Search results for: enhanced data encryption

Authors: Shaukat Ali, Kanber Sedef, Mustafa Yilmaz

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This work analyzes a finger mechanism for a prosthetic hand that will help in improving the living standards of people who have lost their hands for a variety of reasons. The finger mechanism is single degree of freedom and hence has advantages such as compact size, reduced mass and less energy consumption. The proposed finger mechanism is a six bar linkage actuated by a single motor. The kinematic, static and dynamic analyses have been done by using the conventional methods of mechanism analysis. The kinematic results present the motion of the proposed finger mechanism and location of the fingertip. The static and dynamic analyses provide the useful information about the gripping force at the fingertip for various configurations and the selection of motor that will move the finger over its range of configuration. This single motor finger mechanism is simple and resembles the human finger’s motion suitable for grasping operation. This study can be used in the optimization of geometrical parameters of the proposed mechanism to obtain the desired configurations with minimum torque and enhanced griping.

Keywords: dynamics, finger mechanism, grasping, kinematics

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Authors: Jacob Wahl, Jane Zhang

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This paper describes the development and characterization of a prototype IoT network for use with agricultural imaging and monitoring applications. The sensor and gateway nodes are designed using the ESP32 SoC with integrated Bluetooth Low Energy 4.2 and Wi-Fi. A development board, the Arducam IoTai ESP32, is used for prototyping, testing, and power measurements. Google’s Firebase is used as the cloud storage site for image data collected by the sensor. The sensor node captures images using the OV2640 2MP camera module and transmits the image data to the gateway via Bluetooth Low Energy. The gateway then uploads the collected images to Firebase via a known nearby Wi-Fi network connection. This image data can then be processed and analyzed by computer vision and machine learning pipelines to assess crop growth or other needs. The sensor node achieves a wireless transmission data throughput of 220kbps while consuming 150mA of current; the sensor sleeps at 162µA. The sensor node device lifetime is estimated to be 682 days on a 6600mAh LiPo battery while acquiring five images per day based on the development board power measurements. This network can be utilized by any application that requires high data rates, low power consumption, short-range communication, and large amounts of data to be transmitted at low-frequency intervals.

Keywords: Bluetooth low energy, ESP32, firebase cloud, IoT, smart farming

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Authors: M. Soubadra Devy, Savitha Swamy, Chethana V. Casiker

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Sustainable smart cities are emerging as an important concept in response to the exponential rise in the world’s urbanizing population. While earlier, only technical, economic and governance based solutions were considered, more and more layers are being added in recent times. With the prefix of 'sustainability', solutions which help in judicious use of resources without negatively impacting the environment have become critical. We present a case study of Bangalore city which has transformed from being a garden city and pensioners' paradise to being an IT city with a huge, young population from different regions and diverse cultural backgrounds. This has had a big impact on the green spaces in the city and the biodiversity that they support, as well as on farming/gardening practices. Edible landscapes comprising farms lands, home gardens and neighbourhood parks (NPs henceforth) were examined. The land prices of areas having NPs were higher than those that did not indicate an appreciation of their aesthetic value. NPs were part of old and new residential areas largely managed by the municipality. They comprised manicured gardens which were similar in vegetation structure and composition. Results showed that NPs that occurred in higher density supported reasonable levels of biodiversity. In situations where NPs occurred in lower density, the presence of a larger green space such as a heritage park or botanical garden enhanced the biodiversity of these parks. In contrast, farm lands and home gardens which were common within the city are being lost at an unprecedented scale to developmental projects. However, there is also the emergence of a 'neo-culture' of home-gardening that promotes 'locovory' or consumption of locally grown food as a means to a sustainable living and reduced carbon footprint. This movement overcomes the space constraint by using vertical and terrace gardening techniques. Food that is grown within cities comprises of vegetables and fruits which are largely pollinator dependent. This goes hand in hand with our landscape-level study that has shown that cities support pollinator diversity. Maintaining and improving these man-made ecosystems requires analysing the functioning and characteristics of the existing structures of governance. Social network analysis tool was applied to NPs to examine relationships, between actors and ties. The management structures around NPs, gaps, and means to strengthen the networks from the current state to a near-ideal state were identified for enhanced services. Learnings from NPs were used to build a hypothetical governance structure and functioning of integrated governance of NPs and edible landscapes to enhance ecosystem services such as biodiversity support, food production, and aesthetic value. They also contribute to the sustainability axis of smart cities.

Keywords: biodiversity support, ecosystem services, edible green spaces, neighbourhood parks, sustainable smart city

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Authors: S. Tunmee, P. Wongpanya, I. Toda, X. L. Zhou, Y. Nakaya, N. Konkhunthot, S. Arakawa, H. Saitoh

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The hydrogenated amorphous carbon films (a-C:H) were deposited on p-type Si (100) substrates at different thicknesses by radio frequency plasma enhanced chemical vapor deposition technique (rf-PECVD). Raman spectra display asymmetric diamond-like peaks, representative of the a-C:H films. The decrease of intensity ID/IG ratios revealed the sp3 content arise at different thicknesses of the a-C:H films. In terms of mechanical properties, the high hardness and elastic modulus values show the elastic and plastic deformation behaviors related to sp3 content in amorphous carbon films. Electro chemical properties showed that the a-C:H films exhibited excellent corrosion resistance in air-saturated 3.5 wt% NaCl solution for pH 2 at room temperature. Thickness increasing affected the small sp2 clusters in matrix, restricting the velocity transfer and exchange of electrons. The deposited a-C:H films exhibited excellent mechanical properties and corrosion resistance.

