Search results for: infrared range sensors

Authors: Emad E. Abdallah, Alaa E. Abdallah, Bajes Y. Alskarnah

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We introduce a robust three-dimensional watermarking algorithm for copyright protection and indexing. The basic idea behind our technique is to measure the interquartile range or the spread of the 3D model vertices. The algorithm starts by converting all the vertices to spherical coordinate followed by partitioning them into small groups. The proposed algorithm is slightly altering the interquartile range distribution of the small groups based on predefined watermark. The experimental results on several 3D meshes prove perceptual invisibility and the robustness of the proposed technique against the most common attacks including compression, noise, smoothing, scaling, rotation as well as combinations of these attacks.

Keywords: watermarking, three-dimensional models, perceptual invisibility, interquartile range, 3D attacks

Procedia PDF Downloads 474

Authors: Dalila Hammiche, Lisa Klaai, Sonia Imzi, Amar Boukerrou

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The fight against plastic pollution implies the development of polymers as alternatives to synthetic polymers. Starch is a natural polymer that can easily be plasticized by means of additives. The objective of this work is to develop and characterize biodegradable biofilms based on starch, plasticized by glycerol (20 and 30%). The elaboration of the biofilms was carried out by the casting method under simple conditions. The samples were characterized by infrared spectroscopy analysis with Fourier transform (FTIR), thermogravimetric analysis, and biodegradability test. Infrared spectral analysis showed that the 30% and 20% glycerol films have the same chemical structure and no functional group changes occurred. Thermogravimetric analysis showed that a 30% glycerol film has higher thermal stability than a 20% glycerol film. Biodegradability test showed that the lower the percentage of glycerol, the more easily the biofilm degrades.

Keywords: starch, natural sources, FTIR, thermogravimetric analysis, biodegradability test

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Authors: Chinmay Shah

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The project is all about development of a close loop traffic light control system using PLC (Programmable Logic Controller). This project is divided into two parts which are hardware and software. The hardware part for this project is a model of four way junction of a traffic light. Three indicator lamps (Red, Yellow and Green) are installed at each lane for represents as traffic light signal. This traffic control model is a replica of actuated traffic control. Actuated traffic control system is a close loop traffic control system which controls the timing of the indicator lamps depending on the fluidity of traffic for a particular lane. To make it autonomous, in each lane three IR sensors are placed which helps to sense the percentage of traffic present on any particular lane. The IR Sensors and Indicator lamps are connected to LG PLC XGB series. The PLC controls every signal which is coming from the inputs (IR Sensors) to software and display to the outputs (Indicator lamps). Default timing for the indicator lamps is 30 seconds for each lane. But depending on the percentage of traffic present, if the traffic is nearly 30-35%, green lamp will be on for 10 seconds, for 65-70% traffic it will be 20 seconds, for full 100% traffic it will be on for full 30 seconds. The software part that operates with LG PLC is “XG 5000” Programmer. Using this software, the ladder logic diagram is programmed to control the traffic light base on the flow chart. At the end of this project, the traffic light system is actuated successfully by PLC.

Keywords: close loop, IR sensor, PLC, light control system

Procedia PDF Downloads 571

Authors: Xiang Yu, Chuntao Feng, Lu Yang, Meiyang Song, Wenhao Zhou

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The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.

Keywords: FMCW radar, fall detection, 3D CNN, time-varying range-doppler features

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Authors: Richard Mitchell, Robert Mitchell, Thai Duong, Kyungbin Bae, Daegon Kim, Youngsub Lee, Inho Kim, Inho Park, Hyungseok Lee

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Although X-band radar is commonly used to measure the properties of ocean waves, the use of a higher frequency has several advantages, such as increased backscatter coefficient, better Doppler sensitivity, lower power, and a smaller package. A low-power Ku-band radar system was developed to demonstrate these advantages. It is fully coherent, and it interleaves short and long pulses to achieve a transmit duty ratio of 25%, which makes the best use of solid-state amplifiers. The range scales are 2 km, 4 km, and 8 km. The minimum range is 100 m, 200 m, and 400 m for the three range scales, and the range resolution is 4 m, 8 m, and 16 m for the three range scales. Measurements of the significant wave height, wavelength, wave period, and wave direction have been made using traditional 3D-FFT methods. Radar and ultrasonic sensor results collected over an extended period of time at a coastal site in South Korea are presented.

