Search results for: detecting of envelope modulation on noise

Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

Procedia PDF Downloads 43

Authors: Yu-Lin Shen, Ming-Kuen Chang

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In addition to a considerable amount of machinery and equipment, intricacies of the transmission pipeline exist in Petrochemical plants. Long term corrosion may lead to pipeline thinning and rupture, causing serious safety concerns. With the advances in non-destructive testing technology, more rapid and long-range ultrasonic detection techniques are often used for pipeline inspection, EMAT without coupling to detect, it is a non-contact ultrasonic, suitable for detecting elevated temperature or roughened e surface of line. In this study, we prepared artificial defects in pipeline for Electromagnetic Acoustic Transducer Testing (EMAT) to survey the relationship between the defect location, sizing and the EMAT signal. It was found that the signal amplitude of EMAT exhibited greater signal attenuation with larger defect depth and length.. In addition, with bigger flat hole diameter, greater amplitude attenuation was obtained. In summary, signal amplitude attenuation of EMAT was affected by the defect depth, defect length and the hole diameter and size.

Keywords: EMAT, artificial defect, NDT, ultrasonic testing

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Authors: Jalal M. Abdallah

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This paper presents experimental studies carried out on a three phase transformer to investigate and develop the transformer models, which help in testing procedures, describing and evaluating the transformer dielectric conditions process and methods such as: the partial discharge (PD) localization in windings. The measurements are based on the transfer function methods in transformer windings by frequency response analysis (FRA). Numbers of tests conditions were applied to obtain the sensitivity frequency responses of a transformer for different type of faults simulated in a particular phase. The frequency responses were analyzed for the sensitivity of different test conditions to detect and identify the starting of small faults, which are sources of PD. In more detail, the aim is to explain applicability and sensitivity of advanced PD measurements for small short circuits and its localization. The experimental results presented in the paper will help in understanding the sensitivity of FRA measurements in detecting various types of internal winding short circuits in the transformer.

Keywords: frequency response analysis (FRA), measurements, transfer function, transformer

Procedia PDF Downloads 277

Authors: Amal Alshahrani, Allan Ramsay

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Paraphrasing is one of the important tasks in natural language processing; i.e. alternative ways to express the same concept by using different words or phrases. Paraphrases can be used in many natural language applications, such as Information Retrieval, Machine Translation, Question Answering, Text Summarization, or Information Extraction. To obtain pairs of sentences that are paraphrases we create a system that automatically extracts paraphrases from a corpus, which is built from different sources of news article since these are likely to contain paraphrases when they report the same event on the same day. There are existing simple standard approaches (e.g. TF-IDF vector space, cosine similarity) and alignment technique (e.g. Dynamic Time Warping (DTW)) for extracting paraphrase which have been applied to the English. However, the performance of these approaches could be affected when they are applied to another language, for instance Arabic language, due to the presence of phenomena which are not present in English, such as Free Word Order, Zero copula, and Pro-dropping. These phenomena will affect the performance of these algorithms. Thus, if we can analysis how the existing algorithms for English fail for Arabic then we can find a solution for Arabic. The results are promising.

Keywords: natural language processing, TF-IDF, cosine similarity, dynamic time warping (DTW)

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Authors: Vijaya Yuvaram Singh V M, Kameshwar Rao J V

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The challenge with development of neural network based methods for medical is the availability of data. Anatomical landmark detection in the medical domain is a process to find points on the x-ray scan report of the patient. Most of the time this task is done manually by trained professionals as it requires precision and domain knowledge. Traditionally object detection based methods are used for landmark detection. Here, we utilize reinforcement learning and query based method to train a single agent capable of detecting multiple landmarks. A deep Q network agent is trained to detect single and multiple landmarks present on hip and shoulder from x-ray scan of a patient. Here a single agent is trained to find multiple landmark making it superior to having individual agents per landmark. For the initial study, five images of different patients are used as the environment and tested the agents performance on two unseen images.

