  
Author(s):  
Renan Yuji Koga Ferreira ◽  
Guilherme Camargo Fabricio De Melloy ◽  
Fabio Sakurayz ◽  
Wesley Attrot
Keyword(s):  
Feature Extraction ◽  
Early Detection ◽  
Embedded System ◽  
Wavelet Transforms ◽  
System Development ◽  
Heart Diseases ◽  
Low Cost ◽  
Computational Cost ◽  
Extraction Algorithm ◽  
Low Computational Cost

Many deaths are caused from heart diseases and several of them could be prevented with early detection. Many people do not have conditions to seek for a doctor or sometimes there are not enough physicians to attend them. In order to detect heart diseases we are developing an electrocardiogram feature extraction algorithm using wavelet transforms prioritizing a low computational cost. This algorithm will be integrated in an embedded system that is under development. This system is going to be accessible, portable and have low cost, because we intend to assist people, mostly those who live in precarious regions, that do not have a physician to attend them. To execute tests on our algorithm we will use the ECG records from MITBIH database and after that we will classify the heartbeats in order to detect anomalies on them.

scholarly journals Adaptive single-channel EEG artifact removal with applications to clinical monitoring

2021 ◽  
Author(s):  
Matteo Dora ◽  
David holcman
Keyword(s):  
Real Time ◽  
Single Channel ◽  
Low Cost ◽  
Computational Cost ◽  
Clinical Monitoring ◽  
Artifact Removal ◽  
Anesthesia Monitoring ◽  
Data Driven Approach ◽  
Movement Artifacts ◽  
Low Computational Cost

Objective: Electroencephalography (EEG) has become very common in clinical practice due to its relatively low cost, ease of installation, non-invasiveness, and good temporal resolution. Portable EEG devices are increasingly popular in clinical monitoring applications such as sleep scoring or anesthesia monitoring. In these situations, for reasons of speed and simplicity only few electrodes are used and contamination of the EEG signal by artifacts is inevitable. Visual inspection and manual removal of artifacts is often not possible, especially in real-time applications. Our goal is to develop a flexible technique to remove EEG artifacts in these contexts with minimal supervision. Methods: We propose here a new wavelet-based method which allows to remove artifacts from single-channel EEGs. The method is based on a datadriven renormalization of the wavelet components and is capable of adaptively attenuate artifacts of different nature. We benchmark our method against alternative artifact removal techniques. Results: We assessed the performance of the proposed method on publicly available datasets comprising ocular, muscular, and movement artifacts. The proposed method shows superior performances on different kinds of artifacts and signal-to-noise levels. Finally, we present an application of our method to the monitoring of general anesthesia. Conclusions: We show that our method can successfully attenuate various types of artifacts in single-channel EEG. Significance: Thanks to its data-driven approach and low computational cost, the proposed method provides a valuable tool to remove artifacts in real-time EEG applications with few electrodes, such as monitoring in special care units.

scholarly journals An Acoustic Sensing Gesture Recognition System Design Based on a Hidden Markov Model

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4803
Author(s):  
Bruna Salles Moreira ◽  
Angelo Perkusich ◽  
Saulo O. D. Luiz
Keyword(s):  
Gesture Recognition ◽  
Markov Models ◽  
Hidden Markov ◽  
Low Cost ◽  
Computational Cost ◽  
Recognition System ◽  
Machine Learning Techniques ◽  
Training Time ◽  
Interactive Surface ◽  
Artificial Neural Network Ann

Many human activities are tactile. Recognizing how a person touches an object or a surface surrounding them is an active area of research and it has generated keen interest within the interactive surface community. In this paper, we compare two machine learning techniques, namely Artificial Neural Network (ANN) and Hidden Markov Models (HMM), as they are some of the most common techniques with low computational cost used to classify an acoustic-based input. We employ a small and low-cost hardware design composed of a microphone, a stethoscope, a conditioning circuit, and a microcontroller. Together with an appropriate surface, we integrated these components into a passive gesture recognition input system for experimental evaluation. To perform the evaluation, we acquire the signals using a small microphone and send it through the microcontroller to MATLAB’s toolboxes to implement and evaluate the ANN and HMM models. We also present the hardware and software implementation and discuss the advantages and limitations of these techniques in gesture recognition while using a simple alphabet of three geometrical figures: circle, square, and triangle. The results validate the robustness of the HMM technique that achieved a success rate of 90%, with a shorter training time than the ANN.

scholarly journals A Method to Compensate for the Errors Caused by Temperature in Structured-Light 3D Cameras

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2073
Author(s):  
Oriol Vila ◽  
Imma Boada ◽  
David Raba ◽  
Esteve Farres
Keyword(s):  
Low Cost ◽  
Computational Cost ◽  
Depth Map ◽  
Industrial Applications ◽  
The Other ◽  
Effect Of Temperature ◽  
Step Method ◽  
Hyperbolic Paraboloid ◽  
Thermal Chamber ◽  
Low Computational Cost

