Search results for: wireless sensors networks

Authors: Javier Sedano-Cibrián, Julio Manuel de Luis-Ruiz, Rubén Pérez-Álvarez, Raúl Pereda-García, Beatriz Malagón-Picón

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Structural inspection activities are necessary to ensure the correct functioning of infrastructures. Unmanned Aerial Vehicle (UAV) techniques have become more popular than traditional techniques. Specifically, UAV Photogrammetry allows time and cost savings. The development of this technology has permitted the use of low-cost thermal sensors in UAVs. The representation of 3D thermal models with this type of equipment is in continuous evolution. The direct processing of thermal images usually leads to errors and inaccurate results. A methodology is proposed for the generation of 3D thermal models using dual sensors, which involves the application of visible Red-Blue-Green (RGB) and thermal images in parallel. Hence, the RGB images are used as the basis for the generation of the model geometry, and the thermal images are the source of the surface temperature information that is projected onto the model. Mining/industrial facilities representations that are obtained can be used for inspection activities.

Keywords: aerial thermography, data processing, drone, low-cost, point cloud

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Authors: Kamalpreet Kaur, Harjit Pal Singh, Vikas Khullar

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In Wireless Sensor Network (WSN), the main limitation is generally inimitable energy consumption during processing of the sensor nodes. Cluster head (CH) election is one of the main issues that can reduce the energy consumption. Therefore, discovering energy saving routing protocol is the focused area for research. In this paper, fuzzy-based energy aware routing protocol is presented, which enhances the stability and network lifetime of the network. Fuzzy logic ensures the well-organized selection of CH by taking four linguistic variables that are concentration, energy, centrality, and distance to base station (BS). The results show that the proposed protocol shows better results in requisites of stability and throughput of the network.

Keywords: ERA, fuzzy logic, network model, WSN

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Authors: Kherbache Mehdi

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Within the framework of the validation of the Master in business administration marketing and sales in INSIM institute international in management Blida, we get the opportunity to do a professional internship in Sonelgaz Enterprise and a thesis. The thesis deals with the integration of social networking in the communication strategy of a company. The problematic is: How communicate with social network can be a solution for companies? The challenges stressed by this thesis were to suggest limits and recommendations to Sonelgaz Enterprise concerning social networks. The whole social networks represent more than a billion people as a potential target for the companies. Thanks to research and a qualitative approach, we have identified tree valid hypothesis. The first hypothesis allows confirming that using social networks cannot be ignored by any company in its communication strategy. However, the second hypothesis demonstrates that it’s necessary to prepare a strategy that integrates social networks in the communication plan of the company. The risk of this strategy is very limited because failure on social networks is not a restraint for the enterprise, social networking is not expensive and, a bad image which could result from it is not as important in the long-term. Furthermore, the return on investment is difficult to evaluate. Finally, the last hypothesis shows that firms establish a new relation between consumers and brands thanks to the proximity allowed by social networks. After the validation of the hypothesis, we suggested some recommendations to Sonelgaz Enterprise regarding the communication through social networks. Firstly, the company must use the interactivity of social network in order to have fruitful exchanges with the community. We also recommended having a strategy to treat negative comments. The company must also suggest delivering resources to the community thanks to a community manager, in order to have a good relation with the community. Furthermore, we advised using social networks to do business intelligence. Sonelgaz Enterprise can have some creative and interactive contents with some amazing applications on Facebook for example. Finally, we recommended to the company to be not intrusive with “fans” or “followers” and to be open to all the platforms: Twitter, Facebook, Linked-In for example.

Keywords: social network, buzz, communication, consumer, return on investment, internet users, web 2.0, Facebook, Twitter, interaction

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Authors: Salah Ghamari

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In this study, the ability of self organizing map artificial (SOM) neural networks in clustering the wheat seeds varieties according to morphological properties of them was considered. The SOM is one type of unsupervised competitive learning. Experimentally, five morphological features of 300 seeds (including three varieties: gaskozhen, Md and sardari) were obtained using image processing technique. The results show that the artificial neural network has a good performance (90.33% accuracy) in classification of the wheat varieties despite of high similarity in them. The highest classification accuracy (100%) was achieved for sardari.

