Search results for: energy detection
11164 Cu Voids Detection of Electron Beam Inspection at the 5nm Node
Authors: Byungsik Moon
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Electron beam inspection (EBI) has played an important role in detecting defects during the Fab process. The study focused on capturing buried Cu metal voids for 5nm technology nodes in Qualcomm Snapdragon mass production. This paper illustrates a case study where Cu metal voids can be detected without side effects with optimized EBI scanning conditions. The voids were buried in the VIA and not detected effectively by bright field inspection. EBI showed higher detectability, about 10 times that of bright fields, and a lower landing energy of EBI can avoid film damage. A comparison of detectability between EBI and bright field inspection was performed, and TEM confirmed voids that were detected by EBI. Therefore, a much higher detectability of buried Cu metal voids can be achieved without causing film damage.Keywords: electron beam inspection, EBI, landing energy, Cu metal voids, bright field inspection
Procedia PDF Downloads 7511163 Chinese Event Detection Technique Based on Dependency Parsing and Rule Matching
Authors: Weitao Lin
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To quickly extract adequate information from large-scale unstructured text data, this paper studies the representation of events in Chinese scenarios and performs the regularized abstraction. It proposes a Chinese event detection technique based on dependency parsing and rule matching. The method first performs dependency parsing on the original utterance, then performs pattern matching at the word or phrase granularity based on the results of dependent syntactic analysis, filters out the utterances with prominent non-event characteristics, and obtains the final results. The experimental results show the effectiveness of the method.Keywords: natural language processing, Chinese event detection, rules matching, dependency parsing
Procedia PDF Downloads 14111162 Robust Barcode Detection with Synthetic-to-Real Data Augmentation
Authors: Xiaoyan Dai, Hsieh Yisan
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Barcode processing of captured images is a huge challenge, as different shooting conditions can result in different barcode appearances. This paper proposes a deep learning-based barcode detection using synthetic-to-real data augmentation. We first augment barcodes themselves; we then augment images containing the barcodes to generate a large variety of data that is close to the actual shooting environments. Comparisons with previous works and evaluations with our original data show that this approach achieves state-of-the-art performance in various real images. In addition, the system uses hybrid resolution for barcode “scan” and is applicable to real-time applications.Keywords: barcode detection, data augmentation, deep learning, image-based processing
Procedia PDF Downloads 17411161 Design and Modeling of a Green Building Energy Efficient System
Authors: Berhane Gebreslassie
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Conventional commericial buildings are among the highest unwisely consumes enormous amount of energy and as consequence produce significant amount Carbon Dioxide (CO2). Traditional/conventional buildings have been built for years without consideration being given to their impact on the global warming issues as well as their CO2 contributions. Since 1973, simulation of Green Building (GB) for Energy Efficiency started and many countries in particular the US showed a positive response to minimize the usage of energy in respect to reducing the CO2 emission. As a consequence many software companies developed their own unique building energy efficiency simulation software, interfacing interoperability with Building Information Modeling (BIM). The last decade has witnessed very rapid growing number of researches on GB energy efficiency system. However, the study also indicates that the results of current GB simulation are not yet satisfactory to meet the objectives of GB. In addition most of these previous studies are unlikely excluded the studies of ultimate building energy efficiencies simulation. The aim of this project is to meet the objectives of GB by design, modeling and simulation of building ultimate energy efficiencies system. This research project presents multi-level, L-shape office building in which every particular part of the building materials has been tested for energy efficiency. An overall of 78.62% energy is saved, approaching to NetZero energy saving. Furthermore, the building is implements with distributed energy resources like renewable energies and integrating with Smart Building Automation System (SBAS) for controlling and monitoring energy usage.Keywords: ultimate energy saving, optimum energy saving, green building, sustainable materials and renewable energy