Keywords: reinforcement learning, medical landmark detection, multi target detection, deep neural network

Procedia PDF Downloads 137

Authors: Bahaa Eldin Kornah

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The organism profile for peri-prosthetic joint infection caused by hematogenous seeding or direct inoculations is changing. The organisms that cause prosthetic joint infections range from normal skin colonizers to highly virulent pathogens. The pathogens continue to evolve. While Staphylococcus aureus continues to be the leading organism, gram-negative bacilli account for approximately 7% of cases and that incidence is increasing. Methicillin-resistant S. aureus(MRSA) accounts for approximately 10% of all infections occurring in the community setting and 20% of those in the health care setting. The list of organisms causing PJI has expanded in recent years. It is important to have an understanding of which organisms may be causing a periprosthetic joint infection based on where the patient contracted it and their recent medical history. Also, recent technology has expanded rapidly and new methods to detect the pathogen and why we failed in detecting it. There are a number of explanations for the latter finding, perhaps the most important reason being the liberal use of antibiotics that interferes with the isolation of the infective organism.

Keywords: infection, periprosthetic, hip, organism profile, joint infection, joint infection

Procedia PDF Downloads 78

Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

Procedia PDF Downloads 151

Authors: P. L. D. N. M. de Silva, S. G. Edirisinghe, R. Weerasuriya

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High peak-to-average power ratio (PAPR) is a concern of orthogonal frequency division multiplexing (OFDM) based visible light communication (VLC) systems. Discrete Fourier Transform spread (DFT-s) OFDM is an alternative single carrier modulation scheme which would address this concern. Employing channel coding techniques is another mechanism to reduce the PAPR. Previous research has been conducted to study the impact of these techniques separately. However, to the best of the knowledge of the authors, no study has been done so far to identify the improvement which can be harnessed by hybridizing these two techniques for VLC systems. Therefore, this is a novel study area under this research. In addition, channel coding techniques such as Polar codes and Turbo codes have been tested in the VLC domain. However, other efficient techniques such as Hamming coding and Convolutional coding have not been studied too. Therefore, the authors present the impact of the hybrid of DFT-s OFDM and Channel coding (Hamming coding and Convolutional coding) on PAPR in VLC systems using Matlab simulations.

Keywords: convolutional coding, discrete Fourier transform spread orthogonal frequency division multiplexing, hamming coding, peak-to-average power ratio, visible light communications

Procedia PDF Downloads 150

Authors: Mohamed Ben Amar, Najib Souissi, Chedly Bradai

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A Taguchi design investigation has been made into the relationship between the ductility and process variables in a squeeze cast 2017A wrought aluminium alloy. The considered process parameters were: squeeze pressure, melt temperature and die preheating temperature. An orthogonal array (OA), main effect, signal-to-noise (S/N) ratio, and the analysis of variance (ANOVA) are employed to analyze the effect of casting parameters. The results have shown that the selected parameters significantly affect the ductility of 2017A wrought Al alloy castings. Optimal squeeze cast process parameters were provided to illustrate the proposed approach and the results were proven to be trustworthy through practical experiments.

Keywords: Taguchi method, squeeze casting, process parameters, ductility, microstructure

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Authors: Josselyn Mata Calidonio, Arianna I. Maddox, Kimberly Hamad-Schifferli

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Rapid diagnostics are critical infectious disease tools that are designed to detect a known biomarker using antibodies specific to that biomarker. However, a way to detect unknown viruses has not yet been achieved in a paper test format. We describe here a route to make an adaptable paper immunoassay that can detect an unknown biomarker, demonstrating it on SARS-CoV-2 variants. The immunoassay repurposes cross-reactive antibodies raised against the alpha variant. Gold nanoparticles of two different colors conjugated to two different antibodies create a colorimetric signal, and machine learning of the resulting colorimetric pattern is used to train the assay to discriminate between variants of alpha and Omicron BA.5. By using principal component analysis, the colorimetric test patterns can pick up and discriminate an unknown that it has not encountered before, Omicron BA.1. The test has an accuracy of 100% and a potential calculated discriminatory power of 900. We show that it can be used adaptively and that it can be used to pick up emerging variants without the need to raise new antibodies.

