Search results for: resolution digital data

Authors: Aleksandra Ristic

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The Coronavirus Disease – 2019 hit Europe in February 2020, and infections took place in four waves. It left consequences and demanded changes for the future. More than half of European countries responded quickly by declaring a state of emergency and introducing various containment measures that have had a major impact on individuals’ lives in recent years. Closing public lives was largely achieved by limited access and/or closing public institutions and services, including the closure of educational institutions. Teaching in classrooms converted to distance learning. In the research, we used a quantitative study to analyze various factors of distance learning that influenced pupils in different segments: teachers’ availability, family support, entire online conference learning, successful distance learning, time for themselves, reliable sources, teachers’ feedback, successful distance learning, online participation classes, motivation and teachers’ communication and theoretical review of the importance of digital skills, e-learning Index, World comparison of e-learning in the past, digital education plans for the field of Europe. We have gathered recommendations and distance learning solutions to improve the learning process by strengthening teachers and creating more tiered strategies for setting and achieving learning goals by the children.

Keywords: availability, digital skills, distance learning, resources

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Authors: Amirreza Razzaghipour Sorkhab

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Hearing loss is one of the greatest common chronic health situations of older people. Hearing aids are the common treatment, and they recover the quality of life in older adults. Even so, comparatively few older adults with simple, mild to moderate, adult-onset, sensorineural hearing loss use hearing aids. It shouldn’t be expected that more expensive hearing aids always produce better outcomes. Given the importance of quality pledge, approaches of quantifying hearing aid fitting achievement are needed. Studies showed an important reduction in handicap following 3 weeks of hearing aid use, signifying the feasibility of using the Hearing Hindrance Inventory for the Elderly as an outcome measure for hearing aid success after a brief interval of hearing aid use. The results showed important development of the quality of life after three months of using a hearing aid in all members and improvement of their most important problems, i.e., the communication and exchange of data. Hearing loss can impair the conversation of information and so decreases the quality of life. Hearing aids have progressivemeaningfully over the past decade, chiefly due to the growing of digital technology. The next decade should see an even greater number of innovations to hearing aid technology. Development in digital hearing aids will be driven by investigate advances in the next fields such as wireless technology, hearing science, and cognitive scienceMoreover, emerging trends such as connectivity and individuation will also drive new technology. We hope that the advancement of technology will be enough to meet the needs of people with hearing aids.

Keywords: hearing loss, hearing aid, hearing aid technology, health

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Authors: Liang-Hsuan Chen, Sheng-Shing Nien

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This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

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Authors: G. Magalhães-Mota, C. Magro, S. Sério, E. Mateus, P. A. Ribeiro, A. B. Ribeiro, M. Raposo

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Triclosan [5-chloro-2-(2,4-dichlorophenoxy) phenol], belonging to the class of Pharmaceuticals and Personal Care Products (PPCPs), is a broad-spectrum antimicrobial agent and bactericide. Because of its antimicrobial efficacy, it is widely used in personal health and skin care products, such as soaps, detergents, hand cleansers, cosmetics, toothpastes, etc. However, it has been considered to disrupt the endocrine system, for instance, thyroid hormone homeostasis and possibly the reproductive system. Considering the widespread use of triclosan, it is expected that environmental and food safety problems regarding triclosan will increase dramatically. Triclosan has been found in river water samples in both North America and Europe and is likely widely distributed wherever triclosan-containing products are used. Although significant amounts are removed in sewage plants, considerable quantities remain in the sewage effluent, initiating widespread environmental contamination. Triclosan undergoes bioconversion to methyl-triclosan, which has been demonstrated to bio accumulate in fish. In addition, triclosan has been found in human urine samples from persons with no known industrial exposure and in significant amounts in samples of mother's milk, demonstrating its presence in humans. The action of sunlight in river water is known to turn triclosan into dioxin derivatives and raises the possibility of pharmacological dangers not envisioned when the compound was originally utilized. The aim of this work is to detect low concentrations of triclosan in an aqueous complex matrix through the use of a sensor array system, following the electronic tongue concept based on impedance spectroscopy. To achieve this goal, we selected the appropriate molecules to the sensor so that there is a high affinity for triclosan and whose sensitivity ensures the detection of concentrations of at least nano-molar. Thin films of organic molecules and oxides have been produced by the layer-by-layer (LbL) technique and sputtered onto glass solid supports already covered by gold interdigitated electrodes. By submerging the films in complex aqueous solutions with different concentrations of triclosan, resistance and capacitance values were obtained at different frequencies. The preliminary results showed that an array of interdigitated electrodes sensor coated or uncoated with different LbL and films, can be used to detect TCS traces in aqueous solutions in a wide range concentration, from 10⁻¹² to 10⁻⁶ M. The PCA method was applied to the measured data, in order to differentiate the solutions with different concentrations of TCS. Moreover, was also possible to trace a curve, the plot of the logarithm of resistance versus the logarithm of concentration, which allowed us to fit the plotted data points with a decreasing straight line with a slope of 0.022 ± 0.006 which corresponds to the best sensitivity of our sensor. To find the sensor resolution near of the smallest concentration (Cs) used, 1pM, the minimum measured value which can be measured with resolution is 0.006, so the ∆logC =0.006/0.022=0.273, and, therefore, C-Cs~0.9 pM. This leads to a sensor resolution of 0.9 pM for the smallest concentration used, 1pM. This attained detection limit is lower than the values obtained in the literature.