Procedia PDF Downloads 27711160 A Fast Silhouette Detection Algorithm for Shadow Volumes in Augmented Reality
Authors: Hoshang Kolivand, Mahyar Kolivand, Mohd Shahrizal Sunar, Mohd Azhar M. Arsad
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Real-time shadow generation in virtual environments and Augmented Reality (AR) was always a hot topic in the last three decades. Lots of calculation for shadow generation among AR needs a fast algorithm to overcome this issue and to be capable of implementing in any real-time rendering. In this paper, a silhouette detection algorithm is presented to generate shadows for AR systems. Δ+ algorithm is presented based on extending edges of occluders to recognize which edges are silhouettes in the case of real-time rendering. An accurate comparison between the proposed algorithm and current algorithms in silhouette detection is done to show the reduction calculation by presented algorithm. The algorithm is tested in both virtual environments and AR systems. We think that this algorithm has the potential to be a fundamental algorithm for shadow generation in all complex environments.Keywords: silhouette detection, shadow volumes, real-time shadows, rendering, augmented reality
Procedia PDF Downloads 44311159 Capturing the Stress States in Video Conferences by Photoplethysmographic Pulse Detection
Authors: Jarek Krajewski, David Daxberger
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We propose a stress detection method based on an RGB camera using heart rate detection, also known as Photoplethysmography Imaging (PPGI). This technique focuses on the measurement of the small changes in skin colour caused by blood perfusion. A stationary lab setting with simulated video conferences is chosen using constant light conditions and a sampling rate of 30 fps. The ground truth measurement of heart rate is conducted with a common PPG system. The proposed approach for pulse peak detection is based on a machine learning-based approach, applying brute force feature extraction for the prediction of heart rate pulses. The statistical analysis showed good agreement (correlation r = .79, p<0.05) between the reference heart rate system and the proposed method. Based on these findings, the proposed method could provide a reliable, low-cost, and contactless way of measuring HR parameters in daily-life environments.Keywords: heart rate, PPGI, machine learning, brute force feature extraction
Procedia PDF Downloads 12511158 De Broglie Wavelength Defined by the Rest Energy E0 and Its Velocity
Authors: K. Orozović, B. Balon
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In this paper, we take a different approach to de Broglie wavelength, as we relate it to relativistic physics. The quantum energy of the photon radiated by a body with de Broglie wavelength, as it moves with velocity v, can be defined within relativistic physics by rest energy E₀. In this way, we can show the connection between the quantum of radiation energy of the body and the rest of energy E₀ and thus combine what has been incompatible so far, namely relativistic and quantum physics. So, here we discuss the unification of relativistic and quantum physics by introducing the factor k that is analog to the Lorentz factor in Einstein's theory of relativity.Keywords: de Brogli wavelength, relativistic physics, rest energy, quantum physics
Procedia PDF Downloads 15711157 Facility Anomaly Detection with Gaussian Mixture Model
Authors: Sunghoon Park, Hank Kim, Jinwon An, Sungzoon Cho
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Internet of Things allows one to collect data from facilities which are then used to monitor them and even predict malfunctions in advance. Conventional quality control methods focus on setting a normal range on a sensor value defined between a lower control limit and an upper control limit, and declaring as an anomaly anything falling outside it. However, interactions among sensor values are ignored, thus leading to suboptimal performance. We propose a multivariate approach which takes into account many sensor values at the same time. In particular Gaussian Mixture Model is used which is trained to maximize likelihood value using Expectation-Maximization algorithm. The number of Gaussian component distributions is determined by Bayesian Information Criterion. The negative Log likelihood value is used as an anomaly score. The actual usage scenario goes like a following. For each instance of sensor values from a facility, an anomaly score is computed. If it is larger than a threshold, an alarm will go off and a human expert intervenes and checks the system. A real world data from Building energy system was used to test the model.Keywords: facility anomaly detection, gaussian mixture model, anomaly score, expectation maximization algorithm
Procedia PDF Downloads 27211156 Modeling and Benchmarking the Thermal Energy Performance of Palm Oil Production Plant
Authors: Mathias B. Michael, Esther T. Akinlabi, Tien-Chien Jen
