Search results for: LCL filter

Authors: Wildan Maulana Wildan, Siti Annisa Rahmayani Icha

Abstract:

Nowadays advances in information technology are needed by all the inhabitants of the earth for the sake of ease all their work, but it is worth to introduced the technological advances in the world of children. Before the technology is growing rapidly, children busy with various of traditional games and have high socialization. Moreover, after it presence, almost all of children spend more their time for playing gadget, It can affect the education of children and will change the character and personality children. However, children also can not be separated with the technology. Because the technology insight knowledge of children will be more extensive. Because the world can not be separated with advances in technology as well as with children, there should be developed a smartphone operating system that is child-friendly. The operating system is able to filter contents that do not deserve children, even in this system there is a reminder of a time study, prayer time and play time for children and there are interactive contents that will help the development of education and children's character. Children need technology, and there are some ways to introduce it to children. We must look at the characteristics of children in different environments. Thus advances in technology can be beneficial to the world children and their parents, and educators do not have to worry about advances in technology. We should be able to take advantage of advances in technology best possible.

Keywords: information technology, smartphone operating system, education, character

Procedia PDF Downloads 476

Authors: Krishnamoorthy Shanmugaraj, Malaichamy Ilanchelian

Abstract:

Ascorbic acid is an essential component in the diet of humans, and also is a typical long used pharmaceutical agent. In the present contribution, we have carried out a detailed study on the binding interaction of ascorbic acid (AA) with bovine hemoglobin (BHb) using steady state emission, time resolved fluorescence, UV-Vis absorption, circular dichroism (CD), Fourier transform infra-red (FT-IR) and three dimensional emission (3D) spectral studies. The results from the emission spectral studies unveiled that the quenching of BHb emission by AA is attributed to the formation of a complex in the ground state (static in nature) after correcting for inner filter effect. The binding parameters calculated from corrected emission quenching data revealed that BHb exhibited a significant binding affinity towards AA. Moreover, AA induced tertiary and secondary conformational changes of BHb were monitored by UV-Vis absorption, CD, FT-IR and 3D emission spectral studies. The results presented here will help to further understand the credible mechanism of BHb-AA system which is expected to provide insights into conformational and microenvironmental changes of BHb.

Keywords: ascorbic acid, bovine hemoglobin, circular dichroism, three dimensional emission spectral studies

Procedia PDF Downloads 937

Authors: Akshat Kumar, Vidushi

Abstract:

This paper identifies 27 KOIs, 26 of which are currently classified as candidates and one as false positives that have a high probability of being confirmed. For this purpose, 11 machine learning algorithms were implemented on the cumulative kepler dataset sourced from the NASA exoplanet archive; it was observed that the best-performing model was HistGradientBoosting and XGBoost with a test accuracy of 93.5%, and the lowest-performing model was Gaussian NB with a test accuracy of 54%, to test model performance F1, cross-validation score and RUC curve was calculated. Based on the learned models, the significant characteristics for confirm exoplanets were identified, putting emphasis on the object’s transit and stellar properties; these characteristics were namely koi_count, koi_prad, koi_period, koi_dor, koi_ror, and koi_smass, which were later considered to filter out the potential KOIs. The paper also calculates the Earth similarity index based on the planetary radius and equilibrium temperature for each KOI identified to aid in their classification.

Keywords: Kepler objects of interest, exoplanets, space exploration, machine learning, earth similarity index, transit photometry

Procedia PDF Downloads 29

Authors: Tomasz Wejrzanowski, Łukasz Kaczmarek, Michał Maksimczuk

Abstract:

High-resolution X-ray computed microtomography (µCT) is a non-destructive technique commonly used to determine the internal structure of reservoir rock sample. This study concerns µCT analysis of Silurian and Ordovician shales and mudstones from a borehole in the Baltic Basin, north of Poland. The spatial resolution of the µCT images obtained was 27 µm, which enabled the authors to create accurate 3-D visualizations and to calculate the ratio of pores and fractures volume to the total sample volume. A total of 1024 µCT slices were used to create a 3-D volume of sample structure geometry. These µCT slices were processed to obtain a clearly visible image and the volume ratio. A copper X-ray source filter was used to reduce image artifacts. Due to accurate technical settings of µCT it was possible to obtain high-resolution 3-D µCT images of low X-ray transparency samples. The presented results confirm the utility of µCT implementations in geoscience and show that µCT has still promising applications for reservoir exploration and characterization.

