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Détails du magazine
Format
Magazine
eISSN
1178-5608
Première publication
01 Jan 2008
Période de publication
1 fois par an
Langues
Anglais

Chercher

Volume 14 (2021): Edition 1 (January 2021)

Détails du magazine
Format
Magazine
eISSN
1178-5608
Première publication
01 Jan 2008
Période de publication
1 fois par an
Langues
Anglais

Chercher

21 Articles
Accès libre

Improving sand flow rate measurement using the wavelet transform and ultrasonic sensors

Publié en ligne: 22 Feb 2021
Pages: 1 - 13

Résumé

Abstract

Accurate sand flow rate measurement is needed to minimize the side effects of sand production in gas fields. There are concerns about the accuracy of sand flow measurement using the sand measuring devices available on the market. In this paper, ultrasonic sensors and discrete wavelet transform signal analysis method is used to measure the sand flow rate. It is found that the strength of the discrete wavelet coefficients in the frequency range of 15–62 kHz has a linear relationship with sand flow rate. This finding provides a new methodology to accurately measure sand flow rate. The proposed method does not need fluid velocity as a prerequisite for sand rate measurement, so it greatly simplifies the system design when flow meters are not used for fluid velocity measurement. Also, this method has a much simpler calibration procedure compared to that of the sand detectors commonly used in the industry.

Mots clés

  • Wavelet transform
  • Sand flow rate measurement
  • Ultrasonic sensor
  • Signal processing
  • Time-frequency domain
Accès libre

Energy harvested end nodes and performance improvement of LoRa networks

Publié en ligne: 01 Mar 2021
Pages: 1 - 15

Résumé

Abstract

LoRa technology is derived from chirp spread spectrum (CSS) having embedded forward error correction (FEC). A wide band is used for transmissions to counter interference and to handle frequency offsets. The paper investigates low power wide area networks (LPWAN) transmissions in the uplink, where the end nodes are powered by using energy harvested from the surroundings. Long-range (LoRa) networks demonstrate their capability to support Internet of Things (IoT) applications, where the end nodes utilize the harvested energy for transmission to gateways using different spreading factor (SF) codes. The work fairly improves the throughput of the LoRa nodes while keeping the other parameters, like time duration of the energy harvesting (EH), SF, and transmit power, optimally. Initially, a mathematical expression is derived for collisions between packets of the end nodes; keeping this as an important factor, an algorithm is proposed that fairly assigns SFs to the nodes. Simulation results confirm the improvement in packet error rate and time on air when fewer LoRa nodes are used for lower SFs, as compared to higher SFs. The number of LoRa nodes that can communicate using SF = 7 is almost four times as compared to using SF = 11, while maintaining a low packet error rate. Also, for SF = 7, changing the coding rate from 1 to 4 increases time on air by around 20 ms, while time on air increases by 1,200 ms for SF = 12. The energy efficiency is also compared for different SFs and different transmission powers. A lower SF and lower transmission powers are more suitable for smaller distance and provides better energy efficiency.

Mots clés

  • LoRa
  • IoT
  • Energy harvesting
  • LoRaWAN
  • ToA
  • Gateway
  • Smart sensors
Accès libre

An overview of technologies and devices against COVID-19 pandemic diffusion: virus detection and monitoring solutions

Publié en ligne: 11 Mar 2021
Pages: 1 - 28

Résumé

Abstract

The year 2020 will remain in the history for the diffusion of the COVID-19 virus, originating a pandemic on a world scale with over a million deaths. From the onset of the pandemic, the scientific community has made numerous efforts to design systems to detect the infected subjects in ever-faster times, allowing both to intervene on them, to avoid dangerous complications, and to contain the pandemic spreading. In this paper, we present an overview of different innovative technologies and devices fielded against the SARS-CoV-2 virus. The various technologies applicable to the rapid and reliable detection of the COVID-19 virus have been explored. Specifically, several magnetic, electrochemical, and plasmonic biosensors have been proposed in the scientific literature, as an alternative to nucleic acid-based real-time reverse transcription Polymerase Chain Reaction (PCR) (RT-qPCR) assays, overcoming the limitations featuring this typology of tests (the need for expensive instruments and reagents, as well as of specialized staff, and their reliability). Furthermore, we investigated the IoT solutions and devices, reported on the market and in the scientific literature, to contain the pandemic spreading, by avoiding the contagion, acquiring the parameters of suspected users, and monitoring them during the quarantine period.

Mots clés

  • SARS-CoV-2
  • Pandemic
  • Tracking devices
  • RT-PCR assay
  • Magnetic biosensors
  • IoT frameworks
  • Spike protein
  • Antibodies
  • Remote monitoring systems
Accès libre

Monitoring and analysis of low-voltage network with smart grid architecture model by developing use cases

Publié en ligne: 23 Mar 2021
Pages: 1 - 19

Résumé

Abstract

The objective of this paper is to show the characteristics of smart meters enabling to monitor and analyze the low-voltage (LV) network. This is achieved by developing use cases, where power quality and outage data are transferred from smart meters through distribution network to the control center. To visualize the monitoring process of LV network, the use cases are mapped into smart grid architecture model. The paper proposes a solution to analyze the LV network interruption and power quality problems (over-voltage, under-voltage, voltage sags, and swells). Thus, this paper provides a smart platform for monitoring LV network.

Mots clés

  • Advanced metering infrastructure
  • Outage management
  • Power quality monitoring
  • Use cases
  • Smart grid architecture model
Accès libre

Development of Low Cost Autonomous Underwater Vehicle Platform

Publié en ligne: 15 Jul 2021
Pages: 1 - 22

Résumé

Abstract

This paper presents the development of a low-cost autonomous underwater vehicle (AUV). For research, industrial and military underwater applications, AUVs are generally used, which modeling, system identification and control of these vehicles pose serious challenges due to the vehicles’ complex, inherently nonlinear, and time-varying dynamics. Here, the AUV is considered to have 6-DOF for the development of the electrical, electronics, power distribution, sensors, and actuators. A low-cost IMU is used along with other reasonably low-cost detectors, such as a magnetometer and a water pressure sensor for depth evaluation. This study addresses the configuration and selection of the onboard instruments required to collect data using a processing unit (PC104) based on-board data logger to record complete manoeuvring data obtained from various sensors and process it based on the experiment. Real-time validations using Hardware-in-Loop (HIL) simulations are carried out. HIL simulations help to simulate the behavior of the developed model for surge, pitch and yaw movement, and also it makes clear that the used identification methods are feasible for real time control. Real time experiments are carried out with the developed 6-DOF instrumented AUV platform in various conditions and environments to validate its dynamics identification with adaptive controller and the results are presented for surge, the control of pitch, and yaw. The results revealed that the adaptive controller can effectively control the developed AUV and show its robust properties in the real world.