Keywords: thickness, mechanical properties, electrochemical corrosion properties, a-C:H film

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Authors: Elitza Z. Ambrus, Bjoern Hartig, Ryan McKay

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Individuals’ self-judgments might be malleable and influenced by comparison with a random value. On the one hand, self-judgments reflect our self-image, which is typically considered to be stable in adulthood. Indeed, people also strive hard to maintain a fixed, positive moral image of themselves. On the other hand, research has shown the robustness of the so-called anchoring effect on judgments and decisions. The anchoring effect refers to the influence of a previously considered comparative value (anchor) on a consecutive absolute judgment and reveals that individuals’ estimates of various quantities are flexible and can be influenced by a salient random value. The present study extends the anchoring paradigm to the domain of the self. We also investigate whether participants are more susceptible to self-serving anchors, i.e., anchors that enhance participant’s self-image, especially their moral self-image. In a pre-reregistered study via the online platform Prolific, 249 participants (156 females, 89 males, 3 other and 1 who preferred not to specify their gender; M = 35.88, SD = 13.91) ranked themselves on eight personality characteristics. However, in the anchoring conditions, respondents were asked to first indicate whether they thought they would rank higher or lower than a given anchor value before providing their estimated rank in comparison to 100 other anonymous participants. A high and a low anchor value were employed to differentiate between anchors in a desirable (self-serving) direction and anchors in an undesirable (self-diminishing) direction. In the control treatment, there was no comparison question. Subsequently, participants provided their self-rankings on the eight personality traits with two personal characteristics for each combination of the factors desirable/undesirable and moral/non-moral. We found evidence of an anchoring effect for self-judgments. Moreover, anchoring was more efficient when people were anchored in a self-serving direction: the anchoring effect was enhanced when supporting a more favorable self-view and mitigated (even reversed) when implying a deterioration of the self-image. The self-serving anchoring was more pronounced for moral than for non-moral traits. The data also provided evidence in support of a better-than-average effect in general as well as a magnified better-than-average effect for moral traits. Taken together, these results suggest that self-judgments might not be as stable in adulthood as previously thought. In addition, considerations of constructing and maintaining a positive self-image might interact with the anchoring effect on self-judgments. Potential implications of our results concern the construction and malleability of self-judgments as well as the psychological mechanism shaping anchoring.

Keywords: anchoring, better-than-average effect, self-judgments, self-serving anchoring

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Authors: Lauren C. Porter, Andrew Curtis, Eric Jefferis, Susanne Mitchell

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A wealth of research has been generated examining the variation in crime across neighborhoods. However, there is also a striking degree of crime concentration within neighborhoods. A number of studies show that a small percentage of street segments, intersections, or addresses account for a large portion of crime. Not surprisingly, a focus on these crime hot spots can be an effective strategy for reducing community level crime and related ills, such as health problems. However, research is also limited in an important respect. Studies tend to use official data to identify hot spots, such as 911 calls or calls for service. While the use of call data may be more representative of the actual level and distribution of crime than some other official measures (e.g. arrest data), call data still suffer from the 'dark figure of crime.' That is, there is most certainly a degree of error between crimes that occur versus crimes that are reported to the police. In this study, we present an alternative method of identifying crime hot spots, that does not rely on official data. In doing so, we highlight the potential utility of neighborhood-insiders to identify and understand crime dynamics within geographic spaces. Specifically, we use spatial video and geo-narratives to record the crime insights of 36 police, ex-offenders, and residents of a high crime neighborhood in northeast Ohio. Spatial mentions of crime are mapped to identify participant-identified hot spots, and these are juxtaposed with calls for service (CFS) data. While there are bound to be differences between these two sources of data, we find that one location, in particular, a corner store, emerges as a hot spot for all three groups of participants. Yet it does not emerge when we examine CFS data. A closer examination of the space around this corner store and a qualitative analysis of narrative data reveal important clues as to why this store may indeed be a hot spot, but not generate disproportionate calls to the police. In short, our results suggest that researchers who rely solely on official data to study crime hot spots may risk missing some of the most dangerous places.