Keywords: measurement of ocean wave parameters, Ku-band radar, coherent radar, compact radar

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Authors: Rabbia Idrees, Ananda Maiti, Saurabh Garg, Muhammad Bilal Amin

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IoT devices are the basic building blocks of IoT network that generate enormous volume of real-time and high-speed data to help organizations and companies to take intelligent decisions. To integrate this enormous data from multisource and transfer it to the appropriate client is the fundamental of IoT development. The handling of this huge quantity of devices along with the huge volume of data is very challenging. The IoT devices are battery-powered and resource-constrained and to provide energy efficient communication, these IoT devices go sleep or online/wakeup periodically and a-periodically depending on the traffic loads to reduce energy consumption. Sometime these devices get disconnected due to device battery depletion. If the node is not available in the network, then the IoT network provides incomplete, missing, and inaccurate data. Moreover, many IoT applications, like vehicle tracking and patient tracking require the IoT devices to be mobile. Due to this mobility, If the distance of the device from the sink node become greater than required, the connection is lost. Due to this disconnection other devices join the network for replacing the broken-down and left devices. This make IoT devices dynamic in nature which brings uncertainty and unreliability in the IoT network and hence produce bad quality of data. Due to this dynamic nature of IoT devices we do not know the actual reason of abnormal data. If data are of poor-quality decisions are likely to be unsound. It is highly important to process data and estimate data quality before bringing it to use in IoT applications. In the past many researchers tried to estimate data quality and provided several Machine Learning (ML), stochastic and statistical methods to perform analysis on stored data in the data processing layer, without focusing the challenges and issues arises from the dynamic nature of IoT devices and how it is impacting data quality. A comprehensive review on determining the impact of dynamic nature of IoT devices on data quality is done in this research and presented a data quality model that can deal with this challenge and produce good quality of data. This research presents the data quality model for the sensors monitoring water quality. DBSCAN clustering and weather sensors are used in this research to make data quality model for the sensors monitoring water quality. An extensive study has been done in this research on finding the relationship between the data of weather sensors and sensors monitoring water quality of the lakes and beaches. The detailed theoretical analysis has been presented in this research mentioning correlation between independent data streams of the two sets of sensors. With the help of the analysis and DBSCAN, a data quality model is prepared. This model encompasses five dimensions of data quality: outliers’ detection and removal, completeness, patterns of missing values and checks the accuracy of the data with the help of cluster’s position. At the end, the statistical analysis has been done on the clusters formed as the result of DBSCAN, and consistency is evaluated through Coefficient of Variation (CoV).

Keywords: clustering, data quality, DBSCAN, and Internet of things (IoT)

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Authors: Caner Koc, Dilara Gerdan Koc, Mustafa Vatandas

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The fundamental components of autonomous agricultural robot design, such as having a working understanding of coordinates, correctly constructing the desired route, and sensing environmental elements, are the most important. A variety of sensors, hardware, and software are employed by agricultural robots to find these systems.These enable the fully automated driving system of an autonomous vehicle to simulate how a human-driven vehicle would respond to changing environmental conditions. To calculate the vehicle's motion trajectory using data from the sensors, this automation system typically consists of a sophisticated software architecture based on object detection and driving decisions. In this study, the software architecture of an autonomous agricultural vehicle is compared to the trajectory planning techniques.

Keywords: agriculture 5.0, computational intelligence, motion planning, trajectory planning

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Authors: Gong Zhang, Hong Cai, Bin Dong, Jifang Tao, Aiqun Liu, Dim-Lee Kwong, Yuandong Gu

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An on-chip refractive index sensor with high sensitivity and large measurement range is demonstrated in this paper. The sensing structures are based on Mach-Zehnder interferometer configuration, built on the SOI substrate. The wavelength sensitivity of the sensor is estimated to be 3129 nm/RIU. Meanwhile, according to the interference pattern period changes, the measured period sensitivities are 2.9 nm/RIU (TE mode) and 4.21 nm/RIU (TM mode), respectively. As such, the wavelength shift and the period shift can be used for fine index change detection and larger index change detection, respectively. Therefore, the sensor design provides an approach for large index change measurement with high sensitivity.