Mots clés

  • Underwater vehicle
  • Autonomous
  • Modeling
  • AUV modeling
  • System integration
Accès libre

Device-to-device and mobile user communication with queuing in NOMA-based network

Publié en ligne: 31 Mar 2021
Pages: 1 - 6

Résumé

Abstract

In this paper, device-to-device (D2D) pairs use the uplink resource of a mobile user. The transmission is done using a non-orthogonal multiple access (NOMA) technology. The D2D pairs are placed in a queue with maximum threshold time. The channel is allocated to D2D pairs using the TDMA scheme with the first in first out (FIFO) principle. Considering the slots of time division multiple access (TDMA) and channel state, the channel is shared by one D2D pair with the mobile user. The signal to interference (SIC) is employed for D2D pair or mobile user based on NOMA. A hybrid of TDMA and NOMA is used in which time and bit allocation are judiciously adopted. The results are simulated for four different scenarios of power and rate requirements with reduced latency and interference.

Mots clés

  • Non-orthogonal multiple access (NOMA)
  • Device to device (D2D) communication
  • Latency
  • QoS
  • Relay
  • TDMA
Accès libre

Fractal microstrip patch antennas for dual-band and triple-band wireless applications

Publié en ligne: 09 Apr 2021
Pages: 1 - 9

Résumé

Abstract

In this paper, the design and development of dual-band and triple-band fractal microstrip patch antennas with enhanced gain are presented. The structure is based on the Sierpinski carpet fractal, where the multiband functionality is achieved by applying the fractal iteration technique. The fractal antenna characteristics along with analysis of the reflection coefficient and the radiation patterns for each iteration are presented. The dual-band fractal microstrip patch antenna (DBFMPA) is operating at 4.9 and 5.3 GHz and the triple-band fractal microstrip patch antenna (TBFMPA) is operating at 2.4, 5.3, and 5.9 GHz. The defected ground structure (DGS) and a reflector plane is utilized for enhancing the gain of the antenna. Design and optimization of the DBFMPA and TBFMPA are done using the Computer Simulation Technology (CST) Microwave Studio Suite. The presented DBFMPA and TBFMPA are suitable for industrial, scientific, and medical (ISM) wireless applications.

Mots clés

  • Dual-band antenna
  • Triple-band antenna
  • Fractals
  • Reflection coefficient
  • Gain enhancement
Accès libre

Comparative study of Kalman filter-based target motion analysis by incorporating Doppler frequency measurements

Publié en ligne: 28 Apr 2021
Pages: 1 - 12

Résumé

Abstract

Target motion analysis is a key requirement of autonomous and self-driving machines like drones and robots. However, with strict weight limits, the aerospace industry is always on the hunt for simpler and lighter sensing solutions. Continuous-wave Doppler radars are the simplest radars that can easily obtain a target’s relative velocity using the Doppler shift in the received wave. However, these radars cannot provide the target’s range. In this work, we address the problem of obtaining target’s range and velocity by incorporating Doppler frequency measurements from a simple continuous wave Doppler radar. To this end, we find out the movement patterns and maneuvers that an observer can make to converge to the target’s location. After presenting the observability requirements, we design and compare various non-linear Kalman filter-based target trackers. We experimented with different simulation scenarios to compare the tracking results with bearings-only, frequency-only, and bearings-frequency measurement sets. In our analysis, Unscented Kalman Filter with bearings-frequency measurements performed best. Experiments show that an observer can locate the target accurately within 10 cm by incorporating Doppler frequency measurements. Moreover, it also reduced the convergence time to a fraction of a second.

Mots clés

  • Target motion analysis
  • TMA
  • Bearings
  • Doppler frequency
  • Kalman filter
  • Observability conditions
Accès libre

TDMA-clustering-based approach to avoid the reader-to-tag collision problem during the stocktaking process

Publié en ligne: 28 May 2021
Pages: 1 - 14

Résumé

Abstract

The reader-to-tag collision problem occurs when multiple readers try to access the same tag simultaneously. The traditional collision avoidance techniques such as RTS (request to send) and CTS (clear to send) are not applicable because a reader may communicate with multiple tags simultaneously. In this paper, we introduce a collaborative communication protocol to avoid reader-to-tag collisions using TDMA and clustering approaches. The protocol targets the RFID-WSN static systems arranged in a square grid topology, which we can find in different RFID applications such as warehouse stocktaking, parking cars, agricultural fields, and libraries. In such simple topologies, the other proposed reader collision solutions for general use of RFID systems are not efficient since they cannot avoid all possible collisions, and worse of that, some of them are not even detectable, which is intolerable for stocktaking applications. Moreover, they are complicated and heavy in resources, while read throughput is limited. Our protocol presents a simple solution for simple RFID systems with better performances. To validate the proposed protocol, we presented a model using the Process Meta Language (Promela), which is executed under the simple Promela interpreter (SPIN) model checker to verify the protocol properties as deadlocks and livelocks. Also as a proof of concept, we have done a first-step performance analysis using the java runtime.

Mots clés

  • RFID
  • Reader Collision
  • Communication Protocol
  • WSN
  • Clustering
  • TDMA
Accès libre

A review on high dynamic range (HDR) image quality assessment

Publié en ligne: 12 Jul 2021
Pages: 1 - 17

Résumé

Abstract

This paper presents a literature review on the method of measuring high dynamic range (HDR) image quality. HDR technology can help maximize user satisfaction level when using HDR images-based visual services. The advance of HDR technology indirectly presents a more difficult challenge to the image quality assessment method due to the high sensitivity of the human visual system (HVS) to various kinds of distortions that may arise in HDR images. This is related to the process of HDR image generation, which in general can be classified into two broad categories: the formation using the multiple exposure fusion (MEF) method and the inverse tone mapping operator (ITMO) method. In this paper, we will outline how HDR image quality measurement method works and describe some examples of these measurement methods which are related to the way the HDR images are fabricated. From these methods, it can be seen that most of them are still focused on full-reference and no-reference quality models. We argue that there is still room for the development of reduced-reference HDR image quality assessment.

