Search results for: sensor node dataprocessing

Authors: Sayed Obeidullah Abrar

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Nanosensor is the combination of two terms nanoparticles and sensors. These are chemical or physical sensor constructed using nanoscale components, usually microscopic or submicroscopic in size. These sensors are very sensitive and can detect single virus particle or even very low concentrations of substances that could be potentially harmful. Nanosensors have a large scope of research especially in the field of medical sciences, military applications, pharmaceuticals etc.

Keywords: HIV/AIDS, nanosensors, DNA, RNA

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Authors: A. Douara, N. Kermas, B. Djellouli

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In this study, we report calculations of gate capacitance of AlGaN/GaN HEMTs with nextnano device simulation software. We have used a physical gate capacitance model for III-V FETs that incorporates quantum capacitance and centroid capacitance in the channel. These simulations explore various device structures with different values of barrier thickness and channel thickness. A detailed understanding of the impact of gate capacitance in HEMTs will allow us to determine their role in future 10 nm physical gate length node.

Keywords: gate capacitance, AlGaN/GaN, HEMTs, quantum capacitance, centroid capacitance

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Authors: Mona Awad Wanis Gad

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The method of factory making plans has changed loads, in particular, whilst it's miles approximately making plans the factory building itself. Factory making plans have the venture of designing merchandise, plants, tactics, organization, regions, and the construction of a factory. Ordinary restructuring is turning into greater essential for you to preserve the competitiveness of a manufacturing unit. Regulations in new regions, shorter lifestyle cycles of product and manufacturing era, in addition to a VUCA global (Volatility, Uncertainty, Complexity and Ambiguity) cause extra common restructuring measures inside a factory. A digital factory model is the planning foundation for rebuilding measures and turns into a critical device. Furthermore, digital building fashions are increasingly being utilized in factories to help facility management and manufacturing processes. First, exclusive styles of digital manufacturing unit fashions are investigated, and their residences and usabilities to be used instances are analyzed. Within the scope of research are point cloud fashions, building statistics fashions, photogrammetry fashions, and those enriched with sensor information are tested. It investigated which digital fashions permit a simple integration of sensor facts and in which the variations are. In the end, viable application areas of virtual manufacturing unit models are determined by a survey, and the respective digital manufacturing facility fashions are assigned to the application areas. Ultimately, an application case from upkeep is selected and implemented with the assistance of the best virtual factory version. It is shown how a completely digitalized preservation process can be supported by a digital manufacturing facility version by offering facts. Among different functions, the virtual manufacturing facility version is used for indoor navigation, facts provision, and display of sensor statistics. In summary, the paper suggests a structuring of virtual factory fashions that concentrates on the geometric representation of a manufacturing facility building and its technical facilities. A practical application case is proven and implemented. For that reason, the systematic selection of virtual manufacturing facility models with the corresponding utility cases is evaluated.

Keywords: augmented reality, digital factory model, factory planning, restructuring digital factory model, photogrammetry, factory planning, restructuring building information modeling, digital factory model, factory planning, maintenance

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Authors: Sunday B. Alabi, Edikan P. Felix, Aniediong M. Umo

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Crystal size distribution is of great importance in the sugar factories. It determines the market value of granulated sugar and also influences the cost of production of sugar crystals. Typically, sugar is produced using fed-batch vacuum evaporative crystallizer. The crystallization quality is examined by crystal size distribution at the end of the process which is quantified by two parameters: the average crystal size of the distribution in the mean aperture (MA) and the width of the distribution of the coefficient of variation (CV). Lack of real-time measurement of the sugar crystal size hinders its feedback control and eventual optimisation of the crystallization process. An attractive alternative is to use a soft sensor (model-based method) for online estimation of the sugar crystal size. Unfortunately, the available models for sugar crystallization process are not suitable as they do not contain variables that can be measured easily online. The main contribution of this paper is the development of a regression model for estimating the sugar crystal size as a function of input variables which are easy to measure online. This has the potential to provide real-time estimates of crystal size for its effective feedback control. Using 7 input variables namely: initial crystal size (Lo), temperature (T), vacuum pressure (P), feed flowrate (Ff), steam flowrate (Fs), initial super-saturation (S0) and crystallization time (t), preliminary studies were carried out using Minitab 14 statistical software. Based on the existing sugar crystallizer models, and the typical ranges of these 7 input variables, 128 datasets were obtained from a 2-level factorial experimental design. These datasets were used to obtain a simple but online-implementable 6-input crystal size model. It seems the initial crystal size (Lₒ) does not play a significant role. The goodness of the resulting regression model was evaluated. The coefficient of determination, R² was obtained as 0.994, and the maximum absolute relative error (MARE) was obtained as 4.6%. The high R² (~1.0) and the reasonably low MARE values are an indication that the model is able to predict sugar crystal size accurately as a function of the 6 easy-to-measure online variables. Thus, the model can be used as a soft sensor to provide real-time estimates of sugar crystal size during sugar crystallization process in a fed-batch vacuum evaporative crystallizer.