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Thermal energy consumption in palm oil production plant comprises mainly of steam, hot water and hot air. In most efficient plants, hot water and air are generated from the steam supply system. Research has shown that thermal energy utilize in palm oil production plants is about 70 percent of the total energy consumption of the plant. In order to manage the plants’ energy efficiently, the energy systems are modelled and optimized. This paper aimed to present the model of steam supply systems of a typical palm oil production plant in Ghana. The models include exergy and energy models of steam boiler, steam turbine and the palm oil mill. The paper further simulates the virtual plant model to obtain the thermal energy performance of the plant under study. The simulation results show that, under normal operating condition, the boiler energy performance is considerably below the expected level as a result of several factors including intermittent biomass fuel supply, significant moisture content of the biomass fuel and significant heat losses. The total thermal energy performance of the virtual plant is set as a baseline. The study finally recommends number of energy efficiency measures to improve the plant’s energy performance.Keywords: palm biomass, steam supply, exergy and energy models, energy performance benchmark
Procedia PDF Downloads 35011155 Forster Energy Transfer and Optoelectronic Properties of (PFO/TiO2)/Fluorol 7GA Hybrid Thin Films
Authors: Bandar Ali Al-Asbahi, Mohammad Hafizuddin Haji Jumali
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Forster energy transfer between poly (9,9'-di-n-octylfluorenyl-2,7-diyl) (PFO)/TiO2 nanoparticles (NPs) as a donor and Fluorol 7GA as an acceptor has been studied. The energy transfer parameters were calculated by using mathematical models. The dominant mechanism responsible for the energy transfer between the donor and acceptor molecules was Forster-type, as evidenced by large values of quenching rate constant, energy transfer rate constant and critical distance of energy transfer. Moreover, these composites which were used as an emissive layer in organic light emitting diodes, were investigated in terms of current density–voltage and electroluminescence spectra.Keywords: energy transfer parameters, forster-type, electroluminescence, organic light emitting diodes
Procedia PDF Downloads 42811154 Bounds on the Laplacian Vertex PI Energy
Authors: Ezgi Kaya, A. Dilek Maden
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A topological index is a number related to graph which is invariant under graph isomorphism. In theoretical chemistry, molecular structure descriptors (also called topological indices) are used for modeling physicochemical, pharmacologic, toxicologic, biological and other properties of chemical compounds. Let G be a graph with n vertices and m edges. For a given edge uv, the quantity nu(e) denotes the number of vertices closer to u than v, the quantity nv(e) is defined analogously. The vertex PI index defined as the sum of the nu(e) and nv(e). Here the sum is taken over all edges of G. The energy of a graph is defined as the sum of the eigenvalues of adjacency matrix of G and the Laplacian energy of a graph is defined as the sum of the absolute value of difference of laplacian eigenvalues and average degree of G. In theoretical chemistry, the π-electron energy of a conjugated carbon molecule, computed using the Hückel theory, coincides with the energy. Hence results on graph energy assume special significance. The Laplacian matrix of a graph G weighted by the vertex PI weighting is the Laplacian vertex PI matrix and the Laplacian vertex PI eigenvalues of a connected graph G are the eigenvalues of its Laplacian vertex PI matrix. In this study, Laplacian vertex PI energy of a graph is defined of G. We also give some bounds for the Laplacian vertex PI energy of graphs in terms of vertex PI index, the sum of the squares of entries in the Laplacian vertex PI matrix and the absolute value of the determinant of the Laplacian vertex PI matrix.Keywords: energy, Laplacian energy, laplacian vertex PI eigenvalues, Laplacian vertex PI energy, vertex PI index
Procedia PDF Downloads 24611153 Low Cost Real Time Robust Identification of Impulsive Signals
Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman
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This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.Keywords: sound detection, impulsive signal, background noise, neural network
Procedia PDF Downloads 32211152 An Investigation on the Energy Absorption of Sandwich Panels With Aluminium Foam Core under Perforation Test
Authors: Minoo Tavakoli, Mojtaba Zebarjad, Golestanipour
