Search results for: sensors and actuators faults

Authors: Atef Alaaeddine Sarraj, Brendan Jackman, Frank Walsh

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Tomorrow’s car will be more automated and increasingly connected. Innovative and intuitive interfaces are essential to accompany this functional enrichment. For that, today the automotive companies are competing to offer an advanced driver assistance system (ADAS) which will be able to provide enhanced navigation, collision avoidance, intersection support and lane keeping. These vision-based functions require an accurately calibrated camera. To achieve such differentiation in ADAS requires sophisticated sensors and efficient algorithms. This paper explores the different calibration methods applicable to vehicle-mounted fish-eye cameras with arbitrary fields of view and defines the first steps towards a self-calibration method that adequately addresses ADAS requirements. In particular, we present a self-calibration method after comparing different camera calibration algorithms in the context of ADAS requirements. Our method gathers data from unknown scenes while the car is moving, estimates the camera intrinsic and extrinsic parameters and corrects the wide-angle distortion. Our solution enables continuous and real-time detection of objects, pedestrians, road markings and other cars. In contrast, other camera calibration algorithms for ADAS need pre-calibration, while the presented method calibrates the camera without prior knowledge of the scene and in real-time.

Keywords: advanced driver assistance system (ADAS), fish-eye, real-time, self-calibration

Procedia PDF Downloads 252

Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha

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Catecholamines are vital neurotransmitters that mediate a variety of central nervous system functions, such as motor control, cognition, emotion, memory processing, and endocrine modulation. Dysfunctions in catecholamine neurotransmission are induced in some neurologic and neuropsychiatric diseases. Changeable neurotransmitters level in biological fluids can be a marker of several neurological disorders. Because of its significance in analytical techniques and diagnostics, sensitive and selective detection of neurotransmitters is increasingly attracting a lot of attention in different areas of bio-analysis or biomedical research. Recently, optical techniques for the detection of catecholamines have attracted interests due to their reasonable cost, convenient control, as well as maneuverability in biological environments. Nevertheless, with the observed need for a sensitive and selective catecholamines sensor, the development of a convenient method for this neurotransmitter is still at its basic level. The manipulation of nanostructured materials in conjunction with biological molecules has led to the development of a new class of hybrid-modified enzymatic sensors in which both enhancement of charge transport and biological activity preservation may be obtained. Immobilization of biomaterials on electrode surfaces is the crucial step in fabricating electrochemical as well as optical biosensors and bioelectronic devices. Continuing systematic investigation in manufacturing of enzyme–conducting sensitive systems, here is presented a convenient fluorescence as well as electrochemical sensing strategy for catecholamines detection.

Keywords: biosensors, catecholamines, fluorescence, enzymes

Procedia PDF Downloads 113

Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah

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Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Keywords: detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter

Procedia PDF Downloads 393

Authors: Adeniyi Onasanya, Maher Elshakankiri

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In recent years, the Internet of Things (IoT) has constituted a driving force of modern technological advancement, and it has become increasingly common as its impacts are seen in a variety of application domains, including healthcare. IoT is characterized by the interconnectivity of smart sensors, objects, devices, data, and applications. With the unprecedented use of IoT in industrial, commercial and domestic, it becomes very imperative to harness the benefits and functionalities associated with the IoT technology in (re)assessing the provision and positioning of healthcare to ensure efficient and improved healthcare delivery. In this research, we are focusing on two important services in healthcare systems, which are cancer care services and business analytics/cloud services. These services incorporate the implementation of an IoT that provides solution and framework for analyzing health data gathered from IoT through various sensor networks and other smart devices in order to improve healthcare delivery and to help health care providers in their decision-making process for enhanced and efficient cancer treatment. In addition, we discuss the wireless sensor network (WSN), WSN routing and data transmission in the healthcare environment. Finally, some operational challenges and security issues with IoT-based healthcare system are discussed.

Keywords: IoT, smart health care system, business analytics, (wireless) sensor network, cancer care services, cloud services

Procedia PDF Downloads 178

Authors: Liqian Li, Yu Liu, Karen Colins

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The dose rate present in a seriously contaminated area can be indirectly determined by monitoring radiation damage to inexpensive commercial electronics, instead of deploying expensive radiation hardened sensors. EEPROMs (Electrically Erasable Read Only Memories) are a good candidate for this purpose because they are inexpensive and are sensitive to radiation exposure. When the total ionizing dose threshold is reached, an EEPROM chip will show signs of damage that can be monitored and transmitted by less susceptible electronics. The dose rate can then be determined from the known threshold dose and the exposure time, assuming the radiation field remains constant with time. Therefore, the threshold dose needs to be well understood before this method can be used. There are many factors affecting the threshold dose, such as the gamma ray energy spectrum, the operating voltage, etc. The purpose of this study was to experimentally determine how the threshold dose depends on dose rate, temperature, voltage, and duty factor. It was found that the duty factor has the strongest effect on the total ionizing dose threshold, while the effect of the other three factors that were investigated is less significant. The effect of temperature was found to be opposite to that expected to result from annealing and is yet to be understood.

