Search results for: multi sensor image fusion
7318 Industrial Practical Training for Mechanical Engineering Students: A Multidisciplinary Approach
Authors: Bashiru Olayinka Adisa, Najeem Lateef
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The integrated knowledge in the application of mechanical engineering, microprocessor and electronic sensor technologies is becoming the basic skill of a modern engineer in machinery based processes. To meet this objective, we have developed a cross-disciplinary industrial training to teach essential hard technical and soft project skills to the mechanical engineering students in mid-curriculum. Ten groups of students were selected to participate in a 150 hour program. The students were required to design and build a robot with ability to follow tracks and pick/place target blocks in specific locations. The students were trained to integrate the knowledge of computer aid design, electronics, sensor theories and motor technology to fabricate a workable robot as a major outcome of this course. On completion of the project, students competed for top robot honors by demonstrating their robots' movements and performance in pick/place to a panel of judges.Keywords: electronics, sensor theories and motor, robot, technology
Procedia PDF Downloads 2807317 Nutritional Status and Body Image Perception among Thai Adolescents
Authors: Nareemarn Neelapaichit, Sookfong Wongsathapat, Noppawan Piaseu
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Body image plays an important role in adolescents. Thai adolescents put high concern on their body image result in unsatisfied their body shapes. Therefore, inappropriate weight management methods have been used. This study examined the body image perception and the nutritional status of Thai adolescents. Body mass index screening was done on 181 nursing students of Ramathibodi School of Nursing to categorized obesity, overweight, normal weight and underweight respondents by using recommended body-mass index (BMI) cut-off points for Asian populations. Self report questionnaire on demographics and body image perception were completed. Results showed that the respondents were mainly female (93.4%) and their mean age were 19.2 years. The prevalence of obesity, overweight, normal weight and underweight of the nursing students were 5.5%, 7.2%, 55.2% and 32.0%, respectively. Of all the respondents, 57.5% correctly perceived themselves, with 37.0% overestimating and 5.5% underestimating their weight status. Of those in the obesity category, 20.0% correctly perceived themselves and 80.0% perceived themselves as overweight. For overweight category, total respondents correctly perceived themselves. Fifty two percent of the normal weight respondents perceived themselves as overweight and 2.0% perceived themselves as obesity. Of the underweight respondents, 77.6% correctly perceived themselves and 20.7% perceived themselves as normal weight. These findings show high occurrence of body image misperception among Thai adolescents. Being concerned with this situation can promote adolescents for healthy weight and practice appropriate weight management methods.Keywords: nutritional status, body image perception, Thai adolescents, body-mass index (BMI)
Procedia PDF Downloads 3977316 Characterization of Agroforestry Systems in Burkina Faso Using an Earth Observation Data Cube
Authors: Dan Kanmegne
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Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification
Procedia PDF Downloads 1457315 Dielectric Properties of NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄ Ceramics at Microwave Frequency
Authors: Yih-Chien Chen, Tse-Lung Lin
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The microwave characteristics of NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄ are studied to determine the feasibility of their use in the liquid sensor. The microwave characteristics of NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄ are determined using X-ray diffraction (XRD) patterns. The permittivity (𝜀r) of NdTi₍₀.₄₉₎Ge₀.₀₁Mo₀.₅O₄ that is sintered at 1425 ℃ for 4 h is 17.6, the unloaded quality factor (Qu×f) is 33,400 GHz, and it has a temperature coefficient at the resonance frequency (TCF) of -30.7 ppm/℃. The proposed liquid sensor is at the 5G FR1 bands.Keywords: NdTi₍₀.₅₋ₓ₎GeₓMo₀.₅O₄, X-ray diffraction pattern, permittivity, Unloaded quality factor
Procedia PDF Downloads 2937314 Root Mean Square-Based Method for Fault Diagnosis and Fault Detection and Isolation of Current Fault Sensor in an Induction Machine
Authors: Ahmad Akrad, Rabia Sehab, Fadi Alyoussef
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Nowadays, induction machines are widely used in industry thankful to their advantages comparing to other technologies. Indeed, there is a big demand because of their reliability, robustness and cost. The objective of this paper is to deal with diagnosis, detection and isolation of faults in a three-phase induction machine. Among the faults, Inter-turn short-circuit fault (ITSC), current sensors fault and single-phase open circuit fault are selected to deal with. However, a fault detection method is suggested using residual errors generated by the root mean square (RMS) of phase currents. The application of this method is based on an asymmetric nonlinear model of Induction Machine considering the winding fault of the three axes frame state space. In addition, current sensor redundancy and sensor fault detection and isolation (FDI) are adopted to ensure safety operation of induction machine drive. Finally, a validation is carried out by simulation in healthy and faulty operation modes to show the benefit of the proposed method to detect and to locate with, a high reliability, the three types of faults.Keywords: induction machine, asymmetric nonlinear model, fault diagnosis, inter-turn short-circuit fault, root mean square, current sensor fault, fault detection and isolation
Procedia PDF Downloads 1997313 Highly Sensitive Nanostructured Chromium Oxide Sensor for Analysis of Diabetic Patient’s Breath
Authors: Nipin Kohli, Ravi Chand Singh