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Metallic sandwich structures with aluminum foam core are good energy absorbers. In this paper, perforation test were carried out on different samples to study energy absorption. In the experiments, effect of several parameters, i.e. skin thickness and thickness of foam core, on the energy absorption, delamination zone of back faces and deformation strain(φ) are discussed. Results show that increasing plates thickness will results in more absorbed energy and delamination. Moreover, thickening foam core has the same effect.Keywords: sandwich panel, aluminium foam, perforation, energy absorption
Procedia PDF Downloads 42311151 Deepfake Detection for Compressed Media
Authors: Sushil Kumar Gupta, Atharva Joshi, Ayush Sonawale, Sachin Naik, Rajshree Khande
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The usage of artificially created videos and audio by deep learning is a major problem of the current media landscape, as it pursues the goal of misinformation and distrust. In conclusion, the objective of this work targets generating a reliable deepfake detection model using deep learning that will help detect forged videos accurately. In this work, CelebDF v1, one of the largest deepfake benchmark datasets in the literature, is adopted to train and test the proposed models. The data includes authentic and synthetic videos of high quality, therefore allowing an assessment of the model’s performance against realistic distortions.Keywords: deepfake detection, CelebDF v1, convolutional neural network (CNN), xception model, data augmentation, media manipulation
Procedia PDF Downloads 1311150 Nearly Zero-Energy Regulation and Buildings Built with Prefabricated Technology: The Case of Hungary
Authors: András Horkai, Attila Talamon, Viktória Sugár
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There is an urgent need nowadays to reduce energy demand and the current level of greenhouse gas emission and use renewable energy sources increase in energy efficiency. On the other hand, the European Union (EU) countries are largely dependent on energy imports and are vulnerable to disruption in energy supply, which may, in turn, threaten the functioning of their current economic structure. Residential buildings represent a significant part of the energy consumption of the building stock. Only a small part of the building stock is exchanged every year, thus it is essential to increase the energy efficiency of the existing buildings. Present paper focuses on the buildings built with industrialized technology only, and their opportunities in the boundaries of nearly zero-energy regulation. Current paper shows the emergence of panel construction method, and past and present of the ‘panel’ problem in Hungary with a short outlook to Europe. The study shows as well as the possibilities for meeting the nearly zero and cost optimized requirements for residential buildings by analyzing the renovation scenarios of an existing residential typology.Keywords: Budapest, energy consumption, industrialized technology, nearly zero-energy buildings
Procedia PDF Downloads 34811149 Bundle Block Detection Using Spectral Coherence and Levenberg Marquardt Neural Network
Authors: K. Padmavathi, K. Sri Ramakrishna
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This study describes a procedure for the detection of Left and Right Bundle Branch Block (LBBB and RBBB) ECG patterns using spectral Coherence(SC) technique and LM Neural Network. The Coherence function finds common frequencies between two signals and evaluate the similarity of the two signals. The QT variations of Bundle Blocks are observed in lead V1 of ECG. Spectral Coherence technique uses Welch method for calculating PSD. For the detection of normal and Bundle block beats, SC output values are given as the input features for the LMNN classifier. Overall accuracy of LMNN classifier is 99.5 percent. The data was collected from MIT-BIH Arrhythmia database.Keywords: bundle block, SC, LMNN classifier, welch method, PSD, MIT-BIH, arrhythmia database
Procedia PDF Downloads 28311148 Perspectives of Renewable Energy in 21st Century in India: Statistics and Estimation
Authors: Manoj Kumar, Rajesh Kumar
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With the favourable geographical conditions at Indian-subcontinent, it is suitable for flourishing renewable energy. Increasing amount of dependence on coal and other conventional sources is driving the world into pollution and depletion of resources. This paper presents the statistics of energy consumption and energy generation in Indian Sub-continent, which notifies us with the increasing energy demands surpassing energy generation. With the aggrandizement in demand for energy, usage of coal has increased, since the major portion of energy production in India is from thermal power plants. The increase in usage of thermal power plants causes pollution and depletion of reserves; hence, a paradigm shift to renewable sources is inevitable. In this work, the capacity and potential of renewable sources in India are analyzed. Based on the analysis of this work, future potential of these sources is estimated.Keywords: depletion of reserves, energy consumption and generation, emmissions, global warming, renewable sources