Keywords: EEPROM, ionizing radiation, radiation effects on electronics, total ionizing dose, wireless sensor networks

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

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Authors: Nuray Ucar, Pelin Altay, Ilkay Ozsev Yuksek

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Graphene oxide fibers have recently received increasing attention due to their excellent properties such as high specific surface area, high mechanical strength, good thermal properties and high electrical conductivity. They have shown notable potential in various applications including batteries, sensors, filtration and separation and wearable electronics. Carbon nanotubes (CNTs) have unique structural, mechanical, and electrical properties and can be used together with graphene oxide fibers for several application areas such as lithium ion batteries, wearable electronics, etc. Metals salts that can be converted into metal ions and metal oxide can be also used for several application areas such as battery, purification natural gas, filtration, absorption. This study investigates the effects of CNT and metal complex compounds (MnCl₂, metal salts) on the morphological structure of graphene oxide fibers. The graphene oxide dispersion was manufactured by modified Hummers method, and continuous graphene oxide fibers were produced with wet spinning. The CNT and MnCl₂ were incorporated into the coagulation baths during wet spinning process. Produced composite continuous fibers were analyzed with SEM, SEM-EDS and AFM microscopies and as spun fiber counts were measured.

Keywords: continuous graphene oxide fiber, Hummers' method, CNT, MnCl₂

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Authors: Yo-Sheng Lin, Run-Chi Liu, Chien-Chu Ji, Chih-Chung Chen, Chien-Chin Wang

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A W-band double-balanced mixer for direct up-conversion using standard 90 nm CMOS technology is reported. The mixer comprises an enhanced double-balanced Gilbert cell with PMOS negative resistance compensation for conversion gain (CG) enhancement and current injection for power consumption reduction and linearity improvement, a Marchand balun for converting the single LO input signal to differential signal, another Marchand balun for converting the differential RF output signal to single signal, and an output buffer amplifier for loading effect suppression, power consumption reduction and CG enhancement. The mixer consumes low power of 6.9 mW and achieves LO-port input reflection coefficient of -17.8~ -38.7 dB and RF-port input reflection coefficient of -16.8~ -27.9 dB for frequencies of 90~100 GHz. The mixer achieves maximum CG of 3.6 dB at 95 GHz, and CG of 2.1±1.5 dB for frequencies of 91.9~99.4 GHz. That is, the corresponding 3 dB CG bandwidth is 7.5 GHz. In addition, the mixer achieves LO-RF isolation of 36.8 dB at 94 GHz. To the authors’ knowledge, the CG, LO-RF isolation and power dissipation results are the best data ever reported for a 94 GHz CMOS/BiCMOS up-conversion mixer.

Keywords: CMOS, W-band, up-conversion mixer, conversion gain, negative resistance compensation, output buffer amplifier

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

Procedia PDF Downloads 133

Authors: Chih-Hsing Lin, Wen-Ching Chen, Chih-Ting Kuo, Gang-Neng Sung, Chih-Chyau Yang, Chien-Ming Wu, Chun-Ming Huang

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This paper proposes a cellular-based structure health monitoring device (HMD) for temporary bridge monitoring without the requirement of power line and internet service. The proposed HMD includes sensor node, power module, cellular gateway, and rechargeable batteries. The purpose of HMD focuses on short-term collection of civil infrastructure information. It achieves the features of low cost by using three 1-axis accelerometers with data synchronization problem being solved. Furthermore, instead of using data acquisition system (DAQ) sensed data is transmitted to Host through cellular gateway. Compared with 3-axis accelerometer, our proposed 1-axis accelerometers based device achieves 50.5% cost saving with high sensitivity 2000mv/g. In addition to fit different monitoring environments, the proposed system can be easily replaced and/or extended with different PCB boards, such as communication interfaces and sensors, to adapt to various applications. Therefore, with using the proposed device, the real-time diagnosis system for civil infrastructure damage monitoring can be conducted effectively.