Keywords: crystal size, regression model, soft sensor, sugar, vacuum evaporative crystallizer

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Authors: R. M. López-Gutiérrez, L. Cardoza-Avendaño, H. Cervantes-de Ávila, J. A. Michel-Macarty, C. Cruz-Hernández, A. Arellano-Delgado, R. Carmona-Rodríguez

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In this paper, synchronization of multiple chaotic semiconductor lasers is achieved by appealing to complex system theory. In particular, we consider dynamical networks composed by semiconductor laser, as interconnected nodes, where the interaction in the networks are defined by coupling the first state of each node. An interesting case is synchronized with master-slave configuration in star topology. Nodes of these networks are modeled for the laser and simulated by Matlab. These results are applicable to private communication.

Keywords: chaotic laser, network, star topology, synchronization

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Authors: Kaiyi Zhang, Wenlong Li, Haicheng Li, Yifei Luo, Zheng Li, Xiaoshi Wang, Xiaodong Chen

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Plant wearable sensors facilitate the real-time monitoring of plant physiological status. In situ monitoring of the plant chlorophyll content over days could provide valuable information on the photosynthetic capacity, nitrogen content, and general plant health. However, it cannot be achieved by current chlorophyll measuring methods. Here, a miniaturized and plant-wearable chlorophyll meter was developed for rapid, non-destructive, in situ, and long-term chlorophyll monitoring. This reflectance-based chlorophyll sensor with 1.5 mm thickness and 0.2 g weight (1000 times lighter than the commercial chlorophyll meter), includes a light emitting diode (LED) and two symmetric photodetectors (PDs) on a flexible substrate and is patched onto the leaf upper epidermis with a conformal light guiding layer. A chlorophyll content index (CCI) calculated based on this sensor shows a better linear relationship with the leaf chlorophyll content (r² > 0.9) than the traditional chlorophyll meter. This meter can wirelessly communicate with a smartphone to monitor the leaf chlorophyll change under various stresses and indicate the unhealthy status of plants for long-term application of plants under various stresses earlier than chlorophyll meter and naked-eye observation. This wearable chlorophyll sensing patch is promising in smart and precision agriculture.

Keywords: plant wearable sensors, reflectance-based measurements, chlorophyll content monitoring, smart agriculture

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Authors: Tariq A. El Shheibia, Halima Mohamed Belhamad

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This paper is considered securing data based on multi-path protocol (SDMP) in mobile ad hoc network utilizing OPNET simulator modular 14.5, including the AODV routing protocol at the network as based multi-path algorithm for message security in MANETs. The main idea of this work is to present a way that is able to detect the attacker inside the MANETs. The detection for this attacker will be performed by adding some effective parameters to the network.

Keywords: MANET, AODV, malicious node, OPNET

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Authors: Muhammad Arif Khan, Haroon Idrees, Imran Aziz, Sidra Mushtaq

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Social platforms like online discussion and mailing groups are well aligned with academic as well as professional learning spaces. Professional communities are increasingly moving to online forums for sharing and capturing the intellectual abilities. This study investigated dynamics of social connectivity of yahoo mailing groups of Pakistani Library and Information Science (LIS) professionals using Graph Theory technique. Design/Methodology: Social Network Analysis is the increasingly concerned domain for scientists in identifying whether people grow together through online social interaction or, whether they just reflect connectivity. We have conducted a longitudinal study using Network Graph Theory technique to analyze the large data-set of email communication. The data was collected from three yahoo mailing groups using network analysis software over a period of six months i.e. January to June 2016. Findings of the network analysis were reviewed through focus group discussion with LIS experts and selected respondents of the study. Data were analyzed in Microsoft Excel and network diagrams were visualized using NodeXL and ORA-Net Scene package. Findings: Findings demonstrate that professionals and students exhibit intellectual growth the more they get tied within a network by interacting and participating in communication through online forums. The study reports on dynamics of the large network by visualizing the email correspondence among group members in a network consisting vertices (members) and edges (randomized correspondence). The model pair wise relationship between group members was illustrated to show characteristics, reasons, and strength of ties. Connectivity of nodes illustrated the frequency of communication among group members through examining node coupling, diffusion of networks, and node clustering has been demonstrated in-depth. Network analysis was found to be a useful technique in investigating the dynamics of the large network.

Keywords: emailing networks, network graph theory, online social platforms, yahoo mailing groups

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Authors: Raana Babadi Fathipour

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Tea, second only to water in global consumption rates, holds a significant place as the beverage of choice for many around the world. The process of fermenting tea leaves plays a crucial role in determining its ultimate quality, traditionally assessed through meticulous observation by tea tasters and laboratory analysis. However, advancements in technology have paved the way for innovative electronic sensing platforms like the electronic nose (e-nose), electronic tongue (e-tongue), and electronic eye (e-eye). These cutting-edge tools, coupled with sophisticated data processing algorithms, not only expedite the assessment of tea's sensory qualities based on consumer preferences but also establish new benchmarks for this esteemed bioactive product to meet burgeoning market demands worldwide. By harnessing intricate data sets derived from electronic signals and deploying multivariate statistical techniques, these technological marvels can enhance accuracy in predicting and distinguishing tea quality with unparalleled precision. In this contemporary exploration, a comprehensive overview is provided of the most recent breakthroughs and viable solutions aimed at addressing forthcoming challenges in the realm of tea analysis. Utilizing bio-mimicking Electronic Sensory Perception systems (ESPs), researchers have developed innovative technologies that enable precise and instantaneous evaluation of the sensory-chemical attributes inherent in tea and its derivatives. These sophisticated sensing mechanisms are adept at deciphering key elements such as aroma, taste, and color profiles, transitioning valuable data into intricate mathematical algorithms for classification purposes. Through their adept capabilities, these cutting-edge devices exhibit remarkable proficiency in discerning various teas with respect to their distinct pricing structures, geographic origins, harvest epochs, fermentation processes, storage durations, quality classifications, and potential adulteration levels. While voltammetric and fluorescent sensor arrays have emerged as promising tools for constructing electronic tongue systems proficient in scrutinizing tea compositions, potentiometric electrodes continue to serve as reliable instruments for meticulously monitoring taste dynamics within different tea varieties. By implementing a feature-level fusion strategy within predictive models, marked enhancements can be achieved regarding efficiency and accuracy levels. Moreover, by establishing intrinsic linkages through pattern recognition methodologies between sensory traits and biochemical makeup found within tea samples, further strides are made toward enhancing our understanding of this venerable beverage's complex nature.