Keywords: triclosan, layer-by-layer, impedance spectroscopy, electronic tongue

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Authors: A. Larrousi, M. Elkeurti, K. Amara, M. Zemouli, L. H. Coudert, I. R. Medvedev, F. C. De Lucia, Atsuko Maeda, R. W. C. McKellar, D. Appadoo

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Experimental and theoretical investigations of the microwave and far infrared spectra of CH3COD are reported. Two hundred twelve lines were identified in the far infrared spectrum recorded using the Canadian synchrotron radiation light source. Two thousand one hundred and sixty-eight lines in vt=0,1 and 216 in vt=2 have been measured in the microwave spectrum obtained using the fast scan submillimeter spectroscopic technique. A global analysis of the new data and of already available microwave lines has been carried out and yielded values for rotation–torsion parameters. The unitless weighted standard deviation of the fit is 1.6. 46 parameters and 216 lines were identified.

Keywords: CH3COD, torsion, the microwave spectra, far infrared spectra high resolution

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Authors: S.Balaji, R.Sujatha, M. Ramakrishnan

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Signcryption is a cryptographic primitive that fulfills both the functions of digital signature and public key encryption simultaneously in low cost when compared with the traditional signature-then-encryption approach. In this paper, we propose a novel mouse movement based key generation technique to generate secret keys which is secure against the outer and insider attacks. Tag Key Encapsulation Mechanism (KEM) process is implemented using True Random Number Generator (TRNG) method. This TRNG based key is used for data encryption in the Data Encapsulation Mechanism (DEM). We compare the statistical reports of the proposed system with the previous methods which implements TKEM based on pseudo random number generator

Keywords: pseudo random umber generator, signcryption, true random number generator, node deployment

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Authors: R. Daïra, V. Chalvidan

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We present the speckle interferometry method to determine the deformation of a piece. This method of holographic imaging using a CCD camera for simultaneous digital recording of two states object and reference. The reconstruction is obtained numerically. This latest method has the advantage of being simpler than the methods currently available, and it does not suffer the holographic configuration faults online. Furthermore, it is entirely digital and avoids heavy analysis after recording the hologram. This work was carried out in the laboratory HOLO 3 (optical metrology laboratory in Saint Louis, France) and it consists in controlling qualitatively and quantitatively the deformation of object by using a camera CCD connected to a computer equipped with software of Fringe Analysis.

Keywords: speckle, nondestructive testing, interferometry, image processing

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Authors: M. Dabirinezhad, M. Bayat Pour, A. Dabirinejad

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In 2020, the technology was introduced to solve some of the deficiencies of direct digital radiology. SDDR is an invention that is capable of capturing dental images without human intervention, and it was invented by the authors of this paper. Adjusting the radiology wave dose is a part of the dentists, radiologists, and dental nurses’ tasks during the radiology photography process. In this paper, an improvement will be added to enable SDDR to set the suitable radiology wave dose according to the density and age of the patients automatically. The separate sensors will be included in the sensors’ package to use the ultrasonic wave to detect the density of the teeth and change the wave dose. It facilitates the process of dental photography in terms of time and enhances the accuracy of choosing the correct wave dose for each patient separately. Since the radiology waves are well known to trigger off other diseases such as cancer, choosing the most suitable wave dose can be helpful to decrease the side effect of that for human health. In other words, it decreases the exposure time for the patients. On the other hand, due to saving time, less energy will be consumed, and saving energy can be beneficial to decrease the environmental impact as well.