Keywords: Mach-Zehnder interferometer, nanotechnology, refractive index sensing, sensors

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Authors: Ramandeep Kaur M. Malhi, Prashant K. Srivastava, G.Sandhya Kiran

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Quantitative estimates of foliar biochemicals, namely chlorophyll content (CC), serve as key information for the assessment of plant productivity, stress, and the availability of nutrients. This also plays a critical role in predicting the dynamic response of any vegetation to altering climate conditions. The advent of hyperspectral data with an enhanced number of available wavelengths has increased the possibility of acquiring improved information on CC. Retrieval of CC is extensively carried through well known spectral indices derived from hyperspectral data. In the present study, an attempt is made to develop hyperspectral indices by identifying optimum bands for CC estimation in Butea monosperma (Lam.) Taub growing in forests of Shoolpaneshwar Wildlife Sanctuary, Narmada district, Gujarat State, India. 196 narrow bands of EO-1 Hyperion images were screened, and the best optimum wavelength from blue, green, red, and near infrared (NIR) regions were identified based on the coefficient of determination (R²) between band reflectance and laboratory estimated CC. The identified optimum wavelengths were then employed for developing 12 hyperspectral indices. These spectral index values and CC values were then correlated to investigate the relation between laboratory measured CC and spectral indices. Band 15 of blue range and Band 22 of green range, Band 40 of the red region, and Band 79 of NIR region were found to be optimum bands for estimating CC. The optimum band based combinations on hyperspectral data proved to be the most effective indices for quantifying Butea CC with NDVI and TVI identified as the best (R² > 0.7, p < 0.01). The study demonstrated the significance of band characterization in the development of the best hyperspectral indices for the chlorophyll estimation, which can aid in monitoring the vitality of forests.

Keywords: band, characterization, chlorophyll, hyperspectral, indices

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Authors: Wided Abidi, Tahar Ezzedine

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Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

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Authors: Lim Teck Beng, Thiha Kyaw, Poh Boon Kiat, Lee Ngai Meng

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This work presents discussion on the possibility of merging two emerging technologies in microwave; wireless power transfer (WPT) and RF energy harvesting. The current state of art of the two technologies is discussed and the strength and weakness of the two technologies is also presented. The equivalent circuit of wireless power transfer is modeled and explained as how the range and efficiency can be further increased by controlling certain parameters in the receiver. The different techniques of harvesting the RF energy from the ambient are also extensive study. Last but not least, we demonstrate that a low power wireless sensor network (WSN) can be power up by RF energy harvesting. The WSN is designed to transmit every 3 minutes of information containing the temperature of the environment and also the voltage of the node. One thing worth mention is both the sensors that are used for measurement are also powering up by the RF energy harvesting system.

Keywords: energy harvesting, wireless power transfer, wireless sensor network and magnetic coupled resonator

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Authors: Tuğçe Yücel

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A Wireless Sensor Network(WSN) is a collection of sensor nodes which are deployed randomly in an area for surveillance. Efficient utilization of limited battery energy of sensors for increased network lifetime as well as data security are major design objectives for WSN. Moreover secure transmission of data sensed to a base station for further processing. Producing multiple copies of data packets and sending them on different paths is one of the strategies for this purpose, which leads to redundant energy consumption and hence reduced network lifetime. In this work we develop a restricted multi-copy multipath strategy where data move through ‘frequently’ or ‘heavily’ used sensors is copied by the sensor incident to such central nodes and sent on node-disjoint paths. We develop a mixed integer programing(MIP) model and heuristic approach present some preleminary test results.

Keywords: MIP, sensor, telecommunications, WSN

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Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

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The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

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Authors: Ch. Sridevi, A. Chalapathi Rao, P. Srinivasulu

