Search results for: virtual optical memory

Authors: C. N. Okafor, M. Maaza, T. A. E. Mokrani

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A proton exchange membrane has been developed for Direct Methanol Fuel Cell (DMFC). The nanofiber network composite membranes were prepared by interconnected network of Nafion (perfuorosulfonic acid) nanofibers that have been embedded in an uncharged and inert polymer matrix, by electro-spinning. The spinning solution of Nafion with a low concentration (1 wt. % compared to Nafion) of high molecular weight poly(ethylene oxide), as a carrier polymer. The interconnected network of Nafion nanofibers with average fiber diameter in the range of 160-700nm, were used to make the membranes, with the nanofiber occupying up to 85% of the membrane volume. The matrix polymer was cross-linked with Norland Optical Adhesive 63 under UV. The resulting membranes showed proton conductivity of 0.10 S/cm at 25°C and 80% RH; and methanol permeability of 3.6 x 10-6 cm2/s.

Keywords: composite membrane, electrospinning, fuel cell, nanofibers

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Authors: Fabrizio Logiurato

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Light Polarization has many technological applications, and its discovery was crucial to reveal the transverse nature of the electromagnetic waves. However, despite its fundamental and practical importance, in high school, this property of light is often neglected. This is a pity not only for its conceptual relevance, but also because polarization gives the possibility to perform many brilliant experiments with low cost materials. Moreover, the treatment of this matter lends very well to an interdisciplinary approach between art, biology and technology, which usually makes things more interesting to students. For these reasons, we have developed, and in this work, we introduce a laboratory on light polarization for high school and undergraduate students. They can see beautiful pictures when birefringent materials are set between two crossed polarizing filters. Pupils are very fascinated and drawn into by what they observe. The colourful images remind them of those ones of abstract painting or alien landscapes. With this multidisciplinary teaching method, students are more engaged and participative, and also, the learning process of the respective physics concepts is more effective.

Keywords: light polarization, optical activity, multidisciplinary education, science and art

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Authors: M. Sari Yilmaz, N. Karamahmut Mermer

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Coal fly ash is formed as a solid waste product from the combustion of coal in coal fired power stations. Huge amounts of fly ash are produced globally every year and are predicted to increase. Nowadays, less than half of the fly ash is used as a raw material for cement manufacturing, construction and the rest of it is disposed as a waste causing yet another environmental concern. For this reason, the recycling of this kind of slurries into useful materials is quite important in terms of economical and environmental aspects. The purpose of this study is to evaluate the Orhaneli and Tuncbilek coal fly ashes for utilization in some industrial applications. Therefore the mineralogical and chemical compositions of these fly ashes were analyzed by X-ray fluorescence (XRF) spectroscopy and X-ray diffraction (XRD). The silicon (Si) and aluminum (Al) in the fly ashes were activated by alkali fusion technique with sodium hydroxide. The obtained extracts were analyzed for Si and Al content by inductively coupled plasma optical emission spectrometry (ICP-OES).

Keywords: extraction, fly ash, fusion, XRD

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Authors: Satish Y. Deodhar

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Science without history is like a man without memory. The colossal history of India stores many ideas on economic ethics and public policy, which have been forgotten in the course of time. This paper is an attempt to bring to the fore contributions from ancient Indian treatises. In this context, the paper briefly summarizes alternative economic ideas such as communism, capitalism, and the holistic approach of ancient Indian writings. Thereafter, the idea of a welfare brick for an individual consisting of three dimensions -Purusharthas, Ashramas, and Varnas is discussed. Given the contours of the welfare brick, the concept of the state, its economic policies, markets, prices, interest rates, and credit are covered next. This is followed by delving into the treatment of land, property rights, guilds, and labour relations. The penultimate section summarises the economic advice offered to the head of a household in the treatise Shukranitisara. Finally, in concluding comments, the relevance of ancient Indian writings for modern times is discussed -both for pedagogy and economic policies.

Keywords: ancient Indian treatises, history of economic thought, science of political economy, Sanskrit

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Authors: Rodrigo S. Fonseca, Antônio C. P. Veiga

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Aiming at helping people with some movement limitation that makes typing and communication difficult, there is a need to customize an assistive tool with a learning environment that helps the user in order to optimize text input, identifying the error and providing the correction and possibilities of choice in the Portuguese language. The work presents an Orthographic and Grammatical System that can be incorporated into writing environments, improving and facilitating the use of an alphanumeric keyboard, using a prototype built using a genetic algorithm in addition to carrying out the prediction, which can occur based on the quantity and position of the inserted letters and even placement in the sentence, ensuring the sequence of ideas using a Long Short Term Memory (LSTM) neural network. The prototype optimizes data entry, being a component of assistive technology for the textual formulation, detecting errors, seeking solutions and informing the user of accurate predictions quickly and effectively through machine learning.