Keywords: dental direct digital imaging, environmental impacts, SDDR technology, wave dose

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Authors: Giacomo Rossi, Bernardo Favini, Eugenio Giacomazzi, Franca Rita Picchia, Nunzio Maria Salvatore Arcidiacono

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A numerical technique for mesh refinement in the HeaRT (Heat Release and Transfer) numerical code is presented. In the CFD framework, Large Eddy Simulation (LES) approach is gaining in importance as a tool for simulating turbulent combustion processes, also if this approach has an high computational cost due to the complexity of the turbulent modeling and the high number of grid points necessary to obtain a good numerical solution. In particular, when a numerical simulation of a big domain is performed with a structured grid, the number of grid points can increase so much that the simulation becomes impossible: this problem can be overcame with a mesh refinement technique. Mesh refinement technique developed for HeaRT numerical code (a staggered finite difference code) is based on an high order reconstruction of the variables at the grid interfaces by means of a least square quasi-ENO interpolation: numerical code is written in modern Fortran (2003 standard of newer) and is parallelized using domain decomposition and message passing interface (MPI) standard.

Keywords: LES, multi-resolution, ENO, fortran

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Authors: Zain Khalid

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The paper outlines the trends of cyber financial crimes and frauds – approximating upto – in Pakistan after the enactment of The Prevention of Electronic Crimes Act in 2016. The paper elaborates on the newer methods that fraudsters have adopted after tighter preventive and counter measures were employed in Pakistan partly as a result of following the international finance related commitments, particularly the FATF regulations. The paper adopts case studies methods to highlight various aspects of the financial frauds and crimes committed and later investigated jointly by Pakistan’s one of the federal law enforcement agencies, the Federal Investigation Agency, and Mobilink Microfinance Bank , Pakistan’s premier microfinance bank. It additionally enriches the data through expert interviews – with crime investigators and the experts to carry out an in-depth analysis of the various factors involving the crime. This paper emphasizes the structural and situational factors that shape up the cyber financial crimes in Pakistan vis-à-vis digital illiteracy and lack of awareness among the users of financial services. This paper, thus, on the basis of findings and expert interviews, suggests policy reforms to reduce the instances of the financial crimes, especially in the remotest areas of the country.

Keywords: financial crimes, cyber crimes, digital literacy, terrorism financing, banking sector

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Authors: Saeed Asiri

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The Novel Automated System (NAS) has the control system of the level of chlorine and acid (i.e. pH level) through a feedback in three forms of synchronous alerts. The feedback is in the form of an alert voice, a visible color, and a message on a digital screen. In addition, NAS contains a slide-in container in which chemicals are used to treat the problems of chlorine and acid levels independently. Moreover, NAS has a net in front of it to clean the pool on the surface of the water from leaves and wastes and so on which is controlled through a remote control. The material used is a lightweight aluminum with mechanical and electric parts integrated with each other. In fact, NAS is qualified to serve as an assistant security guard for swimming pools because it has the characteristics that make it unique and smart.

Keywords: novel automated system, pool safety, maintenance, pH level, digital screen

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Authors: Keroles Akram Saed Ghatas

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The near future will bring significant changes in modern organizations and management due to the growing role of intangible assets and knowledge workers. The area of copyright, intellectual property, digital (intangible) assets and media redistribution appears to be one of the greatest challenges facing business and society in general and management sciences and organizations in particular. The proposed article examines the views and perceptions of fairness in digital media sharing among Harvard Law School's LL.M.s. Students, based on 50 qualitative interviews and 100 surveys. The researcher took an ethnographic approach to her research and entered the Harvard LL.M. in 2016. at, a Face book group that allows people to connect naturally and attend in-person and private events more easily. After listening to numerous students, the researcher conducted a quantitative survey among 100 respondents to assess respondents' perceptions of fairness in digital file sharing in various contexts (based on media price, its availability, regional licenses, copyright holder status, etc.). to understand better . .). Based on the survey results, the researcher conducted long-term, open-ended and loosely structured ethnographic interviews (50 interviews) to further deepen the understanding of the results. The most important finding of the study is that Harvard lawyers generally support digital piracy in certain contexts, despite having the best possible legal and professional knowledge. Interestingly, they are also more accepting of working for the government than the private sector. The results of this study provide a better understanding of how “fairness” is perceived by the younger generation of lawyers and pave the way for a more rational application of licensing laws.