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Diabetes mellitus is a serious illness and can be life-threatening if left untreated. Acetone present in the exhaled breath of a diabetic person is a biomarker of patients suffering from diabetes mellitus and is higher than its usual concentration present in the breath of healthy people. In the present work, a portable gas sensor system based on chromium oxide (Cr₂O₃) nanoparticles has been developed that can analyze diabetic patient’s breath. Undoped and indium (In) doped Cr₂O₃ nanoparticles were synthesized by a chemical route and characterized by X-ray diffraction, scanning electron microscopy, Raman spectroscopy, UV-visible spectroscopy, and photoluminescence spectroscopy for their structural, morphological and optical properties. Thick film gas sensors were fabricated out of synthesized samples. To diagnose diabetes, the sensors’ response to low concentrations of acetone was measured, and it was found that the addition of indium dramatically enhances the acetone gas sensing response. Moreover, the fabricated sensors were highly stable, reproducible and resistant to humidity. Enhancement of sensor response of doped sensors towards acetone can be ascribed to increase in defects due to addition of a dopant, and it was found that in-doped Cr₂O₃ sensors are more useful for analysis of breath of diabetic patients.Keywords: Diabetes mellitus, nanoparticles, raman spectroscopy, sensor
Procedia PDF Downloads 1437312 A Study on Optimum Shape in According to Equivalent Stress Distributions at the Die and Plug in the Multi-Pass Drawing Process
Authors: Yeon-Jong Jeong, Mok-Tan Ahn, Seok-Hyeon Park, Seong-Hun Ha, Joon-Hong Park, Jong-Bae Park
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Multi-stage drawing process is an important technique for forming a shape that cannot be molded in a single process. multi-stage drawing process in number of passes and the shape of the die are an important factors influencing the productivity and formability of the product. The number and shape of the multi-path in the mold of the drawing process is very influencing the productivity and formability of the product. Half angle of the die and mandrel affects the drawing force and it also affects the completion of the final shape. Thus reducing the number of pass and the die shape optimization are necessary to improve the formability of the billet. Analyzing the load on the die through the FEM analysis and in consideration of the formability of the material presents a die model.Keywords: multi-pass shape drawing, equivalent stress, FEM, finite element method, optimum shape
Procedia PDF Downloads 4817311 Human-Centric Sensor Networks for Comfort and Productivity in Offices: Integrating Environmental, Body Area Network, and Participatory Sensing
Authors: Chenlu Zhang, Wanni Zhang, Florian Schaule
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Indoor environment in office buildings directly affects comfort, productivity, health, and well-being of building occupants. Wireless environmental sensor networks have been deployed in many modern offices to monitor and control the indoor environments. However, indoor environmental variables are not strong enough predictors of comfort and productivity levels of every occupant due to personal differences, both physiologically and psychologically. This study proposes human-centric sensor networks that integrate wireless environmental sensors, body area network sensors and participatory sensing technologies to collect data from both environment and human and support building operations. The sensor networks have been tested in one small-size and one medium-size office rooms with 22 participants for five months. Indoor environmental data (e.g., air temperature and relative humidity), physiological data (e.g., skin temperature and Galvani skin response), and physiological responses (e.g., comfort and self-reported productivity levels) were obtained from each participant and his/her workplace. The data results show that: (1) participants have different physiological and physiological responses in the same environmental conditions; (2) physiological variables are more effective predictors of comfort and productivity levels than environmental variables. These results indicate that the human-centric sensor networks can support human-centric building control and improve comfort and productivity in offices.Keywords: body area network, comfort and productivity, human-centric sensors, internet of things, participatory sensing
Procedia PDF Downloads 1397310 Feature Weighting Comparison Based on Clustering Centers in the Detection of Diabetic Retinopathy
Authors: Kemal Polat
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In this paper, three feature weighting methods have been used to improve the classification performance of diabetic retinopathy (DR). To classify the diabetic retinopathy, features extracted from the output of several retinal image processing algorithms, such as image-level, lesion-specific and anatomical components, have been used and fed them into the classifier algorithms. The dataset used in this study has been taken from University of California, Irvine (UCI) machine learning repository. Feature weighting methods including the fuzzy c-means clustering based feature weighting, subtractive clustering based feature weighting, and Gaussian mixture clustering based feature weighting, have been used and compered with each other in the classification of DR. After feature weighting, five different classifier algorithms comprising multi-layer perceptron (MLP), k- nearest neighbor (k-NN), decision tree, support vector machine (SVM), and Naïve Bayes have been used. The hybrid method based on combination of subtractive clustering based feature weighting and decision tree classifier has been obtained the classification accuracy of 100% in the screening of DR. These results have demonstrated that the proposed hybrid scheme is very promising in the medical data set classification.Keywords: machine learning, data weighting, classification, data mining
Procedia PDF Downloads 3267309 On Privacy-Preserving Search in the Encrypted Domain