Keywords: adaptive immunoassay, detecting unknown viruses, gold nanoparticles, paper immunoassay, repurposing antibodies

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Authors: B. Hossen, Y. Helmut

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Soil salinity is a major problem for the coastal region of Bangladesh, which has been increasing for the last four decades. Determination of soil salinity is essential for proper land use planning for agricultural crop production. The aim of the research is to estimate and monitor the soil salinity in the study area. Remote sensing can be an effective tool for detecting soil salinity in data-scarce conditions. In the research, Landsat 8 is used, which required atmospheric and radiometric correction, and nine soil salinity indices are applied to develop a soil salinity map. Ground soil salinity data, i.e., EC value, is collected as a printed map which is then scanned and digitized to develop a point shapefile. Linear regression is made between satellite-based generated map and ground soil salinity data, i.e., EC value. The results show that maximum R² value is found for salinity index SI 7 = G*R/B representing 0.022. This minimal R² value refers that there is a negligible relationship between ground EC value and salinity index generated value. Hence, these indices are not appropriate to assess soil salinity though many studies used those soil salinity indices successfully. Therefore, further research is necessary to formulate a model for determining the soil salinity in the coastal of Bangladesh.

Keywords: soil salinity, EC, Landsat 8, salinity indices, linear regression, remote sensing

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Authors: Carlos Ferreira, Paulo Freitas, Valentim Freitas

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Creative industries’ workers are becoming more prominent as countries move towards intellectual-based economies. Consequently, the nature and essence of the workplace needs to be reconfigured so that creativity and productivity can be better promoted at these spaces. Using a multidisciplinary approach and a user-centered methodology, combining product design, electronic engineering, software and human-computer interaction, we have designed and developed a new seat that uses embedded sensors and actuators to increase the overall well-being of its users, their productivity and their creativity. Our contribution focuses on the parameters that most affect the user’s work on these kinds of spaces, which are, according to our study, noise and temperature. We describe the design process for a new interactive seat targeted at improving workspace productivity.

Keywords: human-computer interaction, usability, user interface, creativity, ergonomics

Procedia PDF Downloads 217

Authors: S. Mogili, J. S. Kuang, N. Zhang

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Knee joints, the beam column connections found at the roof level of a moment resisting frame buildings, are inherently different from conventional interior and exterior beam column connections in the way that forces from adjoining members are transferred into joint and then resisted by the joint. A knee connection has two distinct load resisting mechanisms, each for closing and opening actions acting simultaneously under reversed cyclic loading. In spite of many distinct differences in the behaviour of shear resistance in knee joints, there are no special design provisions in the major design codes available across the world due to lack of in-depth research on the knee connections. To understand the relative importance of opening and closing actions in design, it is imperative to study knee joints under varying shear stresses, especially at higher opening-to-closing shear stress ratios. Three knee joint specimens, under different input shear stresses, were designed to produce a varying ratio of input opening to closing shear stresses. The design was carried out in such a way that the ratio of flexural strength of beams with consideration of axial forces in opening to closing actions are maintained at 0.5, 0.7, and 1.0, thereby resulting in the required variation of opening to closing joint shear stress ratios among the specimens. The behaviour of these specimens was then carefully studied in terms of closing and opening capacities, hysteretic behaviour, and envelope curves to understand the differences in joint performance based on which an attempt to suggest design guidelines for knee joints is made emphasizing the relative importance of opening and closing actions. Specimens with relatively higher opening stresses were observed to be more vulnerable under the action of seismic loading.

Keywords: Knee-joints, large-scale testing, opening and closing shear stresses, seismic performance

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Authors: Joanna Cabaj, Sylwia Baluta, Karol Malecha

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

Keywords: biosensors, catecholamines, fluorescence, enzymes

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Authors: Eid Alharbi, Yaser Miaji

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The importance of fruit quality and freshness is potential in today’s life. Most recent studies show and automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics design, NIR, fruit quality, spectroscopic technology

Procedia PDF Downloads 395

Authors: Adedayo Oke Adelakun

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The chaotic dynamics of periodically forced oscillators with smooth potential has been extensively investigated via theoretical, numerical and experimental simulations. With the advent of the study of chaotic dynamics by means of method of multiple time scale analysis, Melnikov theory, bifurcation diagram, Poincare's map, bifurcation diagrams and Lyapunov exponents, it has become necessary to seek for a better understanding of nonlinear oscillator with noisy term. In this paper, we examine the influence of noise on complex dynamical behaviour of periodically forced F6 - Duffing oscillator for specific choice of noisy parameters. The inclusion of noisy term improves the dynamical behaviour of the oscillator which may have wider application in secure communication than smooth potential.

