Search results for: optical music recognition

Authors: M. M. Moharam, E. M. Elsayed, M. M. Rashad

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Single phase Cu₂O films have been prepared via an electrodeposition technique onto ITO glass substrates at room temperature. Likewise, Cu₂O films were deposited using a potentiostatic process from an alkaline electrolyte containing copper (II) nitrate and 1M sodium citrate. Single phase Cu₂O films were electrodeposited at a cathodic deposition potential of 500mV for a reaction period of 90 min, and pH of 12 to yield a film thickness of 0.49 µm. The mechanism for nucleation of Cu₂O films was found to vary with deposition potential. Applying the Scharifker and Hills model at -500 and -600 mV to describe the mechanism of nucleation for the electrochemical reaction, the nucleation mechanism consisted of a mix between instantaneous and progressive growth mechanisms at -500 mV, while above -600 mV the growth mechanism was instantaneous. Using deposition times from 30 to 90 min at -500 mV deposition potential, pure Cu2O films with different microstructures were electrodeposited. Changing the deposition time from 30 to 90 min varied the microstructure from cubic to more complex polyhedra. The transmittance of electrodeposited Cu₂O films ranged from 20-70% in visible range, and samples exhibited a 2.4 eV band gap. The electrical resistivity for electrodeposited Cu₂O films was found to decrease with increasing deposition time from 0.854 x 105 Ω-cm at 30 min to 0.221 x 105 Ω-cm at 90 min without any thermal treatment following the electrodeposition process.

Keywords: Cu₂O, electrodeposition, film thickness, characterization, optical properties

Procedia PDF Downloads 205

Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

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Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

Procedia PDF Downloads 469

Authors: Paul Hernandez-Herrera, Fernando Montoya, Juan Manuel Rendon, Alberto Darszon, Gabriel Corkidi

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Intracellular calcium ([Ca2+]i) regulates sperm motility. The analysis of [Ca2+]i has been traditionally achieved in two dimensions while the real movement of the cell takes place in three spatial dimensions. Due to optical limitations (high speed cell movement and low light emission) important data concerning the three dimensional movement of these flagellated cells had been neglected. Visualizing [Ca2+]i in 3D is not a simple matter since it requires complex fluorescence microscopy techniques where the resulting images have very low intensity and consequently low SNR (Signal to Noise Ratio). In 4D sequences, this problem is magnified since the flagellum oscillates (for human sperm) at least at an average frequency of 15 Hz. In this paper, a novel approach to extract the flagellum’s center-line in 4D stacks is presented. For this purpose, an iterative algorithm based on the fast-marching method is proposed to extract the flagellum’s center-line. Quantitative and qualitative results are presented in a 4D stack to demonstrate the ability of the proposed algorithm to trace the flagellum’s center-line. The method reached a precision and recall of 0.96 as compared with a semi-manual method.

Keywords: flagellum, minimal path, segmentation, sperm

Procedia PDF Downloads 277

Authors: B. Sabayan, A. Alidadi, S. Ebrahimi, N. M. Bakhshani

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Neuropsychological problems are more common in hemodialysis (HD) patients than in healthy individuals. The aim of this study was to investigate the effect of long term HD on memory types of HD patients. To assess the different type of memory, we used memory parts of the Persian Papers and Pencil Cognitive assessment package (PCAP) and Addenbrooke's Cognitive Examination (ACE-R). Our study included 80 HD patients of whom 39 had less than six months of HD and 41 patients and another group which had a history of HD more than six months. The population had a mean age of 51.60 years old and 27.5% of them were female. The scores of patients who have been hemodialyzed for a long time (median time of HD was up to 4 years) had lower score in anterograde, explicit, visual, recall and recognition memory (5.44±1.07, 9.49±3.472, 22.805±6.6913, 5.59±10.435, 11.02±3.190 score) than the HD patients who underwent HD for a shorter term, where the median time was 3 to 5 months (P<0.01). The regression result shows that, by increasing the HD duration, all memory types are reduced (R2=0.600, P<0.01). The present study demonstrated that HD patients who were under HD for a long time had significantly lower scores in the different types of memory. However, additional researches are needed in this area.