Authors: Chun-Shien Lu
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Privacy-preserving query has recently received considerable attention in the signal processing and multimedia community. It is also a critical step in wireless sensor network for retrieval of sensitive data. The purposes of privacy-preserving query in both the areas of signal processing and sensor network are the same, but the similarity and difference of the adopted technologies are not fully explored. In this paper, we first review the recently developed methods of privacy-preserving query, and then describe in a comprehensive manner what we can learn from the mutual of both areas.Keywords: encryption, privacy-preserving, search, security
Procedia PDF Downloads 2567308 Multi-Pass Shape Drawing Process Design for Manufacturing of Automotive Reinforcing Agent with Closed Cross-Section Shape using Finite Element Method Analysis
Authors: Mok-Tan Ahn, Hyeok Choi, Joon-Hong Park
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Multi-stage drawing process is an important technique for forming a shape that cannot be molded in a single process. multi-stage drawing process in number of passes and the shape of the die are an important factor influencing the productivity and moldability of the product. The number and shape of the multi-path in the mold of the drawing process is very influencing the productivity and moldability of the product. Half angle of the die and mandrel affects the drawing force and it also affects the completion of the final shape. Thus reducing the number of pass and the die shape optimization are necessary to improve the formability of the billet. The purpose of this study, Analyzing the load on the die through the FEM analysis and in consideration of the formability of the material presents a die model.Keywords: automotive reinforcing agent, multi-pass shape drawing, automotive parts, FEM analysis
Procedia PDF Downloads 4557307 Reversible and Adaptive Watermarking for MRI Medical Images
Authors: Nisar Ahmed Memon
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A new medical image watermarking scheme delivering high embedding capacity is presented in this paper. Integer Wavelet Transform (IWT), Companding technique and adaptive thresholding are used in this scheme. The proposed scheme implants, recovers the hidden information and restores the input image to its pristine state at the receiving end. Magnetic Resonance Imaging (MRI) images are used for experimental purposes. The scheme first segment the MRI medical image into non-overlapping blocks and then inserts watermark into wavelet coefficients having a high frequency of each block. The scheme uses block-based watermarking adopting iterative optimization of threshold for companding in order to avoid the histogram pre and post processing. Results show that proposed scheme performs better than other reversible medical image watermarking schemes available in literature for MRI medical images.Keywords: adaptive thresholding, companding technique, data authentication, reversible watermarking
Procedia PDF Downloads 2967306 Optimisation of Energy Harvesting for a Composite Aircraft Wing Structure Bonded with Discrete Macro Fibre Composite Sensors
Authors: Ali H. Daraji, Ye Jianqiao
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The micro electrical devices of the wireless sensor network are continuously developed and become very small and compact with low electric power requirements using limited period life conventional batteries. The low power requirement for these devices, cost of conventional batteries and its replacement have encouraged researcher to find alternative power supply represented by energy harvesting system to provide an electric power supply with infinite period life. In the last few years, the investigation of energy harvesting for structure health monitoring has increased to powering wireless sensor network by converting waste mechanical vibration into electricity using piezoelectric sensors. Optimisation of energy harvesting is an important research topic to ensure a flowing of efficient electric power from structural vibration. The harvesting power is mainly based on the properties of piezoelectric material, dimensions of piezoelectric sensor, its position on a structure and value of an external electric load connected between sensor electrodes. Larger surface area of sensor is not granted larger power harvesting when the sensor area is covered positive and negative mechanical strain at the same time. Thus lead to reduction or cancellation of piezoelectric output power. Optimisation of energy harvesting is achieved by locating these sensors precisely and efficiently on the structure. Limited published work has investigated the energy harvesting for aircraft wing. However, most of the published studies have simplified the aircraft wing structure by a cantilever flat plate or beam. In these studies, the optimisation of energy harvesting was investigated by determination optimal value of an external electric load connected between sensor electrode terminals or by an external electric circuit or by randomly splitting piezoelectric sensor to two segments. However, the aircraft wing structures are complex than beam or flat plate and mostly constructed from flat and curved skins stiffened by stringers and ribs with more complex mechanical strain induced on the wing surfaces. This aircraft wing structure bonded with discrete macro fibre composite sensors was modelled using multiphysics finite element to optimise the energy harvesting by determination of the optimal number of sensors, location and the output resistance load. The optimal number and location of macro fibre sensors were determined based on the maximization of the open and close loop sensor output voltage using frequency response analysis. It was found different optimal distribution, locations and number of sensors bounded on the top and the bottom surfaces of the aircraft wing.Keywords: energy harvesting, optimisation, sensor, wing
Procedia PDF Downloads 3027305 A Hybrid Digital Watermarking Scheme
