Search results for: semiconductor gas sensor

Authors: Taha Bensiradj, Samira Moussaoui

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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.

Keywords: HSVN, ITS, VANET, WSN

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Authors: Niloofar Zebarjad

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This research aims at finding a tool to provide basketball players with real-time audio feedback on their shooting form in free throw shots. Free throws played a pivotal role in taking the lead in fierce competitions. The major problem in performing an accurate free throw seems to be improper training. Since the arm movement during the free throw shot is complex, the coach or the athlete might miss the movement details during practice. Hence, there is a necessity to create a system that measures arm movements' critical characteristics and control for improper kinematics. The proposed setup in this study quantifies arm kinematics and provides real-time feedback as an audio signal consisting of a gyroscope sensor. Spatial shoulder angle data are transmitted in a mobile application in real-time and can be saved and processed for statistical and analysis purposes. The proposed system is easy to use, inexpensive, portable, and real-time applicable. Objectives: This research aims to modify and control the free throw using audio feedback and determine if and to what extent the new setup reduces errors in arm formations during throws and finally assesses the successful throw rate. Methods: One group of elite basketball athletes and two novice athletes (control and study group) participated in this study. Each group contains 5 participants being studied in three separate sessions over a week. Results: Empirical results showed enhancements in the free throw shooting style, shot pocket (SP), and locked position (LP). The mean values of shoulder angle were controlled on 25° and 45° for SP and LP, respectively, recommended by valid FIBA references. Conclusion: Throughout the experiments, the system helped correct and control the shoulder angles toward the targeted pattern of shot pocket (SP) and locked position (LP). According to the desired results for arm motion, adding another sensor to measure and control the elbow angle is recommended.

Keywords: audio-feedback, basketball, free-throw, locked-position, motor-control, shot-pocket

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Authors: Flora Paganelli

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The radiometric performance of remotely sensed images is important for volcanic monitoring. The Thermal Infrared Sensor (TIRS) on-board Landsat 8 was designed with specific requirements in regard to the noise-equivalent change in temperature (NEΔT) at ≤ 0.4 K at 300 K for the two thermal infrared bands B10 and B11. This study investigated the on-orbit NEΔT of the TIRS two bands from a scene-based method using clear-sky images over the volcanic activity of Kīlauea Volcano and the active East Rift Zone (Hawaii), in order to optimize the use of TIRS data. Results showed that the NEΔTs of the two bands exceeded the design specification by an order of magnitude at 300 K. Both separate bands and split window algorithm were examined to estimate the effect of NEΔT on the land surface temperature (LST) retrieval, and NEΔT contribution to the final LST error. These results were also useful in the current efforts to assess the requirements for volcanology research campaign using the Hyperspectral Infrared Imager (HyspIRI) whose airborne prototype MODIS/ASTER instruments is plan to be flown by NASA as a single campaign to the Hawaiian Islands in support of volcanology and coastal area monitoring in 2016.

Keywords: landsat 8, radiometric performance, thermal infrared sensor (TIRS), volcanology

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Authors: Adkham Paiziev, Fikrat Kerimov

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Near Infrared Spectroscopy (NIRS) is one of the biophotonic techniques which can be used to monitor oxygenation and hemodynamics in a variety of human tissues, including skeletal muscle. In the present work, we are offering tissue oximetry (OxyPrem) to measure hemodynamic parameters of skeletal muscles in rest and exercise. Purpose: - To elaborate the new wireless, portable, noninvasive, wearable NIRS device to measure skeletal muscle oxygenation during exercise. - To test this device on brachioradialis muscle of wrestler volunteers by using combined method of arterial occlusion (AO) and NIRS (AO+NIRS). Methods: Oxyprem NIRS device has been used together with AO test. AO test and Isometric brachioradialis muscle contraction experiments have been performed on one group of wrestler volunteers. ‘Accu- Measure’ caliper (USA) to measure skinfold thickness (SFT) has been used. Results: Elaborated device consists on power supply box, a sensor head and installed ‘Tubis’ software for data acquisition and to compute deoxyhemoglobin ([HHb), oxyhemoglobin ([O2Hb]), tissue oxygenation (StO2) and muscle tissue oxygen consumption (mVO2). Sensor head consists on four light sources with three light emitting diodes with nominal wavelengths of 760 nm, 805 nm, and 870 nm, and two detectors. AO and isometric voluntary forearm muscle contraction (IVFMC) on five healthy male subjects (23,2±0.84 in age, 0.43±0.05cm of SFT ) and four female subjects (22.0±1.0 in age and 0.24±0.04 cm SFT) has been measured. mVO2 for control group has been calculated (-0.65%/sec±0.07) for male and -0.69%/±0.19 for female subjects). Tissue oxygenation index for wrestlers in average about 75% whereas for control group StO2 =63%. Second experiment was connected with quality monitoring muscle activity during IVFMC at 10%,30% and 50% of MVC. It has been shown, that the concentration changes of HbO2 and HHb positively correlated to the contraction intensity. Conclusion: We have presented a portable multi-channel wireless NIRS device for real-time monitoring of muscle activity. The miniaturized NIRS sensor and the usage of wireless communication make the whole device have a compact-size, thus can be used in muscle monitoring.