Keywords: hemodialysis patients, duration of hemodialysis, memory types, Zahedan

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Authors: Pogula Rakesh, T. Kishore Kumar

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Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.

Keywords: adaptive filter, adaptive noise canceller, mean squared error, noise reduction, NLMS, RLS, SNR, SNR loss

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Authors: Lowanika Victor Tibane, David Mamba

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Human body, animals, and plants depend on certain essential metals in permissible quantities for their survival. Excessive metal concentration may cause severe malfunctioning of the organisms and even fatal in extreme cases. Because of gold mining in the Witwatersrand basin in South Africa, enormous untreated mine dumps comprise elevated concentration of essential trace elements. Elevated quantities of trace metal have direct negative impact on the quality of soil for different land use types, reduce soil efficiency for plant growth, and affect the health human and animals. A total of 21 subsoil samples were examined using inductively coupled plasma optical emission spectrometry and X-ray fluorescence methods and the results elevated men concentration of Fe (36,433.39) > S (5,071.83) > Cu (1,717,28) > Mn (612.81) > Cr (74.52) > Zn (68.67) > Ni (40.44) > Co (9.63) > P (3.49) > Mo > (2.74), reported in mg/kg. Using various contamination indices, it was discovered that the sites surveyed are on average moderately contaminated with Co, Cr, Cu, Mn, Ni, S, and Zn. The ecological risk assessment revealed a low ecological risk for Cr, Ni and Zn, whereas Cu poses a very high ecological risk.

Keywords: essential trace elements, soil contamination, contamination indices, toxicity, descriptive statistics, ecological risk evaluation

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Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

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The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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Authors: Zafar Mahmood, Surayya Naz, Nazir Shah Khattak

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The degree of freedom relates to our capability to observe or model the energy paths within the system. Higher the number of energy paths being modeled leaves to us a higher degree of freedom, but increasing the time and modeling complexity rendering it useless for today’s world’s need for minimum time to market. Since the number of residuals that can be uniquely isolated are dependent on the number of independent outputs of the system, increasing the number of sensors required. The examples of discrete position sensors that may be used to form an array include limit switches, Hall effect sensors, optical sensors, magnetic sensors, etc. Their mechanical design can usually be tailored to fit in the transitional path of an STME in a variety of mechanical configurations. The case studies into multi-sensor system were carried out and actual data from sensors is used to test this generic framework. It is being investigated, how the proper modeling of limit switches as timing sensors, could lead to unified and neutral residual space while keeping the implementation cost reasonably low.

Keywords: low-cost limit sensors, fault diagnostics, Single Throw Mechanical Equipment (STME), parameter estimation, parity-space

Procedia PDF Downloads 603

Authors: Hosseini Siahi Zohreh, Sana Mohammad Jafar

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With increase in fat and over weight in children and its undesirable effects on different organisms of the body and since many of the sicknesses are due to over weight and with losing weight these sicknesses disappear, and on the other hand with mal nutrition and under weight in children other kind of sicknesses such as derogation of body's security system, frequent infection, insufficient growth, shortness, and delay in maturity etc. are some of the signs of being under weight. Therefore recognition of signs of over weight and under weight and their prevalence in children are important. To determine this difficulty we have used the body mass index as screening tool since it is very prevalent and a good and important guide and has very good relation with body fat in children. In this study 2321 students from primary schools in Behbahan have been chosen randomly and evaluated by height and weight and their body mass index have been calculated and then recorded on the BMI percentile diagram which is for age and gender. The following results obtained: The amount of total fat, over weight and slimness are 9.3, 12.1 and 12.32 percent respectively. Therefore 21.4% of the children were over weighted. It did not show any meaningful statistical relation in fat conditions among boys and girls, but there has been a meaningful statistical relation in slimness among boys and girls.