Authors: Nazish Saleem Abbas, Muhammad Haris Jamil, Hamid Sharif
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Digital watermarking is a technique that allows an individual to add and hide secret information, copyright notice, or other verification message inside a digital audio, video, or image. Today, with the advancement of technology, modern healthcare systems manage patients’ diagnostic information in a digital way in many countries. When transmitted between hospitals through the internet, the medical data becomes vulnerable to attacks and requires security and confidentiality. Digital watermarking techniques are used in order to ensure the authenticity, security and management of medical images and related information. This paper proposes a watermarking technique that embeds a watermark in medical images imperceptibly and securely. In this work, digital watermarking on medical images is carried out using the Least Significant Bit (LSB) with the Discrete Cosine Transform (DCT). The proposed methods of embedding and extraction of a watermark in a watermarked image are performed in the frequency domain using LSB by XOR operation. The quality of the watermarked medical image is measured by the Peak signal-to-noise ratio (PSNR). It was observed that the watermarked medical image obtained performing XOR operation between DCT and LSB survived compression attack having a PSNR up to 38.98.Keywords: watermarking, image processing, DCT, LSB, PSNR
Procedia PDF Downloads 477304 Geographic Information System Using Google Fusion Table Technology for the Delivery of Disease Data Information
Authors: I. Nyoman Mahayasa Adiputra
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Data in the field of health can be useful for the purposes of data analysis, one example of health data is disease data. Disease data is usually in a geographical plot in accordance with the area. Where the data was collected, in the city of Denpasar, Bali. Disease data report is still published in tabular form, disease information has not been mapped in GIS form. In this research, disease information in Denpasar city will be digitized in the form of a geographic information system with the smallest administrative area in the form of district. Denpasar City consists of 4 districts of North Denpasar, East Denpasar, West Denpasar and South Denpasar. In this research, we use Google fusion table technology for map digitization process, where this technology can facilitate from the administrator and from the recipient information. From the administrator side of the input disease, data can be done easily and quickly. From the receiving end of the information, the resulting GIS application can be published in a website-based application so that it can be accessed anywhere and anytime. In general, the results obtained in this study, divided into two, namely: (1) Geolocation of Denpasar and all of Denpasar districts, the process of digitizing the map of Denpasar city produces a polygon geolocation of each - district of Denpasar city. These results can be utilized in subsequent GIS studies if you want to use the same administrative area. (2) Dengue fever mapping in 2014 and 2015. Disease data used in this study is dengue fever case data taken in 2014 and 2015. Data taken from the profile report Denpasar Health Department 2015 and 2016. This mapping can be useful for the analysis of the spread of dengue hemorrhagic fever in the city of Denpasar.Keywords: geographic information system, Google fusion table technology, delivery of disease data information, Denpasar city
Procedia PDF Downloads 1297303 Neural Network Based Compressor Flow Estimator in an Aircraft Vapor Cycle System
Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini
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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor
Procedia PDF Downloads 1467302 The Analysis of the Effect of Brand Image on Creating Brand Loyalty with the Structural Equation Model: A Research Study on the Sports Equipment Brand Users
Authors: Murat Erdoğdu, Murat Koçyiğit
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Brand image and brand loyalty are among the most important relational marketing elements for brand owners to be able to set up long – term relationships with their customers and to maintain these relationships. Brand owners improve their brand images with the positive perceptions remaining in the consumers’ minds. In addition, they try to find the customers that are both emotionally and behaviourally faithful to themselves in order to set up long – term relationships. Therefore, the aim of this study is to analyse the effects of the brand image that has a very important role among relational marketing elements on the brand loyalty in terms of the variables such as the perceived value, the trust in brand and the brand satisfaction. In this context, a conceptual model was created to determine the effect of the brand image on the brand loyalty thanks to the Structural Equation Model (SEM). According to this aim and this model, the study was carried out in the scope of the data collected through the questionnaires in Konya with the method of convenience sampling. The results of the research showed that the brand image has positive significant effects on the perceived value and the trust in brand and that the trust in brand has positive significant effects on the brand satisfaction, and that the brand satisfaction has positive significant effects on the brand loyalty. Thus, the hypotheses that the brand image has direct effects on the perceived value and the trust in brand and that the trust in brand has direct effects on the brand satisfaction and that the brand satisfaction has direct effects on the brand loyalty were supported. In addition, the findings about whether the perceived value has a significant effect on the brand satisfaction were also acquired.Keywords: brand image, brand loyalty, perceived value, satisfaction, trust
Procedia PDF Downloads 4407301 The Application of Image Analyzer to Study the Effects of Pericarp in the Imbibition Process of Melia dubia Seeds
Authors: Satya Srii, V., Nethra, N.