Keywords: classifier system, tea, polyphenol, sensor, taste sensor

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Authors: Natalia V. Beloglazova, Pieterjan Lenain, Martin Hedstrom, Dietmar Knopp, Sarah De Saeger

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In recent years polycyclic aromatic hydrocarbons (PAHs), which represent a hazard to humans and entire ecosystem, have been receiving an increased interest due to their mutagenic, carcinogenic and endocrine disrupting properties. They are formed in all incomplete combustion processes of organic matter and, as a consequence, ubiquitous in the environment. Benzo(a)pyrene (BaP) is on the priority list published by the Environmental Agency (US EPA) as the first PAH to be identified as a carcinogen and has often been used as a marker for PAHs contamination in general. It can be found in different types of water samples, therefore, the European Commission set up a limit value of 10 ng L–1 (10 ppt) for BAP in water intended for human consumption. Generally, different chromatographic techniques are used for PAHs determination, but these assays require pre-concentration of analyte, create large amounts of solvent waste, and are relatively time consuming and difficult to perform on-site. An alternative robust, stand-alone, and preferably cheap solution is needed. For example, a sensing unit which can be submerged in a river to monitor and continuously sample BaP. An affinity sensor based on capacitive transduction was developed. Natural antibodies or their synthetic analogues can be used as ligands. Ideally the sensor should operate independently over a longer period of time, e.g. several weeks or months, therefore the use of molecularly imprinted polymers (MIPs) was discussed. MIPs are synthetic antibodies which are selective for a chosen target molecule. Their robustness allows application in environments for which biological recognition elements are unsuitable or denature. They can be reused multiple times, which is essential to meet the stand-alone requirement. BaP is a highly lipophilic compound and does not contain any functional groups in its structure, thus excluding non-covalent imprinting methods based on ionic interactions. Instead, the MIPs syntheses were based on non-covalent hydrophobic and π-π interactions. Different polymerization strategies were compared and the best results were demonstrated by the MIPs produced using electropolymerization. 4-vinylpyridin (VP) and divinylbenzene (DVB) were used as monomer and cross-linker in the polymerization reaction. The selectivity and recovery of the MIP were compared to a non-imprinted polymer (NIP). Electrodes were functionalized with natural receptor (monoclonal anti-BaP antibody) and with MIPs selective towards BaP. Different sets of electrodes were evaluated and their properties such as sensitivity, selectivity and linear range were determined and compared. It was found that both receptor can reach the cut-off level comparable to the established ML, and despite the fact that the antibody showed the better cross-reactivity and affinity, MIPs were more convenient receptor due to their ability to regenerate and stability in river till 7 days.

Keywords: antibody, benzo(a)pyrene, capacitive sensor, MIPs, river water

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Authors: H. C. Woo, F. Bouanis, C. S. Cojocaur

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Graphene, which consists of a single layer of carbon atoms in a honeycomb lattice, is an interesting potential optoelectronic material because of graphene’s high carrier mobility, zero bandgap, and electron–hole symmetry. Graphene can absorb light and convert it into a photocurrent over a wide range of the electromagnetic spectrum, from the ultraviolet to visible and infrared regimes. Over the last several years, a variety of graphene-based photodetectors have been reported, such as graphene transistors, graphene-semiconductor heterojunction photodetectors, graphene based bolometers. It is also reported that there are several physical mechanisms enabling photodetection: photovoltaic effect, photo-thermoelectric effect, bolometric effect, photogating effect, and so on. In this work, we report a simple approach for the realization of graphene based resistive photo-detection devices and the measurements of their photoelectrical response. The graphene were synthesized directly on the glass substrate by novel growth method patented in our lab. Then, the metal electrodes were deposited by thermal evaporation on it, with an electrode length and width of 1.5 mm and 300 μm respectively, using Co to fabricate simple graphene based resistive photosensor. The measurements show that the graphene resistive devices exhibit a photoresponse to the illumination of visible light. The observed re-sistance response was reproducible and similar after many cycles of on and off operations. This photoelectrical response may be attributed not only to the direct photocurrent process but also to the desorption of oxygen. Our work shows that the simple graphene resistive devices have potential in photodetection applications.