Keywords: genetic algorithm, neural networks, word prediction, machine learning

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Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

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Authors: Najm Alotaibi

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Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture.

Keywords: human motion capture, computer vision, vision-based, tracking

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Authors: I. Algul, G. Akgun, H. Kurtaran

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Dynamic analysis of composite doubly curved panels with variable thickness subjected to different pulse types using Generalized Differential Quadrature method (GDQ) is presented in this study. Panels with variable thickness are used in the construction of aerospace and marine industry. Giving variable thickness to panels can allow the designer to get optimum structural efficiency. For this reason, estimating the response of variable thickness panels is very important to design more reliable structures under dynamic loads. Dynamic equations for composite panels with variable thickness are obtained using virtual work principle. Partial derivatives in the equation of motion are expressed with GDQ and Newmark average acceleration scheme is used for temporal discretization. Several examples are used to highlight the effectiveness of the proposed method. Results are compared with finite element method. Effects of taper ratios, boundary conditions and loading type on the response of composite panel are investigated.

Keywords: differential quadrature method, doubly curved panels, laminated composite materials, small displacement

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Authors: Muhammad Ammar, Talha Ali, Abdul Basit, Bakhtawar Rajput, Zobia Sohail

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Music note detection is an area of study for the past few years and has its own influence in music file generation from sheet music. We proposed a method to detect music notes on sheet music using basic thresholding and blob detection. Subsequently, we created a notes dictionary using a semi-supervised learning approach. After notes detection, for each test image, the new symbols are added to the dictionary. This makes the notes detection semi-automatic. The experiments are done on images from a dataset and also on the captured images. The developed approach showed almost 100% accuracy on the dataset images, whereas varying results have been seen on captured images.

Keywords: music note, sheet music, optical music recognition, blob detection, thresholding, dictionary generation

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Authors: H. Fazlinejad, A. Halvaee

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In this study, characteristics of ATIG welds using ZnO flux on aluminum was investigated and compared with TIG welds. Autogenously AC-ATIG bead on plate welding was applied on Al1050 plate with a coating of ZnO as the flux. Different levels of welding current and flux layer thickness was considered to study the effect of heat input and flux quantity on ATIG welds and was compared with those of TIG welds. Geometrical investigation of the weld cross sections revealed that penetration depth of the ATIG welds with ZnO flux, was increased up to 2 times in some samples compared to the TIG welds. Optical metallographic and Scanning Electron Microscopy (SEM) observations revealed similar microstructures in TIG and ATIG welds. Composition of the ATIG welds slag was also analyzed using X-ray diffraction. In both TIG and ATIG samples, the lowest values of microhardness were observed in the HAZ.

Keywords: ATIG, active flux, weld penetration, Al 1050, ZnO

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Authors: J. J. Rickard, A. Belli, P. Goldberg Oppenheimer

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Medical diagnostics, environmental monitoring, homeland security and forensics increasingly demand specific and field-deployable analytical technologies for quick point-of-care diagnostics. Although technological advancements have made optical methods well-suited for miniaturization, a highly-sensitive detection technique for minute sample volumes is required. Raman spectroscopy is a well-known analytical tool, but has very weak signals and hence is unsuitable for trace level analysis. Enhancement via localized optical fields (surface plasmons resonances) on nanoscale metallic materials generates huge signals in surface-enhanced Raman scattering (SERS), enabling single molecule detection. This enhancement can be tuned by manipulation of the surface roughness and architecture at the sub-micron level. Nevertheless, the development and application of SERS has been inhibited by the irreproducibility and complexity of fabrication routes. The ability to generate straightforward, cost-effective, multiplex-able and addressable SERS substrates with high enhancements is of profound interest for SERS-based sensing devices. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing. The superior detection properties and the ability to fabricate SERS substrates on the miniaturized scale, will facilitate the development of advanced and novel opto-fluidic devices, such as portable detection systems, and will offer numerous applications in biomedical diagnostics, forensics, ecological warfare and homeland security.