Keywords: artificial neural networks, clustering, self organizing map, wheat variety

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Authors: Nurul Bin Ibrahim

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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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Authors: A. D'Alessandro, F. Ubertini, A. L. Materazzi

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In the field of civil engineering, Structural Health Monitoring is a topic of growing interest. Effective monitoring instruments permit the control of the working conditions of structures and infrastructures, through the identification of behavioral anomalies due to incipient damages, especially in areas of high environmental hazards as earthquakes. While traditional sensors can be applied only in a limited number of points, providing a partial information for a structural diagnosis, novel transducers may allow a diffuse sensing. Thanks to the new tools and materials provided by nanotechnology, new types of multifunctional sensors are developing in the scientific panorama. In particular, cement-matrix composite materials capable of diagnosing their own state of strain and tension, could be originated by the addition of specific conductive nanofillers. Because of the nature of the material they are made of, these new cementitious nano-modified transducers can be inserted within the concrete elements, transforming the same structures in sets of widespread sensors. This paper is aimed at presenting the results of a research about a new self-sensing nanocomposite and about the implementation of smart sensors for Structural Health Monitoring. The developed nanocomposite has been obtained by inserting multi walled carbon nanotubes within a cementitious matrix. The insertion of such conductive carbon nanofillers provides the base material with piezoresistive characteristics and peculiar sensitivity to mechanical modifications. The self-sensing ability is achieved by correlating the variation of the external stress or strain with the variation of some electrical properties, such as the electrical resistance or conductivity. Through the measurement of such electrical characteristics, the performance and the working conditions of an element or a structure can be monitored. Among conductive carbon nanofillers, carbon nanotubes seem to be particularly promising for the realization of self-sensing cement-matrix materials. Some issues related to the nanofiller dispersion or to the influence of the nano-inclusions amount in the cement matrix need to be carefully investigated: the strain sensitivity of the resulting sensors is influenced by such factors. This work analyzes the dispersion of the carbon nanofillers, the physical properties of the fresh dough, the electrical properties of the hardened composites and the sensing properties of the realized sensors. The experimental campaign focuses specifically on their dynamic characterization and their applicability to the monitoring of full-scale elements. The results of the electromechanical tests with both slow varying and dynamic loads show that the developed nanocomposite sensors can be effectively used for the health monitoring of structures.

Keywords: carbon nanotubes, self-sensing nanocomposites, smart cement-matrix sensors, structural health monitoring

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Authors: Ibrahim Ozkan

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In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.

Keywords: cooperative network, adaptive modulation and coding, hybrid ARQ, correlated fading

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Authors: Takuya Sumi, Syoko Nukaya, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

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We propose an unconstrained measurement system for scratching motion based on mathematical model of unconstrained bed sensing method which could measure the bed vibrations due to the motion of the person on the bed. In this paper, we construct mathematical model of the unconstrained bed monitoring system, and we apply the unconstrained bed sensing method to the system for detecting scratching motion. The proposed sensors are placed under the three bed feet. When the person is lying on the bed, the output signals from the sensors are proportional to the magnitude of the vibration due to the scratching motion. Hence, we could detect the subject’s scratching motion from the output signals from ceramic sensors. We evaluated two scratching motions using the proposed system in the validity experiment as follows: First experiment is the subject’s scratching the right side cheek with his right hand, and; second experiment is the subject’s scratching the shin with another foot. As the results of the experiment, we recognized the scratching signals that enable the determination when the scratching occurred. Furthermore, the difference among the amplitudes of the output signals enabled us to estimate where the subject scratched.

Keywords: unconstrained bed sensing method, scratching, body movement, itchy, piezoceramics

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Authors: Chad Brown

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This paper establishes general conditions for the convergence rates of nonparametric sieve estimators with dependent data. We present two key results: one for nonstationary data and another for stationary mixing data. Previous theoretical results often lack practical applicability to deep neural networks (DNNs). Using these conditions, we derive convergence rates for DNN sieve estimators in nonparametric regression settings with both nonstationary and stationary mixing data. The DNN architectures considered adhere to current industry standards, featuring fully connected feedforward networks with rectified linear unit activation functions, unbounded weights, and a width and depth that grows with sample size.