Keywords: crime, narrative, video, neighborhood

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Authors: Mahdi Bazarganigilani

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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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Authors: Nasim Eslamirad, Mahdi Rasoulinezhad, Francesco De Luca, Sadok Ben Yahia, Kimmo Sakari Lylykangas, Francesco Pilla

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With the ongoing urbanization, cities face increasing environmental challenges impacting human well-being. To tackle these issues, data-driven approaches in urban analysis have gained prominence, leveraging urban data to promote sustainability. Integrating Machine Learning techniques enables researchers to analyze and predict complex environmental phenomena like Urban Heat Island occurrences in urban areas. This paper demonstrates the implementation of data-driven approach and interpretable Machine Learning algorithms with interpretability techniques to conduct comprehensive data analyses for sustainable urban design. The developed framework and algorithms are demonstrated for Tallinn, Estonia to develop sustainable urban strategies to mitigate urban heat waves. Geospatial data, preprocessed and labeled with UHI levels, are used to train various ML models, with Logistic Regression emerging as the best-performing model based on evaluation metrics to derive a mathematical equation representing the area with UHI or without UHI effects, providing insights into UHI occurrences based on buildings and urban features. The derived formula highlights the importance of building volume, height, area, and shape length to create an urban environment with UHI impact. The data-driven approach and derived equation inform mitigation strategies and sustainable urban development in Tallinn and offer valuable guidance for other locations with varying climates.

Keywords: data-driven approach, machine learning transparent models, interpretable machine learning models, urban heat island effect

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Authors: Francisco Pereira, António Augusto Vicente, Filipe Vaz, Joel Borges, Pedro Geada

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Light is a growth-limiting factor in microalgae cultivation, where factors like spectral components, intensity, and duration, often characterized by its wavelength, are well-reported to have a substantial impact on cell growth rates and, consequently, photosynthetic performance and mitigation of CO2, one of the most significant greenhouse gases (GHGs). Photobioreactors (PBRs) are commonly used to grow microalgae under controlled conditions, but they often fail to provide an even light distribution to the cultures. For this reason, there is a pressing need for innovations aiming at enhancing the efficient utilization of light. So, one potential approach to address this issue is by implementing plasmonic films, such as the localized surface plasmon resonance (LSPR). LSPR is an optical phenomenon connected to the interaction of light with metallic nanostructures. LSPR excitation is characterized by the oscillation of unbound conduction electrons of the nanoparticles coupled with the electromagnetic field from incident light. As a result of this excitation, highly energetic electrons and a strong electromagnetic field are generated. These effects lead to an amplification of light scattering, absorption, and extinction of specific wavelengths, contingent on the nature of the employed nanoparticle. Thus, microalgae might benefit from this biotechnology as it enables the selective filtration of inhibitory wavelengths and harnesses the electromagnetic fields produced, which could lead to enhancements in both biomass and metabolite productivity. This study aimed at implementing and evaluating a “plasmon-enhanced PBR”. The goal was to utilize LSPR thin films to enhance the growth and CO2 bio-fixation rate of Chlorella vulgaris. The internal/external walls of the PBRs were coated with a TiO2 matrix containing different nanoparticles (Au, Ag, and Au-Ag) in order to evaluate the impact of this approach on microalgae’s performance. Plasmonic films with distinct compositions resulted in different Chlorella vulgaris growth, ranging from 4.85 to 6.13 g.L-1. The highest cell concentrations were obtained with the metallic Ag films, demonstrating a 14% increase compared to the control condition. Moreover, it appeared to be no differences in growth between PBRs with inner and outer wall coatings. In terms of CO2 bio-fixation, distinct rates were obtained depending on the coating applied, ranging from 0.42 to 0.53 gCO2L-1d-1. Ag coating was demonstrated to be the most effective condition for carbon fixation by C. vulgaris. The impact of LSPR films on the biochemical characteristics of biomass (e.g., proteins, lipids, pigments) was analysed as well. Interestingly, Au coating yielded the most significant enhancements in protein content and total pigments, with increments of 15 % and 173 %, respectively, when compared to the PBR without any coating (control condition). Overall, the incorporation of plasmonic films in PBRs seems to have the potential to improve the performance and efficiency of microalgae cultivation, thereby representing an interesting approach to increase both biomass production and GHGs bio-mitigation.

Keywords: CO₂ bio-fixation, plasmonic effect, photobioreactor, photosynthetic microalgae

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Authors: F. Kovács, K. Kádár, G. Hosszú, Á. T. Balogh, T. Zsedrovits, N. Kersner, A. Nagy, Gy. Jeney

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The paper presents a novel screening method to indicate congenital heart diseases (CHD), which otherwise could remain undetected because of their low level. Therefore, not belonging to the high-risk population, the pregnancies are not subject to the regular fetal monitoring with ultrasound echocardiography. Based on the fact that CHD is a morphological defect of the heart causing turbulent blood flow, the turbulence appears as a murmur, which can be detected by fetal phonocardiography (fPCG). The proposed method applies measurements on the maternal abdomen and from the recorded sound signal a sophisticated processing determines the fetal heart murmur. The paper describes the problems and the additional advantages of the fPCG method including the possibility of measurements at home and its combination with the prescribed regular cardiotocographic (CTG) monitoring. The proposed screening process implemented on a telemedicine system provides an enhanced safety against hidden cardiac diseases.