Keywords: cognitive impairments, communication disorders, death penalty, executive function communication disorders, cognitive disorders, capital murder, executive function death penalty, egyptian law absence, justice, political cases piracy, digital sharing, perception of fairness, legal profession

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Authors: Daniel R. dos Santos, Mateus S. Maldonado, Estevão J. R. Batista

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The military commanders increasingly dependent on spatial awareness, as knowing where enemy are, understanding how war battle scenarios change over time, and visualizing these trends in ways that offer insights for decision-making. Thanks to advancements in geospatial technologies and artificial intelligence algorithms, the commanders are now able to modernize military operations on a universal scale. Thus, geovisualisation has become an essential asset in the defense sector. It has become indispensable for better decisionmaking in dynamic/temporal scenarios, operation planning and management for the war field, situational awareness, effective planning, monitoring, and others. For example, a 3D visualization of war field data contributes to intelligence analysis, evaluation of postmission outcomes, and creation of predictive models to enhance decision-making and strategic planning capabilities. However, old-school visualization methods are slow, expensive, and unscalable. Despite modern technologies in generating 3D point clouds, such as LIDAR and stereo sensors, monocular depth values based on deep learning can offer a faster and more detailed view of the environment, transforming single images into visual information for valuable insights. We propose a dedicated monocular depth reconstruction approach via deep learning techniques for 3D geovisualisation of satellite images. It introduces scalability in terrain reconstruction and data visualization. First, a dataset with more than 7,000 satellite images and associated digital elevation model (DEM) is created. It is based on high resolution optical and radar imageries collected from Planet and Copernicus, on which we fuse highresolution topographic data obtained using technologies such as LiDAR and the associated geographic coordinates. Second, we developed an imagery-DEM fusion strategy that combine feature maps from two encoder-decoder networks. One network is trained with radar and optical bands, while the other is trained with DEM features to compute dense 3D depth. Finally, we constructed a benchmark with sparse depth annotations to facilitate future research. To demonstrate the proposed method's versatility, we evaluated its performance on no annotated satellite images and implemented an enclosed environment useful for Geovisualisation applications. The algorithms were developed in Python 3.0, employing open-source computing libraries, i.e., Open3D, TensorFlow, and Pythorch3D. The proposed method provides fast and accurate decision-making with GIS for localization of troops, position of the enemy, terrain and climate conditions. This analysis enhances situational consciousness, enabling commanders to fine-tune the strategies and distribute the resources proficiently.

Keywords: depth, deep learning, geovisualisation, satellite images

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Authors: Samir Roy

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This paper investigates the relationship among knowledge, technology, and empowerment. In Physics power is defined as rate of doing work. In everyday use, the meaning of the word power is related to the capacity to bring change of value in the world. It appears that the popular aphorism “Knowledge is power” should be revisited in the context of contemporary states of affairs. For instance, classical mechanics is a system of knowledge, so also thermodynamics. But neither of them, per se, is sufficient to produce automobilin es. Boolean algebra, the logical foundation of digital electronic computers, was introduced by George Boole in 1847. But that knowledge was practically useless for almost one hundred years until digital electronics was developed in early twentieth century, which eventually led to invention of digital electronic computers. Empowerment of women is a burning issue in the arena of social justice. However, if we carefully analyze the functional elements of women’s empowerment, we find them to be highly technology driven as well as technology dependent in real life. On the other hand, technology has empowered modern states to maintain social order and promote democracy in an effective manner. This paper includes a few case studies to establish the close correspondence between knowledge, especially scientific knowledge, technology, and empowerment. It appears that in contemporary scenario, “Technology is power” is a more appropriate statement than the traditional aphorism “Knowledge is power”.

Keywords: knowledge, science, technology, empowerment, change, social justice

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Authors: Chiung-Hui Chen

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Diagram and drawing are important ways to communicate and the reproduce of architectural design, Due to the development of information and communication technology, the professional thinking of architecture and interior design are also change rapidly. In development process of design, diagram always play very important role. This study is based on diagram theories, observe and record interaction between man and objects, objects and space, and space and time in a modern nuclear family. Construct a method for diagram to systematically and visualized describe the space plan of a modern nuclear family toward a intelligent design, to assist designer to retrieve information and check/review event pattern of past and present.