Keywords: graphene, resistive sensor, optoelectronics, photoresponse

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Authors: Yasin Ghasemi-Zadeh, Yousef Kavian

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Wireless body area networks (WBANs) technology has achieved lots of popularity over the last decade with a wide range of medical applications. This paper presents an asynchronous media access control (MAC) protocol based on B-MAC protocol by giving an application for medical issues. In WBAN applications, there are some serious problems such as energy, latency, link reliability (quality of wireless link) and throughput which are mainly due to size of sensor networks and human body specifications. To overcome these problems and improving link reliability, we concentrated on MAC layer that supports mobility models for medical applications. In the presented protocol, preamble frames are divided into some sub-frames considering the threshold level. Actually, the main reason for creating shorter preambles is the link reliability where due to some reasons such as water, the body signals are affected on some frequency bands and causes fading and shadowing on signals, therefore by increasing the link reliability, these effects are reduced. In case of mobility model, we use MoBAN model and modify that for some more areas. The presented asynchronous MAC protocol is modeled by OMNeT++ simulator. The results demonstrate increasing the link reliability comparing to B-MAC protocol where the packet reception ratio (PRR) is 92% also covers more mobility areas than MoBAN protocol.

Keywords: wireless body area networks (WBANs), MAC protocol, link reliability, mobility, biomedical

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Authors: Amal E. Ahmed, Levent Trabzon

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Due to the low concentration of the analytes in biological samples, the use of Biological Microelectromechanical System (Bio-MEMS) biosensors for biomolecules detection results in a minuscule output signal that is not good enough for practical applications. In response to this, a need has arisen for an optimized biosensor capable of giving high output signal in response the detection of few analytes in the sample; the ultimate goal is being able to convert the attachment of a single biomolecule into a measurable quantity. For this purpose, MEMS microcantilevers based biosensors emerged as a promising sensing solution because it is simple, cheap, very sensitive and more importantly does not need analytes optical labeling (Label-free). Among the different microcantilever transducing techniques, piezoresistive based microcantilever biosensors became more prominent because it works well in liquid environments and has an integrated readout system. However, the design of piezoresistive microcantilevers is not a straightforward problem due to coupling between the design parameters, constraints, process conditions, and performance. It was found that the parameters that can be optimized to enhance the sensitivity of Piezoresistive microcantilever-based sensors are: cantilever dimensions, cantilever material, cantilever shape, piezoresistor material, piezoresistor doping level, piezoresistor dimensions, piezoresistor position, Stress Concentration Region's (SCR) shape and position. After a systematic analyzation of the effect of each design and process parameters on the sensitivity, a step-wise optimization approach was developed in which almost all these parameters were variated one at each step while fixing the others to get the maximum possible sensitivity at the end. At each step, the goal was to optimize the parameter in a way that it maximizes and concentrates the stress in the piezoresistor region for the same applied force thus get the higher sensitivity. Using this approach, an optimized sensor that has 73.5x times higher electrical sensitivity (ΔR⁄R) than the starting sensor was obtained. In addition to that, this piezoresistive microcantilever biosensor it is more sensitive than the other similar sensors previously reported in the open literature. The mechanical sensitivity of the final senior is -1.5×10-8 Ω/Ω ⁄pN; which means that for each 1pN (10-10 g) biomolecules attach to this biosensor; the piezoresistor resistivity will decrease by 1.5×10-8 Ω. Throughout this work COMSOL Multiphysics 5.0, a commercial Finite Element Analysis (FEA) tool, has been used to simulate the sensor performance.

Keywords: biosensor, microcantilever, piezoresistive, stress concentration region (SCR)

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Authors: Branislav Timotijevic, Yves Petremand, Markus Luetzelschwab, Dara Bayat, Laurent Aebi

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Optical miniaturized sensors with remote readout are required devices for the monitoring in harsh electromagnetic environments. As an example, in turbo and hydro generators, excessively high vibrations of the end-windings can lead to dramatic damages, imposing very high, additional service costs. A significant change of the generator temperature can also be an indicator of the system failure. Continuous monitoring of vibrations, temperature, humidity, and gases is therefore mandatory. The high electromagnetic fields in the generators impose the use of non-conductive devices in order to prevent electromagnetic interferences and to electrically isolate the sensing element to the electronic readout. Metal-free sensors are good candidates for such systems since they are immune to very strong electromagnetic fields and given the fact that they are non-conductive. We have realized miniature optical accelerometer and temperature sensors for a remote sensing of the harsh environments using the common, inexpensive silicon Micro Electro-Mechanical System (MEMS) platform. Both devices show highly linear response. The accelerometer has a deviation within 1% from the linear fit when tested in a range 0 – 40 g. The temperature sensor can provide the measurement accuracy better than 1 °C in a range 20 – 150 °C. The design of other type of sensors for the environments with high electromagnetic interferences has also been discussed.

Keywords: optical MEMS, temperature sensor, accelerometer, remote sensing, harsh environment

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Authors: Walter Bernhofer, Peter Haber, Tobias Mayer, Manfred Mayr, Markus Ziegler

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Current preventive maintenance measures are cost intensive and not efficient. With the available sensor data of state of the art internet of things devices new possibilities of automated data processing emerge. Current advances in data science and in machine learning enable new, so called predictive maintenance technologies, which empower data scientists to forecast possible system failures. The goal of this approach is to cut expenses in preventive maintenance by automating the detection of possible failures and to improve efficiency and quality of maintenance measures. Additionally, a centralization of the sensor data monitoring can be achieved by using this approach. This paper describes the approach of three students to define a reference architecture for a predictive maintenance solution in the internet of things domain with a connected smartphone app for service technicians. The reference architecture is validated by a case study. The case study is implemented with current Microsoft Azure cloud technologies. The results of the case study show that the reference architecture is valid and can be used to achieve a system for predictive maintenance execution with the cloud components of Microsoft Azure. The used concepts are technology platform agnostic and can be reused in many different cloud platforms. The reference architecture is valid and can be used in many use cases, like gas station maintenance, elevator maintenance and many more.