Keywords: cardiac murmurs, fetal phonocardiography, screening of CHDs, telemedicine system

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Authors: Ruchi Yadav, Shivani Pandey, Prachi Srivastava

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Microarrays provide a rich source of data on the molecular working of cells. Each microarray reports on the abundance of tens of thousands of mRNAs. Virtually every human disease is being studied using microarrays with the hope of finding the molecular mechanisms of disease. Bioinformatics analysis plays an important part of processing the information embedded in large-scale expression profiling studies and for laying the foundation for biological interpretation. A basic, yet challenging task in the analysis of microarray gene expression data is the identification of changes in gene expression that are associated with particular biological conditions. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. One of the most popular platforms for microarray analysis is Bioconductor, an open source and open development software project based on the R programming language. This paper describes specific procedures for conducting quality assessment, visualization and preprocessing of Affymetrix Gene Chip and also details the different bioconductor packages used to analyze affymetrix microarray data and describe the analysis and outcome of each plots.

Keywords: microarray analysis, R language, affymetrix visualization, bioconductor

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Authors: Sankara Rao Gollu, Ramakant Sharma, G. Srinivas, Souvik Kundu, Dipti Gupta

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In recent years, bulk heterojunction organic solar cells (BHJ OSCs) based on polymer–fullerene attracted a large research attention due to their numerous advantages such as light weight, easy processability, eco-friendly, low-cost, and capability for large area roll-to-roll manufacturing. BHJ OSCs usually suffer from insufficient light absorption due to restriction on keeping thin ( < 150 nm) photoactive layer because of small exciton diffusion length ( ~ 10 nm) and low charge carrier mobilities. It is thus highly desirable that light absorption as well as charge transport properties are enhanced by alternative methods so as to improve the device efficiency. In this work, therefore, we have focused on the strategy of incorporating metallic nanostructures in the active layer or charge transport layer to enhance the absorption and improve the charge transport.

Keywords: organic solar cell, efficiency, bulk heterojunction, polymer-fullerene

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Authors: Anup Kumar Keshri, Arvind Agarwal

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Carbon nanotube (CNT) reinforced aluminum oxide (Al2O3) composite coating was synthesized on the steel substrate using plasma spraying technique. Three different compositions of coating such as Al2O3, Al2O¬3-4 wt. % CNT and Al2O3-8 wt. % CNT were synthesized and the fracture strength was determined using the four point bend test. Uniform dispersion of CNTs over Al2O3 powder particle was successfully achieved. With increasing CNT content, porosity in the coating showed decreasing trend and hence contributed towards enhanced mechanical properties such as hardness (~12% increased) and elastic modulus (~34 % increased). Fracture strength of the coating was found to be increasing with the CNT additions. By reinforcement of 8 wt. % of CNT, fracture strength increased by ~2.5 times. The improvement in fracture strength of Al2O3-CNT coating was attributed to three competitive phenomena viz. (i) lower porosity (ii) higher hardness and elastic modulus (iii) CNT bridging between splats.

Keywords: aluminum oxide, carbon nanotube, fracture strength, plasma spraying

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Authors: Siddhartha Khare, Suyash Khare

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Phenology, a crucial discipline in ecology, offers insights into the seasonal dynamics of organisms within natural ecosystems and the underlying environmental triggers. Leveraging the potent capabilities of digital repeat photography, PhenoCams capture invaluable data on the phenology of crops, plants, and trees. These cameras yield digital imagery in Red Green Blue (RGB) color channels, and some advanced systems even incorporate Near Infrared (NIR) bands. This study presents compelling case studies employing PhenoCam technology to unravel the phenology of black spruce trees. Through the analysis of RGB color channels, a range of essential color metrics including red chromatic coordinate (RCC), green chromatic coordinate (GCC), blue chromatic coordinate (BCC), vegetation contrast index (VCI), and excess green index (ExGI) are derived. These metrics illuminate variations in canopy color across seasons, shedding light on bud and leaf development. This, in turn, facilitates a deeper understanding of phenological events and aids in delineating the growth periods of trees and plants. The initial phase of this study addresses critical questions surrounding the fidelity of continuous canopy greenness records in representing bud developmental phases. Additionally, it discerns which color-based index most accurately tracks the seasonal variations in tree phenology within evergreen forest ecosystems. The subsequent section of this study delves into the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology. This is achieved through a fortnightly comparative analysis of the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). By employing PhenoCam technology and leveraging advanced color metrics, this study significantly advances our comprehension of black spruce tree phenology, offering valuable insights for ecological research and management.