Keywords: digital diagram, information model, context aware, data analysis

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Authors: Alejandro Molina-Villegas, Silvia Fernández-Sabido, Eduardo Mendoza-Vargas, Fátima Miranda-Pestaña

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The automatic detection of indigenous languages ​​in digital texts is essential to promote their inclusion in digital media. Underrepresented languages, such as Maya, are often excluded from language detection tools like Google’s language-detection library, LANGDETECT. This study addresses these limitations by developing a hybrid language detection solution that accurately distinguishes Maya (YUA) from Spanish (ES). Two strategies are employed: the first focuses on creating a profile for the Maya language within the LANGDETECT library, while the second involves training a Naive Bayes classification model with two categories, YUA and ES. The process includes comprehensive data preprocessing steps, such as cleaning, normalization, tokenization, and n-gram counting, applied to text samples collected from various sources, including articles from La Jornada Maya, a major newspaper in Mexico and the only media outlet that includes a Maya section. After the training phase, a portion of the data is used to create the YUA profile within LANGDETECT, which achieves an accuracy rate above 95% in identifying the Maya language during testing. Additionally, the Naive Bayes classifier, trained and tested on the same database, achieves an accuracy close to 98% in distinguishing between Maya and Spanish, with further validation through F1 score, recall, and logarithmic scoring, without signs of overfitting. This strategy, which combines the LANGDETECT profile with a Naive Bayes model, highlights an adaptable framework that can be extended to other underrepresented languages in future research. This fills a gap in Natural Language Processing and supports the preservation and revitalization of these languages.

Keywords: indigenous languages, language detection, Maya language, Naive Bayes classifier, natural language processing, low-resource languages

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Authors: Ivy Jessen Galvan

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Over the past decade, a phenomenon has emerged at the frontier of the digital economy: a wave of ‘disruptive’ technologies that offer digital solutions to variety of everyday problems, challenging the way traditional industries operate. Most of these disruptive technologies are applications ('apps') that rely on the Internet to connect people to people for sharing, selling, renting, or lending, creating a unique economic model wherein users provide for other users’ demand – called 'collaborative economy.' Although collaborative economy is spreading in every part of the world, there may be different ways in which this phenomenon is unfolding throughout the developing countries. In this study, the characteristics of collaborative economy in the Philippines are highlighted and compared from observations in the developed world. The paper looks at two leading collaborative economy ventures in the Philippines – Grab and Shopee – probing into how these smartphone-based platforms place technology into the 'micro-frictions' of the Philippine developing context. Using framing analysis on interviews conducted among Grab and Shopee users in Metro Manila, three frames have been identified: 1) metropolitan solution; 2) financial inclusion and; 3) formalization of labor. This research contextualizes the Fourth Industrial Revolution in ASEAN by analyzing the effect of a digital economy in everyday life.

Keywords: ASEAN Unicorns, collaborative economy, developing countries, fourth industrial revolution

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Authors: Alicia Regodon Puyalto, Alfonso Garcia-Santos

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This article presents a method to analyze the use of indoor spaces based on data analytics obtained from inbuilt digital devices. The study uses the data generated by the in-place devices, such as smart locks, Wi-Fi routers, and electrical sensors, to gain additional insights on space occupancy, user behaviour, and comfort. Those devices, originally installed to facilitate remote operations, report data through the internet that the research uses to analyze information on human real-time use of spaces. Using an in-place Internet of Things (IoT) network enables a faster, more affordable, seamless, and scalable solution to analyze building interior spaces without incorporating external data collection systems such as sensors. The methodology is applied to a real case study of coliving, a residential building of 3000m², 7 floors, and 80 users in the centre of Madrid. The case study applies the method to classify IoT devices, assess, clean, and analyze collected data based on the analysis framework. The information is collected remotely, through the different platforms devices' platforms; the first step is to curate the data, understand what insights can be provided from each device according to the objectives of the study, this generates an analysis framework to be escalated for future building assessment even beyond the residential sector. The method will adjust the parameters to be analyzed tailored to the dataset available in the IoT of each building. The research demonstrates how human-centered data analytics can improve the future spatial design of indoor spaces.

Keywords: in-place devices, IoT, human-centred data-analytics, spatial design

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Authors: Bâlc Denisa-Maria

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This paper aims to present some ways of preserving a language heritage in the global era. Teaching a second language to foreign students does not imply only teaching the grammar and the vocabulary in order to reach the 4 skills, but it means constant work on developing strategies to make the students aware of the heritage that the language they learn has. Teachers and professors need to be aware of the fact that language is in constant change, they need to adjust their techniques to the digital era, but they also have to be aware of the changes, the good and the bad parts of globalizations. How is it possible to preserve the patrimony of a certain language in a globalized era? What transformations does a language face in time? What does it mean to preserve the heritage of a language through L2 teaching? What makes a language special? What impact does it have on the foreign students? How can we, as teachers, preserve the heritage of our language? Would it be everything about books, films, music, cultural events or what else? How is it possible to include digital programs in your teaching and preserving the patrimony of a language at the same time? How does computational linguistics help us in teaching a certain language? All these questions will be tackled during the essay, with special accent on the definition of a language heritage, the new perspectives for teachers/ professors, everything in a multimodal and complex way of presenting the context. The objectives of this research are: - to present some ways of preserving the heritage of a certain language against globalization - to illustrate what preservation means for L2 teaching - to encourage teachers to be aware of their language patrimony The main contributions of my research are on moving the discussion of preserving a certain language patrimony in the context of L2 teaching.