Keywords: assessment, students, Behbahan, Body Mass Index

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Authors: Nunziata Ivana Guarneri, Arcangelo Bruna, Giuseppe Spampinato, Antonio Buemi

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In the last decade, automotive companies have invested a lot in terms of innovation about many aspects regarding the automatic driver assistance systems. One innovation regards the usage of a smart camera placed on the car’s side mirror for monitoring the back and lateral road situation. A common road scenario is the overtaking of the preceding car and, in this case, a brief distraction or a loss of concentration can lead the driver to undertake this action, even if there is an already overtaking vehicle, leading to serious accidents. A valid support for a secure drive can be a smart camera system, which is able to automatically analyze the road scenario and consequentially to warn the driver when another vehicle is overtaking. This paper describes a method for monitoring the side view of a vehicle by using camera optical flow motion vectors. The proposed solution detects the presence of incoming vehicles, assesses their distance from the host car, and warns the driver through different levels of alert according to the estimated distance. Due to the low complexity and computational cost, the proposed system ensures real time performances.

Keywords: camera calibration, ego-motion, Kalman filters, object tracking, real time systems

Procedia PDF Downloads 218

Authors: P. S. Jagadeesh Kumar, S. Meenakshi Sundaram, Wenli Hu, Yang Yung

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In 3D video games, the dominance of production is unceasingly growing with a protruding level of affordability in terms of budget. Afterward, the automation of speech-lip synchronization technique is customarily onerous and has advanced a critical research subject in virtual reality based 3D video games. This paper presents one of these automatic tools, precisely riveted on the synchronization of the speech and the lip movement of the game characters. A robust and precise speech recognition segment that systematized with Algebraic Code Excited Linear Prediction method is developed which unconventionally delivers lip sync results. The Algebraic Code Excited Linear Prediction algorithm is constructed on that used in code-excited linear prediction, but Algebraic Code Excited Linear Prediction codebooks have an explicit algebraic structure levied upon them. This affords a quicker substitute to the software enactments of lip sync algorithms and thus advances the superiority of service factors abridged production cost.

Keywords: algebraic code excited linear prediction, speech-lip synchronization, video games, virtual reality

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Authors: Joel Niklaus, Matthias Sturmer

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The publication of judicial proceedings is a cornerstone of many democracies. It enables the court system to be made accountable by ensuring that justice is made in accordance with the laws. Equally important is privacy, as a fundamental human right (Article 12 in the Declaration of Human Rights). Therefore, it is important that the parties (especially minors, victims, or witnesses) involved in these court decisions be anonymized securely. Today, the anonymization of court decisions in Switzerland is performed either manually or semi-automatically using primitive software. While much research has been conducted on anonymization for tabular data, the literature on anonymization for unstructured text documents is thin and virtually non-existent for court decisions. In 2019, it has been shown that manual anonymization is not secure enough. In 21 of 25 attempted Swiss federal court decisions related to pharmaceutical companies, pharmaceuticals, and legal parties involved could be manually re-identified. This was achieved by linking the decisions with external databases using regular expressions. An automated re-identification system serves as an automated test for the safety of existing anonymizations and thus promotes the right to privacy. Manual anonymization is very expensive (recurring annual costs of over CHF 20M in Switzerland alone, according to an estimation). Consequently, many Swiss courts only publish a fraction of their decisions. An automated anonymization system reduces these costs substantially, further leading to more capacity for publishing court decisions much more comprehensively. For the re-identification system, topic modeling with latent dirichlet allocation is used to cluster an amount of over 500K Swiss court decisions into meaningful related categories. A comprehensive knowledge base with publicly available data (such as social media, newspapers, government documents, geographical information systems, business registers, online address books, obituary portal, web archive, etc.) is constructed to serve as an information hub for re-identifications. For the actual re-identification, a general-purpose language model is fine-tuned on the respective part of the knowledge base for each category of court decisions separately. The input to the model is the court decision to be re-identified, and the output is a probability distribution over named entities constituting possible re-identifications. For the anonymization system, named entity recognition (NER) is used to recognize the tokens that need to be anonymized. Since the focus lies on Swiss court decisions in German, a corpus for Swiss legal texts will be built for training the NER model. The recognized named entities are replaced by the category determined by the NER model and an identifier to preserve context. This work is part of an ongoing research project conducted by an interdisciplinary research consortium. Both a legal analysis and the implementation of the proposed system design ESRA will be performed within the next three years. This study introduces the system design of ESRA, an end-to-end system for re-identification and anonymization of Swiss court decisions. Firstly, the re-identification system tests the safety of existing anonymizations and thus promotes privacy. Secondly, the anonymization system substantially reduces the costs of manual anonymization of court decisions and thus introduces a more comprehensive publication practice.