Keywords: hierarchical structure, periodically forced oscillator, noisy parameters, dynamical behaviour, F6 - duffing oscillator

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

Procedia PDF Downloads 247

Authors: Saghar Karimi, Mohammad Saeed Ahrari Khafi, Amin Abolhasani Foroughi

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In recent decades, keeping exotic species as pet animals has become widespread. Turtles are exotic species from chelonians, which are interested by many people. Caspian pond and European pond turtles from Emydidea family are commonly kept as pets in Iran. Presence of the shell in turtles makes achievement to a comprehensive clinical examination impossible. Respiratory system is one of the most important structures to be examined completely. Presence of the air in the respiratory system makes radiography the first modality to think of; however, image quality would be affected by the shell. Computed tomography (CT) as a radiography-based and non-invasive technique provides cross-sectional scans with little superimposition. The aim of this study was to depict normal computed tomographic anatomy of the respiratory system in Caspian Pond Turtle. Five adult Caspian pond turtle were scanned using a 16-detector CT machine. Our results showed that computed tomography is able to well illustrated different parts of respiratory system in turtle and can be used for detecting abnormalities and disorders.

Keywords: anatomy, computed tomography, respiratory system, turtle

Procedia PDF Downloads 194

Authors: Adam Y. Sulaiman, Donal F. Cotter, Ming J. Huang, Neil J. Hewitt

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Suitable low global warming potential (GWP) refrigerants that conform to F-gas regulations are required to extend the operational envelope of high-temperature heat pumps (HTHPs) used for industrial waste heat recovery processes. The thermophysical properties and characteristics of these working fluids need to be assessed to provide a comprehensive understanding of operational effectiveness in HTHP applications. This paper presents the results of a theoretical simulation to investigate a range of low-GWP refrigerants and their suitability to supersede refrigerants HFC-245fa and HFC-365mfc. A steady-state thermodynamic model of a single-stage HTHP with an internal heat exchanger (IHX) was developed to assess system cycle characteristics at temperature ranges between 50 to 80 °C heat source and 90 to 150 °C heat sink. A practical approach to maximize the operational efficiency was examined to determine the effects of regulating minimum superheat within the process and subsequent influence on energetic and exergetic efficiencies. A comprehensive map of minimum superheat across the HTHP operating variables were used to assess specific tipping points in performance at 30 and 70 K temperature lifts. Based on initial results, the refrigerants HCFO-1233zd(E) and HFO-1336mzz(Z) were found to be closely aligned matches for refrigerants HFC-245fa and HFC-365mfc. The overall results show effective performance for HCFO-1233zd(E) occurs between 5-7 K minimum superheat, and HFO-1336mzz(Z) between 18-21 K dependant on temperature lift. This work provides a method to optimize refrigerant selection based on operational indicators to maximize overall HTHPs system performance.

Keywords: high-temperature heat pump, minimum superheat, energy & exergy efficiency, low GWP refrigerants

Procedia PDF Downloads 163

Authors: S. M. Ahuja

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There are about 12000 stone crusher units in India and are located in clusters around urban areas to the stone quarries. These crushers create lot of fugitive dust emissions and noise pollution which is a major health hazard for the people working in the crushers and also living in its vicinity. Ambient air monitoring was carried out near various stone crushers and it has been observed that fugitive emission varied from 300 to 8000 mg/Nm3. A number of stone crushers were thoroughly studied and their existing pollution control devices were examined. Limitations in the existing technology were also studied. A technology consisting of minimal effective spray nozzles to reduce the emissions at source followed by a containment cum control system having modular cyclones as air pollution control device has been conceived. Besides preliminary energy audit has also been carried out in some of the stone crushers which indicates substantial potential for energy saving.

Keywords: stone crushers, spray nozzles, energy audit

Procedia PDF Downloads 323

Authors: A. Benyahia, M. Zergoug, M. Amir, M. Fodil

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The main objective of this work is to enhance the Pulsed Eddy Current (PEC) response from the aluminum structure using signal processing. Cracks and metal loss in different structures cause changes in PEC response measurements. In this paper, time-frequency analysis is used to represent PEC response, which generates a large quantity of data and reduce the noise due to measurement. Power Spectral Density (PSD) after Wavelet Decomposition (PSD-WD) is proposed for defect detection. The experimental results demonstrate that the cracks in the surface can be extracted satisfactorily by the proposed methods. The validity of the proposed method is discussed.