Keywords: sieve extremum estimates, nonparametric estimation, deep learning, neural networks, rectified linear unit, nonstationary processes

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Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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Authors: Marcya Burden, Savonna Greer

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In the wake of social unrest around the world, protest movements have been captured like never before. As protest movements have evolved, so too have their visibility and sources of coverage. Long gone are the days of print media as our only glimpse into the action surrounding a protest. Now, with social networks such as Facebook, Instagram and Snapchat, we have access to real-time video footage of protest movements and human rights activism that can reach millions of people within seconds. This research paper investigated various social media network platforms’ statistical usage data in the areas of human rights activism and protest movements, paralleling with other past forms of media coverage. This research demonstrates that social networks are extremely important to protest movements and human rights activism. With over 2.9 billion users across social media networks globally, these platforms are the heart of most recent protests and human rights activism. This research shows the paradigm shift from the Selma March of 1965 to the more recent protests of Ferguson in 2014, Ni Una Menos in 2015, and End Sars in 2018. The research findings demonstrate that today, almost anyone may use their social networks to protest movement leaders and human rights activists. From a student to an 80-year-old professor, the possibility of reaching billions of people all over the world is limitless. Findings show that 82% of the world’s internet population is on social networks 1 in every 5 minutes. Over 65% of Americans believe social media highlights important issues. Thus, there is no need to have a formalized group of people or even be known online. A person simply needs to be engaged on their respective social media networks (Facebook, Twitter, Instagram, Snapchat) regarding any cause they are passionate about. Information may be exchanged in real time around the world and a successful protest can begin.

Keywords: activism, protests, human rights, networks

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Authors: Surah Aldakhl, Dafer Alali, Mohamed Zohdy

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The next generation of electricity grid infrastructure, known as the "smart grid," integrates smart ICT (information and communication technology) into existing grids in order to alleviate the drawbacks of existing one-way grid systems. Future power systems' efficiency and dependability are anticipated to significantly increase thanks to the Smart Grid, especially given the desire for renewable energy sources. The security of the Smart Grid's cyber infrastructure is a growing concern, though, as a result of the interconnection of significant power plants through communication networks. Since cyber-attacks can destroy energy data, beginning with personal information leaking from grid members, they can result in serious incidents like huge outages and the destruction of power network infrastructure. We shall thus propose a secure smart energy management system based on the Blockchain as a remedy for this problem. The power transmission and distribution system may undergo a transformation as a result of the inclusion of optical fiber sensors and blockchain technology in smart grids. While optical fiber sensors allow real-time monitoring and management of electrical energy flow, Blockchain offers a secure platform to safeguard the smart grid against cyberattacks and unauthorized access. Additionally, this integration makes it possible to see how energy is produced, distributed, and used in real time, increasing transparency. This strategy has advantages in terms of improved security, efficiency, dependability, and flexibility in energy management. An in-depth analysis of the advantages and drawbacks of combining blockchain technology with optical fiber is provided in this paper.

Keywords: smart grids, blockchain, fiber optic sensor, security

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Authors: Darshana Thomas, Edward Wilkie, James Irvine

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The Internet of things (IoT) is currently a highly researched topic, especially within the context of the smart home. These are small sensors that are capable of gathering data and transmitting it to a server. The majority of smart home products use protocols such as ZigBee or Bluetooth Low Energy (BLE). As these small sensors are increasing in number, the need to implement these with much more capable and ubiquitous transmission technology is necessary. The high power consumption is the reason that holds these small sensors back from using other protocols such as the most ubiquitous form of communication, WiFi. Comparing the power consumption of existing transmission technologies to one with WiFi inbuilt, would provide a better understanding for choosing between these technologies. We have developed a small IoT device with WiFi capability and proven that it is much more efficient than the first protocol, 433 MHz. We extend our work in this paper and compare WiFi power consumption with the other most widely used protocol BLE. The experimental results in this paper would conclude whether the developed prototype is capable in terms of power consumption to replace the existing protocol BLE with WiFi.