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An image analyzer system is described to study the process of imbibition in Melia dubia seeds. The experimental system consisted of control C (seeds with intact pericarp) with two treatments, namely T1 (seeds with pericarp punctured) and T2 (naked seeds without pericarp). The measurement software in the image analyzer can determine the area and perimeter as descriptors of changes in seed size during swelling resulting from imbibition. Using the area and perimeter parameter, the imbibition process in C, T1, and T2 was described by a series of curves similar to the triphasic pattern of water uptake, with the extent and rate depending upon the treatment. Naked seeds without pericarp (T2) took lesser time to reach phase III during imbition followed by seeds with pericarp punctured (T1) while the seeds with intact pericarp (C) were the slowest to attain phase III. This shows the effect of pericarp in acting as a potential inhibitor to imbibition inducing a large delay in germination. The sensitivity and feasibility of the method to investigate individual seeds within a population imply that the image analyzer has high potential in seed biology studies.Keywords: germination, imbibition, image analyzer, Melia dubia, pericarp
Procedia PDF Downloads 1397300 Influence of High-Resolution Satellites Attitude Parameters on Image Quality
Authors: Walid Wahballah, Taher Bazan, Fawzy Eltohamy
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One of the important functions of the satellite attitude control system is to provide the required pointing accuracy and attitude stability for optical remote sensing satellites to achieve good image quality. Although offering noise reduction and increased sensitivity, time delay and integration (TDI) charge coupled devices (CCDs) utilized in high-resolution satellites (HRS) are prone to introduce large amounts of pixel smear due to the instability of the line of sight. During on-orbit imaging, as a result of the Earth’s rotation and the satellite platform instability, the moving direction of the TDI-CCD linear array and the imaging direction of the camera become different. The speed of the image moving on the image plane (focal plane) represents the image motion velocity whereas the angle between the two directions is known as the drift angle (β). The drift angle occurs due to the rotation of the earth around its axis during satellite imaging; affecting the geometric accuracy and, consequently, causing image quality degradation. Therefore, the image motion velocity vector and the drift angle are two important factors used in the assessment of the image quality of TDI-CCD based optical remote sensing satellites. A model for estimating the image motion velocity and the drift angle in HRS is derived. The six satellite attitude control parameters represented in the derived model are the (roll angle φ, pitch angle θ, yaw angle ψ, roll angular velocity φ֗, pitch angular velocity θ֗ and yaw angular velocity ψ֗ ). The influence of these attitude parameters on the image quality is analyzed by establishing a relationship between the image motion velocity vector, drift angle and the six satellite attitude parameters. The influence of the satellite attitude parameters on the image quality is assessed by the presented model in terms of modulation transfer function (MTF) in both cross- and along-track directions. Three different cases representing the effect of pointing accuracy (φ, θ, ψ) bias are considered using four different sets of pointing accuracy typical values, while the satellite attitude stability parameters are ideal. In the same manner, the influence of satellite attitude stability (φ֗, θ֗, ψ֗) on image quality is also analysed for ideal pointing accuracy parameters. The results reveal that cross-track image quality is influenced seriously by the yaw angle bias and the roll angular velocity bias, while along-track image quality is influenced only by the pitch angular velocity bias.Keywords: high-resolution satellites, pointing accuracy, attitude stability, TDI-CCD, smear, MTF
Procedia PDF Downloads 4027299 A Multi-Criteria Decision Making Approach for Disassembly-To-Order Systems under Uncertainty
Authors: Ammar Y. Alqahtani
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In order to minimize the negative impact on the environment, it is essential to manage the waste that generated from the premature disposal of end-of-life (EOL) products properly. Consequently, government and international organizations introduced new policies and regulations to minimize the amount of waste being sent to landfills. Moreover, the consumers’ awareness regards environment has forced original equipment manufacturers to consider being more environmentally conscious. Therefore, manufacturers have thought of different ways to deal with waste generated from EOL products viz., remanufacturing, reusing, recycling, or disposing of EOL products. The rate of depletion of virgin natural resources and their dependency on the natural resources can be reduced by manufacturers when EOL products are treated as remanufactured, reused, or recycled, as well as this will cut on the amount of harmful waste sent to landfills. However, disposal of EOL products contributes to the problem and therefore is used as a last option. Number of EOL need to be estimated in order to fulfill the components demand. Then, disassembly process needs to be performed to extract