Keywords: fractures, material density, pores, structure

Procedia PDF Downloads 224

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 143

Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

Abstract:

Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

Procedia PDF Downloads 306

Authors: Syahira Ibrahim, Herlina Abdul Rahim

Abstract:

The amylose content is an essential element in determining the texture and taste of rice grains. This paper evaluates the use of VIS-SWNIRS in estimating the amylose content for seven varieties of rice grains available in the Malaysian market. Each type consists of 30 samples and all the samples are scanned using the spectroscopy to obtain a range of values between 680-1000nm. The Savitzky-Golay (SG) smoothing filter is applied to each sample’s data before the Principal Component Regression (PCR) technique is used to examine the data and produce a single value for each sample. This value is then compared with reference values obtained from the standard iodine colorimetric test in terms of its coefficient of determination, R2. Results show that this technique produced low R2 values of less than 0.50. In order to improve the result, the range should include a wavelength range of 1100-2500nm and the number of samples processed should also be increased.

Keywords: amylose content, diffuse reflectance, Malaysia rice grain, principal component regression (PCR), Visible and Shortwave near-infrared spectroscopy (VIS-SWNIRS)

Procedia PDF Downloads 357

Authors: Chapman Eze Nnadozie

Abstract:

Relational databases constitute a very vital tool for the effective management and administration of both personal and organizational data. Data access ranges from a single user database management software to a more complex distributed server system. This paper intends to appraise the use a programming language extension like structured query language (SQL) to establish links to a relational database (Microsoft Access 2013) using Visual C++ 9 programming language environment. The methodology used involves the creation of tables to form a database using Microsoft Access 2013, which is Object Linking and Embedding (OLE) database compliant. The SQL command is used to query the tables in the database for easy extraction of expected records inside the visual C++ environment. The findings of this paper reveal that records can easily be accessed and manipulated to filter exactly what the user wants, such as retrieval of records with specified criteria, updating of records, and deletion of part or the whole records in a table.

Keywords: data access, database, database management system, OLE, programming language, records, relational database, software, SQL, table

Procedia PDF Downloads 161

Authors: Myung Ho Lee, Hee Seung Lim, Young Jae Maeng, Chang Hoon Lee

Abstract:

This study presents an automatic sequential extraction device for Pu and Am isotopes in radioactive waste samples from the nuclear power plant with anion exchange resin and TRU resin. After radionuclides were leached from the radioactive waste samples with concentrated HCl and HNO₃, the sample was allowed to evaporate to dryness after filtering the leaching solution with 0.45 micron filter. The Pu isotopes were separated in HNO₃ medium with anion exchange resin. For leaching solution passed through the anion exchange column, the Am isotopes were sequentially separated with TRU resin. Automatic sequential extraction device built-in software information of separation for Pu and Am isotopes was developed. The purified Pu and Am isotopes were measured by alpha spectrometer, respectively, after the micro-precipitation of neodymium. The data of Pu and Am isotopes in radioactive waste with an automatic sequential extraction device developed in this study were validated with the ICP-MS system.