Keywords: cellular-based structural health monitoring, cost-effective 1-axis accelerometers, short-term monitoring, structural engineering

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Sanjeet Patra, Soham Roychowdhury

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In recent times, functionally graded dielectric elastomer (FGDE) has gained significant attention within the realm of soft actuation due to its dual capacity to exert highly localized stresses while maintaining its compliant characteristics on application of electro-mechanical loading. Nevertheless, the full potential of dielectric elastomer (DE) has not been fully explored due to their susceptibility to instabilities when subjected to electro-mechanical loads. As a result, study and analysis of such instabilities becomes crucial for the design and realization of dielectric actuators. Prismatic bifurcation is a type of instability that has been recognized in a DE tube. Though several studies have reported on the analysis for prismatic bifurcation in an isotropic DE tube, there is an insufficiency in studies related to prismatic bifurcation of FGDE tubes. Therefore, this paper aims to determine the onset of prismatic bifurcations on an incompressible FGDE tube when subjected to electrical loading across the thickness of the tube and internal pressurization. The analysis has been conducted by imposing two axial boundary conditions on the tube, specifically axially free ends and axially clamped ends. Additionally, the rigidity modulus of the tube has been linearly graded in the direction of thickness where the inner surface of the tube has a lower stiffness than the outer surface. The static equilibrium equations for deformation of the axisymmetric tube are derived and solved using numerical technique. The condition for prismatic bifurcation of the axisymmetric static equilibrium solutions has been obtained by using the linearized incremental constitutive equations. Two modes of bifurcations, corresponding to two different non-circular cross-sectional geometries, have been explored in this study. The outcomes reveal that the FGDE tubes experiences prismatic bifurcation before the Hessian criterion of failure is satisfied. It is observed that the lower mode of bifurcation can be triggered at a lower critical voltage as compared to the higher mode of bifurcation. Furthermore, the tubes with larger stiffness gradient require higher critical voltages for triggering the bifurcation. Moreover, with the increase in stiffness gradient, a linear variation of the critical voltage is observed with the thickness of the tube. It has been found that on applying internal pressure to a tube with low thickness, the tube becomes less susceptible to bifurcations. A thicker tube with axially free end is found to be more stable than the axially clamped end tube at higher mode of bifurcation.

Keywords: critical voltage, functionally graded dielectric elastomer, linearized incremental approach, modulus of rigidity, prismatic bifurcation

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Authors: Tolga Arda Eraslan

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The quality of the indoor environment is significant to occupants’ health, comfort, and productivity, as Covid-19 spread throughout the world, people started spending most of their time indoors. Since buildings are getting bigger, mechanical ventilation systems are widely used where natural ventilation is insufficient. Four primary tasks of a ventilation system have been identified indoor air quality, comfort, contamination control, and energy performance. To fulfill such requirements, air diffusers, which are a part of the ventilation system, have begun to enter our lives in different airflow distribution systems. Detailed observations are needed to assure that such devices provide high levels of comfort effectiveness and energy efficiency. This study addresses these needs. The objective of this article is to observe air characterizations of different air diffusers at different angles and their effect on people by the thermal comfort model in CFD simulation and to validate the outputs with the help of data results based on a simulated office room. Office room created to provide validation; Equipped with many thermal sensors, including head height, tabletop, and foot level. In addition, CFD simulations were carried out by measuring the temperature and velocity of the air coming out of the supply diffuser. The results considering the flow interaction between diffusers and surroundings showed good visual illustration.

Keywords: computational fluid dynamics, fanger’s model, predicted mean vote, thermal comfort

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Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

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Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

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Authors: Ka Hin Kevin Lee, Jacob Lindh, Yue Qing LI

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The biomechanics of golf swing performance are increasingly being investigated to better understand the relationship between gender and equipment choices. Gender-based variations in swing mechanics, particularly wrist kinematics, are thought to have a substantial influence on performance. While current studies show gender differences in wrist motions and the impact of club selection, there is little study on amateur collegiate golfers. This demography provides a unique perspective, spanning professional and leisure activity and providing significant biomechanical aspects. This study looks into gender differences in wrist kinematics during golf swings, specifically angular velocities (yaw, pitch, and roll) and the impact of club choice. Ten undergraduate golfers (five male and five female) took part in the study, each doing five swings with a 7-iron and a driver. Participants used their own clubs to guarantee familiarity and minimize variation. Xsens MTw Awinda wireless motion sensors were mounted on their forearms and wrists, gathering high-resolution motion data at 100 Hz. A thorough calibration procedure was used to synchronise sensor data with individual stances. The trial replicated real-world playing settings, with players told to take full-power swings. Data were processed and analysed in MATLAB, with angular velocity profiles extracted for each swing.