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The location accuracy of data products is a critical parameter in assessing the geometric performance of satellite sensors. This study focuses on reliability analysis of onboard sensors to evaluate their performance in terms of location accuracy performance over time. The analysis utilizes field failure data and employs the weibull distribution to determine the reliability and in turn to understand the improvements or degradations over a period of time. The analysis begins by scrutinizing the location accuracy error which is the root mean square (RMS) error of differences between ground control point coordinates observed on the product and the map and identifying the failure data with reference to time. A significant challenge in this study is to thoroughly analyze the possibility of an infant mortality phase in the data. To address this, the Weibull distribution is utilized to determine if the data exhibits an infant stage or if it has transitioned into the operational phase. The shape parameter beta plays a crucial role in identifying this stage. Additionally, determining the exact start of the operational phase and the end of the infant stage poses another challenge as it is crucial to eliminate residual infant mortality or wear-out from the model, as it can significantly increase the total failure rate. To address this, an approach utilizing the well-established statistical Laplace test is applied to infer the behavior of sensors and to accurately ascertain the duration of different phases in the lifetime and the time required for stabilization. This approach also helps in understanding if the bathtub curve model, which accounts for the different phases in the lifetime of a product, is appropriate for the data and whether the thresholds for the infant period and wear-out phase are accurately estimated by validating the data in individual phases with Weibull distribution curve fitting analysis. Once the operational phase is determined, reliability is assessed using Weibull analysis. This analysis not only provides insights into the reliability of individual sensors with regards to location accuracy over the required period of time, but also establishes a model that can be applied to automate similar analyses for various sensors and parameters using field failure data. Furthermore, the identification of the best-performing sensor through this analysis serves as a benchmark for future missions and designs, ensuring continuous improvement in sensor performance and reliability. Overall, this study provides a methodology to accurately determine the duration of different phases in the life data of individual sensors. It enables an assessment of the time required for stabilization and provides insights into the reliability during the operational phase and the commencement of the wear-out phase. By employing this methodology, designers can make informed decisions regarding sensor performance with regards to location accuracy, contributing to enhanced accuracy in satellite-based applications.

Keywords: bathtub curve, geometric performance, Laplace test, location accuracy, reliability analysis, Weibull analysis

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Authors: Sayed Isahaq Hossain, K. T. Chang, Moustapha Ndour

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Inference of the phreatic line through earth dams is of paramount importance because it could be directly associated with piping phenomena which may lead to the dam failure. Normally in the field, the instrumentations such as ‘diver’ and ‘standpipe’ are to be used to identify the seepage conditions which only provide point data with a fair amount of interpolation or assumption. Here in this paper, we employed high-resolution fiber optic cable sensors (FOCS) based on Raman Scattering in order to obtain a very accurate phreatic line and seepage profile. Unlike the above-mention devices which pinpoint the water level location, this kind of Distributed Fiber Optics Sensing gives us more reliable information due to its inherent characteristics of continuous measurement.

Keywords: standpipe, diver, FOCS, monitoring, Raman scattering

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Authors: Chun-Ming Huang, Yi-Jun Liu, Yi-Jie Hsieh, Jin-Ju Chue, Wei-Lin Lai, Chun-Yu Chen, Chih-Chyau Yang, Chien-Ming Wu

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The market of wearable devices has been growing rapidly in two years. The integration of sensors and wearable devices has become the trend of the next technology products. Thus, the academics and industries are eager to cultivate talented persons in sensing technology. Currently, academic and industries have more and more demands on the integrations of versatile sensors and applications, especially for the teams who focus on the development of sensor circuit architectures. These teams tape-out many MEMs sensors chips through the chip fabrication service from National Chip Implementation Center (CIC). However, most of these teams are only able to focus on the circuit design of MEMs sensors; they lack the key support of further system demonstration. This paper follows the CIC’s main mission of promoting the chip/system advanced design technology and aims to establish the environments of the modularized sensing system platform and the system design flow with the measurement and calibration technology. These developed environments are used to support these research teams and help academically advanced sensor designs to perform the system demonstration. Thus, the research groups can promote and transfer their advanced sensor designs to industrial and further derive the industrial economic values. In this paper, the modularized sensing platform is proposed to enable the system demonstration for advanced sensor chip design. The environment of sensor measurement and calibration is established for academic to achieve an accurate sensor result. Two reference sensor designs cooperated with the modularized sensing platform are given to show the sensing system integration and demonstration. These developed environments and platforms are currently provided to academics in Taiwan, and so that the academics can obtain a better environment to perform the system demonstration and improve the research and teaching quality.