individual components and subassemblies. Smart products, built with sensors embedded and network connectivity to enable the collection and exchange of data, utilize sensors that are implanted into products during production. These sensors are used for remanufacturers to predict an optimal warranty policy and time period that should be offered to customers who purchase remanufactured components and products. Sensor-provided data can help to evaluate the overall condition of a product, as well as the remaining lives of product components, prior to perform a disassembly process. In this paper, a multi-period disassembly-to-order (DTO) model is developed that takes into consideration the different system uncertainties. The DTO model is solved using Nonlinear Programming (NLP) in multiple periods. A DTO system is considered where a variety of EOL products are purchased for disassembly. The model’s main objective is to determine the best combination of EOL products to be purchased from every supplier in each period which maximized the total profit of the system while satisfying the demand. This paper also addressed the impact of sensor embedded products on the cost of warranties. Lastly, this paper presented and analyzed a case study involving various simulation conditions to illustrate the applicability of the model.Keywords: closed-loop supply chains, environmentally conscious manufacturing, product recovery, reverse logistics
Procedia PDF Downloads 1377298 Crab Shell Waste Chitosan-Based Thin Film for Acoustic Sensor Applications
Authors: Maydariana Ayuningtyas, Bambang Riyanto, Akhiruddin Maddu
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Industrial waste of crustacean shells, such as shrimp and crab, has been considered as one of the major issues contributing to environmental pollution. The waste processing mechanisms to form new, practical substances with added value have been developed. Chitosan, a derived matter from chitin, which is obtained from crab and shrimp shells, performs prodigiously in broad range applications. A chitosan composite-based diaphragm is a new inspiration in fiber optic acoustic sensor advancement. Elastic modulus, dynamic response, and sensitivity to acoustic wave of chitosan-based composite film contribute great potentials of organic-based sound-detecting material. The objective of this research was to develop chitosan diaphragm application in fiber optic microphone system. The formulation was conducted by blending 5% polyvinyl alcohol (PVA) solution with dissolved chitosan at 0%, 1% and 2% in 1:1 ratio, respectively. Composite diaphragms were characterized for the morphological and mechanical properties to predict the desired acoustic sensor sensitivity. The composite with 2% chitosan indicated optimum performance with 242.55 µm thickness, 67.9% relative humidity, and 29-76% light transmittance. The Young’s modulus of 2%-chitosan composite material was 4.89×104 N/m2, which generated the voltage amplitude of 0.013V and performed sensitivity of 3.28 mV/Pa at 1 kHz. Based on the results above, chitosan from crustacean shell waste can be considered as a viable alternative material for fiber optic acoustic sensor sensing pad development. Further, the research in chitosan utilisation is proposed as novel optical microphone development in anthropogenic noise controlling effort for environmental and biodiversity conservation.Keywords: acoustic sensor, chitosan, composite, crab shell, diaphragm, waste utilisation
Procedia PDF Downloads 2577297 Framework for Performance Measure of Super Resolution Imaging
Authors: Varsha Hemant Patil, Swati A. Bhavsar, Abolee H. Patil
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Image quality assessment plays an important role in image evaluation. This paper aims to present an investigation of classic techniques in use for image quality assessment, especially for super-resolution imaging. Researchers have contributed a lot towards the development of super-resolution imaging techniques. However, not much attention is paid to the development of metrics for testing the performance of developed techniques. In this paper, the study report of existing image quality measures is given. The paper classifies reviewed approaches according to functionality and suitability for super-resolution imaging. Probable modifications and improvements of these to suit super-resolution imaging are presented. The prime goal of the paper is to provide a comprehensive reference source for researchers working towards super-resolution imaging and suggest a better framework for measuring the performance of super-resolution imaging techniques.Keywords: interpolation, MSE, PSNR, SSIM, super resolution
Procedia PDF Downloads 987296 Low-Noise Amplifier Design for Improvement of Communication Range for Wake-Up Receiver Based Wireless Sensor Network Application
Authors: Ilef Ketata, Mohamed Khalil Baazaoui, Robert Fromm, Ahmad Fakhfakh, Faouzi Derbel
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The integration of wireless communication, e. g. in real-or quasi-real-time applications, is related to many challenges such as energy consumption, communication range, latency, quality of service, and reliability. To minimize the latency without increasing energy consumption, wake-up receiver (WuRx) nodes have been introduced in recent works. Low-noise amplifiers (LNAs) are introduced to improve the WuRx sensitivity but increase the supply current severely. Different WuRx approaches exist with always-on, power-gated, or duty-cycled receiver designs. This paper presents a comparative study for improving communication range and decreasing the energy consumption of wireless sensor nodes.Keywords: wireless sensor network, wake-up receiver, duty-cycled, low-noise amplifier, envelope detector, range study