Keywords: automatic sequential extraction device, Pu isotopes, Am isotopes, alpha spectrometer, radioactive waste samples, ICP-MS system

Procedia PDF Downloads 36

Authors: Montaceur Zaghdoud, Mohamed Moussaoui, Jalel Akaichi

Abstract:

Frequent subgraph mining refers usually to graph matching and it is widely used in when analyzing big data with large graphs. A lot of research works dealt with structural exact or inexact graph matching but a little attention is paid to semantic matching when graph vertices and/or edges are attributed and typed. Therefore, it seems very interesting to integrate background knowledge into the analysis and that extracted frequent subgraphs should become more pruned by applying a new semantic filter instead of using only structural similarity in graph matching process. Consequently, this paper focuses on developing a new hybrid approximate structuralsemantic graph matching to discover a set of frequent subgraphs. It uses simultaneously an approximate structural similarity function based on graph edit distance function and a possibilistic vertices similarity function based on affinity function. Both structural and semantic filters contribute together to prune extracted frequent set. Indeed, new hybrid structural-semantic frequent subgraph mining approach searches will be suitable to be applied to several application such as community detection in social networks.

Keywords: approximate graph matching, hybrid frequent subgraph mining, graph mining, possibility theory

Procedia PDF Downloads 371

Authors: Yadpiroon Onmek, Jean Triboulet, Sebastien Druon, Bruno Jouvencel

Abstract:

The objective of this paper is to develop the 3D underwater reconstruction of archaeology object, which is based on the fusion between a sonar system and stereo camera system. The underwater images are obtained from a calibrated camera system. The multiples image pairs are input, and we first solve the problem of image processing by applying the well-known filter, therefore to improve the quality of underwater images. The features of interest between image pairs are selected by well-known methods: a FAST detector and FLANN descriptor. Subsequently, the RANSAC method is applied to reject outlier points. The putative inliers are matched by triangulation to produce the local sparse point clouds in 3D space, using a pinhole camera model and Euclidean distance estimation. The SFM technique is used to carry out the global sparse point clouds. Finally, the ICP method is used to fusion the sonar information with the stereo model. The final 3D models have a précised by measurement comparing with the real object.

Keywords: 3D reconstruction, archaeology, fusion, stereo system, sonar system, underwater

Procedia PDF Downloads 283

Authors: Bhuyain Mobarok Hossain

Abstract:

Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

Procedia PDF Downloads 271

Authors: Nada Slimane, Foued Theljani, Faouzi Bouani

Abstract:

The paper addresses the problem of fault diagnosis for systems operating in several modes (normal or faulty) based on states assessment. We use, for this purpose, a methodology consisting of three main processes: 1) sequential data clustering, 2) linear model regression and 3) state filtering. Typically, Kalman Filter (KF) is an algorithm that provides estimation of unknown states using a sequence of I/O measurements. Inevitably, although it is an efficient technique for state estimation, it presents two main weaknesses. First, it merely predicts states without being able to isolate/classify them according to their different operating modes, whether normal or faulty modes. To deal with this dilemma, the KF is endowed with an extra clustering step based fully on sequential version of the k-means algorithm. Second, to provide state estimation, KF requires state space models, which can be unknown. A linear regularized regression is used to identify the required models. To prove its effectiveness, the proposed approach is assessed on a simulated benchmark.

Keywords: clustering, diagnosis, Kalman Filtering, k-means, regularized regression

Procedia PDF Downloads 152

Authors: Abe D. Desta

Abstract:

This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

Procedia PDF Downloads 79

Authors: Edwin Forero-Garcia, Jaime Vitola, Brayan Cardenas, Johan Casagua

Abstract:

This research article presents the integration of electronic and computer systems, which developed an ultrasonic signal processing system that performs the capture, adaptation, and analog-digital conversion to later carry out its processing and visualization. The capture and adaptation of the signal were carried out from the design and implementation of an analog electronic system distributed in stages: 1. Coupling of impedances; 2. Analog filter; 3. Signal amplifier. After the signal conditioning was carried out, the ultrasonic information was digitized using a digital microcontroller to carry out its respective processing. The digital processing of the signals was carried out in MATLAB software for the elaboration of A-Scan, B and D-Scan types of ultrasonic images. Then, advanced processing was performed using the SAFT technique to improve the resolution of the Scan-B-type images. Thus, the information from the ultrasonic images was displayed in a user interface developed in .Net with Visual Studio. For the validation of the system, ultrasonic signals were acquired, and in this way, the non-invasive inspection of the structures was carried out and thus able to identify the existing pathologies in them.