Keywords: artificial intelligence, courts, legal tech, named entity recognition, natural language processing, ·privacy, topic modeling

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Authors: C. S. Paglia

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The deformation and the crystallization in a 7075-T651 friction stir weld, in particular for regions directly in contact with the mechanical action of the rotating probe, have been investigated by means of optical microscopy. The investigation enabled to identify regions of the weld differently affected by the deformation caused by the welding process. The highly deformed grains in the horizontal direction close to the plate margin were indicative of shear movements along the horizontal plane, while highly deformed grains along the plate margin in the vertical direction were indicative of vertical shear movements of opposite directions, which superimposed the shear movement along the horizontal plane. The vertical shear movements were not homogeneous through the plate thickness. The microstructure indicated that after the probe passes, the grain growth may take place under static conditions. The small grains microstructure of the nugget region, formed after the main dynamic recrystallization process, develops to an equiaxed microstructure. A material transport influenced by the rotating shoulder was also observed from the trailing to the advancing side of the weld.

Keywords: AA7075-T651, friction stir welding, deformation, crystallization

Procedia PDF Downloads 118

Authors: V. Santamarina Campos, M. de Miguel Molina, B. de Miguel Molina, M. Á. Carabal Montagud

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With this contribution, we want to show a successful example of the application of the Design Thinking methodology, in the European project 'Technology transfer of Remotely Piloted Aircraft Systems (RPAS) for the creative industry'. The use of this methodology has allowed us to design and build a drone, based on the real needs of prospective users. It has demonstrated that this is a powerful tool for generating innovative ideas in the field of robotics, by focusing its effectiveness on understanding and solving real user needs. In this way, with the support of an interdisciplinary team, comprised of creatives, engineers and economists, together with the collaboration of prospective users from three European countries, a non-linear work dynamic has been created. This teamwork has generated a sense of appreciation towards the creative industries, through continuously adaptive, inventive, and playful collaboration and communication, which has facilitated the development of prototypes. These have been designed to enable filming and photography in interior spaces, within 13 sectors of European creative industries: Advertising, Architecture, Fashion, Film, Antiques and Museums, Music, Photography, Televison, Performing Arts, Publishing, Arts and Crafts, Design and Software. Furthermore, it has married the real needs of the creative industries, with what is technologically and commercially viable. As a result, a product of great value has been obtained, which offers new business opportunities for small companies across this sector.

Keywords: design thinking, design for effectiveness, methodology, active toolkit, storyboards, PAR, focus group, innovation, RPAS, indoor drone, aerial film, creative industry, end users, stakeholder

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Authors: Abdurrahim A. Elouzi, Abdurrauf M. Gusbi, Ali M. Elgerbi