Keywords: skeletal muscle, oxygenation, instrumentation, near infrared spectroscopy

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Authors: Wei Zheng, Mao Ji, Zhe Hou, Meng Huang, Bo Qi

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The transformer is the key equipment of the power system. Winding deformation is one of the main transformer defects, and timely and effective detection of the transformer winding deformation can ensure the safe and stable operation of the transformer to the maximum extent. When winding deformation occurs, the size, shape and spatial position of the winding will change, which directly leads to the change of magnetic flux leakage distribution. Therefore, it is promising to study the online detection method of the transformer winding deformation based on magnetic flux leakage characteristics, in which the key step is to study the optimal placement method of magnetic flux leakage sensors inside the transformer. In this paper, a simulation model of the transformer winding deformation is established to obtain the internal magnetic flux leakage distribution of the transformer under normal operation and different winding deformation conditions, and the law of change of magnetic flux leakage distribution due to winding deformation is analyzed. The results show that different winding deformation leads to different characteristics of the magnetic flux leakage distribution. On this basis, an optimized placement of magnetic flux leakage sensors inside the transformer is proposed to provide a basis for the online detection method of transformer winding deformation based on the magnetic flux leakage characteristics.

Keywords: magnetic flux leakage, sensor placement method, transformer, winding deformation

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Authors: Irina Veselova, Maria Makedonskaya, Olga Eremina, Alexandr Sidorov, Eugene Goodilin, Tatyana Shekhovtsova

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Such catecholamines as dopamine, norepinephrine, and epinephrine are the principal neurotransmitters in the sympathetic nervous system. Catecholamines and their metabolites are considered to be important markers of socially significant diseases such as atherosclerosis, diabetes, coronary heart disease, carcinogenesis, Alzheimer's and Parkinson's diseases. Currently, neurotransmitters can be studied via electrochemical and chromatographic techniques that allow their characterizing and quantification, although these techniques can only provide crude spatial information. Besides, the difficulty of catecholamine determination in biological materials is associated with their low normal concentrations (~ 1 nM) in biomaterials, which may become even one more order lower because of some disorders. In addition, in blood they are rapidly oxidized by monoaminooxidases from thrombocytes and, for this reason, the determination of neurotransmitter metabolism indicators in an organism should be very rapid (15—30 min), especially in critical states. Unfortunately, modern instrumental analysis does not offer a complex solution of this problem: despite its high sensitivity and selectivity, HPLC-MS cannot provide sufficiently rapid analysis, while enzymatic biosensors and immunoassays for the determination of the considered analytes lack sufficient sensitivity and reproducibility. Fluorescent and SERS-sensors remain a compelling technology for approaching the general problem of selective neurotransmitter detection. In recent years, a number of catecholamine sensors have been reported including RNA aptamers, fluorescent ribonucleopeptide (RNP) complexes, and boronic acid based synthetic receptors and the sensor operated in a turn-off mode. In this work we present the fluorescent and SERS turn-on sensor systems based on the bio- or chemorecognizing nanostructured films {chitosan/collagen-Tb/Eu/Cu-nanoparticles-indicator reagents} that provide the selective recognition, visualization, and sensing of the above mentioned catecholamines on the level of nanomolar concentrations in biomaterials (cell cultures, tissue etc.). We have (1) developed optically transparent porous films and gels of chitosan/collagen; (2) ensured functionalization of the surface by molecules-'recognizers' (by impregnation and immobilization of components of the indicator systems: biorecognizing and auxiliary reagents); (3) performed computer simulation for theoretical prediction and interpretation of some properties of the developed materials and obtained analytical signals in biomaterials. We are grateful for the financial support of this research from Russian Foundation for Basic Research (grants no. 15-03-05064 a, and 15-29-01330 ofi_m).