Keywords: bluetooth, internet of things (IoT), power consumption, WiFi

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: B. G. Sheeparamatti, J. S. Kadadevarmath

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Microcantilevers are the basic MEMS devices, which can be used as sensors, actuators, and electronics can be easily built into them. The detection principle of microcantilever sensors is based on the measurement of change in cantilever deflection or change in its resonance frequency. The objective of this work is to explore the analogies between the mechanical and electrical equivalent of microcantilever beams. Normally scientists and engineers working in MEMS use expensive software like CoventorWare, IntelliSuite, ANSYS/Multiphysics, etc. This paper indicates the need of developing the electrical equivalent of the MEMS structure and with that, one can have a better insight on important parameters, and their interrelation of the MEMS structure. In this work, considering the mechanical model of the microcantilever, the equivalent electrical circuit is drawn and using a force-voltage analogy, it is analyzed with circuit simulation software. By doing so, one can gain access to a powerful set of intellectual tools that have been developed for understanding electrical circuits. Later the analysis is performed using ANSYS/Multiphysics - software based on finite element method (FEM). It is observed that both mechanical and electrical domain results for a rectangular microcantilevers are in agreement with each other.

Keywords: electrical equivalent circuit analogy, FEM analysis, micro cantilevers, micro sensors

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Authors: Ishak Suleiman, Ahmad Kamsani Samingan, Yeoh Chun Yeow, Abdul Aziz Bin Abdul Rahman

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In this paper, we evaluate the benefits of distributed 4x4 MIMO LTE downlink systems compared to that of the co-located 4x4 MIMO LTE downlink system. The performance evaluation was carried out experimentally by using Wireless Open-Access Research Platform (WARP), where the comparison between the 4x4 MIMO LTE transmission downlink system in distributed and co-located techniques was examined. The measured Error Vector Magnitude (EVM) results showed that the distributed technique achieved better system performance compared to the co-located arrangement.

Keywords: multiple-input-multiple-output (MIMO), distributed MIMO, co-located MIMO, LTE

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Authors: Amel Ltifi, Ahmed Zouinkhi, Med Salim Bouhlel

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Spontaneous networks such as VANET are in general deployed in an open and thus easily accessible environment. Therefore, they are vulnerable to attacks. Trust management is one of a set of security solutions dedicated to this type of networks. Moreover, the strong mobility of the nodes (in the case of VANET) makes the establishment of a trust management system complex. In this paper, we present a concept of ‘Active Vehicle’ which means an autonomous vehicle that is able to make decision about trustworthiness of alert messages transmitted about road accidents. The behavior of an “Active Vehicle” is modeled using Petri Nets.

Keywords: active vehicle, cooperation, petri nets, trust management, VANET

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Authors: Jared Oluoch

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Connected vehicles are equipped with wireless sensors that aid in Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication. These vehicles will in the near future provide road safety, improve transport efficiency, and reduce traffic congestion. One of the challenges for connected vehicles is how to ensure that information sent across the network is secure. If security of the network is not guaranteed, several attacks can occur, thereby compromising the robustness, reliability, and efficiency of the network. This paper discusses existing security mechanisms and unique properties of connected vehicles. The methodology employed in this work is exploratory. The paper reviews existing security solutions for connected vehicles. More concretely, it discusses various cryptographic mechanisms available, and suggests areas of improvement. The study proposes a combination of symmetric key encryption and public key cryptography to improve security. The study further proposes message aggregation as a technique to overcome message redundancy. This paper offers a comprehensive overview of connected vehicles technology, its applications, its security mechanisms, open challenges, and potential areas of future research.

Keywords: VANET, connected vehicles, 802.11p, WAVE, DSRC, trust, security, cryptography

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Authors: Mekha Mathew, Varun P Gopi

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Wireless Capsule Endoscopy (WCE) has become a great device in Gastrointestinal (GI) tract diagnosis, which can examine the entire GI tract, especially the small intestine without invasiveness and sedation. Bleeding in the digestive tract is a symptom of a disease rather than a disease itself. Hence the detection of bleeding is important in diagnosing many diseases. In this paper we proposes a novel method for distinguishing bleeding regions from normal regions based on Contourlet transform and Local Binary Pattern (LBP). Experiments show that this method provides a high accuracy rate of 96.38% in CIE XYZ colour space for k-Nearest Neighbour (k-NN) classifier.