Keywords: acquisition, signal processing, ultrasound, SAFT, HMI

Procedia PDF Downloads 77

Authors: Ellana Boada, Eric Santos-Clotas, Alba Cabrera-Codony, Maria Martin, Lluis Baneras, Frederic Gich

Abstract:

Volatile methylsiloxanes (VMS) are a group of manmade silicone compounds widely used in household and industrial applications that end up on the biogas produced through the anaerobic digestion of organic matter in landfills and wastewater treatment plants. The presence of VMS during the biogas energy conversion can cause damage on the engines, reducing the efficiency of this renewable energy source. Non regenerative adsorption onto activated carbon is the most widely used technology to remove siloxanes from biogas, while new trends point out that biotechnology offers a low-cost and environmentally friendly alternative to conventional technologies. The first objective of this research was to enrich, isolate and identify bacterial species able to grow using siloxane molecules as a sole carbon source: anoxic wastewater sludge was used as initial inoculum in liquid anoxic enrichments, adding D4 (as representative siloxane compound) previously adsorbed on activated carbon. After several months of acclimatization, liquid enrichments were plated onto solid media containing D4 and thirty-four bacterial isolates were obtained. 16S rRNA gene sequencing allowed the identification of strains belonging to the following species: Ciceribacter lividus, Alicycliphilus denitrificans, Pseudomonas aeruginosa and Pseudomonas citronellolis which are described to be capable to degrade toxic volatile organic compounds. Kinetic assays with 8 representative strains revealed higher cell growth in the presence of D4 compared to the control. Our second objective was to characterize the community composition and diversity of the microbial community present in the enrichments and to elucidate whether the isolated strains were representative members of the community or not. DNA samples were extracted, the 16S rRNA gene was amplified (515F & 806R primer pair), and the microbiome analyzed from sequences obtained with a MiSeq PE250 platform. Results showed that the retrieved isolates only represented a minor fraction of the microorganisms present in the enrichment samples, which were represented by Alpha, Beta, and Gamma proteobacteria as dominant groups in the category class thus suggesting that other microbial species and/or consortia may be important for D4 biodegradation. These results highlight the need of additional protocols for the isolation of relevant D4 degraders. Currently, we are developing molecular tools targeting key genes involved in siloxane biodegradation to identify and quantify the capacity of the isolates to metabolize D4 in batch cultures supplied with a synthetic gas stream of air containing 60 mg m⁻³ of D4 together with other volatile organic compounds found in the biogas mixture (i.e. toluene, hexane and limonene). The isolates were used as inoculum in a biotrickling filter containing lava rocks and activated carbon to assess their capacity for siloxane removal. Preliminary results of biotrickling filter performance showed 35% of siloxane biodegradation in a contact time of 14 minutes, denoting that biological siloxane removal is a promising technology for biogas upgrading.

Keywords: bacterial cultivation, biogas upgrading, microbiome, siloxanes

Procedia PDF Downloads 228

Authors: Saumya Srivastava, Rina Maiti

Abstract:

In order to achieve a better performance of vehicle detection in a complex environment, we present an efficient approach for a multi-vehicle detection system using an adaptive sliding window technique. For a given frame, image segmentation is carried out to establish the region of interest. Gradient computation followed by thresholding, denoising, and morphological operations is performed to extract the binary search image. Near-region field and far-region field are defined to generate hypotheses using the adaptive sliding window technique on the resultant binary search image. For each vehicle candidate, features are extracted using a histogram of oriented gradients, and a pre-trained support vector machine is applied for hypothesis verification. Later, the Kalman filter is used for tracking the vanishing point. The experimental results show that the method is robust and effective on various roads and driving scenarios. The algorithm was tested on highways and urban roads in India.