Keywords: case study, internet of things, predictive maintenance, reference architecture

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Authors: Bivek Bhusal, Ana Legrand

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Detection of crop stress is one of the major applications of remote sensing in agriculture. Multiple studies have demonstrated the capability of remote sensing using Unmanned Aerial Vehicle (UAV)-based multispectral imagery for detection of plant stress, but none so far on Nitrogen (N) stress and PLH feeding stress on green beans. In view of its wide host range, geographical distribution, and damage potential, Potato leafhopper- Empoasca fabae (Harris) has been emerging as a key pest in several countries. Monitoring methods for potato leafhopper (PLH) damage, as well as the laboratory techniques for detecting Nitrogen deficiency, are time-consuming and not always easily affordable. A study was initiated to demonstrate if the multispectral sensor attached to a drone can detect PLH stress and N deficiency in beans. Small-plot trials were conducted in the summer of 2023, where cages were used to manipulate PLH infestation in green beans (Provider cultivar) at their first-trifoliate stage. Half of the bean plots were introduced with PLH, and the others were kept insect-free. Half of these plots were grown with the recommended amount of N, and the others were grown without N. Canopy reflectance was captured using a five-band multispectral sensor. Our findings indicate that drone imagery could detect stress due to a lack of N and PLH damage in beans.

Keywords: potato leafhopper, nitrogen, remote sensing, spectral reflectance, beans

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Authors: Houda Najeh, Mahendra Pratap Singh, Stéphane Ploix, Antoine Caucheteux, Karim Chabir, Mohamed Naceur Abdelkrim

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Building system is highly vulnerable to different kinds of faults and human misbehaviors. Energy efficiency and user comfort are directly targeted due to abnormalities in building operation. The available fault diagnosis tools and methodologies particularly rely on rules or pure model-based approaches. It is assumed that model or rule-based test could be applied to any situation without taking into account actual testing contexts. Contextual tests with validity domain could reduce a lot of the design of detection tests. The main objective of this paper is to consider fault validity when validate the test model considering the non-modeled events such as occupancy, weather conditions, door and window openings and the integration of the knowledge of the expert on the state of the system. The concept of heterogeneous tests is combined with test validity to generate fault diagnoses. A combination of rules, range and model-based tests known as heterogeneous tests are proposed to reduce the modeling complexity. Calculation of logical diagnoses coming from artificial intelligence provides a global explanation consistent with the test result. An application example shows the efficiency of the proposed technique: an office setting at Grenoble Institute of Technology.

Keywords: heterogeneous tests, validity, building system, sensor grids, sensor fault, diagnosis, fault detection and isolation

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Authors: Amita Singha

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The project describes the scope of magnetic braking. The potential applications of the braking system can be a de-accelerating system to increase the safety of an elevator or any guided rail transportation system.

Keywords: boost and buck converter, electromagnet, elevator, ferromagnetic material, sensor, solenoid, timer

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Authors: Kaiwan S. Ismael, Ergun Ercelebi, Majeed Nader

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This paper describes the design and implementation of a hardware setup for online monitoring of 24 refrigerators inside blood bank center using the microcontroller and CAN bus for communications between each node. Due to the security of locations in the blood bank hall and difficulty of monitoring of each refrigerator separately, this work proposes a solution to monitor all the blood bank refrigerators in one location. CAN-bus system is used because it has many applications and advantages, especially for this system due to easy in use, low cost, providing a reduction in wiring, fast to repair and easily expanding the project without a problem.

Keywords: control area network (CAN), monitoring blood bank center, PIC microcontroller, MPLAB IDE

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Authors: Dongju Kim, Youngjoo Suh, Hyojin Kim, Gyeongyeong Kim

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Acoustic Emission Testing (AET) is widely used to test the structural integrity of an operational hydrogen storage container, and clustering algorithms are frequently used in pattern recognition methods to interpret AET results. However, the interpretation of AET results can vary from user to user as the tuning of the relevant parameters relies on the user's experience and knowledge of AET. Therefore, it is necessary to use a deep learning model to identify patterns in acoustic emission (AE) signal data that can be used to classify defects instead. In this paper, a deep learning-based model for classifying the types of defects in hydrogen storage tanks, using AE sensor waveforms, is proposed. As hydrogen storage tanks are commonly constructed using carbon fiber reinforced polymer composite (CFRP), a defect classification dataset is collected through a tensile test on a specimen of CFRP with an AE sensor attached. The performance of the classification model, using one-dimensional convolutional neural network (1-D CNN) and synthetic minority oversampling technique (SMOTE) data augmentation, achieved 91.09% accuracy for each defect. It is expected that the deep learning classification model in this paper, used with AET, will help in evaluating the operational safety of hydrogen storage containers.