Mots clés

  • Reduce-reference (RR)
  • Objective quality assessment
  • Image quality assessment (IQA)
  • High dynamic range (HDR)
  • Inverse tone mapping operator (ITMO)
  • Multi-exposure fusion (MEF)
Accès libre

An efficient sentiment analysis using topic model based optimized recurrent neural network

Publié en ligne: 22 Jun 2021
Pages: 1 - 12

Résumé

Abstract

In recent years, topic modeling and deep neural network-based methods have attracted much attention in sentiment analysis of online reviews. This paper presents a hybrid topic model-based approach for aspect extraction and sentiment classification of textual reviews. Latent Dirichlet allocation applied for aspect extraction and two-layer bi-directional long short-term memory (LSTM) for sentiment classification. This work also proposes a hill climbing-based approach for tunning model hyperparameters. The proposed model evaluated on three different datasets. Compared to the single-layer Bi-LSTM model, the proposed model gives 95, 95, and 86% accuracy for the movie, mobile, and hotel domain, respectively.

Mots clés

  • Bi-LSTM
  • LDA
  • Hill-climbing
  • Classification
  • Hyperparameters
Accès libre

Performance evaluation of vertical handover in Internet of Vehicles

Publié en ligne: 28 Jun 2021
Pages: 1 - 16

Résumé

Abstract

Internet of Vehicles (IoV) is developed by integrating the intelligent transportation system (ITS) and the Internet of Things (IoT). The goal of IoV is to allow vehicles to communicate with other vehicles, humans, pedestrians, roadside units, and other infrastructures. Two potential technologies of V2X communication are dedicated short-range communication (DSRC) and cellular network technologies. Each of these has its benefits and limitations. DSRC has low latency but it limits coverage area and lacks spectrum availability. Whereas 4G LTE offers high bandwidth, wider cell coverage range, but the drawback is its high transmission time intervals. 5G offers enormous benefits to the present wireless communication technology by providing higher data rates and very low latencies for transmissions but is prone to blockages because of its inability to penetrate through the objects. Hence, considering the above issues, single technology will not fully accommodate the V2X requirements which subsequently jeopardize the effectiveness of safety applications. Therefore, for efficient V2X communication, it is required to interwork with DSRC and cellular network technologies. One open research challenge that has gained the attention of the research community over the past few years is the appropriate selection of networks for handover in a heterogeneous IoV environment. Existing solutions have addressed the issues related to handover and network selection but they have failed to address the need for handover while selecting the network. Previous studies have only mentioned that the network is being selected directly for handover or it was connected to the available radio access. Due to this, the occurrence of handover had to take place frequently. Hence, in this research, the integration of DSRC, LTE, and mmWave 5G is incorporated with handover decision, network selection, and routing algorithms. The handover decision is to ensure whether there is a need for vertical handover by using a dynamic Q-learning algorithm. Then, the network selection is based on a fuzzy-convolution neural network that creates fuzzy rules from signal strength, distance, vehicle density, data type, and line of sight. V2V chain routing is proposed to select V2V pairs using a jellyfish optimization algorithm that takes into account the channel, vehicle characteristics, and transmission metrics. This system is developed in an OMNeT++ simulator and the performances are evaluated in terms of mean handover, handover failure, mean throughput, delay, and packet loss.

Mots clés

  • 4G LTE
  • DSRC
  • Internet of Vehicles
  • mmwave 5G
  • Network selection
  • Vertical handover
Accès libre

FBG sensors for seismic control and detection in extradosed bridges

Publié en ligne: 08 Jul 2021
Pages: 1 - 13

Résumé

Abstract

Robust fiber Bragg grating (FBG) sensors network to civil engineering structures is presented as real-time monitoring deviation against seismic effects. The network is based on FBG sensors. The base element is a special type of chirped FBG that is validated. The developed network is applied in one of the two towers of concrete and extradosed type of Rades-La Goulette Bridge in Tunisia that in aggressive environment, to enhance the installed conventional structural health monitoring system (SHMS). Precisely, tilt influences of seismic parameters are calculated. Test procedure and obtained results are discussed.

Mots clés

  • FBG sensors network
  • Structural health monitoring system
  • Bridge
  • Seismic effects
  • Tower
  • Tilt
Accès libre

Development of a computer-based simple pendulum experiment set for teaching and learning physics

Publié en ligne: 28 Jul 2021
Pages: 1 - 8

Résumé

Abstract

The development of a cost-effective experiment set is essential for teaching and learning physics in educational institutes. We aim to develop a computer-based simple pendulum experiment set consisting of a simple pendulum, infrared phototransistor, and Arduino board for calculating the gravitational acceleration (g). We used 13 pendulum lengths with five angles for each length to measure the period of motion. We found linear relationships between lengths and period-squared. The g-value was 9.806 ± 0.025 (average ± standard error) m/s2. Since this experiment set is cost-effective, and more straightforward method to understand, it will benefit the physics learning in educational institutions.

Mots clés

  • Teaching and learning physics
  • Computer-based experiment set
  • Gravitational acceleration
  • Simple pendulum
Accès libre

A face-machine interface utilizing EEG artifacts from a neuroheadset for simulated wheelchair control

Publié en ligne: 28 Jul 2021
Pages: 1 - 10

Résumé

Abstract

Many people suffer from movement disabilities and would benefit from an assistive mobility device with practical control. This paper demonstrates a face-machine interface system that uses motion artifacts from electroencephalogram (EEG) signals for mobility enhancement in people with quadriplegia. We employed an Emotiv EPOC X neuroheadset to acquire EEG signals. With the proposed system, we verified the preprocessing approach, feature extraction algorithms, and control modalities. Incorporating eye winks and jaw movements, an average accuracy of 96.9% across four commands was achieved. Moreover, the online control results of a simulated power wheelchair showed high efficiency based on the time condition. The combination of winking and jaw chewing results in a steering time on the same order of magnitude as that of joystick-based control, but still about twice as long. We will further improve the efficiency and implement the proposed face-machine interface system for a real-power wheelchair.