Procedia PDF Downloads 1137295 Landslide Vulnerability Assessment in Context with Indian Himalayan
Authors: Neha Gupta
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Landslide vulnerability is considered as the crucial parameter for the assessment of landslide risk. The term vulnerability defined as the damage or degree of elements at risk of different dimensions, i.e., physical, social, economic, and environmental dimensions. Himalaya region is very prone to multi-hazard such as floods, forest fires, earthquakes, and landslides. With the increases in fatalities rates, loss of infrastructure, and economy due to landslide in the Himalaya region, leads to the assessment of vulnerability. In this study, a methodology to measure the combination of vulnerability dimension, i.e., social vulnerability, physical vulnerability, and environmental vulnerability in one framework. A combined result of these vulnerabilities has rarely been carried out. But no such approach was applied in the Indian Scenario. The methodology was applied in an area of east Sikkim Himalaya, India. The physical vulnerability comprises of building footprint layer extracted from remote sensing data and Google Earth imaginary. The social vulnerability was assessed by using population density based on land use. The land use map was derived from a high-resolution satellite image, and for environment vulnerability assessment NDVI, forest, agriculture land, distance from the river were assessed from remote sensing and DEM. The classes of social vulnerability, physical vulnerability, and environment vulnerability were normalized at the scale of 0 (no loss) to 1 (loss) to get the homogenous dataset. Then the Multi-Criteria Analysis (MCA) was used to assign individual weights to each dimension and then integrate it into one frame. The final vulnerability was further classified into four classes from very low to very high.Keywords: landslide, multi-criteria analysis, MCA, physical vulnerability, social vulnerability
Procedia PDF Downloads 3017294 RGB-D SLAM Algorithm Based on pixel level Dense Depth Map
Authors: Hao Zhang, Hongyang Yu
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Scale uncertainty is a well-known challenging problem in visual SLAM. Because RGB-D sensor provides depth information, RGB-D SLAM improves this scale uncertainty problem. However, due to the limitation of physical hardware, the depth map output by RGB-D sensor usually contains a large area of missing depth values. These missing depth information affect the accuracy and robustness of RGB-D SLAM. In order to reduce these effects, this paper completes the missing area of the depth map output by RGB-D sensor and then fuses the completed dense depth map into ORB SLAM2. By adding the process of obtaining pixel-level dense depth maps, a better RGB-D visual SLAM algorithm is finally obtained. In the process of obtaining dense depth maps, a deep learning model of indoor scenes is adopted. Experiments are conducted on public datasets and real-world environments of indoor scenes. Experimental results show that the proposed SLAM algorithm has better robustness than ORB SLAM2.Keywords: RGB-D, SLAM, dense depth, depth map
Procedia PDF Downloads 1407293 Robust Medical Image Watermarking based on Contourlet and Extraction Using ICA
Authors: S. Saju, G. Thirugnanam
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In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet
Procedia PDF Downloads 5287292 Artificial Neural Network Approach for Vessel Detection Using Visible Infrared Imaging Radiometer Suite Day/Night Band
Authors: Takashi Yamaguchi, Ichio Asanuma, Jong G. Park, Kenneth J. Mackin, John Mittleman
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In this paper, vessel detection using the artificial neural network is proposed in order to automatically construct the vessel detection model from the satellite imagery of day/night band (DNB) in visible infrared in the products of Imaging Radiometer Suite (VIIRS) on Suomi National Polar-orbiting Partnership (Suomi-NPP).The goal of our research is the establishment of vessel detection method using the satellite imagery of DNB in order to monitor the change of vessel activity over the wide region. The temporal vessel monitoring is very important to detect the events and understand the circumstances within the maritime environment. For the vessel locating and detection techniques, Automatic Identification System (AIS) and remote sensing using Synthetic aperture radar (SAR) imagery have been researched. However, each data has some lack of information due to uncertain operation or limitation of continuous observation. Therefore, the fusion of effective data and methods is important to monitor the maritime environment for the future. DNB is one of the effective data to detect the small vessels such as fishery ships that is difficult to observe in AIS. DNB is the satellite sensor data of VIIRS on Suomi-NPP. In contrast to SAR images, DNB images are moderate resolution and gave influence to the cloud but can observe the same regions in each day. DNB sensor can observe the lights produced from various artifact such as vehicles and buildings in the night and can detect the small vessels from the fishing light on the open water. However, the modeling of vessel detection using DNB is very difficult since complex atmosphere and lunar condition should be considered due to the strong influence of lunar reflection from cloud on DNB. Therefore, artificial neural network was applied to learn the vessel detection model. For the feature of vessel detection, Brightness Temperature at the 3.7 μm (BT3.7) was additionally used because BT3.7 can be used for the parameter of atmospheric conditions.Keywords: artificial neural network, day/night band, remote sensing, Suomi National Polar-orbiting Partnership, vessel detection, Visible Infrared Imaging Radiometer Suite