Keywords: modularized sensing platform, sensor design and calibration, sensor system, sensor system design flow

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Authors: S. Cobos-Guzman

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This paper presents the results of a mechatronic design based on a 4-wheel omnidirectional mobile robot that can be used in indoor logistic applications. The low-level control has been selected using two open-source hardware (Raspberry Pi 3 Model B+ and Arduino Mega 2560) that control four industrial motors, four ultrasound sensors, four optical encoders, a vision system of two cameras, and a Hokuyo URG-04LX-UG01 laser scanner. Moreover, the system is powered with a lithium battery that can supply 24 V DC and a maximum current-hour of 20Ah.The Robot Operating System (ROS) has been implemented in the Raspberry Pi and the performance is evaluated with the selection of the sensors and hardware selected. The mechatronic system is evaluated and proposed safe modes of power distribution for controlling all the electronic devices based on different tests. Therefore, based on different performance results, some recommendations are indicated for using the Raspberry Pi and Arduino in terms of power, communication, and distribution of control for different devices. According to these recommendations, the selection of sensors is distributed in both real-time controllers (Arduino and Raspberry Pi). On the other hand, the drivers of the cameras have been implemented in Linux and a python program has been implemented to access the cameras. These cameras will be used for implementing a deep learning algorithm to recognize people and objects. In this way, the level of intelligence can be increased in combination with the maps that can be obtained from the laser scanner.

Keywords: autonomous, indoor robot, mechatronic, omnidirectional robot

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Authors: Sanaz Seraj, Shohre Rouhani

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Recently, graphene has gained much attention because of its unique optical, mechanical, electrical, and thermal properties. Graphene has been used as a key material in the technological applications in various areas such as sensors, drug delivery, super capacitors, transparent conductor, and solar cell. It has a superior quenching efficiency for various fluorophores. Based on these unique properties, the optical sensors with graphene materials as the energy acceptors have demonstrated great success in recent years. During quenching, the emission of a fluorophore is perturbed by a quencher which can be a substrate or biomolecule, and due to this phenomenon, fluorophore-quencher has been used for selective detection of target molecules. Among fluorescence dyes, 1,8-naphthalimide is well known for its typical intramolecular charge transfer (ICT) and photo-induced charge transfer (PET) fluorophore, strong absorption and emission in the visible region, high photo stability, and large Stokes shift. Derivatives of 1,8-naphthalimides have found applications in some areas, especially fluorescence sensors. Herein, the fluorescence quenching of graphene oxide has been carried out on a naphthalimide dye as a fluorescent probe model. The quenching ability of graphene oxide on naphthalimide dye was studied by UV-VIS and fluorescence spectroscopy. This study showed that graphene is an efficient quencher for fluorescent dyes. Therefore, it can be used as a suitable candidate sensing platform. To the best of our knowledge, studies on the quenching and absorption of naphthalimide dyes by graphene oxide are rare.

Keywords: fluorescence, graphene oxide, naphthalimide dye, quenching

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Authors: Dilip K. Paul

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The most popular mesoporous molecular sieves, Mobil Composition of Matter (MCM) are keenly studied by researchers because of these materials possess amorphous silica wall and have a long range of ordered framework with uniform mesopores. These materials also possess large surface area, which can be up to more than 1000 m2g−1. Herein the investigation is focused upon the synthesis and characterization of chromium and aluminum doped MCM-41 using XRD and FTIR. Acid-base properties of Cr-Al-MCM 41 was investigated by molecularly sensitive transmission FT-IR spectroscopy by adsorbing pyridine. In addition, these MCM nanomaterial was used to catalyze C-C bond formation from acetaldehyde adsorption. The assignment of all infrared peaks during adsorption of pyridine provided detail information on the presence of acid-base sites which in turn helped us to explain the roles of these in the condensation reaction of aldehyde. Reaction mechanisms of C-C bond formation is therefore explored to shed some light on this elusive reaction detail.