Mots clés

  • Human–computer interaction
  • Face-machine interface
  • Neuroheadset
  • EEG artifacts
  • Simulated wheelchair
Accès libre

Improving total nitrogen removal using a neural network ammonia-based aeration control in activated sludge process

Publié en ligne: 23 Sep 2021
Pages: 1 - 16

Résumé

Abstract

Aeration control is a way to have a wastewater treatment plant (WWTP) that uses less energy and produces higher effluent quality to meet state and federal regulations. The goal of this research is to develop a neural network (NN) ammonia-based aeration control (ABAC) that focuses on reducing total nitrogen and ammonia concentration violations by regulating dissolved oxygen (DO) concentration based on the ammonia concentration in the final tank, rather than maintaining the DO concentration at a set elevated value, as most studies do. Simulation platform used in this study is Benchmark Simulation Model No. 1, and the NN ABAC is compared to the Proportional-Integral (PI) ABAC and PI controller. In comparison to the PI controller, the simulation results showed that the proposed controller has a significant improvement in reducing the AECI up to 23.86%, improving the EQCI up to 1.94%, and reducing the overall OCI up to 4.61%. The results of the study show that the NN ABAC can be utilized to improve the performance of a WWTP’s activated sludge system.

Mots clés

  • ABAC
  • Effluent
  • Energy consumption
  • Neural network
  • Wastewater treatment
Accès libre

Using explainable deep learning in da Vinci Xi robot for tumor detection

Publié en ligne: 25 Oct 2021
Pages: 1 - 16

Résumé

Abstract

Deep learning has proved successful in computer-aided detection in interpreting ultrasound images, COVID infections, identifying tumors from computed tomography (CT) scans for humans and animals. This paper proposes applications of deep learning in detecting cancerous cells inside patients via laparoscopic camera on da Vinci Xi surgical robots. The paper presents method for detecting tumor via object detection and classification/localizing using GRAD-CAM. Localization means heat map is drawn on the image highlighting the classified class. Analyzing images collected from publicly available partial robotic nephrectomy videos, for object detection, the final mAP was 0.974 and for classification the accuracy was 0.84.

Mots clés

  • Convolutional neural network
  • Tumor detection
  • YOLOv4
  • GRAD-CAM
  • Live surgery
  • da Vinci Xi
Accès libre

Expansion of detectable area by floating electrodes in capacitive three-dimensional proximity sensor

Publié en ligne: 01 Nov 2021
Pages: 1 - 11

Résumé

Abstract

In the capacitive proximity sensing method, arranging multiple sensing electrodes makes it possible to obtain the three-dimensional position of a nearby object. The author has developed a capacitive proximity sensing method using LC resonance in three reactance elements. In this method, the detectable area can be greatly extended by the floating electrodes, which are capacitively connected to the sensing electrode. By connecting multiple floating electrodes in series, the detectable range can be extended up to the length of the array of floating electrodes. When these electrodes are arranged on a frame, the region surrounded by the frame becomes the detectable area. By applying this frame on any surface, it is possible to make the surface within the opening of the frame a non-contact operating panel, which can be applied as a gesture input device.

Mots clés

  • Capacitive sensor
  • Gesture input device
  • 3D position sensing
  • Non-contact operation
  • Proximity sensor
  • Stray capacitance
Accès libre

Energy-Aware Clustering and Efficient Cluster Head Selection

Publié en ligne: 29 Nov 2021
Pages: 1 - 15

Résumé

Abstract

Clustering is an efficient technique to organize network resources efficiently and, in wireless sensor Networks (WSNs) communications it is used to group sensors with similar characteristics managed by a selected sensor called a Cluster Head (CH). Thus, this paper presents a new approach, namely Energy-Aware Clustering and Efficient Cluster Head Selection (EAC-ECHS) to optimize the performances of WSNs in terms of the network lifetime and enhance energy consumption. In EAC-ECHS, the sensor network is divided into an inter grid and fair clustered Grids. Furthermore, for each clustered Grid, the CH selection is based on the residual energy of sensor, distance to neighbors, and distance to the base station. Simulation experiments have been conducted to examine the performance of EAC-ECHS and previous approaches, and the results demonstrate that EAC-ECHS approach achieves the design objectives in terms energy consumption, network lifetime, and packet delivery ratio.

Mots clés

  • Clustering
  • Energy efficient
  • Hierarchical routing protocol
  • LEACH Network lifetime
  • Residual energy
  • Sensor node
  • Wireless sensor network
Accès libre

Performance evaluation of brain tumor detection using watershed Segmentation and thresholding

Publié en ligne: 24 Nov 2021
Pages: 1 - 12

Résumé

Abstract

Brain tumors and cancers are life-threatening diseases to human beings and have been on the rise. If undetected, they are deadly. With the advent of advanced medical technology, it has become imperative to accurately spot and identify these tumors at the earliest.

The manuscript aims at providing an accurate method to detect and segment brain tumors from MRI scans. This is achieved by implementing watershed segmentation and threshold algorithm paired with pre and post image processing techniques. Apart from detecting the tumor region, the proposed process also enhances image quality by noise removal techniques and image quality improvement. These results give promising values when verified using several evaluation parameters such as Structural Similarity Index Measure (SSIM), Feature Similarity Index Measure (FSIM) and Peak Signal-to-Noise Ratio (PSNR) and stand out among the other similar pre-existing algorithms that they are compared with in a comparative analysis.

Mots clés

  • Brain tumor
  • Evaluation parameters
  • MRI
  • Threshold algorithm
  • Watershed segmentation
Accès libre

Application of an alternative energy source in the form of solar radiation and carbon-based fuel flexible material for the heating of mobile farm housing

Publié en ligne: 29 Nov 2021
Pages: 1 - 11

Résumé

Abstract

In residential and industrial premises, optimum conditions for human activity must be created. In areas without central heating supply, heating of a mobile living space is provided by solid fuel boilers. There may be fuel outages at a distance from an inhabited locality. Therefore, the purpose of the study is to create a heating system for a farmer’s house by using carbon-based fuel flexible materials and solar stations. Farmhouse heating system that heats mobile living quarters remote from power lines and communities through the use of carbon-based fuel flexible materials and solar stations is proposed by the authors. The technical result consists in that, in the claimed system, the heating device is a carbon-based fuel flexible material supplying electricity from the solar station. Carbon-based fuel flexible material is a thermal film (heating grid), which is made by interweaving longitudinal and transverse carbon filaments and, for safety reasons, covered with an electrical insulating material.