Keywords: acoustic emission testing, carbon fiber reinforced polymer composite, one-dimensional convolutional neural network, smote data augmentation

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: John E. Foley, Martin Miele, Raul Fonda, Jon Jacobson

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This paper presents development and implementation of new and innovative data collection and analysis methodologies based on deployment of total field magnetometer arrays. Our research has focused on the development of a vertically-integrated suite of platforms all utilizing common data acquisition, data processing and analysis tools. These survey platforms include low-altitude helicopters and ground-based vehicles, including robots, for terrestrial mapping applications. For marine settings the sensor arrays are deployed from either a hydrodynamic bottom-following wing towed from a surface vessel or from a towed floating platform for shallow-water settings. Additionally, sensor arrays are deployed from tethered remotely operated vehicles (ROVs) for underwater settings where high maneuverability is required. While the primary application of these systems is the detection and mapping of unexploded ordnance (UXO), these system are also used for various infrastructure mapping and geologic investigations. For each application, success is driven by the integration of magnetometer arrays, accurate geo-positioning, system noise mitigation, and stable deployment of the system in appropriate proximity of expected targets or features. Each of the systems collects geo-registered data compatible with a web-enabled data management system providing immediate access of data and meta-data for remote processing, analysis and delivery of results. This approach allows highly sophisticated magnetic processing methods, including classification based on dipole modeling and remanent magnetization, to be efficiently applied to many projects. This paper also briefly describes the initial development of magnetometer-based detection systems deployed from low-altitude helicopter platforms and the subsequent successful transition of this technology to the marine environment. Additionally, we present examples from a range of terrestrial and marine settings as well as ongoing research efforts related to sensor miniaturization for unmanned aerial vehicle (UAV) magnetic field mapping applications.

Keywords: dipole modeling, magnetometer mapping systems, sub-surface infrastructure mapping, unexploded ordnance detection

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Authors: Mohammed Al-Zubaidi, Katherine Ong, Pravin Viswambaram, Steve McCombie, Oliver Oey, Jeremy Ong, Richard Gauci, Ronny Low, Dickon Hayne

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Objective: Lymph node involvement along with distant metastasis in a patient with invasive bladder cancer determines the disease survival, therefeor, it is an essential determinant of the therapeutic management and outcome. This retrospective study aims to determine the accuracy of FDG PET scan in detecting lymphatic involvement and distant metastatic urothelial cancer compared to conventional CT staging. Method: A retrospective review of 76 patients with UC or BC who underwent surgery or confirmatory biopsy that was staged with both CT and 18F-FDG-PET (up to 8 weeks apart) between 2015 and 2020. Fifty-sevenpatients (75%) had formal pelvic LN dissection or biopsy of suspicious metastasis. 18F-FDG-PET reports for positive sites were qualitative depending on SUV Max. On the other hand, enlarged LN by RECIST criteria 1.1 (>10 mm) and other qualitative findings suggesting metastasis were considered positive in CT scan. Histopathological findings from surgical specimens or image-guided biopsies were considered the gold standard in comparison to imaging reports. 18F-FDG-avid or enlarged pelvic LNs with surgically proven nodal metastasis were considered true positives. Performance characteristics of 18F-FDG-PET and CT, including sensitivity, specificity, positive predictive value (PPV), and negative predictive value (PPV), were calculated. Results: Pelvic LN involvement was confirmed histologically in 10/57 (17.5%) patients. Sensitivity, specificity, PPV and NPV of CT for detecting pelvic LN metastases were 41.17% (95% CI:18-67%), 100% (95% CI:90-100%) 100% (95% CI:59-100%) and 78.26% (95% CI:64-89%) respectively. Sensitivity, specificity, PPV and NPV of 18F-FDG-PET for detecting pelvic LN metastases were 62.5% (95% CI:35-85%), 83.78% (95% CI:68-94%), 62.5% (95% CI:35-85%), and 83.78% (95% CI:68-94%) respectively. Pre-operative staging with 18F-FDG-PET identified the distant metastatic disease in 9/76 (11.8%) patients who were occult on CT. This retrospective study suggested that 18F-FDG-PET may be more sensitive than CT for detecting pelvic LN metastases. 7/76 (9.2%) patients avoided cystectomy due to 18F-FDG-PET diagnosed metastases that were not reported on CT. Conclusion: 18F-FDG-PET is more sensitive than CT for pelvic LN metastases, which can be used as the standard modality of bladder cancer staging, as it may change the treatment by detecting lymph node metastasis that was occult in CT. Further research involving randomised controlled trials comparing the diagnostic yield of 18F-FDG-PET and CT in detecting nodal and distant metastasis in UC or BC is warranted to confirm our findings.

Keywords: FDG PET, CT scan, urothelial cancer, bladder cancer

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Authors: Nassiri Khalid, El Hibaoui Abdelaaziz et Hajar Moha

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In this paper, we introduce and analyse a probabilistic distributed algorithm for a construction of a minimum spanning tree on network. This algorithm is based on the handshake concept. Firstly, each network node is considered as a sub-spanning tree. And at each round of the execution of our algorithm, a sub-spanning trees are merged. The execution continues until all sub-spanning trees are merged into one. We analyze this algorithm by a stochastic process.