Keywords: biomechanics, sports, performance, gender, wrist, kinematics

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Authors: Xi Wang, Xiaoming Tao, Raymond C. H. So

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As one of the convenient and noninvasive sensing approaches, the automatic limb girth measurement has been applied to detect intention behind human motion from muscle deformation. The sensing validity has been elaborated by preliminary researches but still need more fundamental study, especially on kinetic contraction modes. Based on the novel fabric strain sensors, a soft and smart limb girth measurement system was developed by the authors’ group, which can measure the limb girth in-motion. Experiments were carried out on elbow isometric flexion and elbow isokinetic flexion (biceps’ isokinetic contractions) of 90°/s, 60°/s, and 120°/s for 10 subjects (2 canoeists and 8 ordinary people). After removal of natural circumferential increments due to elbow position, the joint torque is found not uniformly sensitive to the limb circumferential strains, but declining as elbow joint angle rises, regardless of the angular speed. Moreover, the maximum joint torque was found as an exponential function of the joint’s angular speed. This research highly contributes to the application of the automatic limb girth measuring during kinetic contractions, and it is useful to predict the contraction level of voluntary skeletal muscles.

Keywords: fabric strain sensor, muscle deformation, isokinetic contraction, joint torque, limb girth strain

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Authors: Ashok E. Kalange

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Diagnosis according to Ayurveda is to find the root cause of a disease. Out of the eight different kinds of examinations, Nadi-Pariksha (pulse examination) is important. Nadi-Pariksha is done at the root of the thumb by examining the radial artery using three fingers. Ancient Ayurveda identifies the health status by observing the wrist pulses in terms of 'Vata', 'Pitta' and 'Kapha', collectively called as tridosha, as the basic elements of human body and in their combinations. Diagnosis by traditional pulse analysis – NadiPariksha - requires a long experience in pulse examination and a high level of skill. The interpretation tends to be subjective, depending on the expertise of the practitioner. Present work is part of the efforts carried out in making Nadi-Parikshan objective. Nadi Parikshan Yantra (three point pulse examination system) is developed in our laboratory by using three pressure sensors (one each for the Vata, Pitta and Kapha points on radial artery). The radial pulse data was collected of a large number of subjects. The radial pulse data collected is analyzed on the basis of relative amplitudes of the three point pulses as well as in frequency and time domains. The same subjects were examined by Ayurvedic physician (Nadi Vaidya) and the dominant Dosha - Vata, Pitta or Kapha - was identified. The results are discussed in details in the paper.

Keywords: Nadi Parikshan Yantra, Tridosha, Nadi Pariksha, human pulse data analysis

Procedia PDF Downloads 190

Authors: Nozar Kishi, Babak Kamrani, Filmon Habte

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Natural hazards such as earthquakes and tropical storms, are very frequent and highly destructive in Japan. Japan experiences, every year on average, more than 10 tropical cyclones that come within damaging reach, and earthquakes of moment magnitude 6 or greater. We have developed stochastic catastrophe models to address the risk associated with the entire suite of damaging events in Japan, for use by insurance, reinsurance, NGOs and governmental institutions. KCC’s (Karen Clark and Company) catastrophe models are procedures constituted of four modular segments: 1) stochastic events sets that would represent the statistics of the past events, hazard attenuation functions that could model the local intensity, vulnerability functions that would address the repair need for local buildings exposed to the hazard, and financial module addressing policy conditions that could estimates the losses incurring as result of. The events module is comprised of events (faults or tracks) with different intensities with corresponding probabilities. They are based on the same statistics as observed through the historical catalog. The hazard module delivers the hazard intensity (ground motion or wind speed) at location of each building. The vulnerability module provides library of damage functions that would relate the hazard intensity to repair need as percentage of the replacement value. The financial module reports the expected loss, given the payoff policies and regulations. We have divided Japan into regions with similar typhoon climatology, and earthquake micro-zones, within each the characteristics of events are similar enough for stochastic modeling. For each region, then, a set of stochastic events is developed that results in events with intensities corresponding to annual occurrence probabilities that are of interest to financial communities; such as 0.01, 0.004, etc. The intensities, corresponding to these probabilities (called CE, Characteristics Events) are selected through a superstratified sampling approach that is based on the primary uncertainty. Region specific hazard intensity attenuation functions followed by vulnerability models leads to estimation of repair costs. Extensive economic exposure model addresses all local construction and occupancy types, such as post-linter Shinand Okabe wood, as well as concrete confined in steel, SRC (Steel-Reinforced Concrete), high-rise.