Keywords: biomaterials, fluorescent and SERS-recognition, neurotransmitters, solid-phase turn-on sensor system

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Authors: Eric A. Morris, Xia Liu, Yee Ka Wong, Greg J. Evans, Jeff R. Brook

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Air quality monitoring stations tend to be widely distributed and are often located far from major roadways, thus, determining where, when, and which traffic-related air pollutants (TRAPs) have the greatest impact on public health becomes a matter of extrapolation. Compact, multipollutant sensor systems are an effective solution as they enable several TRAPs to be monitored in a geospatially dense network, thus filling in the gaps between conventional monitoring stations. This work describes two applications of one such system named AirSENCE for gathering actionable air quality data relevant to smart city infrastructures. In the first application, four AirSENCE devices were co-located with traffic monitors around the perimeter of a city block in Oshawa, Ontario. This study, which coincided with the COVID-19 outbreak of 2020 and subsequent lockdown measures, demonstrated a direct relationship between decreased traffic volumes and TRAP concentrations. Conversely, road construction was observed to cause elevated TRAP levels while reducing traffic volumes, illustrating that conventional smart city sensors such as traffic counters provide inadequate data for inferring air quality conditions. The second application used two AirSENCE sensors on opposite sides of a major 2-way commuter road in Toronto. Clear correlations of TRAP concentrations with wind direction were observed, which shows that impacted areas are not necessarily static and may exhibit high day-to-day variability in air quality conditions despite consistent traffic volumes. Both of these applications provide compelling evidence favouring the inclusion of air quality sensors in current and future smart city infrastructure planning. Such sensors provide direct measurements that are useful for public health alerting as well as decision-making for projects involving traffic mitigation, heavy construction, and urban renewal efforts.

Keywords: distributed sensor network, continuous ambient air quality monitoring, Smart city sensors, Internet of Things, traffic-related air pollutants

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Authors: K. Yang, Y. Wei, M. Zhang, S. Yong, R. Torah, J. Tudor, S. Beeby

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E-textiles are traditional textiles with integrated electronic functionality. It is an emerging innovation with numerous applications in fashion, wearable computing, health and safety monitoring, and the military and medical sectors. The piezoelectric effect is a widespread and versatile transduction mechanism used in sensor and actuator applications. Piezoelectric materials produce electric charge when stressed. Conversely, mechanical deformation occurs when an electric field is applied across the material. Lead Zirconate Titanate (PZT) is a widely used piezoceramic material which has been used to fabricate e-textiles through screen printing, electro spinning and hydrothermal synthesis. This paper explores an alternative fabrication process: Spray coating. Spray coating is a straightforward and cost effective fabrication method applicable on both flat and curved surfaces. It can also be applied selectively by spraying through a stencil which enables the required design to be realised on the substrate. This work developed a sprayable PZT based piezoelectric ink consisting of a binder (Fabink-Binder-01), PZT powder (80 % 2 µm and 20 % 0.8 µm) and acetone as a thinner. The optimised weight ratio of PZT/binder is 10:1. The components were mixed using a SpeedMixer DAC 150. The fabrication processes is as follows: 1) Screen print a UV-curable polyurethane interface layer on the textile to create a smooth textile surface. 2) Spray one layer of a conductive silver polymer ink through a pre-designed stencil and dry at 90 °C for 10 minutes to form the bottom electrode. 3) Spray three layers of the PZT ink through a pre-designed stencil and dry at 90 °C for 10 minutes for each layer to form a total thickness of ~250µm PZT layer. 4) Spray one layer of the silver ink through a pre-designed stencil on top of the PZT layer and dry at 90 °C for 10 minutes to form the top electrode. The domains of the PZT elements were aligned by polarising the material at an elevated temperature under a strong electric field. A d33 of 37 pC/N has been achieved after polarising at 90 °C for 6 minutes with an electric field of 3 MV/m. The application of the piezoelectric textile was demonstrated by fabricating a pressure sensor to switch an LED on/off. Other potential applications on e-textiles include motion sensing, energy harvesting, force sensing and a buzzer.