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Antibiotic resistance has become a global public-health problem, thus it is imperative that new antibiotics continue to be developed. Major problems are being experienced in human medicine from antibiotic resistant bacteria. Moreover, no new chemical class of antibiotics has been introduced into medicine in the past two decades. The aim of the current study presents experimental results that evaluate the capability of bio surfactant rhamnolipid on enhancing the efficacy of hydrophobic antibiotics. Serial dilutions of azithromycin and clarithromycin were prepared. A bacterial suspension (approximately 5 X 105 CFU) from an overnight culture in MSM was inoculated into 20 ml sterile test tube each containing a serial 10-fold dilution of the test antibiotic(s) in broth with or without 200 mgL-1 rhamnolipid. The tubes were incubated for 24 h with vigorous shaking at 37°C. Antimicrobial activity in multiple antibiotic-resistant gram-negative bacteria pathogens and gram-positive bacteria were assessed using optical density technique. The results clearly demonstrated that the presence of rhamnolipid significantly improved the efficiency of both antibiotics. We hypothesized that the addition of rhamnolipid at low concentration, causes release of LPS which results in an increase in cell surface hydrophobicity. This allows increased association of cells with hydrophobic antibiotics resulting in increased cytotoxicity rates.

Keywords: hydrophobic antibiotics, biosurfactant, rhamnolipid, azithromycin, clarithromycin

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Authors: Argyro Maria Skourmalla

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The present paper draws on the example of the University of Luxembourg as a multilingual and international setting. The University of Luxembourg, which is located between France, Germany, and Belgium, has adopted a new multilingualism policy in 2020, establishing English, French, German, and Luxembourgish as the official languages of the Institution. With around 7.000 students, more than half of which are international students, the University is a meeting point for languages and cultures. This paper includes data from an online survey that with undergraduate students from different disciplines at the University of Luxembourg. Students shared their personal experience and opinions regarding language use in this higher education context, as well as practices they use in learning in this multilingual context. Findings show the role of technology in assisting students in different aspects of learning this multilingual context. At the same time, more needs to be done to avoid an exclusively monolingual paradigm in higher education. Findings also show that some languages remain ‘unseen’ in this context. Overall, even though linguistic diversity in this University is seen as an asset, a lot needs to be done towards the recognition of staff and students’ linguistic repertoires for inclusion and education equity.

Keywords: higher education, learning, linguistic diversity, multilingual practices

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Authors: Mahfuzur Rahman

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Back-contact solar cells improve optical properties by moving all electrically conducting parts to the back of the cell. The cell's structure allows silicon solar cells to surpass the 25% efficiency barrier and interdigitated solar cells are now the most efficient. In this work, the fabrication of a light, efficient and temperature resistant interdigitated back contact (IBC) solar cell is investigated. This form of solar cell differs from a conventional solar cell in that the electrodes are located at the back of the cell, eliminating the need for grids on the top, allowing the full surface area of the cell to receive sunlight, resulting in increased efficiency. In this project, we will use SILVACO TCAD, an optoelectronic device simulator, to construct a very thin solar cell with dimensions of 100x250um in 2D Luminous. The influence of sunlight intensity and atmospheric temperature on solar cell output power is highly essential and it has been explored in this work. The cell's optimum performance with 150um bulk thickness provides 28.81% efficiency with an 87.68% fill factor rate making it very thin, flexible and resilient, providing diverse operational capabilities.

Keywords: interdigitated, shading, recombination loss, incident-plane, drift-diffusion, luminous, SILVACO

Procedia PDF Downloads 139

Authors: Nelson Nenuwe

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The behavior of interacting electrons in one dimension was studied by calculating correlation functions and critical exponents at zero and external magnetic fields for arbitrary band filling. The technique employed in this study is based on the conformal field theory (CFT). The charge and spin degrees of freedom are separated, and described by two independent conformal theories. A detailed comparison of the t-J model with the repulsive Hubbard model was then undertaken with emphasis on their Tomonaga-Luttinger (TL) liquid properties. Near half-filling the exponents of the t-J model take the values of the strong-correlation limit of the Hubbard model, and in the low-density limit the exponents are those of a non-interacting system. The critical exponents obtained in this study belong to the repulsive TL liquid (conducting phase) and attractive TL liquid (superconducting phase). The theoretical results from this study find applications in one-dimensional organic conductors (TTF-TCNQ), organic superconductors (Bechgaard salts) and carbon nanotubes (SWCNTs, DWCNTs and MWCNTs). For instance, the critical exponent at from this study is consistent with the experimental result from optical and photoemission evidence of TL liquid in one-dimensional metallic Bechgaard salt- (TMTSF)2PF6.