Keywords: typhoon, earthquake, Japan, catastrophe modelling, stochastic modeling, stratified sampling, loss model, ERM

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Authors: Bilal Arshad, Johan Barthelemy, Elliott Pilton, Pascal Perez

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Getting reliable, informative, and up-to-date information about the location, mobility, and behavioural patterns of animals will enhance our ability to research and preserve biodiversity. The fusion of infra-red sensors and camera traps offers an inexpensive way to collect wildlife data in the form of images. However, extracting useful data from these images, such as the identification and counting of animals remains a manual, time-consuming, and costly process. In this paper, we demonstrate that such information can be automatically retrieved by using state-of-the-art deep learning methods. Another major challenge that ecologists are facing is the recounting of one single animal multiple times due to that animal reappearing in other images taken by the same or other camera traps. Nonetheless, such information can be extremely useful for tracking wildlife and understanding its behaviour. To tackle the multiple count problem, we have designed a meshed network of camera traps, so they can share the captured images along with timestamps, cumulative counts, and dimensions of the animal. The proposed method takes leverage of edge computing to support real-time tracking and monitoring of wildlife. This method has been validated in the field and can be easily extended to other applications focusing on wildlife monitoring and management, where the traditional way of monitoring is expensive and time-consuming.

Keywords: computer vision, ecology, internet of things, invasive species management, wildlife management

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Authors: Shyam Ranjan Kumar, Shashikant Rajpal

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Zinc Telluride (ZnTe) is a binary II-VI direct band gap semiconducting material. This semiconducting material has several applications in sensors, photo-electrochemical devices and photovoltaic solar cell. In this study, Zinc telluride (ZnTe) thin films were deposited on nickel substrate by electrodeposition technique using potentiostat/galvanostat at -0.85 V using AR grade of Zinc Chloride (ZnCl2), Tellurium Tetrachloride (TeCl4) in non-aqueous bath. The developed films were physically stable and showed good adhesion. The as deposited ZnTe films were annealed at 400ºC in air. The solid state properties and optical properties of the as deposited and annealed films were carried out by XRD, EDS, SEM, AFM, UV–Visible spectrophotometer, and photoluminescence spectrophotometer. The diffraction peak observed at 2θ = 49.58° with (111) plane indicate the crystalline nature of ZnTe film. Annealing improves the crystalline nature of the film. Compositional analysis reveals the presence of Zn and Te with tellurium rich ZnTe film. SEM photograph at 10000X shows that grains of film are spherical in nature and densely distributed over the surface. The average roughness of the film is measured by atomic force microscopy and it is nearly equal to 60 nm. The direct wide band gap of 2.12 eV is observed by UV-Vis spectroscopy. Luminescence peak of the ZnTe films are also observed in as deposited and annealed case.

Keywords: annealing, electrodeposition, optical properties, thin film, XRD, ZnTe

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Authors: Tugbanur Ozen Balaban, Gultekin Tarcan, Unsal Gemici, Mumtaz Colak, I. Hakki Karamanderesi

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Buyuk Menderes Graben is located in the Western Anatolia (Turkey). The graben has become the largest industrial and agricultural area with a total population exceeding 3.000.000. There are two big cities within the study areas from west to east as Aydın and Denizli. The study area is very rich with regard to cold ground waters and thermal waters. Electrical production using geothermal potential has become very popular in the last decades in this area. Buyuk Menderes Graben is a tectonically active extensional region and is undergoing a north–south extensional tectonic regime which commenced at the latest during Early Middle Miocene period. The basement of the study area consists of Menderes massif rocks that are made up of high-to low-grade metamorphics and they are aquifer for both cold ground waters and thermal waters depending on the location. Neogene terrestrial sediments, which are mainly composed by alluvium fan deposits unconformably cover the basement rocks in different facies have very low permeability and locally may act as cap rocks for the geothermal systems. The youngest unit is Quaternary alluvium which is the shallow regional aquifer consists of Holocene alluvial deposits in the study area. All the waters are of meteoric origin and reflect shallow or deep circulation according to the 8O, 2H and 3H contents. Meteoric waters move to deep zones by fractured system and rise to the surface along the faults. Water samples (drilling well, spring and surface waters) and local seawater were collected between 2010 and 2012 years. Geochemical modeling was calculated distribution of the aqueous species and exchange processes by using PHREEQCi speciation code. Geochemical analyses show that cold ground water types are evolving from Ca–Mg–HCO3 to Na–Cl–SO4 and geothermal aquifer waters reflect the water types of Na-Cl-HCO3 in Aydın. Water types of Denizli are Ca-Mg-HCO3 and Ca-Mg-HCO3-SO4. Thermal water types reflect generally Na-HCO3-SO4. The B versus Cl rates increase from east to west with the proportion of seawater introduced into the fresh water aquifers and geothermal reservoirs. Concentrations of some elements (As, B, Fe and Ni) are higher than the tolerance limit of the drinking water standard of Turkey (TS 266) and international drinking water standards (WHO, FAO etc).