Keywords: piezoelectric, PZT, spray coating, pressure sensor, e-textile

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Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

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Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

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Authors: Jihyun Park, Tae Il Lee, Jae-Min Myoung

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A Silver (Ag) thin film is introduced as a template and doping source for vertically aligned p–type ZnO nanorods. ZnO nanorods were grown using a ammonium hydroxide based hydrothermal process. During the hydrothermal process, the Ag thin film was dissolved to generate Ag ions in the solution. The Ag ions can contribute to doping in the wurzite structure of ZnO and the (111) grain of Ag thin film can be the epitaxial temporal template for the (0001) plane of ZnO. Hence, Ag–doped p–type ZnO nanorods were successfully grown on the substrate, which can be an electrode or semiconductor for the device application. To demonstrate the potentials of this idea, p–n diode was fabricated and its electrical characteristics were demonstrated.

Keywords: hydrothermal process, Ag–doped ZnO nanorods, p–type ZnO

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Authors: Fatima Babar, Majid I. Khan, Malik Najmus Saqib, Muhammad Tahir

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This article provides range based improvements over a well-known single-hop range free localization scheme, Approximate Point in Triangulation (APIT) by proposing an energy efficient Barycentric coordinate based Point-In-Triangulation (PIT) test along with PIT based trilateration. These improvements result in energy efficiency, reduced localization error and improved localization coverage compared to APIT and its variants. Moreover, we propose to embed Received signal strength indication (RSSI) based distance estimation in DV-Hop which is a multi-hop localization scheme. The proposed localization algorithm achieves energy efficiency and reduced localization error compared to DV-Hop and its available improvements. Furthermore, a hybrid multi-hop localization scheme is also proposed that utilize Barycentric coordinate based PIT test and both range based (Received signal strength indicator) and range free (hop count) techniques for distance estimation. Our experimental results provide evidence that proposed hybrid multi-hop localization scheme results in two to five times reduction in the localization error compare to DV-Hop and its variants, at reduced energy requirements.

Keywords: Localization, Trilateration, Triangulation, Wireless Sensor Networks

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Authors: N. Zerzouri, N. Benalia, N. Bensiali

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This work is devoted to an analysis of the operation of a doubly fed induction generator (DFIG) integrated with a wind system. The power transfer between the stator and the network is carried out by acting on the rotor via a bidirectional signal converter. The analysis is devoted to the study of a fault in the converter due to an interruption of the control of a semiconductor. Simulation results obtained by the MATLAB / Simulink software illustrate the quality of the power generated at the default.

Keywords: doubly fed induction generator (DFIG), wind power generation, back to back PWM converter, default switching

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Authors: Deepika Sharma, Bal Krishan

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In this paper, the structure of N-channel VDMOS was designed and analyzed using Silvaco TCAD tools by varying N+ source doping concentration, P-Body doping concentration, gate oxide thickness and the diffuse time. VDMOS is considered to be ideal power switches due to its high input impedance and fast switching speed. The performance of the device was analyzed from the Ids vs Vgs curve. The electrical characteristics such as threshold voltage, gate oxide thickness and breakdown voltage for the proposed device structures were extarcted. Effect of epitaxial layer on various parameters is also observed.

Keywords: on-resistance, threshold voltage, epitaxial layer, breakdown voltage

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Authors: K. Chethana, A. S. Guru Prasad, H. N. Vikranth, H. Varun, S. N. Omkar, S. Asokan

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This paper describes a novel application of Fiber Braggs Grating (FBG) sensors on an unstable platform to assess human postural stability and balance. The FBG sensor based Stability Analyzing Device (FBGSAD) developed demonstrates the applicability of FBG sensors in the measurement of plantar strain to assess the postural stability of subjects on unstable platforms during different stances in eyes open and eyes closed conditions on a rocker board. Comparing the Centre of Gravity (CG) variations measured on the lumbar vertebra of subjects using a commercial accelerometer along with FBGSAD validates the study. The results obtained depict qualitative similarities between the data recorded by both FBGSAD and accelerometer, illustrating the reliability and consistency of FBG sensors in biomechanical applications for both young and geriatric population. The developed FBGSAD simultaneously measures plantar strain distribution and postural stability and can serve as a tool/yardstick to mitigate space motion sickness, identify individuals who are susceptible to falls and to qualify subjects for balance and stability, which are important factors in the selection of certain unique professionals such as aircraft pilots, astronauts, cosmonauts etc.