Keywords: phenology, remote sensing, phenocam, color metrics, NDVI, GCC

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Authors: Najrullah Khan, Athar Ali Khan

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The Topp-Leone distribution was introduced by Topp- Leone in 1955. In this paper, an attempt has been made to fit Topp-Leone Generalized exponential (TPGE) distribution. A real survival data set is used for illustrations. Implementation is done using R and JAGS and appropriate illustrations are made. R and JAGS codes have been provided to implement censoring mechanism using both optimization and simulation tools. The main aim of this paper is to describe and illustrate the Bayesian modelling approach to the analysis of survival data. Emphasis is placed on the modeling of data and the interpretation of the results. Crucial to this is an understanding of the nature of the incomplete or 'censored' data encountered. Analytic approximation and simulation tools are covered here, but most of the emphasis is on Markov chain based Monte Carlo method including independent Metropolis algorithm, which is currently the most popular technique. For analytic approximation, among various optimization algorithms and trust region method is found to be the best. In this paper, TPGE model is also used to analyze the lifetime data in Bayesian paradigm. Results are evaluated from the above mentioned real survival data set. The analytic approximation and simulation methods are implemented using some software packages. It is clear from our findings that simulation tools provide better results as compared to those obtained by asymptotic approximation.

Keywords: Bayesian Inference, JAGS, Laplace Approximation, LaplacesDemon, posterior, R Software, simulation

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Authors: Amir Taghizadeh Vahed, Adithya Thaduri

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Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

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Authors: Vladimir Simovic, Matija Varga, Predrag Oreski

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XHTML and XBRL are the standard languages for creating a database for the purpose of displaying financial statements on web applications. Today, XBRL is one of the most popular languages for business reporting. A large number of countries in the world recognize the role of XBRL language for financial reporting and the benefits that the reporting format provides in the collection, analysis, preparation, publication and the exchange of data (information) which is the positive side of this language. Here we present all advantages and opportunities that a company may have by using the XBRL format for business reporting. Also, this paper presents XBRL and other languages that are used for creating the database, such XML, XHTML, etc. The role of the AJAX complex model and technology will be explained in detail, and during the exchange of financial data between the web client and web server. Here will be mentioned basic layers of the network for data exchange via the web.

Keywords: XHTML, XBRL, XML, JavaScript, AJAX technology, data exchange

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Authors: Ann Devitt, Mairead Brady, Markus Lamest, Stephen Gomez

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This study set out to explore the use of an online collaborative serious game for student learning in a postgraduate introductory marketing module. The simulation game aimed to bridge the theory-practice divide in marketing by allowing students to apply theory in a safe, simulated marketplace. This study addresses the following research questions: Does an online marketing simulation game engage students higher order cognitive skills? Does collaborative activity required develop students’ “soft” skills, such as communication and negotiation? What specific affordances of the online simulation promote learning? This qualitative case study took place in 2014 with 40 postgraduate students on a Business Masters Programme. The two-week intensive module combined lectures with collaborative activity on a marketing simulation game, MMX from Pearsons. The game requires student teams to compete against other teams in a marketplace and design a marketing plan to maximize key performance indicators. The data for this study comprise essays written by students after the module reflecting on their learning on the module. A thematic analysis was conducted of the essays using the following a priori theme sets: 6 levels of the cognitive domain of Blooms taxonomy; 5 principles of Cooperative Learning; affordances of simulation environments including experiential learning; motivation and engagement; goal orientation. Preliminary findings would strongly suggest that the game facilitated students identifying the value of theory in practice, in particular for future employment; enhanced their understanding of group dynamics and their role within that; and impacted very strongly, both positively and negatively on motivation. In particular the game mechanics of MMX, which hinges on the correct identification of a target consumer group, was identified as a key determinant of extrinsic and intrinsic motivation for learners. The findings also suggest that the situation of the simulation game within a broader module which required post-game reflection was valuable in identifying key learning of marketing concepts in both the positive and the negative experiences of the game.

Keywords: simulation, marketing, serious game, cooperative learning, bloom's taxonomy

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Authors: Aymen Sekhri, Emmanuel Kwabena Frimpong, Bolaji Mubarak Ayeyemi, Aleksi Hirvonen, Matias Hirvonen, Tedros Tesfay Andemichael

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Fixation identification, which involves isolating and identifying fixations and saccades in eye-tracking protocols, is an important aspect of eye-movement data processing that can have a big impact on higher-level analyses. However, fixation identification techniques are frequently discussed informally and rarely compared in any meaningful way. With two state-of-the-art algorithms, we will implement fixation detection and analysis in this work. The velocity threshold fixation algorithm is the first algorithm, and it identifies fixation based on a threshold value. For eye movement detection, the second approach is U'n' Eye, a deep neural network algorithm. The goal of this project is to analyze and visualize eye-tracking data from an eye gaze dataset that has been provided. The data was collected in a scenario in which individuals were shown photos and asked whether or not they recognized them. The results of the two-fixation detection approach are contrasted and visualized in this paper.