Keywords: hierarchical electrohydrodynamic patterning, medical diagnostics, point-of care devices, SERS

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Authors: K. Abbas, R. Ahmad, I. A. Khan, S. Saleem, U. Ikhlaq

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Nitriding of p-type Si samples by pulsed DC glow discharge is carried out for different Ar concentrations (30% to 90%) in nitrogen-argon plasma whereas the other parameters like pressure (2 mbar), treatment time (4 hr) and power (175 W) are kept constant. The phase identification, crystal structure, crystallinity, chemical composition, surface morphology and topography of the nitrided layer are studied using X-ray diffraction (XRD), Fourier transform infra-red spectroscopy (FTIR), optical microscopy (OM), scanning electron microscopy (SEM) and atomic force microscopy (AFM) respectively. The XRD patterns reveal the development of different diffraction planes of Si₃N₄ confirming the formation of polycrystalline layer. FTIR spectrum confirms the formation of bond between Si and N. Results reveal that addition of Ar into N₂ plasma plays an important role to enhance the production of active species which facilitate the nitrogen diffusion.

Keywords: crystallinity, glow discharge, nitriding, sputtering

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Authors: Ehab AbdulRazzaq Hussein

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Quantum cryptography (QC) is an emerging technology for secure key distribution with single-photon transmissions. In contrast to classical cryptographic schemes, the security of QC schemes is guaranteed by the fundamental laws of nature. Their security stems from the impossibility to distinguish non-orthogonal quantum states with certainty. A potential eavesdropper introduces errors in the transmissions, which can later be discovered by the legitimate participants of the communication. In this paper, the modeling approach is proposed for QC protocol BB84 using polarization coding. The single-photon system is assumed to be used in the designed models. Thus, Eve cannot use beam-splitting strategy to eavesdrop on the quantum channel transmission. The only eavesdropping strategy possible to Eve is the intercept/resend strategy. After quantum transmission of the QC protocol, the quantum bit error rate (QBER) is estimated and compared with a threshold value. If it is above this value the procedure must be stopped and performed later again.

Keywords: security, key distribution, cryptography, quantum protocols, Quantum Cryptography (QC), Quantum Key Distribution (QKD).

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Authors: Benbya Hind, Belbaly Nassim

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Markets and communities are often cast as alternative forms of knowledge sharing, but an open question is how and why people dynamically transition between them. To study these transitions, we design a technology that allows geographically distributed participants to either buy knowledge (using virtual points) or request it for free. We use a data-driven, inductive approach, studying 550 members in over 5000 interactions, during nine months. Because the technology offered participants choices between market or community forms, we can document both individual and collective transitions that emerge as people cycle between these forms. Our inductive analysis revealed that uncertainties endemic to knowledge sharing were the impetus for these transitions. Communities evoke uncertainties about knowledge sharing’s costs and benefits, which markets resolve by quantifying explicit prices. However, if people manipulate markets, they create uncertainties about the validity of those prices, allowing communities to reemerge to establish certainty via identity-based validation.

Keywords: knowledge sharing, communities, information technology design, transitions, markets

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Authors: Isao Tomita

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Power characteristics are obtained for laser beams of near-infrared and terahertz wavelengths when produced by difference-frequency generation with a quasi-phase-matched (QPM) waveguide made of gallium phosphide (GaP). A refractive-index change of the QPM GaP waveguide is included in computations with Sellmeier’s formula for varying input wavelengths, where optical loss is also included. Although the output power decreases with decreasing photon energy as the beam wavelength changes from near-infrared to terahertz wavelengths, the beam generation with such greatly different wavelengths, which is not achievable with an ordinary laser diode without the replacement of semiconductor material with a different bandgap one, can be made with the same semiconductor (GaP) by changing the QPM period, where a way of changing the period is provided.

Keywords: difference-frequency generation, gallium phosphide, quasi-phase-matching, waveguide

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Authors: Arslan Usman, Abdul Sattar, Hamid Latif, Afshan Ashfaq, Muhammad Rafique, Martin Koch

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Two-dimensional materials have promising applications in optoelectronic and photonics; MoS₂ is the pioneer 2D material in the family of transition metal dichalcogenides. Its optical, optoelectronic, and structural properties are of practical importance along with its exciton dynamics. Exciton, along with exciton complexes, plays a vital role in realizing quantum devices. MoS₂ monolayers were synthesized using chemical vapour deposition (CVD) technique on SiO₂ and hBN substrates. Photoluminescence spectroscopy (PL) was used to identify the monolayer, which also reflects the substrate based peak broadening due to screening effects. In-plane and out of plane characteristic vibrational modes E¹₂g and A₁g, respectively, were detected in a different configuration on the substrate. The B-excitons and trions showed a dominant feature at low temperatures due to electron-phonon coupling effects, whereas their energies are separated by 100 meV.