Procedia PDF Downloads 43311147 Photovoltaic System: An Alternative to Energy Efficiency in a Residence
Authors: Arsenio Jose Mindu
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The concern to carry out a study related to Energy Efficiency arose based on the various debates in international television networks and not only, but also in several forums of national debates. The concept of Energy Efficiency is not yet widely disseminated and /or taken into account in terms of energy consumption, not only at the domestic level but also at the industrial level in Mozambique. In the context of the energy audit, the time during which each of the appliances is connected to the voltage source, the time during which they are in standby mode was recorded on a spreadsheet basis. Based on these data, daily and monthly consumption was calculated. In order to have more accurate information on the daily levels of daily consumption, the electricity consumption was read every hour of the day (from 5:00 am to 11:00 pm), since after 23:00 the energy consumption remains constant. For ten days. Based on the daily energy consumption and the maximum consumption power, the design of the photovoltaic system for the residence was made. With the implementation of the photovoltaic system in order to guarantee energy efficiency, there was a significant reduction in the use of electricity from the public grid, increasing from approximately 17 kwh per day to around 11 kwh, thus achieving an energy efficiency of 67.4 %. That is to say, there was a reduction not only in terms of the amount of energy consumed but also of the monthly expenses with electricity, having increased from around 2,500,00Mt (2,500 meticais) to around 800Mt per month.Keywords: energy efficiency, photovoltaic system, residential sector, Mozambique
Procedia PDF Downloads 20711146 Evaluation of Alternative Energy Sources for Energy Production in Turkey
Authors: Naci Büyükkaracığan, Murat Ahmet Ökmen
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In parallel with the population growth rate, the need of human being for energy sources in the world is gradually increasing incessant. The addition of this situation that demand for energy will be busier in the future, industrialization, the rise in living standards and technological developments, especially in developing countries. Alternative energy sources have aroused interest due to reasons such as serious environmental issues that were caused by fossil energy sources, potentially decreasing reserves, different social, political and economic problems caused by dependency on source providing countries and price instability. Especially in developed countries as European countries and also U.S.A particularly, alternative energy sources such as wind, geothermal, solar and biomass energy, hydrolic and hydrogen have been utilized in different forms, especially in electricity production. It includes a review of technical and environmental factors for energy sources that are potential replacements for fossil fuels and examines their fitness to supply the energy for a high standard of living on a worldwide basis. Despite all developments, fossil energy sources have been overwhelmingly used all around the world in primary energy sources consumption and they will outnumber other energy sources in the short term. Today, parallel to population growth and economy in Turkey, energy sources consumption is increasingly continuing. On one side, Turkey, currently 80% dependent on energy providing countries, has been heavily conducting fossil energy sources raw material quest within its own borders in order to lower the percentage, and the other side, there have been many researches for exploring potential of alternative energy sources and utilization. This case will lead to both a decrease in foreign energy dependency and a variety of energy sources. This study showed the current energy potential of Turkey and presents historical development of these energy sources and their share in electricity production. The research also seeked for answers to arguments that if the potential can be sufficient in the future. As a result of this study, it was concluded that observed geothermal energy, particularly active tectonic regions of Turkey, to have an alternative energy potential could be considered to be valuable on bass wind and solar energy.Keywords: alternative energy sources, energy productions, hydroenergy, solar energy, wind energy
Procedia PDF Downloads 63111145 Safe Zone: A Framework for Detecting and Preventing Drones Misuse
Authors: AlHanoof A. Alharbi, Fatima M. Alamoudi, Razan A. Albrahim, Sarah F. Alharbi, Abdullah M Almuhaideb, Norah A. Almubairik, Abdulrahman Alharby, Naya M. Nagy