Keywords: biomechanics, fiber bragg gratings, plantar strain measurement, postural stability analysis

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Authors: Balgaisha G. Mukanova, Yelbek B. Utepov, Aida G. Nazarova, Alisher Z. Imanov

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The problem of identifying local noise sources on a construction site using a sensor system is considered. Mathematical modeling of detected signals on sensors was carried out, considering signal decay and signal delay time between the source and detector. Recordings of noises produced by construction tools were used as a dependence of noise on time. Synthetic sensor data was constructed based on these data, and a model of the propagation of acoustic waves from a point source in the three-dimensional space was applied. All sensors and sources are assumed to be located in the same plane. A source localization method is checked based on the signal time delay between two adjacent detectors and plotting the direction of the source. Based on the two direct lines' crossline, the noise source's position is determined. Cases of one dominant source and the case of two sources in the presence of several other sources of lower intensity are considered. The number of detectors varies from three to eight detectors. The intensity of the noise field in the assessed area is plotted. The signal of a two-second duration is considered. The source is located for subsequent parts of the signal with a duration above 0.04 sec; the final result is obtained by computing the average value.

Keywords: acoustic model, direction of arrival, inverse source problem, sound localization, urban noises

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Angad S. Kushwaha, Rajeev Kumar, Monika Srivastava, S. K. Srivastava

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A lot of research work is going on in the field of graphene based SPR biosensor. In the conventional SPR based biosensor, graphene is used as a biomolecular recognition element. Graphene adsorbs biomolecules due to carbon based ring structure through sp2 hybridization. The proposed SPR based biosensor configuration will open a new avenue for efficient biosensing by taking the advantage of Graphene and its fascinating nanofabrication properties. In the present study, we have studied an SPR biosensor based on graphene mediated by Zinc Oxide (ZnO) and Gold. In the proposed structure, prism (BK7) base is coated with Zinc Oxide followed by Gold and Graphene. Using the waveguide approach by transfer matrix method, the proposed structure has been investigated theoretically. We have analyzed the reflectance versus incidence angle curve using He-Ne laser of wavelength 632.8 nm. Angle, at which the reflectance is minimized, termed as SPR angle. The shift in SPR angle is responsible for biosensing. From the analysis of reflectivity curve, we have found that there is a shift in SPR angle as the biomolecules get attached on the graphene surface. This graphene layer also enhances the sensitivity of the SPR sensor as compare to the conventional sensor. The sensitivity also increases by increasing the no of graphene layer. So in our proposed biosensor we have found minimum possible reflectivity with optimum level of sensitivity.

Keywords: biosensor, sensitivity, surface plasmon resonance, transfer matrix method

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Authors: W. T. Asheber, L. Chyi-Yeu

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An intelligent robot arm is expected to recognize the desired object, grasp it with appropriate force without dropping or damaging it, and also manipulate and deliver the object to the desired destination safely. This paper presents an intelligent multi-finger robot arm gripper design along with vision, proximity, and tactile sensor for efficient grasping and manipulation tasks. The generic design of the gripper makes it convenient for improved parts manipulation, multi-tasking and ease for components assembly. The proposed design emulates the human’s hand fingers structure using linkages and direct drive through power screw like transmission. The actuation and transmission mechanism is designed in such a way that it has non-back-drivable capability, which makes the fingers hold their position when even unpowered. The structural elements are optimized for a finest performance in motion and force transmissivity of the gripper fingers. The actuation mechanisms is designed specially to drive each finger and also rotate two of the fingers about the palm to form appropriate configuration to grasp various size and shape objects. The gripper has an automatic tool set fixture incorporated into its palm, which will reduce time wastage and do assembling in one go. It is equipped with camera-in-hand integrated into its palm; subsequently an image based visual-servoing control scheme is employed.