Keywords: 2D materials, photoluminescence, AFM, excitons

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Authors: Matar Celine, Gaucel Sebastien, Gontard Nathalie, Guilbert Stephane, Guillard Valerie

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To increase the very short shelf life of fresh fruits and vegetable, Modified Atmosphere Packaging (MAP) allows an optimal atmosphere composition to be maintained around the product and thus prevent its decay. This technology relies on the modification of internal packaging atmosphere due to equilibrium between production/consumption of gases by the respiring product and gas permeation through the packaging material. While, to the best of our knowledge, benefit of MAP for fresh fruits and vegetable has been widely demonstrated in the literature, its effect on shelf life increase has never been quantified and formalized in a clear and simple manner leading difficult to anticipate its economic and environmental benefit, notably through the decrease of food losses. Mathematical modelling of mass transfers in the food/packaging system is the basis for a better design and dimensioning of the food packaging system. But up to now, existing models did not permit to estimate food quality nor shelf life gain reached by using MAP. However, shelf life prediction is an indispensable prerequisite for quantifying the effect of MAP on food losses reduction. The objective of this work is to propose an innovative approach to predict shelf life of MAP food product and then to link it to a reduction of food losses and wastes. In this purpose, a ‘Virtual MAP modeling tool’ was developed by coupling a new predictive deterioration model (based on visual surface prediction of deterioration encompassing colour, texture and spoilage development) with models of the literature for respiration and permeation. A major input of this modelling tool is the maximal percentage of deterioration (MAD) which was assessed from dedicated consumers’ studies. Strawberries of the variety Charlotte were selected as the model food for its high perishability, high respiration rate; 50-100 ml CO₂/h/kg produced at 20°C, allowing it to be a good representative of challenging post-harvest storage. A value of 13% was determined as a limit of acceptability for the consumers, permitting to define products’ shelf life. The ‘Virtual MAP modeling tool’ was validated in isothermal conditions (5, 10 and 20°C) and in dynamic temperature conditions mimicking commercial post-harvest storage of strawberries. RMSE values were systematically lower than 3% for respectively, O₂, CO₂ and deterioration profiles as a function of time confirming the goodness of model fitting. For the investigated temperature profile, a shelf life gain of 0.33 days was obtained in MAP compared to the conventional storage situation (no MAP condition). Shelf life gain of more than 1 day could be obtained for optimized post-harvest conditions as numerically investigated. Such shelf life gain permitted to anticipate a significant reduction of food losses at the distribution and consumer steps. This food losses' reduction as a function of shelf life gain has been quantified using a dedicated mathematical equation that has been developed for this purpose.

Keywords: food losses and wastes, modified atmosphere packaging, mathematical modeling, shelf life prediction

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Authors: A. Attaf A., I. Bouhaf Kharkhachi

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Spray ultrasonic deposition technique of tin disulfide (SnS2) thin films know wide application due to their adequate physicochemical properties for microelectronic applications and especially for solar cells. SnS2 film was deposited by spray ultrasonic technique, on pretreated glass substrates at well-determined conditions.The effect of SnS2 concentration on different optical properties of SnS2 Thin films, such us MEB, XRD, and UV spectroscopy visible spectrum was investigated. MEB characterization technique shows that the morphology of this films is uniform, compact and granular. x-ray diffraction study detects the best growth crystallinity in hexagonal structure with preferential plan (001). The results of UV spectroscopy visible spectrum show that films deposited at 0.1 mol/l is large transmittance greater than 25% in the visible region.The band gap energy is 2.54 Ev for molarity 0.1 mol/l.

Keywords: MEB, thin disulfide, thin films, ultrasonic spray, X-Ray diffraction, UV spectroscopy visible

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Authors: P. S. Jagadeesh Kumar, Mingmin Pan, Xianpei Li, Yanmin Yuan, Tracy Lin Huan

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Researchers are doing enchanting research into the inherited features of Alzheimer’s disease and probable consistent therapies. In Alzheimer’s, memories are extinct in reverse order; memories formed lately are more transitory than those from formerly. Reminiscence therapy includes the conversation of past actions, trials and knowledges with another individual or set of people, frequently with the help of perceptible reminders such as photos, household and other acquainted matters from the past, music and collection of tapes. In this manuscript, the competence of reminiscence therapy for Alzheimer’s disease is measured using logistic regression based linear bootstrap aggregating. Logistic regression is used to envisage the experiential features of the patient’s memory through various therapies. Linear bootstrap aggregating shows better stability and accuracy of reminiscence therapy used in statistical classification and regression of memories related to validation therapy, supportive psychotherapy, sensory integration and simulated presence therapy.