Keywords: human-computer interaction, eye-tracking, CNN, fixations, saccades

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Authors: Abdullah Ababtain, Mouhammad El Hassan, Hassan Assoum, Anas Sakout

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In this paper, a brief literature review on cavitation jets is presented in order to introduce the cavitation mechanism, strategies to assess when cavitation occurs, and the factors that influence cavitation in cavitating jets. The objectivity of the cavitation number often used to predict cavitation is also discussed. The results show that cavitation cannot be foreseen just using the cavitation number. Therefore, more efforts are needed to innovate and develop a self-resonating jet geometry that would be maintains the flow and the pressure in the cavitation condition just earlier than the flow acts on the target that would be used in such operating conditions. This study focused on a particular aspect related to improving drilling efficiency and the rate of penetration (ROP). In addition, a discussion on the methods used to measure cavitation and the factors that affect cavitation occurrence will be discussed. Two different types of cavitation nozzles were designed and tested. It has been shown that the self-resonating cavitation nozzle presents greater performance than standard non-resonating nozzle. It is thus concluded that a self-resonating cavitation jet present a high potential for improving drilling performance.

Keywords: cavitating jet, erosion, cavitation number, rate of penetration (ROP)

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Authors: Anna Citterbergova

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This study explores the safeguards and guarantees to children’s personal data protection under the current EU and US legislative framework, namely the GDPR (2018) and COPPA (2000). Considering that children are online for the majority of their free time, one cannot overlook the negative side effects that may be associated with online participation, which may put children’s wellbeing and their fundamental rights at risk. The question of whether the current relevant legislative framework in relation to the responsibilities of the internet service providers (ISPs) are adequate safeguards and guarantees to children’s personal data protection has been an evolving debate both in the US and in the EU. From a children’s rights perspective, processors of personal data have certain obligations that must meet the international human rights principles (e. g. the CRC, ECHR), which require taking into account the best interest of the child. Accordingly, the need to protect children’s privacy online remains strong and relevant with the expansion of the number and importance of social media platforms to human life. At the same time, the landscape of the internet is rapidly evolving, and commercial interests are taking a more targeted approach in seeking children’s data. Therefore, it is essential to constantly evaluate the ongoing and evolving newly adopted market policies of ISPs that may misuse the gap in the current letter of the law. Previous studies in the field have already pointed out that both GDPR and COPPA may theoretically not be sufficient in protecting children’s personal data. With the focus on social media platforms, this study uses the doctrinal-descriptive method to identifiy the mechanisms enshrined in the GDPR and COPPA designed to protect children’s personal data. In its second part, the study includes a data gathering phase by the national data protection authorities responsible for monitoring and supervision of the GDPR in relation to children’s personal data protection who monitor the enforcement of the data protection rules throughout the European Union an contribute to their consistent application. These gathered primary source of data will later be used to outline the series of benefits and challenges to children’s persona lata protection faced by these institutes and the analysis that aims to suggest if and/or how to hold ISPs accountable while striking a fair balance between the commercial rights and the right to protection of the personal data of children. The preliminary results can be divided into two categories. First, conclusions in the doctrinal-descriptive part of the study. Second, specific cases and situations from the practice of national data protection authorities. While for the first part, concrete conclusions can already be presented, the second part is currently still in the data gathering phase. The result of this research is a comprehensive analysis on the safeguards and guarantees to children’s personal data protection under the current EU and US legislative framework, based on doctrinal-descriptive approach and original empirical data.

Keywords: personal data of children, personal data protection, GDPR, COPPA, ISPs, social media

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Authors: Sourour Ramzi, Claudia Sarrico

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Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.

Keywords: supply chain, education, data envelopment analysis, network DEA

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Authors: Mai M. Khalaf, Hany M. Abd El-Lateef

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A new good application for the sol gel method is to improve the corrosion inhibition properties of carbon steel by the dip coating method of Nano TiO2 films and its modification with Poly Ethylene Glycol (PEG). The prepared coating samples were investigated by different techniques, X-ray diffraction, Scanning Electron Microscopy (SEM), transmission electron microscopy and Energy Dispersive X-ray Spectroscopy (EDAX). The corrosion inhibition performance of the blank carbon steel and prepared coatings samples were evaluated in 0.5 M H2SO4 by using Electrochemical Impedance Spectroscopy (EIS) and potentiodynamic polarization measurements. The results showed that corrosion resistance of carbon steel increases with increasing the number of coated layers of both nano–TiO2 films and its modification of PEG. SEM-EDAX analyses confirmed that the percentage atomic content of iron for the carbon steel in 0.5 M H2SO4 is 83% and after the deposition of the steel in nano TiO2 sol and that with PEG are 94.3% and 93.7% respectively.

Keywords: dip-coatings, corrosion protection, sol gel, TiO2 films, PEG

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Authors: Bangwon Seo

Abstract:

In this paper, we consider multicast device-to-device (D2D) direct communication systems in cellular networks. In multicast D2D communications, nearby mobile devices exchanges, their data directly without going through a base station and a D2D transmitter send its data to multiple D2D receivers that compose of D2D multicast group. We consider wiretap channel where there is an eavesdropper that attempts to overhear the transmitted data of the D2D transmitter. In this paper, we propose a secure transmission scheme in D2D multicast communications in cellular networks. In order to prevent the eavesdropper from overhearing the transmitted data of the D2D transmitter, a precoding vector is employed at the D2D transmitter in the proposed scheme. We perform computer simulations to evaluate the performance of the proposed scheme. Through the simulation, we show that the secrecy rate performance can be improved by selecting an appropriate precoding vector.