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Recently, drones received a rapid interest in different industries worldwide due to its powerful impact. However, limitations still exist in this emerging technology, especially privacy violation. These aircrafts consistently threaten the security of entities by entering restricted areas accidentally or deliberately. Therefore, this research project aims to develop drone detection and prevention mechanism to protect the restricted area. Until now, none of the solutions have met the optimal requirements of detection which are cost-effectiveness, high accuracy, long range, convenience, unaffected by noise and generalization. In terms of prevention, the existing methods are focusing on impractical solutions such as catching a drone by a larger drone, training an eagle or a gun. In addition, the practical solutions have limitations, such as the No-Fly Zone and PITBULL jammers. According to our study and analysis of previous related works, none of the solutions includes detection and prevention at the same time. The proposed solution is a combination of detection and prevention methods. To implement the detection system, a passive radar will be used to properly identify the drone against any possible flying objects. As for the prevention, jamming signals and forceful safe landing of the drone integrated together to stop the drone’s operation. We believe that applying this mechanism will limit the drone’s invasion of privacy incidents against highly restricted properties. Consequently, it effectively accelerates drones‘ usages at personal and governmental levels.Keywords: detection, drone, jamming, prevention, privacy, RF, radar, UAV
Procedia PDF Downloads 21311144 Hybrid Deep Learning and FAST-BRISK 3D Object Detection Technique for Bin-Picking Application
Authors: Thanakrit Taweesoontorn, Sarucha Yanyong, Poom Konghuayrob
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Robotic arms have gained popularity in various industries due to their accuracy and efficiency. This research proposes a method for bin-picking tasks using the Cobot, combining the YOLOv5 CNNs model for object detection and pose estimation with traditional feature detection (FAST), feature description (BRISK), and matching algorithms. By integrating these algorithms and utilizing a small-scale depth sensor camera for capturing depth and color images, the system achieves real-time object detection and accurate pose estimation, enabling the robotic arm to pick objects correctly in both position and orientation. Furthermore, the proposed method is implemented within the ROS framework to provide a seamless platform for robotic control and integration. This integration of robotics, cameras, and AI technology contributes to the development of industrial robotics, opening up new possibilities for automating challenging tasks and improving overall operational efficiency.Keywords: robotic vision, image processing, applications of robotics, artificial intelligent
Procedia PDF Downloads 9711143 Saving Energy at a Wastewater Treatment Plant through Electrical and Production Data Analysis
Authors: Adriano Araujo Carvalho, Arturo Alatrista Corrales
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This paper intends to show how electrical energy consumption and production data analysis were used to find opportunities to save energy at Taboada wastewater treatment plant in Callao, Peru. In order to access the data, it was used independent data networks for both electrical and process instruments, which were taken to analyze under an ISO 50001 energy audit, which considered, thus, Energy Performance Indexes for each process and a step-by-step guide presented in this text. Due to the use of aforementioned methodology and data mining techniques applied on information gathered through electronic multimeters (conveniently placed on substation switchboards connected to a cloud network), it was possible to identify thoroughly the performance of each process and thus, evidence saving opportunities which were previously hidden before. The data analysis brought both costs and energy reduction, allowing the plant to save significant resources and to be certified under ISO 50001.Keywords: energy and production data analysis, energy management, ISO 50001, wastewater treatment plant energy analysis
Procedia PDF Downloads 19711142 FMCW Doppler Radar Measurements with Microstrip Tx-Rx Antennas
Authors: Yusuf Ulaş Kabukçu, Si̇nan Çeli̇k, Onur Salan, Mai̇de Altuntaş, Mert Can Dalkiran, Gökseni̇n Bozdağ, Metehan Bulut, Fati̇h Yaman