Keywords: gripper, intelligent gripper, transmissivity, vision sensor

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Authors: Hafizah Che Hasan, Fateen Nazwa Yusof, Maslina Daud

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Internet of Things (IoT) is a powerful industry system, which end-devices are interconnected and automated, allowing the devices to analyze data and execute actions based on the analysis. The IoT technology leverages the technology of Radio-Frequency Identification (RFID) and Wireless Sensor Network (WSN), including mobile and sensor. These technologies contribute to the evolution of IoT. However, due to more devices are connected each other in the Internet, and data from various sources exchanged between things, confidentiality of the data becomes a major concern. This paper focuses on one of the major challenges in IoT; authentication, in order to preserve data integrity and confidentiality are in place. A few solutions are reviewed based on papers from the last few years. One of the proposed solutions is securing the communication between IoT devices and cloud servers with Elliptic Curve Cryptograhpy (ECC) based mutual authentication protocol. This solution focuses on Hyper Text Transfer Protocol (HTTP) cookies as security parameter.  Next proposed solution is using keyed-hash scheme protocol to enable IoT devices to authenticate each other without the presence of a central control server. Another proposed solution uses Physical Unclonable Function (PUF) based mutual authentication protocol. It emphasizes on tamper resistant and resource-efficient technology, which equals a 3-way handshake security protocol.

Keywords: Internet of Things (IoT), authentication, PUF ECC, keyed-hash scheme protocol

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Authors: Fatima Zohra Rahou, A. Guen Bouazza, B. Bouazza

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Invention of transistor is the foundation of electronics industry. Metal Oxide Semiconductor Field Effect Transistor (MOSFET) has been the key for the development of nanoelectronics technology. In the first part of this manuscript, we present a new generation of MOSFET transistors based on SOI (Silicon-On-Insulator) technology. It is a partially depleted Silicon-On-Insulator (PD SOI MOSFET) transistor simulated by using SILVACO software. This work was completed by the presentation of some results concerning the influence of parameters variation (channel length L and gate oxide thickness Tox) on our PDSOI n-MOSFET structure on its drain current and kink effect.

Keywords: SOI technology, PDSOI MOSFET, FDSOI MOSFET, kink effect

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Authors: Mourad Hrizi

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In this paper, we study the inverse problem of reconstructing an interior interface D appearing in the elliptic partial differential equation: Δu+χ(D)u=0 from the knowledge of the boundary measurements. This problem arises from a semiconductor transistor model. We propose a new shape reconstruction procedure that is based on the Kohn-Vogelius formulation and the topological sensitivity method. The inverse problem is formulated as a topology optimization one. A topological sensitivity analysis is derived from a function. The unknown subdomain D is reconstructed using a level-set curve of the topological gradient. Finally, we give several examples to show the viability of our proposed method.

Keywords: inverse problem, topological optimization, topological gradient, Kohn-Vogelius formulation

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Authors: Sabit Horoz, Ahmet Ekicibil, Omer Sahin, M. Akyol

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In this study, CdZnS and Ni-doped CdZnS quantum dots(QDs) were prepared by the wet-chemical method at room temperature using mercaptoethanol as a capping agent. The structural and magnetic properties of the CdZnS and CdZnS doped with different concentrations of Ni QDs were examined by XRD and magnetic susceptibility measurements, respectively. The average particles size of cubic QDs obtained by full-width half maxima (FWHM) analysis, increases with increasing doping concentrations. The investigation of the magnetic properties showed that the Ni-doped samples exhibit signs of ferromagnetism, on the other hand, un-doped CdZnS is diamagnetic.

Keywords: un-doped and Ni doped CdZnS Quantum Dots (QDs), co-precipitation method, structural and optical properties of QDs, diluted magnetic semiconductor materials (DMSMs)

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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: B. Gueridi, T. Chihi, M. Fatmi, A. Faci

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Some fundamental physical properties of BiGaO₃ were investigated under pressure and temperature effect using generalized gradient approximation and local density approximation approaches. The effect of orientation on Debye temperature and sound waves velocities were estimated from elastic constants. The value of the bulk modulus of BiGaO₃ is a sign of its high hardness because it is linked to an isotropic deformation. BiGaO₃ is a semiconductor and ductile material with covalent bonding (Ga–O), and the Bi-O bonding is ionic. The optical transitions were observed when electrons pass from the top of the valence band (O-2p) to the bottom of the conduction band (Ga-4p or Bi-6p). The thermodynamic parameters are determined in temperature and pressure ranging from 0 to 1800 K and 0 to 50 GPa.