Keywords: Wireless Capsule Endoscopy, local binary pattern, k-NN classifier, contourlet transform

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Authors: Cristian Viespe, Dana Miu

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Surface acoustic wave (SAW) sensors with nanoparticles (NPs) of various dimensions and concentrations embedded in different types of polymer sensing films for detecting volatile organic compounds (VOCs) were studied. The sensors were ‘delay line’ type with a center frequency of 69.4 MHz on ST-X quartz substrates. NPs with different diameters of 7 nm or 13 nm were obtained by laser ablation with lasers having 5 ns or 10 ps pulse durations, respectively. The influence of NPs dimensions and concentrations on sensor properties such as frequency shift, sensitivity, noise and response time were investigated. To the best of our knowledge, the influence of NP dimensions on SAW sensor properties with has not been investigated. The frequency shift and sensitivity increased with increasing NP concentration in the polymer for a given NP dimension and with decreasing NP diameter for a given concentration. The best performances were obtained for the smallest NPs used. The SAW sensor with NPs of 7 nm had a limit of detection (LOD) of 65 ppm (almost five times better than the sensor with polymer alone), and a response time of about 9 s for ethanol.

Keywords: surface acoustic wave sensor, nanoparticles, volatile organic compounds, laser ablation

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Authors: Abdelaziz Beddiaf

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In this work, we present an analysis based on the study of mobility which is a very important electrical parameter of a piezoresistor and which is directly bound to the piezoresistivity effect in piezoresistive pressure sensors. We determine how the temperature affects mobility when the electric potential is applied. For this, a theoretical approach based on mobility in a p-type Silicon piezoresistor with that of a finite difference model for self-heating is developed. So, the evolution of mobility has been established versus time for different doping levels and with temperature rise provoked by self-heating using a numerical model combined with that of mobility. Furthermore, it has been calculated for some geometrical parameters of the sensor, such as membrane side length and thickness. Also, it is computed as a function of bias voltage. It was observed that mobility is strongly affected by the temperature rise induced by the applied potential when the sensor is actuated for a prolonged time as a consequence of drifting in the output response of the sensor. Finally, this work makes it possible to predict their temperature behavior due to self-heating and to improve this effect by optimizing the geometric properties of the device and by reducing the voltage source applied to the bridge.

Keywords: Sensors, Piezoresistivity, Mobility, Bias voltage

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Authors: Deepika Bhalla, Raj Kumar Bansal, Hari Om Gupta

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Dissolved Gas Analysis (DGA) has been widely used for fault diagnosis in a transformer. Artificial neural networks (ANN) have high accuracy but are regarded as black boxes that are difficult to interpret. For many problems it is desired to extract knowledge from trained neural networks (NN) so that the user can gain a better understanding of the solution arrived by the NN. This paper applies a pedagogical approach for rule extraction from function approximating neural networks (REFANN) with application to incipient fault diagnosis using the concentrations of the dissolved gases within the transformer oil, as the input to the NN. The input space is split into subregions and for each subregion there is a linear equation that is used to predict the type of fault developing within a transformer. The experiments on real data indicate that the approach used can extract simple and useful rules and give fault predictions that match the actual fault and are at times also better than those predicted by the IEC method.