Keywords: critical exponents, conformal field theory, Hubbard model, t-J model

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Authors: Bo Wang

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As the first high-resolution civil optical satellite, ZY-3 satellite is able to obtain high-resolution multi-view images with three linear array sensors. The images can be used to generate Digital Elevation Models (DEM) through dense matching of stereo images. However, due to the clouds, forest, water and buildings covered on the images, there are some problems in the dense matching results such as outliers and areas failed to be matched (matching holes). This paper introduced an algorithm to verify the accuracy of DEM that generated by ZY-3 satellite with Shuttle Radar Topography Mission (SRTM). Since the accuracy of SRTM (Internal accuracy: 5 m; External accuracy: 15 m) is relatively uniform in the worldwide, it may be used to improve the accuracy of ZY-3 DEM. Based on the analysis of mass DEM and SRTM data, the processing can be divided into two aspects. The registration of ZY-3 DEM and SRTM can be firstly performed using the conjugate line features and area features matched between these two datasets. Then the ZY-3 DEM can be refined by eliminating the matching outliers and filling the matching holes. The matching outliers can be eliminated based on the statistics on Local Vector Binning (LVB). The matching holes can be filled by the elevation interpolated from SRTM. Some works are also conducted for the accuracy statistics of the ZY-3 DEM.

Keywords: ZY-3 satellite imagery, DEM, SRTM, refinement

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Authors: A. Karunasena, P. Bandara, J. A. T. P. Jayasuriya, P. D. Gallage, J. M. S. D. Jayasundara, L. A. P. Y. P. Nuwanjaya

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Usage of smart learning concepts has increased rapidly all over the world recently as better teaching and learning methods. Most educational institutes such as universities are experimenting those concepts with their students. Smart learning concepts are especially useful for students to learn better in large classes. In large classes, the lecture method is the most popular method of teaching. In the lecture method, the lecturer presents the content mostly using lecture slides, and the students make their own notes based on the content presented. However, some students may find difficulties with the above method due to various issues such as speed in delivery. The purpose of this research is to assist students in large classes in the following content. The research proposes a solution with four components, namely note-taker, slide matcher, reference finder, and question presenter, which are helpful for the students to obtain a summarized version of the lecture note, easily navigate to the content and find resources, and revise content using questions.

Keywords: automatic summarization, extractive text summarization, speech recognition library, sentence extraction, automatic web search, automatic question generator, sentence scoring, the term weight

Procedia PDF Downloads 136

Authors: Marko Kolakovic

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Creative industries are an important sector of growth and development of knowledge economies. They have a positive impact on employment, economic growth, export and the quality of life in the areas where they are developed. Creative sectors include architecture, design, advertising, publishing, music, film, television and radio, video games, visual and performing arts and heritage. Following the positive trends of development of creative industries on the global and European level, this paper analyzes creative industries in general and specific characteristics of creative entrepreneurship. Special focus in this paper is put on the influence of the information communication technology on the development of new creative business models and protection of the intellectual property rights. One part of the paper is oriented on the analysis of the status of creative industries and creative entrepreneurship in Croatia. The main objective of the paper is by using the statistical analysis of creative industries in Croatia and information gained during the interviews with entrepreneurs, to make conclusions about potentials and development of creative industries in Croatia. Creative industries in Croatia are at the beginning of their development and growth strategy still does not exist at the national level. Statistical analysis pointed out that in 2015 creative enterprises made 9% of all enterprises in Croatia, employed 5,5% of employed people and their share in GDP was 4,01%. Croatian creative entrepreneurs are building competitive advantage using their creative resources and creating specific business models. The main obstacles they meet are lack of business experience and impossibility of focusing on the creative activities only. In their business, they use digital technologies and are focused on export. The conclusion is that creative industries in Croatia have development potential, but it is necessary to take adequate measures to use this potential in a right way.