Keywords: gradient, vehicle detection, histograms of oriented gradients, support vector machine

Procedia PDF Downloads 94

Authors: A. Casale, J. Alessi, C. N. Bianchi, G. Bozzini, M. Brunoldi, V. Cappanera, P. Corvisiero, G. Fanciulli, D. Grosso, N. Magnoli, A. Mandich, C. Melchiorre, C. Morri, P. Povero, N. Stasi, M. Taiuti, G. Viano, M. Wurtz

Abstract:

This work describes a real-time algorithm for detecting, tracking and classifying single motorboats, developed using the acoustic data recorded by a hydrophone array within the framework of EU LIFE + project ARION (LIFE09NAT/IT/000190). The project aims to improve the conservation status of bottlenose dolphins through a real-time simultaneous monitoring of their population and surface ship traffic. A Passive Acoustic Monitoring (PAM) system is installed on two autonomous permanent marine buoys, located close to the boundaries of the Marine Protected Area (MPA) of Portofino (Ligurian Sea- Italy). Detecting surface ships is also a necessity in many other sensible areas, such as wind farms, oil platforms, and harbours. A PAM system could be an effective alternative to the usual monitoring systems, as radar or active sonar, for localizing unauthorized ship presence or illegal activities, with the advantage of not revealing its presence. Each ARION buoy consists of a particular type of structure, named meda elastica (elastic beacon) composed of a main pole, about 30-meter length, emerging for 7 meters, anchored to a mooring of 30 tons at 90 m depth by an anti-twist steel wire. Each buoy is equipped with a floating element and a hydrophone tetrahedron array, whose raw data are send via a Wi-Fi bridge to a ground station where real-time analysis is performed. Bottlenose dolphin detection algorithm and ship monitoring algorithm are operating in parallel and in real time. Three modules were developed and commissioned for ship monitoring. The first is the detection algorithm, based on Time Difference Of Arrival (TDOA) measurements, i.e., the evaluation of angular direction of the target respect to each buoy and the triangulation for obtaining the target position. The second is the tracking algorithm, based on a Kalman filter, i.e., the estimate of the real course and speed of the target through a predictor filter. At last, the classification algorithm is based on the DEMON method, i.e., the extraction of the acoustic signature of single vessels. The following results were obtained; the detection algorithm succeeded in evaluating the bearing angle with respect to each buoy and the position of the target, with an uncertainty of 2 degrees and a maximum range of 2.5 km. The tracking algorithm succeeded in reconstructing the real vessel courses and estimating the speed with an accuracy of 20% respect to the Automatic Identification System (AIS) signals. The classification algorithm succeeded in isolating the acoustic signature of single vessels, demonstrating its temporal stability and the consistency of both buoys results. As reference, the results were compared with the Hilbert transform of single channel signals. The algorithm for tracking multiple targets is ready to be developed, thanks to the modularity of the single ship algorithm: the classification module will enumerate and identify all targets present in the study area; for each of them, the detection module and the tracking module will be applied to monitor their course.

Keywords: acoustic-noise, bottlenose-dolphin, hydrophone, motorboat

Procedia PDF Downloads 141

Authors: Rizwan Ullah, Abdar Ali, Zahid Ullah

Abstract:

This paper illustrates the study of three isolated zero voltage switched (ZVS) PWM full bridge (FB) converters to charge the high voltage battery in the charger of electric vehicle (EV). EV battery chargers have several challenges such as high efficiency, high reliability, low cost, isolation, and high power density. The cost of magnetic and filter components in the battery charger is reduced when switching frequency is increased. The increase in the switching frequency increases switching losses. ZVS is used to reduce switching losses and to operate the converter in the battery charger at high frequency. The performance of each of the three converters is evaluated on the basis of ZVS range, dead times of the switches, conduction losses of switches, circulating current stress, circulating energy, duty cycle loss, and efficiency. The limitations and merits of each PWM FB converter are reviewed. The converter with broader ZVS range, high efficiency and low switch stresses is selected for battery charger applications in EV.