Mots clés

  • Alternative energy source
  • Carbon-based fuel flexible material
  • Farmer’s house
  • Heating
  • Premises
  • Solar energy
21 Articles
Accès libre

Improving sand flow rate measurement using the wavelet transform and ultrasonic sensors

Publié en ligne: 22 Feb 2021
Pages: 1 - 13

Résumé

Abstract

Accurate sand flow rate measurement is needed to minimize the side effects of sand production in gas fields. There are concerns about the accuracy of sand flow measurement using the sand measuring devices available on the market. In this paper, ultrasonic sensors and discrete wavelet transform signal analysis method is used to measure the sand flow rate. It is found that the strength of the discrete wavelet coefficients in the frequency range of 15–62 kHz has a linear relationship with sand flow rate. This finding provides a new methodology to accurately measure sand flow rate. The proposed method does not need fluid velocity as a prerequisite for sand rate measurement, so it greatly simplifies the system design when flow meters are not used for fluid velocity measurement. Also, this method has a much simpler calibration procedure compared to that of the sand detectors commonly used in the industry.

Mots clés

  • Wavelet transform
  • Sand flow rate measurement
  • Ultrasonic sensor
  • Signal processing
  • Time-frequency domain
Accès libre

Energy harvested end nodes and performance improvement of LoRa networks

Publié en ligne: 01 Mar 2021
Pages: 1 - 15

Résumé

Abstract

LoRa technology is derived from chirp spread spectrum (CSS) having embedded forward error correction (FEC). A wide band is used for transmissions to counter interference and to handle frequency offsets. The paper investigates low power wide area networks (LPWAN) transmissions in the uplink, where the end nodes are powered by using energy harvested from the surroundings. Long-range (LoRa) networks demonstrate their capability to support Internet of Things (IoT) applications, where the end nodes utilize the harvested energy for transmission to gateways using different spreading factor (SF) codes. The work fairly improves the throughput of the LoRa nodes while keeping the other parameters, like time duration of the energy harvesting (EH), SF, and transmit power, optimally. Initially, a mathematical expression is derived for collisions between packets of the end nodes; keeping this as an important factor, an algorithm is proposed that fairly assigns SFs to the nodes. Simulation results confirm the improvement in packet error rate and time on air when fewer LoRa nodes are used for lower SFs, as compared to higher SFs. The number of LoRa nodes that can communicate using SF = 7 is almost four times as compared to using SF = 11, while maintaining a low packet error rate. Also, for SF = 7, changing the coding rate from 1 to 4 increases time on air by around 20 ms, while time on air increases by 1,200 ms for SF = 12. The energy efficiency is also compared for different SFs and different transmission powers. A lower SF and lower transmission powers are more suitable for smaller distance and provides better energy efficiency.

Mots clés

  • LoRa
  • IoT
  • Energy harvesting
  • LoRaWAN
  • ToA
  • Gateway
  • Smart sensors
Accès libre

An overview of technologies and devices against COVID-19 pandemic diffusion: virus detection and monitoring solutions

Publié en ligne: 11 Mar 2021
Pages: 1 - 28

Résumé

Abstract

The year 2020 will remain in the history for the diffusion of the COVID-19 virus, originating a pandemic on a world scale with over a million deaths. From the onset of the pandemic, the scientific community has made numerous efforts to design systems to detect the infected subjects in ever-faster times, allowing both to intervene on them, to avoid dangerous complications, and to contain the pandemic spreading. In this paper, we present an overview of different innovative technologies and devices fielded against the SARS-CoV-2 virus. The various technologies applicable to the rapid and reliable detection of the COVID-19 virus have been explored. Specifically, several magnetic, electrochemical, and plasmonic biosensors have been proposed in the scientific literature, as an alternative to nucleic acid-based real-time reverse transcription Polymerase Chain Reaction (PCR) (RT-qPCR) assays, overcoming the limitations featuring this typology of tests (the need for expensive instruments and reagents, as well as of specialized staff, and their reliability). Furthermore, we investigated the IoT solutions and devices, reported on the market and in the scientific literature, to contain the pandemic spreading, by avoiding the contagion, acquiring the parameters of suspected users, and monitoring them during the quarantine period.

Mots clés

  • SARS-CoV-2
  • Pandemic
  • Tracking devices
  • RT-PCR assay
  • Magnetic biosensors
  • IoT frameworks
  • Spike protein
  • Antibodies
  • Remote monitoring systems
Accès libre

Monitoring and analysis of low-voltage network with smart grid architecture model by developing use cases

Publié en ligne: 23 Mar 2021
Pages: 1 - 19

Résumé

Abstract

The objective of this paper is to show the characteristics of smart meters enabling to monitor and analyze the low-voltage (LV) network. This is achieved by developing use cases, where power quality and outage data are transferred from smart meters through distribution network to the control center. To visualize the monitoring process of LV network, the use cases are mapped into smart grid architecture model. The paper proposes a solution to analyze the LV network interruption and power quality problems (over-voltage, under-voltage, voltage sags, and swells). Thus, this paper provides a smart platform for monitoring LV network.

Mots clés

  • Advanced metering infrastructure
  • Outage management
  • Power quality monitoring
  • Use cases
  • Smart grid architecture model
Accès libre

Development of Low Cost Autonomous Underwater Vehicle Platform

Publié en ligne: 15 Jul 2021
Pages: 1 - 22

Résumé

Abstract

This paper presents the development of a low-cost autonomous underwater vehicle (AUV). For research, industrial and military underwater applications, AUVs are generally used, which modeling, system identification and control of these vehicles pose serious challenges due to the vehicles’ complex, inherently nonlinear, and time-varying dynamics. Here, the AUV is considered to have 6-DOF for the development of the electrical, electronics, power distribution, sensors, and actuators. A low-cost IMU is used along with other reasonably low-cost detectors, such as a magnetometer and a water pressure sensor for depth evaluation. This study addresses the configuration and selection of the onboard instruments required to collect data using a processing unit (PC104) based on-board data logger to record complete manoeuvring data obtained from various sensors and process it based on the experiment. Real-time validations using Hardware-in-Loop (HIL) simulations are carried out. HIL simulations help to simulate the behavior of the developed model for surge, pitch and yaw movement, and also it makes clear that the used identification methods are feasible for real time control. Real time experiments are carried out with the developed 6-DOF instrumented AUV platform in various conditions and environments to validate its dynamics identification with adaptive controller and the results are presented for surge, the control of pitch, and yaw. The results revealed that the adaptive controller can effectively control the developed AUV and show its robust properties in the real world.