Keywords: Alzheimer’s disease, linear bootstrap aggregating, logistic regression, reminiscence therapy

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Authors: Priyanka R. Oberoi, Chandra B. Maurya, Prakash A. Mahanwar

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Ionizing radiation can cause a drastic change in the physical and chemical properties of the material exposed. Numerous medical devices are sterilized by ionizing radiation. In the current research paper, an attempt was made to develop precise and inexpensive polymeric film dosimeter which can be used for controlling radiation dosage. Polymeric film containing (pH sensitive dye) indicator dye Bromophenol blue (BPB) was casted to check the effect of Gamma radiation on its optical and physical properties. The film was exposed to gamma radiation at 4 kGy/hr in the range of 0 to 300 kGy at an interval of 50 kGy. Release of vinyl acetate from an emulsion on high radiation reacts with the BPB fading the color of the film from blue to light blue and then finally colorless, indicating a change in pH from basic to acidic form. The change was characterized by using CIE l*a*b*, ultra-violet spectroscopy and FT-IR respectively.

Keywords: bromophenol blue, dosimeter, gamma radiation, polymer

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Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

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In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

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Authors: Somayeh Komeylian

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The antenna arrays for the entire 3D spherical coverage have been developed for their potential use in variety of applications such as radars and body-worn devices of the body area networks. In this study, we have rigorously revamped the hybrid antenna array using the optimum geometry of bowtie elements for achieving a significant improvement in the angular discrimination capability as well as in separating two adjacent targets. In this scenario, we have analogously investigated the effectiveness of increasing the virtual array length in fostering and enhancing the directivity and angular resolution in the 10 GHz frequency. The simulation results have extensively verified that the proposed antenna array represents a drastic enhancement in terms of size, directivity, side lobe level (SLL) and, especially resolution compared with the other available geometries. We have also verified that the maximum directivities of the proposed hybrid antenna array represent the robustness to the all  variations, which is accompanied by the uniform 3D scanning characteristic.

Keywords: bowtie antenna, hybrid antenna array, array signal processing, body area networks

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Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

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In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: ANPR, CS, CNN, deep learning, NPL

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Authors: Ridvan Yamanoglu

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In the current study, titanium based composites reinforced by hard nickel alloy particles were produced. Powder metallurgical hot pressing technique was used for the fabrication of composite materials. The composites containing different ratio of hard nickel particles were sintered at 900 oC for 15 and 30 minutes under 50 MPa pressure. All titanium based composites were obtained under a vacuum atmosphere of 10-4 mbar to prevent of oxidation of titanium due to its high reactivity to oxygen. The microstructural characterization of the composite samples was carried out by optical and scanning electron microscopy. The mechanical properties of the samples were determined by means of hardness and wear tests. The results showed that when the nickel particle content increased the mechanical properties of the composites enhanced. The results are discussed in detail and optimum nickel particle content were determined.

Keywords: titanium, composite, nickel, hot pressing

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Authors: Tavee Cheausuwantavee