Keywords: electric vehicle, PWM FB converter, zero voltage switching, circulating energy

Procedia PDF Downloads 413

Authors: Elias Nemer, Greg Vines

Abstract:

Time-frequency transformation and spectral representations of audio signals are commonly used in various machine learning applications. Training networks on frequency features such as the Mel-Spectrogram or Cochleogram have been proven more effective and convenient than training on-time samples. In practical realizations, these features are created on a different processor and/or pre-computed and stored on disk, requiring additional efforts and making it difficult to experiment with different features. In this paper, we provide a PyTorch framework for creating various spectral features as well as time-frequency transformation and time-domain filter-banks using the built-in trainable conv1d() layer. This allows computing these features on the fly as part of a larger network and enabling easier experimentation with various combinations and parameters. Our work extends the work in the literature developed for that end: First, by adding more of these features and also by allowing the possibility of either starting from initialized kernels or training them from random values. The code is written as a template of classes and scripts that users may integrate into their own PyTorch classes or simply use as is and add more layers for various applications.

Keywords: neural networks Mel-Spectrogram, chromagram, cochleogram, discrete Fourrier transform, PyTorch conv1d()

Procedia PDF Downloads 200

Authors: Simon Huston, Ebraheim Lahbash, Ali Parsa

Abstract:

The development of the United Arab Emirates (UAE) into a regional trade, tourism, finance and logistics hub has transformed its real estate markets. However, speculative activity and price volatility remain concerns. UAE residential market values (MV) are exposed to fluctuations in capital flows and migration which in turn are affected by geopolitical uncertainty, oil price volatility, and global investment market sentiment. Internally, a complex interplay between administrative boundaries, land tenure, building quality and evolving location characteristics fragments UAE residential property markets. In short, the UAE Residential Valuation System (UAE-RVS) confronts multiple challenges to collect, filter and analyze relevant information in complex and dynamic spatial and capital markets. A robust (RVS) can mitigate the risk of unhelpful volatility, speculative excess or investment mistakes. The research outlines the institutional, ontological, dynamic, and epistemological issues at play. We highlight the importance of system capabilities, valuation standard salience and stakeholders trust.

Keywords: valuation, property rights, information, institutions, trust, salience

Procedia PDF Downloads 356

Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

Abstract:

Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

Procedia PDF Downloads 238

Authors: Jennis Delina Giles, Nimesha Liyanage, Damindi Senadheera, Dilan Randima, Kushnara Suriyawansa

Abstract:

Mental health is essential during childhood, adolescence, and adulthood. Mental health issues can influence one's thoughts, disposition, and conduct. A record number of mental health problems are caused by a global pandemic. Prevention of mental disease is vital for both children and adults. We desired to develop a web application for those with mental health difficulties. This web application will provide group chat, discussion, a community feed, and counseling services. The community feed function provides information regarding scheduled conversation space meetings, and the counselor uploads uplifting thoughts and tales of patients who received proper care and overcame mental health issues. Community feed can filter content based on user preferences. The mental health system for adults and adolescents will be updated. The community feed delivers relevant and instructive postings, links, and images so that service recipients can benefit from other platform features and receive encouraging words to assist them in overcoming mental health difficulties.