Keywords: preservation, globalization, language heritage, L2 teaching

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Authors: Suleyman Karabal, Timothy L. Burnett, Egemen Avcu, Andrew H. Sherry, Philip J. Withers

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SA508 Grade 3 steel is widely used in the construction of nuclear pressure vessels, where its fracture toughness plays a critical role in ensuring operational safety and reliability. Understanding the ductile failure mechanisms in this steel grade is crucial for designing robust pressure vessels that can withstand severe nuclear environment conditions. In the present study, round bar specimens of SA508 Grade 3 steel with four distinct notch geometries were subjected to tensile loading while capturing continuous 2D images at 5-second intervals in order to monitor any alterations in their geometries to construct true stress-strain curves of the specimens. 3D reconstructions of X-ray computed tomography (CT) images at high-resolution (a spatial resolution of 0.82 μm) allowed for a comprehensive assessment of the influences of second-phase particles (i.e., manganese sulfide inclusions and cementite particles) on ductile failure initiation as a function of applied plastic strain. Additionally, based on 2D and 3D images, plasticity modeling was executed, and the results were compared to experimental data. A specific ‘two-parameter criterion’ was established and calibrated based on the correlation between stress triaxiality and equivalent plastic strain at failure initiation. The proposed criterion demonstrated substantial agreement with the experimental results, thus enhancing our knowledge of ductile fracture behavior in this steel grade. The implementation of X-ray CT and fractography analysis provided new insights into the diverse roles played by different populations of second-phase particles in fracture initiation under varying stress triaxiality conditions.

Keywords: ductile fracture, two-parameter criterion, x-ray computed tomography, stress triaxiality

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Authors: Hooman Torabifard

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In the last few years, with the progress of technology and computers and artificial intelligence entry into all kinds of scientific and industrial fields, the lifestyles of human life have changed and in general, the way of humans live on earth has many changes and development. Until now, some of the changes has occurred in the context of digital images and image processing and still continues. However, besides all the benefits, there have been disadvantages. One of these disadvantages is the multiplicity of images with high volume and data; the focus of this paper is on improving and developing a method for summarizing and enhancing the productivity of these images. The general method used for this purpose in this paper consists of a set of methods based on data obtained from image processing and using the PSO (Particle swarm optimization) algorithm. In the remainder of this paper, the method used is elaborated in detail.

Keywords: image summarization, particle swarm optimization, image threshold, image processing

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Authors: Ilona Buchem, Carolin Gellner

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Over the last few years, the call for the support of senior learners in the development of their digital literacy has become prevalent, mainly due to the progression towards ageing societies paired with advances in digitalisation in all spheres of life, including e-health and electronic patient record (EPA). While major research efforts in supporting senior learners in developing digital literacy have been invested so far in e-learning focusing on knowledge acquisition and cognitive tasks, little research exists in learning models which target virtual mentoring and coaching with the help of pedagogical agents and address the social dimensions of learning. Research from studies with students in the context of formal education has already provided methods for designing intelligent virtual agents in support of personalised learning. However, this research has mostly focused on cognitive skills and has not yet been applied to the context of mentoring/coaching of senior learners, who have different characteristics and learn in different contexts. In this paper, we describe how insights from previous research can be used to develop an intelligent virtual learning coach (agent) for senior learners with a focus on building the social relationship between the agent and the learner and the key task of the agent to socialize learners to the larger context of digital literacy with a focus on electronic health records. Following current approaches to mentoring and coaching, the agent is designed not to enhance and monitor the cognitive performance of the learner but to serve as a trusted friend and advisor, whose role is to provide one-to-one guidance and support sharing of experiences among learners (peers). Based on literature review and synopsis of research on virtual agents and current coaching/mentoring models under consideration of the specific characteristics and requirements of senior learners, we describe the design framework which was applied to design an intelligent virtual learning coach as part of the e-learning system for digital literacy of senior learners in the ePA-Coach project founded by the German Ministry of Education and Research. This paper also presents the results from the evaluation study, which compared the use of the first prototype of the virtual learning coach designed according to the design framework with a voice narration in a multimedia learning environment with senior learners. The focus of the study was to validate the agent design in the context of the persona effect (Lester et al., 1997). Since the persona effect is related to the hypothesis that animated agents are perceived as more socially engaging, the study evaluated possible impacts of agent coaching in comparison with voice coaching on motivation, engagement, experience, and digital literacy.