Keywords: mesoporous nanomaterial, MCM 41, FTIR studies, acid-base studies

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Authors: Seok-Tae Yoon, Jae-Yeong Choi, Gyu-Mok Jeon, Yong-Jin Cho, Jong-Chun Park

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Conventional submarines obtain propulsive force by using an electric propulsion system consisting of a diesel generator, battery, motor, and propeller. In the underwater, the submarine uses the electric power stored in the battery. After that, when a certain amount of electric power is consumed, the submarine floats near the sea water surface and recharges the electric power by using the diesel generator. The voyage carried out while charging the power is called a snorkel, and the high-temperature exhaust gas from the diesel generator forms a heat distribution on the sea water surface. The heat distribution is detected by weapon system equipped with thermo-detector and that is the main cause of reducing the survivability of the submarine. In this paper, an experimental study was carried out to establish optimal operating conditions of a submarine for reduction of infrared signature radiated from the sea water surface. For this, a hot gas generating system and a round acrylic water tank with adjustable water level were made. The control variables of the experiment were set as the mass flow rate, the temperature difference between the water and the hot gas in the water tank, and the water level difference between the air outlet and the water surface. The experimental instrumentation used a thermocouple of T-type to measure the released air temperature on the surface of the water, and a thermography system to measure the thermal energy distribution on the water surface. As a result of the experiment study, we analyzed the correlation between the final released temperature of the exhaust pipe exit in a submarine and the depth of the snorkel, and presented reasonable operating conditions for the infrared signature reduction of submarine.

Keywords: experiment study, flow rate, infrared signature, snorkeling, thermography

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Authors: Ke Lin, Steve Wu Qing Yang, Zhang Nan

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The medicine and drugs has in the past been manufactured to the final products and then used laboratory analysis to verify their quality. However the industry needs crucially a monitoring technique for the final batch to batch quality check. The introduction of process analytical technology (PAT) provides an incentive to obtain real-time information about drugs on the production line, with the following optical techniques being considered: near-infrared (NIR) spectroscopy, Raman spectroscopy and imaging, mid-infrared spectroscopy with the use of chemometric techniques to quantify the final product. However, presents problems in that the spectra obtained will consist of many combination and overtone bands of the fundamental vibrations observed, making analysis difficult. In this work, we describe a non-destructive system and method for capsule and liquid medicine identification, more particularly, using terahertz time-domain spectroscopy and/or designed terahertz portable system for identifying different types of medicine in the package of capsule or in liquid medicine bottles. The target medicine can be detected directly, non-destructively and non-invasively.

Keywords: terahertz, non-destructive, non-invasive, chemical identification

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Authors: Gaëtan Calvar, Christophe Bouvier, Alexis Blasselle

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This paper presents the Sea Striker, a compact hydrofoil designed with the goal to address some of the issues raised by the recent evolutions of naval missions, threats and operation theatres in modern warfare. Able to perform a wide range of operations, the Sea Striker is a 40-meter stealth surface combatant equipped with a gas turbine and aft and forward foils to reach high speeds. The Sea Striker's stealthiness is enabled by the combination of composite structure, exterior design, and the advanced integration of sensors. The ship is fitted with a powerful and adaptable combat system, ensuring a versatile and efficient response to modern threats. Lightly Manned with a core crew of 10, this hydrofoil is highly automated and can be remoted pilote for special force operation or transit. Such a kind of ship is not new: it has been used in the past by different navies, for example, by the US Navy with the USS Pegasus. Nevertheless, the recent evolutions in science and technologies on the one hand, and the emergence of new missions, threats and operation theatres, on the other hand, put forward its concept as an answer to nowadays operational challenges. Indeed, even if multiples opinions and analyses can be given regarding the modern warfare and naval surface operations, general observations and tendencies can be drawn such as the major increase in the sensors and weapons types and ranges and, more generally, capacities; the emergence of new versatile and evolving threats and enemies, such as asymmetric groups, swarm drones or hypersonic missile; or the growing number of operation theatres located in more coastal and shallow waters. These researches were performed with a complete study of the ship after several operational performance computations in order to justify the relevance of using ships like the Sea Striker in naval surface operations. For the selected scenarios, the conception process enabled to measure the performance, namely a “Measure of Efficiency” in the NATO framework for 2 different kinds of models: A centralized, classic model, using large and powerful ships; and A distributed model relying on several Sea Strikers. After this stage, a was performed. Lethal, agile, stealth, compact and fitted with a complete set of sensors, the Sea Striker is a new major player in modern warfare and constitutes a very attractive response between the naval unit and the combat helicopter, enabling to reach high operational performances at a reduced cost.