Keywords: Spanning tree, Distributed Algorithm, Handshake Algorithm, Matching, Probabilistic Analysis

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Authors: A. Rinaldi, A. Proietti, C. Aquarelli, F. Marra, A. Tamburrano, M. Ciminello, M. S. Sarto

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A new type of high sensitive piezoresistive sensors based on graphene was developed within the SARISTU project for application on Structural Health Monitoring (SHM). The new sensor consists of a graphene-based film, obtained through the spray deposition of a colloidal suspension of Multi-Layer Graphene (MLGs) nano platelets over a substrate. MLGs are produced by liquid exfoliation of thermally expanded Graphite Intercalation Compound. An array of 8 sensors is produced by spray deposition over an aeronautical CFRC plate of dimensions 550 mm (length) × 550 mm (width) × 3 mm (thickness). Electromechanical tests were performed in order to assess the sensitivity of the new piezoresistive sensors, which are characterized by an isotropic response. In the quasi-static characterizations, the CFRC plate was clamped on one side and loaded on the opposite one. The local strain map of the plate was then obtained from displacement measurements and numerical analysis. The dynamic tests were performed lying the plate over an anti-vibration table and actuating a piezoelectric element located in the middle of the sensing array. The obtained experimental results demonstrated that the sensors possess a good repeatability and a high constant gauge factor (~200) in the applied strain range 0.001%-0.02%. Moreover, they can follow dynamics up to 400 kHz and for this reason they are good candidates for Lamb-wave analysis.

Keywords: graphene, strain sensor, spray deposition, lamb-wave analysis

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Authors: Kirandeep Kaur, Rohit Mehra, Pargin Bangotra

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Radon and thoron are pervasive radioactive gases and so are their progenies. The progenies of radon and thoron are present in the indoor atmosphere as attached/unattached fractions. In the present work, seasonal variation of concentration of attached and total (attached + unattached) nanosized decay products of indoor radon and thoron has been studied in the dwellings of Bathinda District of Punjab using Deposition based progeny sensors over long integrated times, which are independent of air turbulence. The preliminary results of these measurements are reported particularly regarding DTPS (Direct Thoron Progeny Sensor) and DRPS (Direct Radon Progeny Sensor) for the first time in Bathinda. It has been observed that there is a strong linear relationship in total EERC (Equilibrium Equivalent Radon Concentration) and EETC (Equilibrium Equivalent Thoron Concentration) in rainy season (R2 = 0.83). Further a strong linear relation between total indoor radon concentration and attached fraction has also been observed for the same rainy season (R2= 0.91). The concentration of attached progeny of radon (EERCatt) is 76.3 % of the total Equilibrium Equivalent Radon Concentration (EERC).

Keywords: radon, thoron, progeny, DTPS/DRPS, EERC, EETC, seasonal variation

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Authors: Vishal Kumar, Soumitra Satapathi

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Föster Resonance Energy Transfer (FRET) is a powerful technique used to probe close-range molecular interactions. Physically, the FRET phenomenon manifests as a dipole–dipole interaction between closely juxtaposed fluorescent molecules (10–100 Å). Our effort is to employ this FRET technique to make a prototype device for highly sensitive detection of environment pollutant. Among the most common environmental pollutants, nitroaromatic compounds (NACs) are of particular interest because of their durability and toxicity. That’s why, sensitive and selective detection of small amounts of nitroaromatic explosives, in particular, 2,4,6-trinitrophenol (TNP), 2,4-dinitrotoluene (DNT) and 2,4,6-trinitrotoluene (TNT) has been a critical challenge due to the increasing threat of explosive-based terrorism and the need of environmental monitoring of drinking and waste water. In addition, the excessive utilization of TNP in several other areas such as burn ointment, pesticides, glass and the leather industry resulted in environmental accumulation, and is eventually contaminating the soil and aquatic systems. To the date, high number of elegant methods, including fluorimetry, gas chromatography, mass, ion-mobility and Raman spectrometry have been successfully applied for explosive detection. Among these efforts, fluorescence-quenching methods based on the mechanism of FRET show good assembly flexibility, high selectivity and sensitivity. Here, we report a FRET-based sensor system for the highly selective detection of NACs, such as TNP, DNT and TNT. The sensor system is composed of a copolymer Poly [(N,N-dimethylacrylamide)-co-(Boc-Trp-EMA)] (RP) bearing tryptophan derivative in the side chain as donor and dansyl tagged copolymer P(MMA-co-Dansyl-Ala-HEMA) (DCP) as an acceptor. Initially, the inherent fluorescence of RP copolymer is quenched by non-radiative energy transfer to DCP which only happens once the two molecules are within Förster critical distance (R0). The excellent spectral overlap (Jλ= 6.08×10¹⁴ nm⁴M⁻¹cm⁻¹) between donors’ (RP) emission profile and acceptors’ (DCP) absorption profile makes them an exciting and efficient FRET pair i.e. further confirmed by the high rate of energy transfer from RP to DCP i.e. 0.87 ns⁻¹ and lifetime measurement by time correlated single photon counting (TCSPC) to validate the 64% FRET efficiency. This FRET pair exhibited a specific fluorescence response to NACs such as DNT, TNT and TNP with 5.4, 2.3 and 0.4 µM LODs, respectively. The detection of NACs occurs with high sensitivity by photoluminescence quenching of FRET signal induced by photo-induced electron transfer (PET) from electron-rich FRET pair to electron-deficient NAC molecules. The estimated stern-volmer constant (KSV) values for DNT, TNT and TNP are 6.9 × 10³, 7.0 × 10³ and 1.6 × 104 M⁻¹, respectively. The mechanistic details of molecular interactions are established by time-resolved fluorescence, steady-state fluorescence and absorption spectroscopy confirmed that the sensing process is of mixed type, i.e. both dynamic and static quenching as lifetime of FRET system (0.73 ns) is reduced to 0.55, 0.57 and 0.61 ns DNT, TNT and TNP, respectively. In summary, the simplicity and sensitivity of this novel FRET sensor opens up the possibility of designing optical sensor of various NACs in one single platform for developing multimodal sensor for environmental monitoring and future field based study.