Keywords: artificial neural networks, dissolved gas analysis, rules extraction, transformer

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Authors: Xiaodi Su, Xin Ting Zheng, Laura Sutarlie, Nur Asinah binte Mohamed Salleh, Yong Yu

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Wound healing is a dynamic process with multiple phases. Rapid profiling and quantitative characterization of inflammation and infection remain challenging. We have developed paper-like battery-free multiplexed sensors for holistic wound assessment via quantitative detection of multiple inflammation and infection markers. In one of the designs, the sensor patch consists of a wax-printed paper panel with five colorimetric sensor channels arranged in a pattern resembling a five-petaled flower (denoted as a ‘Petal’ sensor). The five sensors are for temperature, pH, trimethylamine, uric acid, and moisture. The sensor patch is sandwiched between a top transparent silicone layer and a bottom adhesive wound contact layer. In the second design, a palm-like-shaped paper strip is fabricated by a paper-cutter printer (denoted as ‘Palm’ sensor). This sensor strip carries five sensor regions connected by a stem sampling entrance that enables rapid colorimetric detection of multiple bacteria metabolites (aldehyde, lactate, moisture, trimethylamine, tryptophan) from wound exudate. For both the “\’ Petal’ and ‘Palm’ sensors, color images can be captured by a mobile phone. According to the color changes, one can quantify the concentration of the biomarkers and then determine wound healing status and identify/quantify bacterial species in infected wounds. The ‘Petal’ and ‘Palm’ sensors are validated with in-situ animal and ex-situ skin wound models, respectively. These sensors have the potential for integration with wound dressing to allow early warning of adverse events without frequent removal of the plasters. Such in-situ and early detection of non-healing condition can trigger immediate clinical intervention to facilitate wound care management.

Keywords: wound infection, colorimetric sensor, paper fluidic sensor, wound care

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Authors: Mojtaba Farzaneh, Majid Baghaei Nejad

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This article proposes a new Flexible Capacitive Tactile Sensors based on paper sheets. This method combines the parameters of sensor's material and dielectric, and forms a new model of flexible capacitive sensors. The present article tries to present a practical explanation of this method's application and advantages. With the use of this new method, it is possible to make a more flexibility and accurate sensor in comparison with the current models. To assess the performance of this model, the common capacitive sensor is simulated and the proposed model of this article and one of the existing models are assessed. The results of this article indicate that the proposed model of this article can enhance the speed and accuracy of tactile sensor and has less error in comparison with the current models. Based on the results of this study, it can be claimed that in comparison with the current models, the proposed model of this article is capable of representing more flexibility and more accurate output parameters for touching the sensor, especially in abnormal situations and uneven surfaces, and increases accuracy and practicality.

Keywords: capacitive sensor, paper sheets, flexible, tactile, uneven

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Authors: Nada Mouchfiq, Ahmed Habbani, Chaimae Benjbara

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The security aspect of the IoT occupies a place of great importance especially after the evolution that has known this field lastly because it must take into account the transformations and the new applications .Blockchain is a new technology dedicated to the data sharing. However, this does not work the same way in the different systems with different operating principles. This article will discuss network security using the Blockchain to facilitate the sending of messages and information, enabling the use of new processes and enabling autonomous coordination of devices. To do this, we will discuss proposed solutions to ensure a high level of security in these networks in the work of other researchers. Finally, our article will propose a method of security more adapted to our needs as a team working in the ad hoc networks, this method is based on the principle of the Blockchain and that we named ”MPR Blockchain”.

Keywords: Ad hocs networks, blockchain, MPR, security

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Authors: B. Atli-Veltin, A. Vosteen, D. Megan, A. Jedynska, L. K. Cheng

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Composite materials combine the advantages of being lightweight and possessing high strength. This is in particular of interest for the development of large constructions, e.g., aircraft, space applications, wind turbines, etc. One of the shortcomings of using composite materials is the complex nature of the failure mechanisms which makes it difficult to predict the remaining lifetime. Therefore, condition and health monitoring are essential for using composite material for critical parts of a construction. Different types of sensors are used/developed to monitor composite structures. These include ultrasonic, thermography, shearography and fiber optic. The first 3 technologies are complex and mostly used for measurement in laboratory or during maintenance of the construction. Optical fiber sensor can be surface mounted or embedded in the composite construction to provide the unique advantage of in-operation measurement of mechanical strain and other parameters of interest. This is identified to be a promising technology for Structural Health Monitoring (SHM) or Prognostic Health Monitoring (PHM) of composite constructions. Among the different fiber optic sensing technologies, Fiber Bragg Grating (FBG) sensor is the most mature and widely used. FBG sensors can be realized in an array configuration with many FBGs in a single optical fiber. In the current project, different aspects of using embedded FBG for composite wind turbine monitoring are investigated. The activities are divided into two parts. Firstly, FBG embedded carbon composite laminate is subjected to tensile and bending loading to investigate the response of FBG which are placed in different orientations with respect to the fiber. Secondly, the demonstration of using FBG sensor array for temperature and strain sensing and monitoring of a 5 m long scale model of a glass fiber mono-pile is investigated. Two different FBG types are used; special in-house fibers and off-the-shelf ones. The results from the first part of the study are showing that the FBG sensors survive the conditions during the production of the laminate. The test results from the tensile and the bending experiments are indicating that the sensors successfully response to the change of strain. The measurements from the sensors will be correlated with the strain gauges that are placed on the surface of the laminates.