Mots clés

  • Underwater vehicle
  • Autonomous
  • Modeling
  • AUV modeling
  • System integration
Accès libre

Device-to-device and mobile user communication with queuing in NOMA-based network

Publié en ligne: 31 Mar 2021
Pages: 1 - 6

Résumé

Abstract

In this paper, device-to-device (D2D) pairs use the uplink resource of a mobile user. The transmission is done using a non-orthogonal multiple access (NOMA) technology. The D2D pairs are placed in a queue with maximum threshold time. The channel is allocated to D2D pairs using the TDMA scheme with the first in first out (FIFO) principle. Considering the slots of time division multiple access (TDMA) and channel state, the channel is shared by one D2D pair with the mobile user. The signal to interference (SIC) is employed for D2D pair or mobile user based on NOMA. A hybrid of TDMA and NOMA is used in which time and bit allocation are judiciously adopted. The results are simulated for four different scenarios of power and rate requirements with reduced latency and interference.

Mots clés

  • Non-orthogonal multiple access (NOMA)
  • Device to device (D2D) communication
  • Latency
  • QoS
  • Relay
  • TDMA
Accès libre

Fractal microstrip patch antennas for dual-band and triple-band wireless applications

Publié en ligne: 09 Apr 2021
Pages: 1 - 9

Résumé

Abstract

In this paper, the design and development of dual-band and triple-band fractal microstrip patch antennas with enhanced gain are presented. The structure is based on the Sierpinski carpet fractal, where the multiband functionality is achieved by applying the fractal iteration technique. The fractal antenna characteristics along with analysis of the reflection coefficient and the radiation patterns for each iteration are presented. The dual-band fractal microstrip patch antenna (DBFMPA) is operating at 4.9 and 5.3 GHz and the triple-band fractal microstrip patch antenna (TBFMPA) is operating at 2.4, 5.3, and 5.9 GHz. The defected ground structure (DGS) and a reflector plane is utilized for enhancing the gain of the antenna. Design and optimization of the DBFMPA and TBFMPA are done using the Computer Simulation Technology (CST) Microwave Studio Suite. The presented DBFMPA and TBFMPA are suitable for industrial, scientific, and medical (ISM) wireless applications.

Mots clés

  • Dual-band antenna
  • Triple-band antenna
  • Fractals
  • Reflection coefficient
  • Gain enhancement
Accès libre

Comparative study of Kalman filter-based target motion analysis by incorporating Doppler frequency measurements

Publié en ligne: 28 Apr 2021
Pages: 1 - 12

Résumé

Abstract

Target motion analysis is a key requirement of autonomous and self-driving machines like drones and robots. However, with strict weight limits, the aerospace industry is always on the hunt for simpler and lighter sensing solutions. Continuous-wave Doppler radars are the simplest radars that can easily obtain a target’s relative velocity using the Doppler shift in the received wave. However, these radars cannot provide the target’s range. In this work, we address the problem of obtaining target’s range and velocity by incorporating Doppler frequency measurements from a simple continuous wave Doppler radar. To this end, we find out the movement patterns and maneuvers that an observer can make to converge to the target’s location. After presenting the observability requirements, we design and compare various non-linear Kalman filter-based target trackers. We experimented with different simulation scenarios to compare the tracking results with bearings-only, frequency-only, and bearings-frequency measurement sets. In our analysis, Unscented Kalman Filter with bearings-frequency measurements performed best. Experiments show that an observer can locate the target accurately within 10 cm by incorporating Doppler frequency measurements. Moreover, it also reduced the convergence time to a fraction of a second.

Mots clés

  • Target motion analysis
  • TMA
  • Bearings
  • Doppler frequency
  • Kalman filter
  • Observability conditions
Accès libre

TDMA-clustering-based approach to avoid the reader-to-tag collision problem during the stocktaking process

Publié en ligne: 28 May 2021
Pages: 1 - 14

Résumé

Abstract

The reader-to-tag collision problem occurs when multiple readers try to access the same tag simultaneously. The traditional collision avoidance techniques such as RTS (request to send) and CTS (clear to send) are not applicable because a reader may communicate with multiple tags simultaneously. In this paper, we introduce a collaborative communication protocol to avoid reader-to-tag collisions using TDMA and clustering approaches. The protocol targets the RFID-WSN static systems arranged in a square grid topology, which we can find in different RFID applications such as warehouse stocktaking, parking cars, agricultural fields, and libraries. In such simple topologies, the other proposed reader collision solutions for general use of RFID systems are not efficient since they cannot avoid all possible collisions, and worse of that, some of them are not even detectable, which is intolerable for stocktaking applications. Moreover, they are complicated and heavy in resources, while read throughput is limited. Our protocol presents a simple solution for simple RFID systems with better performances. To validate the proposed protocol, we presented a model using the Process Meta Language (Promela), which is executed under the simple Promela interpreter (SPIN) model checker to verify the protocol properties as deadlocks and livelocks. Also as a proof of concept, we have done a first-step performance analysis using the java runtime.

Mots clés

  • RFID
  • Reader Collision
  • Communication Protocol
  • WSN
  • Clustering
  • TDMA
Accès libre

A review on high dynamic range (HDR) image quality assessment

Publié en ligne: 12 Jul 2021
Pages: 1 - 17

Résumé

Abstract

This paper presents a literature review on the method of measuring high dynamic range (HDR) image quality. HDR technology can help maximize user satisfaction level when using HDR images-based visual services. The advance of HDR technology indirectly presents a more difficult challenge to the image quality assessment method due to the high sensitivity of the human visual system (HVS) to various kinds of distortions that may arise in HDR images. This is related to the process of HDR image generation, which in general can be classified into two broad categories: the formation using the multiple exposure fusion (MEF) method and the inverse tone mapping operator (ITMO) method. In this paper, we will outline how HDR image quality measurement method works and describe some examples of these measurement methods which are related to the way the HDR images are fabricated. From these methods, it can be seen that most of them are still focused on full-reference and no-reference quality models. We argue that there is still room for the development of reduced-reference HDR image quality assessment.