Keywords: surface combatant, compact, hydrofoil, stealth, velocity, lethal

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Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

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Authors: Ajay Krishnamurthy, Mariyappan Mahesh Kumar, Sellamuthu Periyar Selvam

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Fruits are considered as functional foods due to the presence of various bioactive compounds available such as polyphenols, which are beneficial to health when consumed as part of our diet. The primary objective of this study was to analyze the various functional groups present in ethanolic extracts of Hylocereus undatus and Garcinia indica and also measure their antibacterial and antioxidant potential respectively thereby affirming its nutraceutical potential. To fulfill our objective, a Fourier - transform Infrared Spectroscopy (FTIR) was conducted for functional group analysis, Total Phenolic Content and DPPH free radical scavenging activity for measuring it anti-oxidant potential and agar-well diffusion assay for antibacterial potential. On careful observation and analysis of the spectrum it was found that both the fruit extracts contain similar compounds viz. Phenols, Alkanes, Alkenes, Aldehydes, Ketones, Carboxylic Acid and Amines. Total phenolic content of H.undatus and G.indica was estimated to be (26.85 ± 1.84 mg GAE/100g) and (32.84 ± 1.63 mg GAE/100g) respectively which corresponds to an inhibition of 84% and 81% respectively. H.undatus shows an inhibition of (3.4 ± 2.1mm) in gram-positive and (4.2 ± 2.24mm) in gram-negative organism on the other hand G.indica shows (2.1 ± 0.98mm) in gram-positive and (3.1 ± 1.44mm) in gram negative. The presence of such diverse compounds in the fruits helps us to understand the necessity for the inclusion of fruits in our daily diet and also helps the pharmaceutical industry in realizing the importance of exotic fruits as a potential nutraceutical.

Keywords: DPPH, fourier-transform infrared spectroscopy (FTIR), Hylocereus undatus, Garcinia indica

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Authors: Yoganathan Karthik, Guhanathan Poravi

Abstract:

Colorizing near-infrared (NIR) images poses unique challenges due to the absence of color information and the nuances in light absorption. In this paper, we present an approach to NIR image colorization utilizing a synthetic dataset generated from visible light images. Our method addresses two major challenges encountered in NIR image colorization: accurately colorizing objects with color variations and avoiding over/under saturation in dimly lit scenes. To tackle these challenges, we propose a Generative Adversarial Network (GAN)-based framework that learns to map NIR images to their corresponding colorized versions. The synthetic dataset ensures diverse color representations, enabling the model to effectively handle objects with varying hues and shades. Furthermore, the GAN architecture facilitates the generation of realistic colorizations while preserving the integrity of dimly lit scenes, thus mitigating issues related to over/under saturation. Experimental results on benchmark NIR image datasets demonstrate the efficacy of our approach in producing high-quality colorizations with improved color accuracy and naturalness. Quantitative evaluations and comparative studies validate the superiority of our method over existing techniques, showcasing its robustness and generalization capability across diverse NIR image scenarios. Our research not only contributes to advancing NIR image colorization but also underscores the importance of synthetic datasets and GANs in addressing domain-specific challenges in image processing tasks. The proposed framework holds promise for various applications in remote sensing, medical imaging, and surveillance where accurate color representation of NIR imagery is crucial for analysis and interpretation.

Keywords: computer vision, near-infrared images, automatic image colorization, generative adversarial networks, synthetic data

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Authors: Armel Asongu Nkembi, Ahmad Fawad

Abstract:

In this paper, we design a smart car parking system using the Node-Red interface, which enables the user to find the nearest parking area from his current location and gives the availability of parking slots in that respective parking area. The closest parking area is determined by sending an HTTP request to an API, and the shortest distance is computed using some mathematical formulations based on the coordinates retrieved. There is also the use of IR sensors to signal the availability or lack of available parking lots within any parking area. The aim is to reduce the time and effort needed to find empty parking lots and also avoid unnecessary traveling through filled parking lots in a parking area. Thus, it reduces fuel consumption, which in turn reduces carbon footprints in the atmosphere and, overall, makes the city much smarter.

Keywords: node-red, smart parking system, API, http request, IR sensors, Internet of Things, smart city, parking lots.