Keywords: virtual learning coach, virtual mentor, pedagogical agent, senior learners, digital literacy, electronic health records

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Authors: Nikolaos Papadakis, Constantinos Condaxakis, Konstantinos Savvakis

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The aim of this paper is to determine the elastic properties (elastic modulus and Poisson ratio) of a composite material based on noncontacting imaging methods. More specifically, the significantly reduced cost of digital cameras has given the opportunity of the high reliability of low-cost strain measurement. The open source platform Ncorr is used in this paper which utilizes the method of digital image correlation (DIC). The use of digital image correlation in measuring strain uses random speckle preparation on the surface of the gauge area, image acquisition, and postprocessing the image correlation to obtain displacement and strain field on surface under study. This study discusses technical issues relating to the quality of results to be obtained are discussed. [0]8 fabric glass/epoxy composites specimens were prepared and tested at different orientations 0[o], 30[o], 45[o], 60[o], 90[o]. Each test was recorded with the camera at a constant frame rate and constant lighting conditions. The recorded images were processed through the use of the image processing software. The parameters of the test are reported. The strain map output which is obtained through strain measurement using Ncorr is validated by a) comparing the elastic properties with expected values from Classical laminate theory, b) through finite element analysis.

Keywords: composites, Ncorr, strain map, videoextensometry

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Authors: Collins Chiemeke, Stephen Ibe, Godwin Onyedim

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This research work on high-resolution seismic tomography method was carried out with the aim of investigating how near-surface geology influences the initial distribution of infrastructural development in an area like Otuoke and its environs. To achieve this objective, seismic tomography method was employed. The result revealed that the overburden (highly-weathered layer) thickness ranges from 27 m to 50 m within the survey area, with an average value of 37 m. The 3D surface analysis for the overburden thickness distribution within the survey area showed that the thickness of the overburden is more in regions with less infrastructural development, and least in built-up areas. The range of velocity distribution from the surface to within a depth of 5 m is about 660 m/s to 1160 m/s, with an average value of 946 m/s. The 3D surface analysis of the velocity distribution also revealed that the areas with large infrastructural development are characterized with large velocity values compared with the undeveloped regions that has average low-velocity values. Hence, one can conclusively say that the initial settlement of Otuoke and its environs and the subsequent infrastructural development was influenced by the underlying near surface geology (rigid earth), among other factors.

Keywords: geology, seismic, infrastructural, near-surface

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Authors: Harald Haas, Andrea Plaschke

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Many of the contemporary major conflicts on this earth could not be solved so far, they either are perpetuated, or they are reflated again and again. Efforts of purely political conflict management or -resolution aim merely at the symptoms of conflict, not its roots. These roots are, in almost every case, also psychological ones. Thus, this contribution aims to shed light on the roots of one of the best known and longest-lasting conflicts: the Palestinian-Israeli one. Methodologies used were the compilation of existing scientific resources, field research in Palestine and Israel, as well as tests conducted with the Adult Attachment Projective in Palestine and Israel. Findings show that the majority of Palestinian, as well as Israeli test participants, show a disorganised attachment pattern which, in connection with the assumption of collective traumatization, seem to be a major obstacle to a lasting and peaceful conflict-resolution between these two peoples. There appears to be no short-term solution for this conflict, especially not within the range of usual Western legislative periods. Both sides ought to be provided with a kind of 'safe haven' over a long period of time, accompanied by a framework of various arrangements of coping with trauma, building lasting and secure relationships, as well as raising and educating present and future generations of Palestinians and Israelis for peace and co-operation with each other.