Keywords: DT, pulsed eddy current, continuous wavelet transform, Mexican hat wavelet mother, defect detection, power spectral density.

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Authors: Ahmad H. Abdelgwad, Ahmed A. Nashat

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Landmine detection is an important and yet challenging problem remains to be solved. Ground Penetrating Radar (GPR) is a powerful and rapidly maturing technology for subsurface threat identification. The detection methodology of GPR depends mainly on the contrast of the dielectric properties of the searched target and its surrounding soil. This contrast produces a partial reflection of the electromagnetic pulses that are being transmitted into the soil and then being collected by the GPR.  One of the most critical hardware components for the performance of GPR is the antenna system. The current paper explores the design and simulation of a pyramidal horn antenna operating at L-band frequencies (1- 2 GHz) to detect a landmine. A prototype model of the GPR system setup is developed to simulate full wave analysis of the electromagnetic fields in different soil types. The contrast in the dielectric permittivity of the landmine and the sandy soil is the most important parameter to be considered for detecting the presence of landmine. L-band horn antenna is proved to be well-versed in the investigation of landmine detection.

Keywords: full wave analysis, ground penetrating radar, horn antenna design, landmine detection

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Authors: Ajay Kadam, Ramesh Kagalkar

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The proposed research objective is to add to a framework for programmed recognition of sound. In this framework the real errand is to distinguish any information sound stream investigate it & anticipate the likelihood of diverse sounds show up in it. To create and industrially conveyed an adaptable sound web crawler a flexible sound search engine. The calculation is clamor and contortion safe, computationally productive, and hugely adaptable, equipped for rapidly recognizing a short portion of sound stream caught through a phone microphone in the presence of frontal area voices and other predominant commotion, and through voice codec pressure, out of a database of over accessible tracks. The algorithm utilizes a combinatorial hashed time-recurrence group of stars examination of the sound, yielding ordinary properties, for example, transparency, in which numerous tracks combined may each be distinguished.

Keywords: fingerprinting, pure tone, white noise, hash function

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Authors: S. Essa, H. Safar, R. Raghupathy

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Human cytomegalovirus (CMV) continues to be a source of severe complications to immunologically immature and immune-compromised hosts. Effective CMV vaccine that diminishes CMV disease in transplant patients and avoids congenital infection remains of high importance as no approved vaccines exist. Though the exact links of defense mechanisms are unidentified, viral-specific antibodies and Th1/Th2 cytokine responses have been involved in controlling viral infections. CMV envelope glycoprotein B (UL55/gB), the matrix proteins (UL83/pp65, UL99/pp28, UL32/pp150), and the assembly protein UL80a/pp38 are known to be targets of antiviral immune responses. In this study, mice were immunized with five HCMV antigens (UL32/pp150, UL80a/pp38, UL99/pp28, and UL83/pp65), and serum samples were collected and evaluated for eliciting viral-specific antibody responses. Moreover, Splenocytes were collected, stimulated, and assessed for cytokine responses. The results demonstrated a CMV-antigen-specific antibody response to pp38 and pp65 (E/C >2.0). The highest titers were detected with pp38 (average E/C 16.275) followed by pp65 (average E/C 7.72). Compared to control cells, splenocytes from PP38 antigen immunized mice gave a significantly higher concentration of GM-CSF, IFN-γ, IL-2 IL-4, IL-5, and IL-17A (P<0.05). Also, splenocytes from pp65 antigen immunized mice resulted in a significantly higher concentration of GM-CSF, IFN-γ, IL-2 IL-4, IL-10, IL-12, IL-17A, and TNF- α. The designation of target CMV peptides by identifying viral-specific antibodies and cytokine responses is vital for understanding the protective immune mechanisms during CMV infection and identifying appropriate viral antigens to develop novel vaccines.