Keywords: Buyuk Menderes, isotope chemistry, geochemical modelling, water quality

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Authors: Mrinmoy Dhara, Vivek K. Sengar, Shovan L. Chattoraj, Soumiya Bhattacharjee

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Remote sensing techniques have emerged as an asset for various geological studies. Satellite images obtained by different sensors contain plenty of information related to the terrain. Digital image processing further helps in customized ways for the prospecting of minerals. In this study, an attempt has been made to map the hydrothermally altered zones using multispectral and hyperspectral datasets of South East Rajasthan. Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) and Hyperion (Level1R) dataset have been processed to generate different Band Ratio Composites (BRCs). For this study, ASTER derived BRCs were generated to delineate the alteration zones, gossans, abundant clays and host rocks. ASTER and Hyperion images were further processed to extract mineral end members and classified mineral maps have been produced using Spectral Angle Mapper (SAM) method. Results were validated with the geological map of the area which shows positive agreement with the image processing outputs. Thus, this study concludes that the band ratios and image processing in combination play significant role in demarcation of alteration zones which may provide pathfinders for mineral prospecting studies.

Keywords: ASTER, hyperion, band ratios, alteration zones, SAM

Procedia PDF Downloads 280

Authors: Tanveer Hussain, Khan Muhammad, Amin Ullah, Mi Young Lee, Sung Wook Baik

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The Big Data generated from distributed vision sensors installed on large scale in smart cities create hurdles in its efficient and beneficial exploration for browsing, retrieval, and indexing. This paper presents a three-folded framework for effective video summarization of such data and provide a compact and representative format of Big Video Data. In the first fold, the paper acquires input video data from the installed cameras and collect clues such as type and count of objects and clarity of the view from a chunk of pre-defined number of frames of each view. The decision of representative view selection for a particular interval is based on fuzzy inference system, acquiring a precise and human resembling decision, reinforced by the known clues as a part of the second fold. In the third fold, the paper forwards the selected view frames to the summary generation mechanism that is supported by a saliency-aware convolution neural network (CNN) model. The new trend of fuzzy rules for view selection followed by CNN architecture for saliency computation makes the multi-view video summarization (MVS) framework a suitable candidate for real-world practice in smart cities.

Keywords: big video data analysis, fuzzy logic, multi-view video summarization, saliency detection

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Authors: S. Palaniyappan, P. K. Chennam, M. Trautmann, H. Ahmad, T. Mehner, T. Lampke, G. Wagner

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In structural-health monitoring of fiber reinforced plastics (FRPs), every single inorganic fiber sensor that are integrated into the bulk material requires an electrical insulation around itself, when the surrounding reinforcing fibers are electrically conductive. This results in a more accurate data acquisition only from the sensor fiber without any electrical interventions. For this purpose, thin nano-films of aluminium oxide (Al₂O₃)-based electrical-insulation coatings have been fabricated around the Silicon Carbide (SiC) single fiber sensors through reactive DC magnetron sputtering technique. The sputtered coatings were amorphous in nature and the thickness of the coatings increased with an increase in the sputter time. Microstructural characterization of the coated fibers performed using scanning electron microscopy (SEM) confirmed a homogeneous circumferential coating with no detectable defects or cracks on the surface. X-ray diffraction (XRD) analyses of the as-sputtered and 2 hours annealed coatings (825 & 1125 ˚C) revealed the amorphous and crystalline phases of Al₂O₃ respectively. Raman spectroscopic analyses produced no characteristic bands of Al₂O₃, as the thickness of the films was in the nanometer (nm) range, which is too small to overcome the actual penetration depth of the laser used. In addition, the influence of the insulation coatings on the mechanical properties of the SiC sensor fibers has been analyzed.

Keywords: Al₂O₃ thin film, electrical insulation coating, PVD process, SiC fibre, single fibre tensile test

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Authors: Mikhail O. Eremin

Abstract:

Seismic activity around the world is clearly a threat to people's lives, as well as infrastructure and capital construction. It is the instability of the latter to powerful earthquakes that most often causes human casualties. Therefore, during construction it is necessary to take into account the risks of large-scale natural disasters. The task of assessing the risks of natural disasters is one of the most urgent at the present time. The final goal of any study of earthquakes is forecasting. This is especially important for seismically active regions of the planet where earthquakes occur frequently. Gorni Altai is one of such regions. In work, we developed the physical-mathematical model of stress-strain state evolution of loaded geomedium with the purpose of numerical simulation of seismic process accompanying the formation of Chuya-Kuray fault zone Gorni Altay, Russia. We build a structural model on the base of seismotectonic and paleoseismogeological investigations, as well as SRTM-data. Base of mathematical model is the system of equations of solid mechanics which includes the fundamental conservation laws and constitutive equations for elastic (Hooke's law) and inelastic deformation (modified model of Drucker-Prager-Nikolaevskii). An initial stress state of the model correspond to gravitational. Then we simulate an activation of a buried dextral strike-slip paleo-fault located in the basement of the model. We obtain the stages of formation and the structure of Chuya-Kuray fault zone. It is shown that results of numerical simulation are in good agreement with field observations in statistical sense. Simulated seismic process is strongly bound to the faults - lineaments with high degree of inelastic strain localization. Fault zone represents en-echelon system of dextral strike-slips according to the Riedel model. The system of surface lineaments is represented with R-, R'-shear bands, X- and Y-shears, T-fractures. Simulated seismic process obeys the laws of Gutenberg-Richter and Omori. Thus, the model describes a self-similar character of deformation and fracture of rocks and geomedia. We also modified the algorithm of determination of separate slip events in the model due to the features of strain rates dependence vs time.