Keywords: bio medical, mental helath care, empower youths & adults, counselling

Procedia PDF Downloads 130

Authors: Joe Amalraj, M. Arunkumar

Abstract:

Haze is an atmospheric phenomenon that signicantly degrades the visibility of outdoor scenes. This is mainly due to the atmosphere particles that absorb and scatter the light. This paper introduces a novel single image approach that enhances the visibility of such degraded images. In this method is a fusion-based strategy that derives from two original hazy image inputs by applying a white balance and a contrast enhancing procedure. To blend effectively the information of the derived inputs to preserve the regions with good visibility, we filter their important features by computing three measures (weight maps): luminance, chromaticity, and saliency. To minimize artifacts introduced by the weight maps, our approach is designed in a multiscale fashion, using a Laplacian pyramid representation. This paper demonstrates the utility and effectiveness of a fusion-based technique for de-hazing based on a single degraded image. The method performs in a per-pixel fashion, which is straightforward to implement. The experimental results demonstrate that the method yields results comparative to and even better than the more complex state-of-the-art techniques, having the advantage of being appropriate for real-time applications.

Keywords: single image de-hazing, outdoor images, enhancing, DSP

Procedia PDF Downloads 379

Authors: Saugata Bose, Ritambhra Korpal

Abstract:

The internet has increased the copy-paste scenarios amongst students as well as amongst researchers leading to different levels of plagiarized documents. For this reason, much of research is focused on for detecting plagiarism automatically. In this paper, an initiative is discussed where Natural Language Processing (NLP) techniques as well as supervised machine learning algorithms have been combined to detect plagiarized texts. Here, the major emphasis is on to construct a framework which detects external plagiarism from monolingual texts successfully. For successfully detecting the plagiarism, n-gram frequency comparison approach has been implemented to construct the model framework. The framework is based on 120 characteristics which have been extracted during pre-processing the documents using NLP approach. Afterwards, filter metrics has been applied to select most relevant characteristics and then supervised classification learning algorithm has been used to classify the documents in four levels of plagiarism. Confusion matrix was built to estimate the false positives and false negatives. Our plagiarism framework achieved a very high the accuracy score.

Keywords: lexical matching, shallow NLP, supervised machine learning algorithm, word n-gram

Procedia PDF Downloads 336

Authors: Takashi Kaburagi, Takamasa Komura, Yosuke Kurihara

Abstract:

Absolute pitch is the ability to identify a musical note without a reference tone. Training for absolute pitch often occurs in preschool education. It is necessary to clarify how well the trainee can make use of synesthesia in order to evaluate the effect of the training. To the best of our knowledge, there are no existing methods for objectively confirming whether the subject is using synesthesia. Therefore, in this study, we present a method to distinguish the use of color-auditory synesthesia from the separate use of color and audition during absolute pitch training. This method measures blood volume in the prefrontal cortex using functional Near-infrared spectroscopy (fNIRS) and assumes that the cognitive step has two parts, a non-linear step and a linear step. For the linear step, we assume a second order ordinary differential equation. For the non-linear part, it is extremely difficult, if not impossible, to create an inverse filter of such a complex system as the brain. Therefore, we apply a method based on a self-organizing map (SOM) and are guided by the available data. The presented method was tested using 15 subjects, and the estimation accuracy is reported.

Keywords: absolute pitch, functional near-infrared spectroscopy, prefrontal cortex, synesthesia

Procedia PDF Downloads 242

Authors: Migena Ceyhan, Zeynep Orhan, Dimitrios Karras

Abstract:

People in modern societies are continuously sharing their experiences, emotions, and thoughts in different areas of life. The information reaches almost everyone in real-time and can have an important impact in shaping people’s way of living. This phenomenon is very well recognized and advantageously used by the market representatives, trying to earn the most from this means. Given the abundance of information, people and organizations are looking for efficient tools that filter the countless data into important information, ready to analyze. This paper is a modest contribution in this field, describing the process of automatically classifying social media comments in the Turkish language into positive or negative. Once data is gathered and preprocessed, feature sets of selected single words or groups of words are build according to the characteristics of language used in the texts. These features are used later to train, and test a system according to different machine learning algorithms (Naïve Bayes, Sequential Minimal Optimization, J48, and Bayesian Linear Regression). The resultant high accuracies can be important feedback for decision-makers to improve the business strategies accordingly.