Keywords: device-to-device communications, wiretap channel, secure transmission, precoding

Procedia PDF Downloads 291

Authors: Andrzej Poszewiecki

Abstract:

The presented paper contributes to the experimental current of research on privacy. The question of privacy is being discussed at length at present, primarily among lawyers and politicians. However, the matter of privacy has been of interest for economists for some time as well. The valuation of privacy by people is of great importance now. This article is about how people valuate their privacy. An experimental method has been utilised in the conducted research – the survey was carried out among customers of an online store, and the studied issue was whether their readiness to sell their data (WTA) was different from the willingness to buy data back (WTP). The basic aim of this article is to analyse whether people shopping on the Internet differentiate their privacy depending on whether they protect or sell it. The achieved results indicate the presence of major differences in this respect, which do not always come up with the original expectations. The obtained results have supported the hypothesis that people are more willing to sell their data than to repurchase them. However, the hypothesis that the value of proposed remuneration affects the willingness to sell/buy back personal data (one’s privacy) has not been supported.

Keywords: privacy, experimental economics, behavioural economics, internet

Procedia PDF Downloads 293

Authors: Kiran Baldavoo, Mishelle Doorasamy

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Universities have a role to play in the preservation of the environment, and the study attempted to evaluate the environmental management accounting (EMA) processes at UKZN. UKZN, a South African university, generates the same direct and indirect environmental impacts as the higher education sector worldwide. This is significant within the context of the South African environment which is constantly plagued by having to effectively manage the already scarce resources of water and energy, evident through the imposition of water and energy restrictions over the recent years. The study’s aim is to increase awareness of having a structured approach to environmental management in order to achieve the strategic environmental goals of the university. The research studied the experiences of key managers within UKZN, with the purpose of exploring the potential factors which influence the decision to adopt and apply EMA within the higher education sector. The study comprised two objectives, namely understanding the current state of accounting practices for managing major environmental costs and identifying factors influencing EMA adoption within the university. The study adopted a case study approach, comprising semi-structured interviews of key personnel involved in Management Accounting, Environmental Management, and Academic Schools within the university. Content analysis was performed on the transcribed interview data. A Theoretical Framework derived from literature was adopted to guide data collection and focus the study. Contingency and Institutional theory was the resultant basis of the derived framework. The findings of the first objective revealed that there was a distinct lack of EMA utilization within the university. There was no distinct policy on EMA, resulting in minimal environmental cost information being brought to the attention of senior management. The university embraced the principles of environmental sustainability; however, efforts to improve internal environmental accountability primarily from an accounting perspective was absent. The findings of the second objective revealed that five key barriers contributed to the lack of EMA utilization within the university. The barriers being attitudinal, informational, institutional, technological, and lack of incentives (financial). The results and findings of this study supported the use and application of EMA within the higher education sector. Participants concurred that EMA was underutilized and if implemented, would realize significant benefits for both the university and environment. Environmental management accounting is being widely acknowledged as a key management tool that can facilitate improved financial and environmental performance via the concept of enhanced environmental accountability. Historically research has been concentrated primarily on the manufacturing industry, due to it generating the greatest proportion of environmental impacts. Service industries are also an integral component of environmental management as they contribute significant environmental impacts, both direct and indirect. Educational institutions such as universities form part of the service sector and directly impact on the environment through the consumption of paper, energy, and water and solid waste generated, with the associated demands.

Keywords: environmental management accounting, environmental impacts, higher education, Southern Africa

Procedia PDF Downloads 124

Authors: M. Vadivel, R. Ramesh Babu

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Spinel ferrite magnetic nanomaterials have received a great deal of attention in recent years due to their wide range of potential applications in various fields such as magnetic data storage and microwave device applications. Among the family of spinel ferrites, cobalt ferrite (CoFe2O4) has been widely used in the field of high-frequency applications because of its remarkable material qualities such as moderate saturation magnetization, high coercivity, large permeability at higher frequency and high electrical resistivity. For aforementioned applications, the materials should have an improved electrical property, especially enhancement in the dielectric properties. It is well known that the substitution of rare earth metal cations in Fe3+ site of CoFe2O4 nanoparticles leads to structural distortion and thus significantly influences the structural and morphological properties whereas greatly modifies the electrical and magnetic properties of a material. In the present investigation, we report on the influence of lanthanum (La3+) ion substitution on the structural, morphological, dielectric and magnetic properties of CoFe2O4 magnetic nanoparticles prepared by co-precipitation method. Powder X-ray diffraction patterns reveal the formation of inverse cubic spinel structure with the signature of LaFeO3 phase at higher La3+ ion concentrations. Raman and Fourier transform infrared spectral analysis also confirms the formation of inverse cubic spinel structure and Fe-O symmetrical stretching vibrations of CoFe2O4 nanoparticles, respectively. Transmission electron microscopy study reveals that the size of the particles gradually increases with increasing La3+ ion concentrations whereas the agglomeration gets slightly reduced for La3+ ion substituted CoFe2O4 nanoparticles than that of undoped CoFe2O4 nanoparticles. Dielectric properties such as dielectric constant and dielectric loss were recorded as a function of frequency and temperature which reveals that the dielectric constant gradually increases with increasing temperatures as well as La3+ ion concentrations. The increased dielectric constant might be the reason that the formation of LaFeO3 secondary phase at higher La3+ ion concentrations. Magnetic measurement demonstrates that the saturation magnetization gradually decreases from 61.45 to 25.13 emu/g with increasing La3+ ion concentrations which is due to the nonmagnetic nature of La3+ ions substitution.