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This study presents a more compact implementation of the 2.4GHz MIT Coffee Can Doppler Radar for 2.6GHz operating frequency. The main difference of our prototype depends on the use of microstrip antennas which makes it possible to transport with a small robotic vehicle. We have designed our radar system with two different channels: Tx and Rx. The system mainly consists of Voltage Controlled Oscillator (VCO) source, low noise amplifiers, microstrip antennas, splitter, mixer, low pass filter, and necessary RF connectors with cables. The two microstrip antennas, one is element for transmitter and the other one is array for receiver channel, was designed, fabricated and verified by experiments. The system has two operation modes: speed detection and range detection. If the switch of the operation mode is ‘Off’, only CW signal transmitted for speed measurement. When the switch is ‘On’, CW is frequency-modulated and range detection is possible. In speed detection mode, high frequency (2.6 GHz) is generated by a VCO, and then amplified to reach a reasonable level of transmit power. Before transmitting the amplified signal through a microstrip patch antenna, a splitter used in order to compare the frequencies of transmitted and received signals. Half of amplified signal (LO) is forwarded to a mixer, which helps us to compare the frequencies of transmitted and received (RF) and has the IF output, or in other words information of Doppler frequency. Then, IF output is filtered and amplified to process the signal digitally. Filtered and amplified signal showing Doppler frequency is used as an input of audio input of a computer. After getting this data Doppler frequency is shown as a speed change on a figure via Matlab script. According to experimental field measurements the accuracy of speed measurement is approximately %90. In range detection mode, a chirp signal is used to form a FM chirp. This FM chirp helps to determine the range of the target since only Doppler frequency measured with CW is not enough for range detection. Such a FMCW Doppler radar may be used in border security of the countries since it is capable of both speed and range detection.Keywords: doppler radar, FMCW, range detection, speed detection
Procedia PDF Downloads 39811141 Application of the Mesoporous Silica Oxidants on Immunochromatography Detections
Authors: Chang, Ya-Ju, Hsieh, Pei-Hsin, Wu, Jui-Chuang, Chen-Yang, Yui Whei
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A mesoporous silica material was prepared to apply to the lateral-flow immunochromatography for detecting a model biosample. The probe antibody is immobilized on the silica surface as the test line to capture its affinity antigen, which laterally flows through the chromatography strips. The antigen is labeled with nano-gold particles, such that the detection can be visually read out from the test line without instrument aids. The result reveals that the mesoporous material provides a vast area for immobilizing the detection probes. Biosening surfaces corresponding with a positive proportion of detection signals is obtained with the biosample loading.Keywords: mesoporous silica, immunochromatography, lateral-flow strips, biosensors, nano-gold particles
Procedia PDF Downloads 60911140 Supervisory Controller with Three-State Energy Saving Mode for Induction Motor in Fluid Transportation
Authors: O. S. Ebrahim, K. O. Shawky, M. O. S. Ebrahim, P. K. Jain
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Induction Motor (IM) driving pump is the main consumer of electricity in a typical fluid transportation system (FTS). It was illustrated that changing the connection of the stator windings from delta to star at no load could achieve noticeable active and reactive energy savings. This paper proposes a supervisory hysteresis liquid-level control with three-state energy saving mode (ESM) for IM in FTS including storage tank. The IM pump drive comprises modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to computer ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. A logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction, considering the motor thermal capacity used. An artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and, computer simulations are performed to show the effectiveness of the proposed control in terms of reliability, power quality and energy/coenergy cost reduction with the suggestion of power factor correction.Keywords: ANN, ESM, IM, star/delta switch, supervisory control, FT, reliability, power quality
Procedia PDF Downloads 19711139 Performance Comparison of Outlier Detection Techniques Based Classification in Wireless Sensor Networks
Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed
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Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks
Procedia PDF Downloads 49811138 Solar Energy Management: A Case Study of Bhubaneswar City
Authors: Rachita Lal