Although low cost red-green-blue-depth (RGB-D) cameras are factory calibrated, to meet the accuracy requirements needed in many industrial applications proper calibration strategies have to be applied. Generally, these strategies do not consider the effect of temperature on the camera measurements. The aim of this paper is to evaluate this effect considering an Orbbec Astra camera. To analyze this camera performance, an experimental study in a thermal chamber has been carried out. From this experiment, it has been seen that produced errors can be modeled as an hyperbolic paraboloid function. To compensate for this error, a two-step method that first computes the error and then corrects it has been proposed. To compute the error two possible strategies are proposed, one based on the infrared distortion map and the other on the depth map. The proposed method has been tested in an experimental scenario with different Orbbec Astra cameras and also in a real environment. In both cases, its good performance has been demonstrated. In addition, the method has been compared with the Kinect v1 achieving similar results. Therefore, the proposed method corrects the error due to temperature, is simple, requires a low computational cost and might be applicable to other similar cameras.

scholarly journals Computing Expectiles Using k-Nearest Neighbours Approach

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 645
Author(s):  
Muhammad Farooq ◽  
Sehrish Sarfraz ◽  
Christophe Chesneau ◽  
Mahmood Ul Hassan ◽  
Muhammad Ali Raza ◽  
...  
Keyword(s):  
Computational Cost ◽  
Real Life ◽  
Distance Measures ◽  
Computational Time ◽  
High Dimensional ◽  
Test Error ◽  
Nearest Neighbours ◽  
Comparable Performance ◽  
Asymmetric Least Squares ◽  
Low Computational Cost

Expectiles have gained considerable attention in recent years due to wide applications in many areas. In this study, the k-nearest neighbours approach, together with the asymmetric least squares loss function, called ex-kNN, is proposed for computing expectiles. Firstly, the effect of various distance measures on ex-kNN in terms of test error and computational time is evaluated. It is found that Canberra, Lorentzian, and Soergel distance measures lead to minimum test error, whereas Euclidean, Canberra, and Average of (L1,L∞) lead to a low computational cost. Secondly, the performance of ex-kNN is compared with existing packages er-boost and ex-svm for computing expectiles that are based on nine real life examples. Depending on the nature of data, the ex-kNN showed two to 10 times better performance than er-boost and comparable performance with ex-svm regarding test error. Computationally, the ex-kNN is found two to five times faster than ex-svm and much faster than er-boost, particularly, in the case of high dimensional data.

scholarly journals A Low-cost System for High-frequency Solar Imagery and Power Data Acquisition

2021 ◽  
Vol 1826 (1) ◽  
pp. 012082
Author(s):  
G F Bassous ◽  
R F Calili ◽  
C R H Barbosa
Keyword(s):  
Data Acquisition ◽  
High Frequency ◽  
Low Cost ◽  
Cost System

scholarly journals Directional TGV-Based Image Restoration under Poisson Noise

2021 ◽  
Vol 7 (6) ◽  
pp. 99
Author(s):  
Daniela di Serafino ◽  
Germana Landi ◽  
Marco Viola
Keyword(s):  
Computed Tomography ◽  
Image Restoration ◽  
Gaussian Noise ◽  
Computational Cost ◽  
Data Fitting ◽  
Poisson Noise ◽  
Glass Fibres ◽  
Leibler Divergence ◽  
Generalized Variation ◽  
Low Computational Cost

We are interested in the restoration of noisy and blurry images where the texture mainly follows a single direction (i.e., directional images). Problems of this type arise, for example, in microscopy or computed tomography for carbon or glass fibres. In order to deal with these problems, the Directional Total Generalized Variation (DTGV) was developed by Kongskov et al. in 2017 and 2019, in the case of impulse and Gaussian noise. In this article we focus on images corrupted by Poisson noise, extending the DTGV regularization to image restoration models where the data fitting term is the generalized Kullback–Leibler divergence. We also propose a technique for the identification of the main texture direction, which improves upon the techniques used in the aforementioned work about DTGV. We solve the problem by an ADMM algorithm with proven convergence and subproblems that can be solved exactly at a low computational cost. Numerical results on both phantom and real images demonstrate the effectiveness of our approach.

scholarly journals Adsorption of Rare Earth Elements from Aqueous Solutions Using Geopolymers

Proceedings ◽  
2018 ◽  
Vol 2 (10) ◽  
pp. 567 ◽  
Author(s):  
Željka Fiket ◽  
Ana Galović ◽  
Gordana Medunić ◽  
Martina Furdek Turk ◽  
Maja Ivanić ◽  
...  
Keyword(s):  
Rare Earth ◽  
Rare Earth Elements ◽  
Aqueous Solutions ◽  
High Efficiency ◽  
Low Cost ◽  
Coal Ash ◽  
Industrial Sector ◽  
Efficient Removal ◽  
Model Solutions ◽  
Technology Applications

Rare earth elements, i.e., lanthanides, are important components of many recently developed technology applications. However, their increasing use in the industrial sector, medicine, and agriculture over the last few decades has provided them with the title of “new pollutants”. Different methods are now applied for the removal of various pollutants from wastewaters, whereby the emphasis is placed on adsorption due to its simplicity, high efficiency, and low cost. In the present study, geopolymers prepared from coal ash were examined regarding their capacity for the adsorption of lanthanides from model solutions. The obtained results indicate the efficient removal of lanthanides by prepared geopolymers, depicting them as effective adsorbents for this group of elements.

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