Keywords: Drucker-Prager model, fault zone, numerical simulation, Riedel bands, seismic process, strike-slip fault

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Authors: Ghada Ben Brahim, Aicha El Rabia, Mohamed Hedi Inoubli

Abstract:

Climate change has exacerbated disparities in the distribution of water resources in Tunisia, resulting in significant degradation in quantity and quality over the past five decades. The Mio-Plio-Quaternary aquifer, the primary water source in the Zarzis region, is subject to climatic, geographical, and geological challenges, as well as human stress. The region is experiencing uneven distribution and growing threats from groundwater salinity and saltwater intrusion. Addressing this challenge is critical for the arid region’s socioeconomic development, and effective water resource management is required to combat climate change and reduce water deficits. This study uses a multidisciplinary approach to determine the groundwater potential of this aquifer, involving geophysics and hydrogeology data analysis. We used advanced techniques such as 3D Euler deconvolution and power spectrum analysis to generate detailed anomaly maps and estimate the depths of density sources, identifying significant Bouguer anomalies trending E-W, NW-SE, and NE-SW. Various techniques, such as wavelength filtering, upward continuation, and horizontal and vertical derivatives, were used to improve the gravity data, resulting in consistent results for anomaly shapes and amplitudes. The Euler deconvolution method revealed two prominent surface faults, trending NE-SW and NW-SE, that have a significant impact on the distribution of sedimentary facies and water quality within the Mio-Plio-Quaternary aquifer. Additionally, depth maxima greater than 1400 m to the North indicate the presence of a Cretaceous paleo-fault. Geoelectrical models and resistivity pseudo-sections were used to interpret the distribution of electrical facies in the Mio-Plio-Quaternary aquifer, highlighting lateral variation and depositional environment type. AI optimises the analysis and interpretation of exploration data, which is important to long-term management and water security. Machine learning algorithms and deep learning models analyse large datasets to provide precise interpretations of subsurface conditions, such as aquifer salinisation. However, AI has limitations, such as the requirement for large datasets, the risk of overfitting, and integration issues with traditional geological methods.

Keywords: mio-plio-quaternary aquifer, Southeastern Tunisia, geophysical methods, hydrogeological analysis, artificial intelligence

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Authors: Rajkumar Ghosh

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Jhakri Thrust (JT) coeval of Sarahan Thrust (ST) was later considered to be part of Chaura Thrust (CT). The Main Central Thrust (MCT) delimits the southern extreme of Higher Himalaya, whereas the northern boundary defines by South Tibetan Detachment System (STDS). STDS is parallel set of north dipping extensional faults. The activation timing of MCT and STDS. MCT activated in two parts (MCT-L during 15- 0.7 Ma, and MCT-U during 25-14 Ma). Similarly, STDS triggered in two parts (STDS-L during 24-12 Ma, and STDS-U during 19-14 Ma). The activation ages for MBT and MFT. Besides, the MBT occurred during 11-9 Ma, and MFT followed as <2.5 Ma. There are two mylonitised zones (zone of S-C fabric) found under the microscope. Dynamic and bulging recrystallization and sub-grain formation was documented under the optical microscope from samples collected from these zones. The varieties of crenulated schistosity are shown in photomicrographs. In a rare and uncommon case, crenulation cleavage and sigmoid Muscovite were found together side-by-side. Recrystallized quartzo-feldspathic grains exist in between crenulation cleavages. These thin-section studies allow three possible hypotheses for such variations in crenulation cleavages. S/SE verging meso- and micro-scale box folds around Chaura might be a manifestation of some structural upliftment. Near Chaura, kink folds are visible. Prominent asymmetric shear sense indicators in augen mylonite are missing in meso-scale but dominantly present under the microscope. The main foliation became steepest (range of dip ~ 65 – 80 º) at this place. The aim of this section is to characterize the box fold and its signature in the regional geology of Himachal Himalaya. Grain Boundary Migration (GBM) associated temperature range (400–750 ºC) from microstructural studies in grain scale along Jhakri-Wangtu transect documented. Oriented samples were collected from the Jhakri-Chaura transect at a regular interval of ~ 1km for strain analysis. The Higher Himalayan Out-of-Sequence Thrust (OOST) in Himachal Pradesh is documented a decade ago. The OOST in other parts of the Himalayas is represented as a line in between MCTL and MCTU. But In Himachal Pradesh area, OOST activated the MCTL as well as in between a zone located south of MCTU. The expectations for strain variation near the OOST are very obvious. But multiple sets of OOSTs may produce a zigzag pattern of strain accumulation for this area and figure out the overprinting structures for multiple sets of OOSTs.