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: COVID-19 pandemic significantly has impacted everyone’s life. Persons with disabilities (PWDs) in Thailand have been also effected by COVID-19 situation in many aspects of their lives, while there have been no more appropriate services of the government and providers. Research projects had been only focused on health precaution and protection. Rapid need assessments on populations and vulnerable groups were limited and conducted via social media and an online survey. However, little is known about the real problems and needs of Thai PWDs during the COVID-19 pandemic for an effective plan and integral services for those PWDs. Therefore, this study aims to explore the diverse problems and needs of Thai PWDs in the COVID -19 pandemic. Results from the study can be used by the government and other stakeholders for further effective services. Methods: This study was used a mixed-method design that consisted of both quantitative and qualitative measures. In terms of the quantitative approach, there were 744 PWDs and caregivers of all types of PWDs selected by proportional multistage stratified random sampling according to their disability classification and geographic location. Questionnaires with 59 items regarding participant characteristics, problems, and needs in health, education, employment, and other social inclusion, were distributed to all participants and some caregivers completed questionnaires when PWDs were not able to due to limited communication and/or literacy skills. Completed questionnaires were analyzed by descriptive statistics. For qualitative design, 62 key informants who were PWDs or caregivers were selected by purposive sampling. Ten focus groups, each consisting of 5-6 participants and 7 in-depth interviews from all the groups identified above, were conducted by researchers across five regions. Focus group and in-depth interview guidelines with 6 items regarding problems and needs in health, education, employment, other social inclusion, and their coping during COVID -19 pandemic. Data were analyzed using a modification of thematic content analysis. Results: Both quantitative and qualitative studies showed that PWDs and their caregivers had significant problems and needs all aspects of their life, including income and employment opportunity, daily living and social inclusion, health, and education, respectively. These problems and needs were related to each other, forming a vicious cycle. Participants also learned from negative pandemic to more positive life aspects, including their health protection, financial plan, family cohesion, and virtual technology literacy and innovation. Conclusion and implications: There have been challenges facing all life aspects of PWDs in Thailand during the COVID -19 pandemic, particularly incomes and daily living. All challenges have been the vicious cycle and complicated. There have been also a positive lesson learned of participants from the pandemic. Recommendations for government and stakeholders in the COVID-19 pandemic for PWDs are the following. First, the health protection strategy and policy of PWDs should be promoted together with other quality of life development including income generation, education and social inclusion. Second, virtual technology and alternative innovation should be enhanced for proactive service providers. Third, accessible information during the pandemic for all PWDs must be concerned. Forth, lesson learned from the pandemic should be shared and disseminated for crisis preparation and a positive mindset in the disruptive world.

Keywords: challenge, COVID-19, disability, Thailand

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Authors: Shireen Simon

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Cyberbullying among schoolchildren and teenagers became a hot issue discussed by Malaysian society. Cyberbullying is a new age of bullying because it uses the modern digital technology intentionally to hurt and degrade someone in the cyber world. Cyberbullying is a problem affecting many teenagers as they embrace online communication and interaction whereby virtual world with no borders. By adopting a qualitative approach, this study has captured 8 cyberbullied victims’ school experience. Even years after leaving school, these 8 cyberbullied victims remember how it feels to be bullied in the cyber world. The principal investigator also tries to identify the possibility factors that contribute to cyberbullying among these 8 victims. The result shows that these victims were bullied differently in cyber world. This study not just primarily focuses on cyberbullying issues among schoolchildren and teenagers; it also addresses the motives and causes of cyberbullying. Lastly, this article will be served as guidance for school teachers, parents and teenagers to prepare to tackle cyberbullying together. Cyberbullying is no laughing matter in our community, and it is time to spread the seeds of peace inspires others to do the same.

Keywords: cyberbullying, cyber victimization, internet, school experience, teenagers

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Kensho Takahashi, Ko Watanabe, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

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Near-infrared spectroscopy (NIRS) has been widely used as a non-invasive method to measure brain activity, but it is corrupted by baseline drift noise. Here we present a method to measure regional cerebral blood flow as a derivative of NIRS output. We investigate whether, when listening to languages, blood flow can reasonably localize and represent regional brain activity or not. The prefrontal blood flow distribution pattern when advanced second-language listeners listened to a second language (L2) was most similar to that when listening to their first language (L1) among the patterns of mean and standard deviation. In experiments with 25 healthy subjects, the maximum blood flow was localized to the left BA46 of advanced listeners. The blood flow presented is robust to baseline drift and stably localizes regional brain activity.

Keywords: NIRS, oxy-hemoglobin, baseline drift, blood flow, working memory, BA46, first language, second language

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Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Fatemeh Rezaei, Babak Shokri

Abstract:

In this study, PMMA films are modified by oxygen plasma treatment for biomedical applications. The plasma generator is capacitively coupled radio frequency (13.56 MHz) power source. The oxygen pressure and gas flow rate are kept constant at 40 mTorr and 30 sccm, respectively and samples are treated for 2 minutes. Hydrophilicity and biocompatibility of PMMA films are studied before and after treatments in different applied powers (10-80 W). In order to monitor the plasma process, the optical emission spectroscopy is used. The wettability and cellular response of samples are investigated by water contact angle (WCA) analysis and MTT assay, respectively. Also, surface free energy (SFE) variations are studied based on the contact angle measurements of three liquids. It is found that RF oxygen plasma treatment enhances the biocompatibility and also hydrophilicity of PMMA films.

Keywords: cellular response, hydrophilicity, MTT assay, PMMA, RF plasma

Procedia PDF Downloads 664