Keywords: hepatitis C virus, peripheral blood mononuclear cells, neutrophils, cytokines

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Authors: Salma Maher, Ahmed Elseragy, Sally Eldeeb

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Nowadays, Urbanism and climate change lead to the rapid growth in energy consumption and the increase of using air-conditioning for cooling. In a hot climate area, there is a need for a new sustainable alternative that is more convenient for an existing situation. The Building envelope controls the heat transfer between the outside and inside the building. While the building façade is the most critical part, types of façade material play a vital role in influences of the energy demand for heating and cooling due to exposure to direct solar radiation throughout the day. Since the beginning of the twentieth century, the use of curtain walls in office buildings façades started to increase rapidly, which lead to more cooling loads in energy consumption. Integrating the living wall system in urban areas as a sustainable renovation and energy-saving method for the built environment will reduce the energy demand of buildings and will also provide environmental benefits. Also, it will balance the urban ecology and enhance urban life quality. The results show that the living wall systems reduce the internal temperature up to 4.0 °C. This research carries on an analytical study by highlighting the different types of living wall systems and verifying their thermal performance, energy-saving, and life potential on the building. These assessing criteria include the reason for using the Living wall systems in the building façade as well as the effect it has upon the surrounding environment. Finally, the paper ends with concluding the effect of using living wall systems on building. And, it suggests a system as long-lasting, and energy-efficient solution to be applied in curtain wall façades in a hot climate area.

Keywords: living wall systems, energy consumption, curtain walls, energy-saving, sustainability, urban life quality

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Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Dimitar Karastoyanov, Todor Penchev

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The paper presents the research of a kind of autonomous mobile robots, intended for work and adaptive perception in unknown and unstructured environment. The objective are robots, dedicated for multi-sensory environment perception and exploration, like measurements and samples taking, discovering and putting a mark on the objects as well as environment interactions–transportation, carrying in and out of equipment and objects. At that ground classification of the different types mobile robots in accordance with the way of locomotion (wheel- or chain-driven, walking, etc.), used drive mechanisms, kind of sensors, end effectors, area of application, etc. is made. Modular system for the mechanical construction of the mobile robots is proposed. Special PLC on the base of AtMega128 processor for robot control is developed. Electronic modules for the wireless communication on the base of Jennic processor as well as the specific software are developed. The methods, means and algorithms for adaptive environment behaviour and tasks realization are examined. The methods of group control of mobile robots and for suspicious objects detecting and handling are discussed too.

Keywords: mobile robots, wireless communications, environment investigations, group control, suspicious objects

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Authors: Grishma D. Solanki, Karshan Kandoriya

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In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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Authors: Gerardo Hernández Sierra

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Today, we are exposed to different anxiogenic stimuli, some of those stimuli (such as traffic, noise, etc.) generates anxiety in people, being the anxiety a factor that can develop different disorders in people. Therefore, and to improve the quality of life of people it is necessary to find new and helpful tools according to the times we’re living to decrease their anxiety state. Moreover, video games are consolidated globally as a way of interactive entertainment characterized by being available to many people, being fun and easy to play. Even so, people reports that they like playing videogames because they decrease their stress (an anxiety detonator). This research will seek the effectiveness of some videogame genres to reduce the intensity of state anxiety in students. Using State Trait Anxiety Inventory (STAI) to do a monitoring of the levels of anxiety pre and post displayed the videogames.

Keywords: anxiety, state trait anxiety inventory (STAI), stress, videogames

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Authors: Salam Khalifa, Naveed Ahmed

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We present a new method to reconstruct a temporally coherent 3D animation from single or multi-view RGB-D video data using unbiased feature point sampling. Given RGB-D video data, in form of a 3D point cloud sequence, our method first extracts feature points using both color and depth information. In the subsequent steps, these feature points are used to match two 3D point clouds in consecutive frames independent of their resolution. Our new motion vectors based dynamic alignment method then fully reconstruct a spatio-temporally coherent 3D animation. We perform extensive quantitative validation using novel error functions to analyze the results. We show that despite the limiting factors of temporal and spatial noise associated to RGB-D data, it is possible to extract temporal coherence to faithfully reconstruct a temporally coherent 3D animation from RGB-D video data.

Keywords: 3D video, 3D animation, RGB-D video, temporally coherent 3D animation

Procedia PDF Downloads 367