Keywords: creative entrepreneurship, knowledge economy, business models, intellectual property

Procedia PDF Downloads 199

Authors: Cruz, G. P., Nagamatsu, R. N., Scacchetti, F. A. P., Merlin, F. K.

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This study aims to assess a set of technical parameters that provide quality products to the companies that produce caps, APL Apucarana / PR, the city that produces most Brazilian caps, in order to verify the potential of Brazilian caps to compete with international brands, recognized by the standard of excellence when it comes to quality of its products. The determination of the technical parameters was arbitrated from textile ABNT, a total of six technical parameters, providing eight tests for cotton caps. For the evaluation, we used as reference a leading brand recognized worldwide (based on their sales volume in $) for comparison with 3 companies of the APL Apucarana. The results showed that, of the 8 tests, of 8 tests, the companies Apucarana did not obtain better performance than the competitor. They obtained the same results in three tests and lower performance in 5. Given these values, it is concluded that local caps are not far from reaching the quality of leading brand. It is recommended that the APL companies use the parameters to evaluate their products, using this information to support decision-making that seek to improve both the product design and its production process, enabling the feasibility for faster international recognition . Thus, they may have an edge over its main competitor.

Keywords: technical parameters, making caps, quality, evaluation

Procedia PDF Downloads 339

Authors: Ren Moses

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The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

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Authors: Shadi Motamedighazvini, Roohollah Taherkhani, Mahdi Mahdikhani, Najme Hashempour

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Nowadays, green building rating systems are an inevitable necessity for managing environmental considerations to achieve green buildings. The aim of this paper is to deliver a detailed recognition of what has been the focus of green building policymakers around the world; It is important to conduct this study in a way that can provide a context for researchers who intend to establish or upgrade existing rating systems. In this paper, fifteen rating systems including four worldwide well-known plus eleven local rating systems which have been selected based on the answers to the questionnaires were examined. Their similarities and differences in mandatory and prerequisite clauses, highest and lowest scores for each criterion, the most frequent criteria, and most frequent sub-criteria are determined. The research findings indicated that although the criteria of energy, water, indoor quality (except Homestar), site and materials (except GRIHA) were common core criteria for all rating systems, their sub-criteria were different. This research, as a roadmap, eliminates the lack of a comprehensive reference that encompasses the key criteria of different rating systems. It shows the local systems need to be revised to be more comprehensive and adaptable to their own country’s conditions such as climate.

Keywords: environmental assessment, green buildings, green building criteria, green building rating systems, sustainability, rating tools

Procedia PDF Downloads 234

Authors: Siva Chander Chabattula, Piyush Kumar Gupta, Debashis Chakraborty, Rama Shanker Verma

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Green nanoparticles have gotten a lot of attention because of their potential applications in tissue regeneration, bioimaging, wound healing, and cancer therapy. The physical and chemical methods to synthesize metal oxide nanoparticles have an environmental impact, necessitating the development of an environmentally friendly green strategy for nanoparticle synthesis. In this study, we used Annona muricata plant leaf extract to synthesize Zinc Oxide nanoparticles (Am-ZnO NPs), which were evaluated using UV/Visible spectroscopy, FTIR spectroscopy, X-Ray Diffraction, DLS, and Zeta potential. Nanoparticles had an optical absorbance of 355 nm and a net negative surface charge of ~ - 2.59 mV. Transmission Electron Microscope characterizes the Shape and size of the nanoparticles. The obtained Am-ZnO NPs are biocompatible and hemocompatible in nature. These nanoparticles caused an anti-cancer therapeutic effect in MIA PaCa2 and MOLT4 cancer cells by inducing oxidative stress, and a change in mitochondrial membrane potential leads to programmed cell death. Further, we observed a reduction in the size of lung cancer spheroids (act as tumor micro-environment) with doxorubicin as a positive control.