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Solar energy is a clean energy source. Because it is readily available in India and has many potential decentralized uses, urban local authorities may use it in various ways to manage the energy needs in the territory under their control. Apart from these and other services for which people pay a substantial number of money, urban local councils play a crucial role in administering essential services like water supply, street lighting, and health care. ULBs may contribute considerably to the transition to solar energy, both for their benefit and simultaneously for several additional direct and indirect advantages at multiple levels. The research primarily focuses on using clean energy management to reduce urban areas' reliance on traditional (electricity) energy. A technique for estimating the rooftop solar power potential using GIS (Geographical Information System) is described. Given that the combustion of fossil fuels produces 75% of India's power, meeting the country's energy needs through renewable energy sources is a step toward sustainable development and combating climate change. The study will further help in categorization, phasing, and understanding the demand and supply and thus calculating the cumulative benefits. The main objectives are to study the consumption of conventional energy in the study area and to identify the potential areas where solar photovoltaic intervention can be installed.Keywords: solar energy, GIS, clean energy management, sustainable development
Procedia PDF Downloads 8811137 Exergy Analyses of Wind Turbine
Authors: Muhammad Abid
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Utilization of renewable energy resources for energy conservation, pollution prevention, resource efficiency and systems integration is very important for sustainable development. In this study, we perform energy and exergy analyses of a wind turbine, located on the roof of Mechanical Engineering Department, King Saud University, and Riyadh, Saudi Arabia. The turbine is part of a hybrid photovoltaic (PV)-wind system with hydrogen storage. The power output from this turbine varies between 1.5 and 5.5 kW with a rated wind speed of 12 m/s and a cut-in wind speed of 2.4 m/s. We utilize a wide range of experimental data in the analysis and assessment. We determine energy and exergy efficiencies. The energy efficiency changes between 0% to 45% while the exergy efficiency varies between 0% and 31.3%. We also determined some of the exergoeconomic parameters that are the ratios of energy and exergy loss rates to the capital cost (R en and R ex), respectively. (R en) changes between 0.96% and 59.03% for different values of velocity while R ex has a maximum value of 53.62% for the highest wind speed.Keywords: exergy, efficiency, performance evaluation, wind energy
Procedia PDF Downloads 36711136 Detection and Tracking for the Protection of the Elderly and Socially Vulnerable People in the Video Surveillance System
Authors: Mobarok Hossain Bhuyain
Abstract:
Video surveillance processing has attracted various security fields transforming it into one of the leading research fields. Today's demand for detection and tracking of human mobility for security is very useful for human security, such as in crowded areas. Accordingly, video surveillance technology has seen a rapid advancement in recent years, with algorithms analyzing the behavior of people under surveillance automatically. The main motivation of this research focuses on the detection and tracking of the elderly and socially vulnerable people in crowded areas. Degenerate people are a major health concern, especially for elderly people and socially vulnerable people. One major disadvantage of video surveillance is the need for continuous monitoring, especially in crowded areas. To assist the security monitoring live surveillance video, image processing, and artificial intelligence methods can be used to automatically send warning signals to the monitoring officers about elderly people and socially vulnerable people.Keywords: human detection, target tracking, neural network, particle filter
Procedia PDF Downloads 16611135 Intrusion Detection in SCADA Systems
Authors: Leandros A. Maglaras, Jianmin Jiang
Abstract:
The protection of the national infrastructures from cyberattacks is one of the main issues for national and international security. The funded European Framework-7 (FP7) research project CockpitCI introduces intelligent intrusion detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable Information and Communication Technology (ICT), whilst the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advanced intrusion detection, analysis and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyberattacks. In this paper, an intrusion detection module capable of detecting malicious network traffic in a Supervisory Control and Data Acquisition (SCADA) system is presented. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automates SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detects anomalies in the system real time. The module is part of an IDS (intrusion detection system) developed under CockpitCI project and communicates with the other parts of the system by the exchange of IDMEF messages that carry information about the source of the incident, the time and a classification of the alarm.Keywords: cyber-security, SCADA systems, OCSVM, intrusion detection
Procedia PDF Downloads 555