Keywords: BiGaO₃ perovskite, optical absorption, first principle, band structure

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Authors: Karchung, S. Ruangsinchaiwanich

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This paper presents open-loop vector control method of induction motor with space vector pulse width modulation (SVPWM) technique. Normally, the closed loop speed control is preferred and is believed to be more accurate. However, it requires a position sensor to track the rotor position which is not desirable to use it for certain workspace applications. This paper exhibits the performance of three-phase induction motor with the simplest control algorithm without the use of a position sensor nor an estimation block to estimate rotor position for sensorless control. The motor stator currents are measured and are transformed to synchronously rotating (d-q-axis) frame by use of Clarke and Park transformation. The actual control happens in this frame where the measured currents are compared with the reference currents. The error signal is fed to a conventional PI controller, and the corrected d-q voltage is generated. The controller outputs are transformed back to three phase voltages and are fed to SVPWM block which generates PWM signal for the voltage source inverter. The open loop vector control model along with SVPWM algorithm is modeled in MATLAB/Simulink software and is experimented and validated in TMS320F28335 DSP board.

Keywords: electric drive, induction motor, open-loop vector control, space vector pulse width modulation technique

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Authors: Chanho Park, Juneseok You, Kuewhan Jang, Sungsoo Na

Abstract:

Detection technique of nanotoxic materials is strongly imperative, because nano-toxic materials can harmfully influence human health and environment as their engineering applications are growing rapidly in recent years. In present work, we report the DNA immobilized quartz crystal microbalance (QCM) based sensor for detection of nano-toxic materials such as silver ions, Hg2+ etc. by using functionalization of quartz crystal with a target-specific DNA. Since the mass of a target material is comparable to that of an atom, the mass change caused by target binding to DNA on the quartz crystal is so small that it is practically difficult to detect the ions at low concentrations. In our study, we have demonstrated fast and in situ detection of nanotoxic materials using quartz crystal microbalance. We report the label-free and highly sensitive detection of silver ion for present case, which is a typical nano-toxic material by using QCM and silver-specific DNA. The detection is based on the measurement of frequency shift of Quartz crystal from constitution of the cytosine-Ag+-cytosine binding. It is shown that the silver-specific DNA measured frequency shift by QCM enables the capturing of silver ions below 100pM. The results suggest that DNA-based detection opens a new avenue for the development of a practical water-testing sensor.

Keywords: nano-toxic ions, quartz crystal microbalance, frequency shift, target-specific DNA

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Authors: Mohammad Ali Karimi, Hossein Tavallali, Abdolhamid Hatefi-Mehrjardi

Abstract:

In this study, an electrochemical sensor based on gold nanoparticles (AuNPs) functionalized improved graphene (AuNPs-IGE) was fabricated for selective determination of L-dopa in the presence of ascorbic acid by a novel self-assembly method. The AuNP IGE modified carbon paste electrode (AuNPs-IGE/CPE) utilized for investigation of the electrochemical behavior of L-dopa in phosphate buffer solution. Compared to bare CPE, AuNPs-IGE/CPE shows novel properties towards the electrochemical redox of levodopa (L-dopa) in phosphate buffer solution at pH 4.0. The oxidation potential of L-dopa shows a significant decrease at the AuNPs-IGE/CPE. The oxidation current of L-dopa is higher than that of the unmodified CPE. AuNPs-IG/CPE shows excellent electrocatalytic activity for the oxidation of ascorbic acid (AA). Using differential pulse voltammetry (DPV) method, the oxidation current is well linear with L-dopa concentration in the range of 0.4–50 µmol L-1, with a detection limit of about 1.41 nmol L-1 (S/N = 3). Therefore, it was applied to measure L-dopa from real samples that recoveries are 94.6-106.2%. The proposed electrode can also effectively avoid the interference of ascorbic acid, making the proposed sensor suitable for the accurate determination of L-dopa in both pharmaceutical preparations and human body fluids.

Keywords: gold nanoparticles, improved graphene, L-dopa, self-assembly

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Authors: Sayed Obeidullah Abrar

Abstract:

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

Procedia PDF Downloads 285

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

Abstract:

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

Abstract:

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

Procedia PDF Downloads 99