Keywords: Chaura Thrust, out-of-sequence thrust, Main Central Thrust, Sarahan Thrust

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Authors: Hamed Khani Arani, Mohammad Shariyat, Armaghan Mohammadian

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In this research, the free vibration of a rectangular sandwich nano-plate (SNP) made of three smart layers in the visco Pasternak foundation is studied. The core of the sandwich is a piezo magnetic nano-plate integrated with two layers of piezoelectric materials. First-order shear deformation plate theory is utilized to derive the motion equations by using Hamilton’s principle, piezoelectricity, and modified couple stress theory. Elastic medium is modeled by visco Pasternak foundation, where the damping coefficient effect is investigated on the stability of sandwich nano-plate. These equations are solved by the differential quadrature method (DQM), considering different boundary conditions. Results indicate the effect of various parameters such as aspect ratio, thickness ratio, shear correction factor, damping coefficient, and boundary conditions on the dimensionless frequency of sandwich nano-plate. The results are also compared by those available in the literature, and these findings can be used for automotive industry, communications equipment, active noise, stability, and vibration cancellation systems and utilized for designing the magnetostrictive actuator, motor, transducer and sensors in nano and micro smart structures.

Keywords: free vibration, modified couple stress theory, sandwich nano-plate, visco Pasternak foundation

Procedia PDF Downloads 139

Authors: M. Bonopera, N. Tullini, C. C. Chen, T. K. Lin, K. C. Chang

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This paper presents the extension of a static method for the axial load identifications in prismatic beam-columns with uncertain length and unknown boundary conditions belonging to generic space structures, such as columns of space frames or struts and ties of space trusses. The non-destructive method requires the knowledge of the beam-column flexural rigidity only. Flexural displacements are measured at five cross sections along the beam-column subjected to an additional vertical load at the mid-span. Unlike analogous dynamic methods, any set of experimental data may be used in the identification procedure. The method is verified by means of many numerical and experimental tests on beam-columns having unknown boundary conditions and different slenderness belonging to three different space prototypes in small-scale. Excellent estimates of the tensile and compressive forces are obtained for the elements with higher slenderness and when the greatest possible distance between sensors is adopted. Moreover, the application of larger values of the vertical load and very accurate displacement measurements are required. The method could be an efficacious technique in-situ, considering that safety inspections will become increasingly important in the near future, especially because of the improvement of the material properties that allowed designing space structures composed of beam-columns with higher slenderness.

Keywords: force identification, in-situ test, space structure, static test

Procedia PDF Downloads 246

Authors: U. Schmidt, D. Dannehl, I. Schuch, J. Suhl, T. Rocksch, R. Salazar-Moreno, E. Fitz-Rodrigues, A. Rojano Aquilar, I. Lopez Cruz, G. Navas Gomez, R. A. Abraham, L. C. Irineo, N. G. Gilberto

Abstract:

The integration of agricultural production systems into urban areas is a challenge for the coming decades. Because of increasing greenhouse gas emission and rising resource consumption as well as costs in animal husbandry, the dietary habits of people in the 21st century have to focus on herbal foods. Intensive plant cultivation systems in large cities and megacities require a smart coupling of information, material and energy flow with the urban infrastructure in terms of Horticulture 4.0. In recent years, many puzzle pieces have been developed for these closed processes at the Humboldt University. To compile these for an urban plant production, it has to be optimized and networked with urban infrastructure systems. In the field of heat energy production, it was shown that with closed greenhouse technology and patented heat exchange and storage technology energy can be provided for heating and domestic hot water supply in the city. Closed water circuits can be drastically reducing the water requirements of plant production in urban areas. Ion sensitive sensors and new disinfection methods can help keep circulating nutrient solutions in the system for a longer time in urban plant production greenhouses.

Keywords: semi closed, greenhouses, urban farming, solar heat collector, closed water cycles, aquaponics

Procedia PDF Downloads 332