Keywords: FRET, nitroaromatic, stern-Volmer constant, tryptophan and dansyl tagged copolymer

Procedia PDF Downloads 136

Authors: R. Pardo, P. Menendez, MA Gil-Olarte, S. Sanchez, E. García, R. Quintana, J. Martín

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Introduction : Within oncoplastic breast techniques there is increased interest in immediate partial breast reconstruction. The volume resected is greater than that of conventional conservative techniques. Central tumours of the breast have classically been treated with a mastectomy with regard to oncological safety and cosmetic secondary effects after wide central resection of the nipple and breast tissue beneath. Oncological results for central quadrantectomy have a recurrence level, disease- free period and survival identical to mastectomy. Grissoti flap is an oncoplastic surgical technique that allows the surgeon to perform a safe central quadrantectomy with excellent cosmetic results. Material and methods: The Grissoti flap is a glandular cutaneous advancement rotation flap that can fill the defect in the central portion of the excised breast. If the inferior border is affected by tumour and further surgery is decided upon at the Multidisciplinary Team Meeting, it will be necessary to perform a mastectomy. All patients with a Grisotti flap undergoing surgery since 2009 were reviewed obtaining the following data: age, hystopathological diagnosis, size, operating time, volume of tissue resected, postoperative admission time, re-excisions due to positive margins affected by tumour, wound dehiscence, complications and recurrence. Analysis and results of sentinel node biopsy were also obtained. Results: 12 patients underwent surgery between 2009-2015. The mean age was 54 years (34-67) . All had a preoperative diagnosis of ductal infiltrative carcinoma of less than 2 cm,. Diagnosis was made with Ultrasound, Mamography or both . Magnetic resonance was used in 5 cases. No patients had preoperative positive axilla after ultrasound exploration. Mean operating time was 104 minutes (84-130). Postoperative stay was 24 hours. Mean volume resected was 159 cc (70-286). In one patient the surgical border was affected by tumour and a further procedure with resection of the affected border was performed as ambulatory surgery. The sentinel node biopsy was positive for micrometastasis in only two cases. In one case lymphadenectomy was performed in 2009. In the other, treated in 2015, no lymphadenectomy was performed as the patient had a favourable histopathological prognosis and the multidisciplinary team meeting agreed that lymphadenectomy was not required. No recurrence has been diagnosed in any of the patients who underwent surgery and they are all disease free at present. Conclusions: Conservative surgery for retroareolar central tumours of the breast results in good local control of the disease with free surgical borders, including resection of the nipple areola complex and pectoral major muscle fascia. Reconstructive surgery with the inferior Grissoti flap adequately fills the defect after central quadrantectomy with creation of a new cutaneous disc where a new nipple areola complex is reconstructed with a local flap or micropigmentation. This avoids the need for contralateral symmetrization. Sentinel Node biopsy can be performed without added morbidity. When feasible, the Grissoti flap will avoid skin-sparing mastectomy for central breast tumours that will require the use of an expander, prosthesis or myocutaneous flap, with all the complications of a more complex operation.

Keywords: Grisotti flap, oncoplastic surgery, central tumours, breast

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition

Procedia PDF Downloads 123

Authors: Anusha Jain, Santosh Vishwanathan, Praveen K. Gupta, Shwetha S., Kavitha S. N.

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Agriculture has a major impact on the Indian economy, with the highest employment ratio than any sector of the country. Currently, most of the traditional agricultural practices and farming methods are manual, which results in farmers not realizing their maximum productivity often due to increasing in labour cost, inefficient use of water sources leading to wastage of water, inadequate soil moisture content, subsequently leading to food insecurity of the country. This research paper aims to solve this problem by developing a full-fledged web application-based platform that has the capacity to associate itself with a Microcontroller-based Automated Irrigation System which schedules the irrigation of crops based on real-time soil moisture content employing soil moisture sensors centric to the crop’s requirements using WSN (Wireless Sensor Networks) and M2M (Machine To Machine Communication) concepts, thus optimizing the use of the available limited water resource, thereby maximizing the crop yield. This robust automated irrigation system provides end-to-end automation of Irrigation of crops at any circumstances such as droughts, irregular rainfall patterns, extreme weather conditions, etc. This platform will also be capable of achieving a nationwide united farming community and ensuring the welfare of farmers. This platform is designed to equip farmers with prerequisite knowledge on tech and the latest farming practices in general. In order to achieve this, the MailChimp mailing service is used through which interested farmers/individuals' email id will be recorded and curated articles on innovations in the world of agriculture will be provided to the farmers via e-mail. In this proposed system, service is enabled on the platform where nearby crop vendors will be able to enter their pickup locations, accepted prices and other relevant information. This will enable farmers to choose their vendors wisely. Along with this, we have created a blogging service that will enable farmers and agricultural enthusiasts to share experiences, helpful knowledge, hardships, etc., with the entire farming community. These are some of the many features that the platform has to offer.

Keywords: WSN (wireless sensor networks), M2M (M/C to M/C communication), automation, irrigation system, sustainability, SAAS (software as a service), soil moisture sensor

Procedia PDF Downloads 131