Mots clés

  • Reduce-reference (RR)
  • Objective quality assessment
  • Image quality assessment (IQA)
  • High dynamic range (HDR)
  • Inverse tone mapping operator (ITMO)
  • Multi-exposure fusion (MEF)
Accès libre

An efficient sentiment analysis using topic model based optimized recurrent neural network

Publié en ligne: 22 Jun 2021
Pages: 1 - 12

Résumé

Abstract

In recent years, topic modeling and deep neural network-based methods have attracted much attention in sentiment analysis of online reviews. This paper presents a hybrid topic model-based approach for aspect extraction and sentiment classification of textual reviews. Latent Dirichlet allocation applied for aspect extraction and two-layer bi-directional long short-term memory (LSTM) for sentiment classification. This work also proposes a hill climbing-based approach for tunning model hyperparameters. The proposed model evaluated on three different datasets. Compared to the single-layer Bi-LSTM model, the proposed model gives 95, 95, and 86% accuracy for the movie, mobile, and hotel domain, respectively.

Mots clés

  • Bi-LSTM
  • LDA
  • Hill-climbing
  • Classification
  • Hyperparameters
Accès libre

Performance evaluation of vertical handover in Internet of Vehicles

Publié en ligne: 28 Jun 2021
Pages: 1 - 16

Résumé

Abstract

Internet of Vehicles (IoV) is developed by integrating the intelligent transportation system (ITS) and the Internet of Things (IoT). The goal of IoV is to allow vehicles to communicate with other vehicles, humans, pedestrians, roadside units, and other infrastructures. Two potential technologies of V2X communication are dedicated short-range communication (DSRC) and cellular network technologies. Each of these has its benefits and limitations. DSRC has low latency but it limits coverage area and lacks spectrum availability. Whereas 4G LTE offers high bandwidth, wider cell coverage range, but the drawback is its high transmission time intervals. 5G offers enormous benefits to the present wireless communication technology by providing higher data rates and very low latencies for transmissions but is prone to blockages because of its inability to penetrate through the objects. Hence, considering the above issues, single technology will not fully accommodate the V2X requirements which subsequently jeopardize the effectiveness of safety applications. Therefore, for efficient V2X communication, it is required to interwork with DSRC and cellular network technologies. One open research challenge that has gained the attention of the research community over the past few years is the appropriate selection of networks for handover in a heterogeneous IoV environment. Existing solutions have addressed the issues related to handover and network selection but they have failed to address the need for handover while selecting the network. Previous studies have only mentioned that the network is being selected directly for handover or it was connected to the available radio access. Due to this, the occurrence of handover had to take place frequently. Hence, in this research, the integration of DSRC, LTE, and mmWave 5G is incorporated with handover decision, network selection, and routing algorithms. The handover decision is to ensure whether there is a need for vertical handover by using a dynamic Q-learning algorithm. Then, the network selection is based on a fuzzy-convolution neural network that creates fuzzy rules from signal strength, distance, vehicle density, data type, and line of sight. V2V chain routing is proposed to select V2V pairs using a jellyfish optimization algorithm that takes into account the channel, vehicle characteristics, and transmission metrics. This system is developed in an OMNeT++ simulator and the performances are evaluated in terms of mean handover, handover failure, mean throughput, delay, and packet loss.

Mots clés

  • 4G LTE
  • DSRC
  • Internet of Vehicles
  • mmwave 5G
  • Network selection
  • Vertical handover
Accès libre

FBG sensors for seismic control and detection in extradosed bridges

Publié en ligne: 08 Jul 2021
Pages: 1 - 13

Résumé

Abstract

Robust fiber Bragg grating (FBG) sensors network to civil engineering structures is presented as real-time monitoring deviation against seismic effects. The network is based on FBG sensors. The base element is a special type of chirped FBG that is validated. The developed network is applied in one of the two towers of concrete and extradosed type of Rades-La Goulette Bridge in Tunisia that in aggressive environment, to enhance the installed conventional structural health monitoring system (SHMS). Precisely, tilt influences of seismic parameters are calculated. Test procedure and obtained results are discussed.

Mots clés

  • FBG sensors network
  • Structural health monitoring system
  • Bridge
  • Seismic effects
  • Tower
  • Tilt
Accès libre

Development of a computer-based simple pendulum experiment set for teaching and learning physics

Publié en ligne: 28 Jul 2021
Pages: 1 - 8

Résumé

Abstract

The development of a cost-effective experiment set is essential for teaching and learning physics in educational institutes. We aim to develop a computer-based simple pendulum experiment set consisting of a simple pendulum, infrared phototransistor, and Arduino board for calculating the gravitational acceleration (g). We used 13 pendulum lengths with five angles for each length to measure the period of motion. We found linear relationships between lengths and period-squared. The g-value was 9.806 ± 0.025 (average ± standard error) m/s2. Since this experiment set is cost-effective, and more straightforward method to understand, it will benefit the physics learning in educational institutions.

Mots clés

  • Teaching and learning physics
  • Computer-based experiment set
  • Gravitational acceleration
  • Simple pendulum
Accès libre

A face-machine interface utilizing EEG artifacts from a neuroheadset for simulated wheelchair control

Publié en ligne: 28 Jul 2021
Pages: 1 - 10

Résumé

Abstract

Many people suffer from movement disabilities and would benefit from an assistive mobility device with practical control. This paper demonstrates a face-machine interface system that uses motion artifacts from electroencephalogram (EEG) signals for mobility enhancement in people with quadriplegia. We employed an Emotiv EPOC X neuroheadset to acquire EEG signals. With the proposed system, we verified the preprocessing approach, feature extraction algorithms, and control modalities. Incorporating eye winks and jaw movements, an average accuracy of 96.9% across four commands was achieved. Moreover, the online control results of a simulated power wheelchair showed high efficiency based on the time condition. The combination of winking and jaw chewing results in a steering time on the same order of magnitude as that of joystick-based control, but still about twice as long. We will further improve the efficiency and implement the proposed face-machine interface system for a real-power wheelchair.