Keywords: cobalt ferrite, co-precipitation, dielectric properties, saturation magnetization

Procedia PDF Downloads 317

Authors: Karan Vishavjit, Aakash Lakra, Shafaq Khan

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The COVID-19 pandemic has pushed healthcare professionals to use big data analytics as a vital tool for tracking and evaluating the effects of contagious viruses. To effectively analyze huge datasets, efficient NoSQL databases are needed. The analysis of post-COVID-19 health and well-being outcomes and the evaluation of the effectiveness of government efforts during the pandemic is made possible by this research’s integration of several datasets, which cuts down on query processing time and creates predictive visual artifacts. We recommend applying sharding and indexing technologies to improve query effectiveness and scalability as the dataset expands. Effective data retrieval and analysis are made possible by spreading the datasets into a sharded database and doing indexing on individual shards. Analysis of connections between governmental activities, poverty levels, and post-pandemic well being is the key goal. We want to evaluate the effectiveness of governmental initiatives to improve health and lower poverty levels. We will do this by utilising advanced data analysis and visualisations. The findings provide relevant data that supports the advancement of UN sustainable objectives, future pandemic preparation, and evidence-based decision-making. This study shows how Big Data and NoSQL databases may be used to address problems with global health.

Keywords: big data, COVID-19, health, indexing, NoSQL, sharding, scalability, well being

Procedia PDF Downloads 70

Authors: Ting-Ting Wen, H. C. Lin

Abstract:

This paper reports a study for the light outcoupling efficiency of the PLED device. In use of a designed substrate combined with nano-line patterns in PLED device, the light outcoupling efficiency can be significantly enhanced. The designed substrate was made by UV imprinting technology, such as triangular microlens arrays on the front and periodic corrugated patterns on the back surface. The nano-line patterns in PLED device was fabricated by advanced microstamping and ink-jet printing techniques. For high angles of observation with respect to the substrate surface normal, the light out intensity of the developed PLED device is increased from 0.05 (a.u.) up to 0.69 (a.u.) at the view angle 85 degree. The designed integration leads to 64% increase of the light out intensity compared with the conventional PLED device.

Keywords: triangular microlens, corrugation patterns, nano-line patterns, PLED device, UV imprinting technology, microstamping

Procedia PDF Downloads 478

Authors: Prashant Neupane, Sumitra Kafle, Asmi Pandey, Laura Mitchell

Abstract:

Pain following caesarean section can influence recovery, patient satisfaction, breast feeding success and mother-child bonding. Since the introduction of enhanced recovery protocols, mothers are often discharged 24 hours later. We identified concerns within our hospital with mothers tolerating poorly controlled pain in order to achieve earlier discharge and subsequently suffering significant pain at home with inadequate analgesia. Methods: We conducted a prospective audit of analgesic prescribing and post-operative pain scores after caesarean section. Mothers were seen on post-operative day one, their pain score recorded on a verbal analogue score from 0-10, and their prescription chart reviewed. A follow-up phone call was then made on post-operative day 3-7 to enquire about pain scores and analgesia use at home. Following this, a standardized proforma for prescribing after the caesarean section was introduced, including the addition of dihydrocodeine that patients can take home following discharge. There were educational update sessions for anesthetists and midwifes, and then a re-audit was conducted months later. Results: Data was collected from 50 women before and after the introduction of the change. Initial audit showed that there was considerable variation in prescribing, with four women prescribed no regular analgesia at all and inconsistency in the dose of oral morphine prescribed. Women were not given any form of analgesia to take home after discharge and were advised to take regular paracetamol and ibuprofen. However, 31/50 (62%) reported that they needed additional analgesia and eight women (16%) even sought prescription for additional analgesia from elsewhere. After the introduction of the change, prescribing was more consistent with all patients prescribed regular analgesia. 46/50 patients were given dihydrocodeine on discharge. Mean pain scores on post-operative day one improved from 5.16 to 3.9, and at home improved from 6.18 to 2.58. Use of dihydrocodeine at home significantly improved patients reporting of severe pain at home from 24% to zero. Discussion: Lack of strong analgesia out of the hospital and the increased demands on activity levels means that women are frequently in more pain at home after discharge. Introduction of a standardized prescription proforma, including the use of to-take-out dihydrocodeine, was successful in improving patient pain scores and the requirement for additional analgesia, both in hospital and at home.

Keywords: analgesia, caesarean section, post-operative pain, standardised

Procedia PDF Downloads 106