Keywords: Biomaterials, nanoparticle, anticancer activity, ZnO nanoparticles

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Authors: M. Pacio, H. Juárez, R. Pérez-Cuapio E. Rosendo, T. Díaz, G. García

Abstract:

In this study, zinc oxide (ZnO) quantum dots (QDs) have been prepared by a simple route. The growth parameters for ZnO QDs were systematically studied inside a SiO2 shell; this shell acts as a capping agent and also enhances stability of the nanoparticles in water. ZnO QDs in silica shell could be produced by initially synthesizing a ZnO colloid (containing ZnO nanoparticles in methanol solution) and then was mixed with 3-aminopropylsiloxane used as SiO2 precursor. ZnO QDs were deposited onto silicon substrates (100) orientation by spin-coating technique. ZnO QDs into a SiO2 shell were pre-heated at 300 °C for 10 min after each coating, that procedure was repeated five times. The films were subsequently annealing in air atmosphere at 500 °C for 2 h to remove the trapped fluid inside the amorphous silica cage. ZnO QDs showed hexagonal wurtzite structure and about 5 nm in diameter. The composition of the films at the surface and in the bulk was obtained by Secondary Ion Mass Spectrometry (SIMS), the spectra revealed the presence of Zn- and Si- related clusters associated to the chemical species in the solid matrix. Photoluminescence (PL) spectra under 325 nm of excitation only show a strong UV emission band corresponding to ZnO QDs, such emission is enhanced with annealing. Our results showed that the method is appropriate for the preparation of ZnO QDs films embedded in a SiO2 shell with high UV photoluminescence.

Keywords: ZnO QDs, sol gel, functionalization

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Authors: Emmanuel Jr. Ballad, Herman Mendoza

Abstract:

The recovery of fine activated carbon with adsorbed gold in the cyanidation tailings of a small-scale gold plant was investigated due to the high amount of gold present. In the study, collectors that were used are kerosene and diesel. Emulsification of the oils was done to improve its collecting property, thus also the recovery. It was found out that the best hydrophile lypophile balance (HLB) of emulsified diesel and kerosene oil is 13 and 12 respectively. The amount of surfactants (SPAN 20 and TWEEN 20) for the best stability of the emulsified oils was found to be 10% in both kerosene and diesel. Optical microscopy showed that the oil dispersion in the water forms spherical droplets like features. The higher the stability, the smaller the droplets and their number were increasing. The smaller droplets indicate better dispersion of oil in the water. Consequently, it will have a greater chance of oil and activated carbon particle interaction during flotation. Due to the interaction of dispersed oil phase with carbon, the hydrophobicity of the carbon will be improved and will be attached to the bubble. Thus, flotation recovery will be increased. Results showed that the recovery of the fine activated carbon using emulsified diesel or kerosene is three times more effective than using pure diesel or kerosene.

Keywords: emulsified oils, flotation, hydrophile lyophile balance, non-ionic surfactants

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Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

Abstract:

A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

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Authors: Meziani Samir, Moussi Abderrahmane, Chaouchi Sofiane, Guendouzi Awatif, Djema Oussama

Abstract:

Laser doping has a large potential for integration into silicon solar cell technologies. The ability to process local, heavily diffused regions in a self-aligned manner can greatly simplify processing sequences for the fabrication of selective emitter. The choice of laser parameters for a laser doping process with 532nm is investigated. Solid state lasers with different power and speed were used for laser doping. In this work, the aim is the formation of selective emitter solar cells with a reduced number of technological steps. In order to have a highly doped localized emitter region, we used a 532 nm laser doping. Note that this region will receive the metallization of the Ag grid by screen printing. For this, we use SOLIDWORKS software to design a single type of pattern for square silicon cells. Sheet resistances, phosphorus doping concentration and silicon bulk lifetimes of irradiated samples are presented. Additionally, secondary ion mass spectroscopy (SIMS) profiles of the laser processed samples were acquired. Scanning electron microscope and optical microscope images of laser processed surfaces at different parameters are shown and compared.

Keywords: laser doping, selective emitter, silicon, solar cells

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Authors: B. Ramesh Naik, T. Venugopal

Abstract:

This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

Procedia PDF Downloads 173