Keywords: feature selection, machine learning, natural language processing, sentiment analysis, social media reviews

Procedia PDF Downloads 124

Authors: Pinghe Wang

Abstract:

In this paper, we demonstrate a tunable long-cavity passive mode-locked fiber laser. The mode locker is a nonlinear amplifying loop mirror (NALM). The cavity frequency of the laser is 465 kHz because that 404m SMF is inserted in the cavity. A tunable bandpass filter with ~1nm 3dB bandwidth is inserted into the cavity to realize tunable mode locking. The passive mode-locked laser at a fixed wavelength is investigated in detail. The experimental results indicate that the laser operates in dissipative soliton resonance (DSR) region. When the pump power is 400mW, the laser generates the rectangular pulses with 10.58 ns pulse duration, 70.28nJ single-pulse energy. When the pump power is 400mW, the laser keeps stable mode locking status in the range from 1523.4nm to 1575nm. During the whole tuning range, the SNR, the pulse duration, the output power and single pulse energy have a little fluctuation because that the gain of the EDF changes with the wavelength.

Keywords: fiber laser, dissipative soliton resonance, mode locking, tunable

Procedia PDF Downloads 212

Authors: Muhammad Hamza

Abstract:

This study attempts to analyze the social media reports regarding Covid-19 that impacted the psyche of Pakistanis. This Study is delimited to hashtags from Tweets on a social media platform. During Covid-19, it has been observed that it affected the psychological conditions of Pakistanis. With the application of the three-dimensional model presented by Fairclough, together with a data analytic software “FireAnt” i.e., social media and data analysis toolkit, which is used to filter, identify, report and export data from social media accurately. A detailed and explicit exploration of the various hashtags by users from different fields was conducted. This study conducted a quantitative as well as qualitative methods of analysis. The study examined the perspectives of the Pakistanis behind the use of various hashtags with the lenses of Critical Discourse Analysis (CDA). While conducting this research, CDA was helpful to reveal the connection between the psyche of the people and the Covid-19 pandemic. It was found that how different Pakistanis used social media and how Covid-19 impacted their psyche. After collecting and analyzing the hashtags from twitter it was concluded that majority of people received negative impact from social media reports, while, some people used their hashtags positively and were found positive during Covid-19, and some people were found neutral.

Keywords: Covid, Covid-19, psyche, Covid Pakistan

Procedia PDF Downloads 32

Authors: M. Benhaliliba, A. Ben Ahmed, C.E. Benouis, A.Ayeshamariam

Abstract:

The properties of nonlinear optical NLOs are examined, and the results confirm the 2.19 eV HOMO-LUMO mismatch. In the Al-Pc cluster, certain functional bond lengths and bond angles have been observed. The Quantum chemical method (DFT and TD-DFT) and Vibrational spectra properties of AlPc are studied. X-ray pattern reveals the crystalline structure along with the (242) orientation of the AlPc organic thin layer. UV-Vis shows the frequency selective behavior of the device. The absorbance of such layer exhibits a high value within the UV range and two consecutive peaks within visible range. Spin coating is used to make an organic diode based on the Aluminium-phthalocynanine (AlPc-Cl) molecule. Under dark and light conditions, electrical characterization of Ag/AlPc/Si/Au is obtained. The diode's high rectifying capability (about 1x104) is subsequently discovered. While the height barrier is constant and saturation current is greatly reliant on light, the ideality factor of such a diode increases to 6.9 which confirms the non-ideality of such a device. The Cheung-Cheung technique is employed to further the investigation and gain additional data such as series resistance and barrier height.

Keywords: AlPc-Cl organic material, nonlinear optic, optical filter, diode

Procedia PDF Downloads 110