Mots clés

  • Human–computer interaction
  • Face-machine interface
  • Neuroheadset
  • EEG artifacts
  • Simulated wheelchair
Accès libre

Improving total nitrogen removal using a neural network ammonia-based aeration control in activated sludge process

Publié en ligne: 23 Sep 2021
Pages: 1 - 16

Résumé

Abstract

Aeration control is a way to have a wastewater treatment plant (WWTP) that uses less energy and produces higher effluent quality to meet state and federal regulations. The goal of this research is to develop a neural network (NN) ammonia-based aeration control (ABAC) that focuses on reducing total nitrogen and ammonia concentration violations by regulating dissolved oxygen (DO) concentration based on the ammonia concentration in the final tank, rather than maintaining the DO concentration at a set elevated value, as most studies do. Simulation platform used in this study is Benchmark Simulation Model No. 1, and the NN ABAC is compared to the Proportional-Integral (PI) ABAC and PI controller. In comparison to the PI controller, the simulation results showed that the proposed controller has a significant improvement in reducing the AECI up to 23.86%, improving the EQCI up to 1.94%, and reducing the overall OCI up to 4.61%. The results of the study show that the NN ABAC can be utilized to improve the performance of a WWTP’s activated sludge system.

Mots clés

  • ABAC
  • Effluent
  • Energy consumption
  • Neural network
  • Wastewater treatment
Accès libre

Using explainable deep learning in da Vinci Xi robot for tumor detection

Publié en ligne: 25 Oct 2021
Pages: 1 - 16

Résumé

Abstract

Deep learning has proved successful in computer-aided detection in interpreting ultrasound images, COVID infections, identifying tumors from computed tomography (CT) scans for humans and animals. This paper proposes applications of deep learning in detecting cancerous cells inside patients via laparoscopic camera on da Vinci Xi surgical robots. The paper presents method for detecting tumor via object detection and classification/localizing using GRAD-CAM. Localization means heat map is drawn on the image highlighting the classified class. Analyzing images collected from publicly available partial robotic nephrectomy videos, for object detection, the final mAP was 0.974 and for classification the accuracy was 0.84.

Mots clés

  • Convolutional neural network
  • Tumor detection
  • YOLOv4
  • GRAD-CAM
  • Live surgery
  • da Vinci Xi
Accès libre

Expansion of detectable area by floating electrodes in capacitive three-dimensional proximity sensor

Publié en ligne: 01 Nov 2021
Pages: 1 - 11

Résumé

Abstract

In the capacitive proximity sensing method, arranging multiple sensing electrodes makes it possible to obtain the three-dimensional position of a nearby object. The author has developed a capacitive proximity sensing method using LC resonance in three reactance elements. In this method, the detectable area can be greatly extended by the floating electrodes, which are capacitively connected to the sensing electrode. By connecting multiple floating electrodes in series, the detectable range can be extended up to the length of the array of floating electrodes. When these electrodes are arranged on a frame, the region surrounded by the frame becomes the detectable area. By applying this frame on any surface, it is possible to make the surface within the opening of the frame a non-contact operating panel, which can be applied as a gesture input device.

Mots clés

  • Capacitive sensor
  • Gesture input device
  • 3D position sensing
  • Non-contact operation
  • Proximity sensor
  • Stray capacitance
Accès libre

Energy-Aware Clustering and Efficient Cluster Head Selection

Publié en ligne: 29 Nov 2021
Pages: 1 - 15

Résumé

Abstract

Clustering is an efficient technique to organize network resources efficiently and, in wireless sensor Networks (WSNs) communications it is used to group sensors with similar characteristics managed by a selected sensor called a Cluster Head (CH). Thus, this paper presents a new approach, namely Energy-Aware Clustering and Efficient Cluster Head Selection (EAC-ECHS) to optimize the performances of WSNs in terms of the network lifetime and enhance energy consumption. In EAC-ECHS, the sensor network is divided into an inter grid and fair clustered Grids. Furthermore, for each clustered Grid, the CH selection is based on the residual energy of sensor, distance to neighbors, and distance to the base station. Simulation experiments have been conducted to examine the performance of EAC-ECHS and previous approaches, and the results demonstrate that EAC-ECHS approach achieves the design objectives in terms energy consumption, network lifetime, and packet delivery ratio.

Mots clés

  • Clustering
  • Energy efficient
  • Hierarchical routing protocol
  • LEACH Network lifetime
  • Residual energy
  • Sensor node
  • Wireless sensor network
Accès libre

Performance evaluation of brain tumor detection using watershed Segmentation and thresholding

Publié en ligne: 24 Nov 2021
Pages: 1 - 12

Résumé

Abstract

Brain tumors and cancers are life-threatening diseases to human beings and have been on the rise. If undetected, they are deadly. With the advent of advanced medical technology, it has become imperative to accurately spot and identify these tumors at the earliest.

The manuscript aims at providing an accurate method to detect and segment brain tumors from MRI scans. This is achieved by implementing watershed segmentation and threshold algorithm paired with pre and post image processing techniques. Apart from detecting the tumor region, the proposed process also enhances image quality by noise removal techniques and image quality improvement. These results give promising values when verified using several evaluation parameters such as Structural Similarity Index Measure (SSIM), Feature Similarity Index Measure (FSIM) and Peak Signal-to-Noise Ratio (PSNR) and stand out among the other similar pre-existing algorithms that they are compared with in a comparative analysis.

Mots clés

  • Brain tumor
  • Evaluation parameters
  • MRI
  • Threshold algorithm
  • Watershed segmentation
Accès libre

Application of an alternative energy source in the form of solar radiation and carbon-based fuel flexible material for the heating of mobile farm housing

Publié en ligne: 29 Nov 2021
Pages: 1 - 11

Résumé

Abstract

In residential and industrial premises, optimum conditions for human activity must be created. In areas without central heating supply, heating of a mobile living space is provided by solid fuel boilers. There may be fuel outages at a distance from an inhabited locality. Therefore, the purpose of the study is to create a heating system for a farmer’s house by using carbon-based fuel flexible materials and solar stations. Farmhouse heating system that heats mobile living quarters remote from power lines and communities through the use of carbon-based fuel flexible materials and solar stations is proposed by the authors. The technical result consists in that, in the claimed system, the heating device is a carbon-based fuel flexible material supplying electricity from the solar station. Carbon-based fuel flexible material is a thermal film (heating grid), which is made by interweaving longitudinal and transverse carbon filaments and, for safety reasons, covered with an electrical insulating material.

Mots clés

  • Alternative energy source
  • Carbon-based fuel flexible material
  • Farmer’s house
  • Heating
  • Premises
  • Solar energy

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