Procedia PDF Downloads 2357291 Robust Quantum Image Encryption Algorithm Leveraging 3D-BNM Chaotic Maps and Controlled Qubit-Level Operations
Authors: Vivek Verma, Sanjeev Kumar
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This study presents a novel quantum image encryption algorithm, using a 3D chaotic map and controlled qubit-level scrambling operations. The newly proposed 3D-BNM chaotic map effectively reduces the degradation of chaotic dynamics resulting from the finite word length effect. It facilitates the generation of highly unpredictable random sequences and enhances chaotic performance. The system’s efficacy is additionally enhanced by the inclusion of a SHA-256 hash function. Initially, classical plain images are converted into their quantum equivalents using the Novel Enhanced Quantum Representation (NEQR) model. The Generalized Quantum Arnold Transformation (GQAT) is then applied to disrupt the coordinate information of the quantum image. Subsequently, to diffuse the pixel values of the scrambled image, XOR operations are performed using pseudorandom sequences generated by the 3D-BNM chaotic map. Furthermore, to enhance the randomness and reduce the correlation among the pixels in the resulting cipher image, a controlled qubit-level scrambling operation is employed. The encryption process utilizes fundamental quantum gates such as C-NOT and CCNOT. Both theoretical and numerical simulations validate the effectiveness of the proposed algorithm against various statistical and differential attacks. Moreover, the proposed encryption algorithm operates with low computational complexity.Keywords: 3D Chaotic map, SHA-256, quantum image encryption, Qubit level scrambling, NEQR
Procedia PDF Downloads 107290 Image Transform Based on Integral Equation-Wavelet Approach
Authors: Yuan Yan Tang, Lina Yang, Hong Li
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Harmonic model is a very important approximation for the image transform. The harmanic model converts an image into arbitrary shape; however, this mode cannot be described by any fixed functions in mathematics. In fact, it is represented by partial differential equation (PDE) with boundary conditions. Therefore, to develop an efficient method to solve such a PDE is extremely significant in the image transform. In this paper, a novel Integral Equation-Wavelet based method is presented, which consists of three steps: (1) The partial differential equation is converted into boundary integral equation and representation by an indirect method. (2) The boundary integral equation and representation are changed to plane integral equation and representation by boundary measure formula. (3) The plane integral equation and representation are then solved by a method we call wavelet collocation. Our approach has two main advantages, the shape of an image is arbitrary and the program code is independent of the boundary. The performance of our method is evaluated by numerical experiments.Keywords: harmonic model, partial differential equation (PDE), integral equation, integral representation, boundary measure formula, wavelet collocation
Procedia PDF Downloads 5587289 Design Of High Sensitivity Transceiver for WSN
Authors: A. Anitha, M. Aishwariya
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The realization of truly ubiquitous wireless sensor networks (WSN) demands Ultra-low power wireless communication capability. Because the radio transceiver in a wireless sensor node consumes more power when compared to the computation part it is necessary to reduce the power consumption. Hence, a low power transceiver is designed and implemented in a 120 nm CMOS technology for wireless sensor nodes. The power consumption of the transceiver is reduced still by maintaining the sensitivity. The transceiver designed combines the blocks including differential oscillator, mixer, envelope detector, power amplifiers, and LNA. RF signal modulation and demodulation is carried by On-Off keying method at 2.4 GHz which is said as ISM band. The transmitter demonstrates an output power of 2.075 mW while consuming a supply voltage of range 1.2 V-5.0 V. Here the comparison of LNA and power amplifier is done to obtain an amplifier which produces a high gain of 1.608 dB at receiver which is suitable to produce a desired sensitivity. The multistage RF amplifier is used to improve the gain at the receiver side. The power dissipation of the circuit is in the range of 0.183-0.323 mW. The receiver achieves a sensitivity of about -95 dBm with data rate of 1 Mbps.Keywords: CMOS, envelope detector, ISM band, LNA, low power electronics, PA, wireless transceiver
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