Keywords: conflict-management, trauma, political psychology, attachment theory

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Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

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Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

Abstract:

Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Elizabeth M. Annoni, Elena G. Tolkacheva

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Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia that is a known prognostic marker for stroke, heart failure and death. Reentrant mechanisms of rotor formation, which are stable electrical sources of cardiac excitation, are believed to cause AF. No existing commercial mapping systems have been demonstrated to consistently and accurately predict rotor locations outside of the pulmonary veins in patients with persistent AF. There is a clear need for robust spatio-temporal techniques that can consistently identify rotors using unique characteristics of the electrical recordings at the pivot point that can be applied to clinical intracardiac mapping. Recently, we have developed four new signal analysis approaches – Shannon entropy (SE), Kurtosis (Kt), multi-scale frequency (MSF), and multi-scale entropy (MSE) – to identify the pivot points of rotors. These proposed techniques utilize different cardiac signal characteristics (other than local activation) to uncover the intrinsic complexity of the electrical activity in the rotors, which are not taken into account in current mapping methods. We validated these techniques using high-resolution optical mapping experiments in which direct visualization and identification of rotors in ex-vivo Langendorff-perfused hearts were possible. Episodes of ventricular tachycardia (VT) were induced using burst pacing, and two examples of rotors were used showing 3-sec episodes of a single stationary rotor and figure-8 reentry with one rotor being stationary and one meandering. Movies were captured at a rate of 600 frames per second for 3 sec. with 64x64 pixel resolution. These optical mapping movies were used to evaluate the performance and robustness of SE, Kt, MSF and MSE techniques with respect to the following clinical limitations: different time of recordings, different spatial resolution, and the presence of meandering rotors. To quantitatively compare the results, SE, Kt, MSF and MSE techniques were compared to the “true” rotor(s) identified using the phase map. Accuracy was calculated for each approach as the duration of the time series and spatial resolution were reduced. The time series duration was decreased from its original length of 3 sec, down to 2, 1, and 0.5 sec. The spatial resolution of the original VT episodes was decreased from 64x64 pixels to 32x32, 16x16, and 8x8 pixels by uniformly removing pixels from the optical mapping video.. Our results demonstrate that Kt, MSF and MSE were able to accurately identify the pivot point of the rotor under all three clinical limitations. The MSE approach demonstrated the best overall performance, but Kt was the best in identifying the pivot point of the meandering rotor. Artifacts mildly affect the performance of Kt, MSF and MSE techniques, but had a strong negative impact of the performance of SE. The results of our study motivate further validation of SE, Kt, MSF and MSE techniques using intra-atrial electrograms from paroxysmal and persistent AF patients to see if these approaches can identify pivot points in a clinical setting. More accurate rotor localization could significantly increase the efficacy of catheter ablation to treat AF, resulting in a higher success rate for single procedures.

Keywords: Atrial Fibrillation, Optical Mapping, Signal Processing, Rotors

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Authors: Faci Youcef

Abstract:

In the present work, an experimental study is carried out using the digital image correlation (DIC) technique to analyze the damage and behavior of woven composite carbon/epoxy under tensile loading. The tension mechanisms associated with failure modes of bolted joints in advanced composites are studied, as well as displacement distribution and strain distribution. The evolution value of bolt angle inclination during tensile tests was studied. In order to compare the distribution of displacements and strains along the surface, figures of image mapping are made. Several factors that are responsible for the failure of fiber-reinforced polymer composite materials are observed. It was found that strain concentrations observed in the specimens can be used to identify full-field damage onset and to monitor damage progression during loading. Moreover, there is an interaction between laminate pattern, laminate thickness, fastener size and type, surface strain concentrations, and out-of-plane displacement. Conclusions include a failure analysis associated with bolt angle inclinations and supported by microscopic visualizations of the composite specimen. The DIC results can be used to develop and accurately validate numerical models.

Keywords: Carbone, woven, damage, digital image, bolted joint, the inclination of angle

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Authors: Sahar Heidary, Ramin Ghasemi Shayan

Abstract:

By the development of new coronavirus (2019-nCoV) pneumonia, chest high-resolution computed tomography (HRCT) has been one of the main investigative implements. To realize timely and truthful diagnostics, defining the radiological features of the infection is of excessive value. The purpose of this impression was to consider the imaging demonstrations of early-stage coronavirus disease 2019 (COVID-19) and to run an imaging base for a primary finding of supposed cases and stratified interference. The right prophetic rate of HRCT was 85%, sensitivity was 73% for all patients. Total accuracy was 68%. There was no important change in these values for symptomatic and asymptomatic persons. These consequences were besides free of the period of X-ray from the beginning of signs or interaction. Therefore, we suggest that HRCT is a brilliant attachment for early identification of COVID-19 pneumonia in both symptomatic and asymptomatic individuals in adding to the role of predictive gauge for COVID-19 pneumonia. Patients experienced non-contrast HRCT chest checkups and images were restored in a thin 1.25 mm lung window. Images were estimated for the existence of lung scratches & a CT severity notch was allocated separately for each patient based on the number of lung lobes convoluted.

Keywords: COVID-19, radiology, respiratory diseases, HRCT

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