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Authors: Gubiani Rino, Nicola Zucchiatti, Da Broi Ugo, Bietresato Marco

Abstract:

The problem of vibrations in agriculture is very important due to the different types of machinery used for the different types of soil in which work is carried out. One of the most commonly used machines is the tractor, where the phenomenon has been studied for a long time by measuring the whole body and placing the sensor on the seat. However, this measurement system does not take into account the characteristics of the drivers, such as their body index (BMI), their gender (male, female) or the muscle fatigue they are subjected to, which is highly dependent on their age for example. The aim of the research was therefore to place sensors not only on the seat but along the spinal column to check the transmission of vibration on drivers with different BMI on different tractors and at different travel speeds and of different genders. The test was also done using wearable sensors such as a dynamometer applied to the muscles, the data of which was correlated with the vibrations produced by the tractor. Initial data show that even on new tractors with pneumatic seats, the vibrations attenuate little and are still correlated with the roughness of the track travelled and the forward speed. Another important piece of data are the root-mean square values referred to 8 hours (A(8)x,y,z) and the maximum transient vibration values (MTVVx,y,z) and, the latter, the MTVVz values were problematic (limiting factor in most cases) and always aggravated by the speed. The MTVVx values can be lowered by having a tyre-pressure adjustment system, able to properly adjust the tire pressure according to the specific situation (ground, speed) in which a tractor is operating.

Keywords: fatigue, effect vibration on health, tractor driver vibrations, vibration, muscle skeleton disorders

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Authors: Lovepreet Kaur Dhugga, Dwijendra P. Singh

Abstract:

Calcium copper titanate (CCTO) was synthesized via the sol-gel auto-combustion method. The precursor was calcined at 800°C and 1000°C for 6 hours providing brown-coloured powders, which were pelletized and sintered at 1000°C for 12 hrs to determine their dielectric behaviour in the frequency range (100Hz-10MHz) at room temperature. The dielectric constant(εr) and loss tangent (tanδ) has been found to be ~ 6153 and 0.5 for 800°C and ~ 5504 and 0.2 for 1000°C respectively, at frequency 1kHz. Microstructure study revealed maximum grain growth occurs in sample calcined at 800°C, responsible for its high dielectric constant. Phase identification of CaCu₃Ti₄O₁₂ has been carried out through X-ray diffraction. It can be used in various electronic applications as it shows large εᵣ and low tanδ values over a wide frequency spectrum, including energy storage devices, microwave shielding, and sensors.

Keywords: calcium copper titanate, dielectric behaviour, microstructure, X-ray diffraction

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Authors: Prakher Mishra, Dikshant Bodana, Saloni Desai, Sudhanshu Dixit, Sopan Agarwal, Shriraj Patel

Abstract:

Railways are sometimes lifeline of nations as they consist of huge network of rail lines and bridges. Reportedly many of the bridges are aging, weak, distressed and accident prone. It becomes a really challenging task for Engineers and workers to keep up a regular maintenance schedule for proper functioning which itself is quite a hard hitting job. In this paper we have come up with an innvovative wireless system of maintenance called BriMAIN. In this system we have installed two types of sensors, first one is called a force sensor which will continously analyse the readings of pressure at joints of the bridges and secondly an MPU-6050 triaxial gyroscope+accelerometer which will analyse the deflection of the deck of the bridge. Apart from this a separate database is also being made at the server room so that the data can be visualized by the engineers and a warning can be issued in case reading of the sensors goes above threshold.

Keywords: Accelerometer, B-MAIN, Gyroscope, MPU-6050

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Authors: Vinita Choudhary

Abstract:

Solidly Acoustic Resonators (SMR) based on ZnO piezoelectric material operating at a frequency of 3.96 GHz and 6.49% coupling factor are used to characterize liquids with different viscosities. This behavior of the sensor is analyzed using Finite Element Modeling. Device architectures encapsulate bulk acoustic wave resonators with MO/SiO₂ Bragg mirror reflector and the silicon substrate. The proposed SMR is based on the mass loading effect response of the sensor to the change in the resonant frequency of the resonator that is caused by the increased density due to the absorption of liquids (water, acetone, olive oil) used in theoretical calculation. The sensitivity of sensors ranges from 0.238 MHz/mPa.s to 83.33 MHz/mPa.s, supported by the Kanazawa model. Obtained results are also compared with previous works on BAW viscosity sensors.

Keywords: solidly mounted resonator, bragg mirror, kanazawa model, finite element model

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