Keywords: Fiber Bragg Gratings, embedded sensors, health monitoring, wind turbine towers

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Authors: Manea Viorel, Puscoci Sorin, Stoichescu Dan Alexandru

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Free Space Optics (FSO) is an optical telecommunication system that uses laser beam to transmit data at high bit rates via terrestrial atmosphere. This article describes a method to obtain higher bit rates, under unfavorable weather conditions using multiple optical beams, which carry information with low optical power. Optical link quality assessment is given by the attenuation on different weather conditions. The goal of this paper is to compare two transmission techniques: mono and multi beam, both affected by atmospheric attenuation, using OOK and L-PPM modulation. Link availability is evaluated using eye-diagram that provides information about the overall bit error rate of the system.

Keywords: free space optics, wireless optic, laser communication, spatial diversity

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Authors: Yuhua Yang, Yingcheng Li

Abstract:

As a new form of intercity economic cooperation, innovation enclaves have received much attention from governments and scholars in China, which are of great significance in promoting the flow of innovation elements and advancing regional integration. Utilizing inter-city linkages of innovation enclaves within and beyond the Yangtze River Delta Region, we construct multi-scalar innovation enclave networks in 2018 and 2022, and analyze the evolutionary characteristics and underlying mechanisms of the networks. Overall, we find that: (1) The intercity innovation enclave networks have the characteristics of preferential connection and are gradually forming a clear multi-scale and hierarchical structure, with Shanghai, Hangzhou and Nanjing as the core and other cities as the general nodes; (2) The intercity innovation enclave networks exhibit local clustering dominated by geographical proximity connections, and are becoming more noticeable in the effect of distance decay and functionally polycentric as the spatial scale decreases; (3) The intercity innovation enclave networks are influenced by both functional distance and multidimensional proximity. While the innovation potential differences caused by urban attributes internally drive the formation of innovation enclave cooperation, geographic proximity, technological proximity and institutional proximity externally affect the selection of cooperation partners.

Keywords: economic enclave, intercity cooperation, proximity, yangtze river delta region

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Authors: Mohammad Zahidul Islam Bhuiyan, Shanyong Wang, Scott William Sloan, Daichao Sheng

Abstract:

Nowadays soil pressure transducers are widely used to measure the soil stress states in laboratory and field experiments. The soil pressure transducers, investigated here, are traditional diaphragm-type earth pressure cells (DEPC) based on strain gauge principle. It is found that the output of these sensors varies with the soil conditions as well as the position of a sensor. Therefore, it is highly recommended to calibrate the pressure sensors based on the similar conditions of their intended applications. The factory calibration coefficients of the EPCs are not reliable to use since they are normally calibrated by applying fluid (a special type of oil) pressure only over load sensing zone, which does not represent the actual field conditions. Thus, the calibration of these sensors is utmost important, and they play a pivotal role for assessing earth pressures precisely. In the present study, TML soil pressure sensor is used to compare its sensitivity under different calibration systems, for example, fluid calibration, and static load calibration with or without soil. The results report that the sensor provides higher sensitivity (more accurate results) under soil calibration system.

Keywords: calibration, soil pressure, earth pressure cell, sensitivity

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Authors: Gunasekaran Raja, Ramkumar Jayaraman

Abstract:

In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

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