Search results for: user generated content

Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

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The simulation in wind tunnel is used thoroughly to model real situations of drainages of air. Besides the automotive industry, a great number of applications can be numbered: dispersion of pollutant, studies of pedestrians comfort and dispersion of particles. This work had the objective of visualizing the characteristics aerodynamics of two automobiles in different ways. To accomplish that drainage of air a fan that generated a speed exists (measured with anemometer of hot thread) of 4,1m/s and 4,95m/s. To visualize the path of the air through the cars, in the wind tunnel, smoke was used, obtained with it burns of vegetable oil. For “to do smoke” vegetable oil was used, that was burned for a tension of 20 V generated by a thread of 2,5 mm. The cars were placed inside of the wind tunnel with the drainage of “air-smoke” and photographed, registering like this the path lines around them, in the 3 different speeds.

Keywords: aerodynamics, vehicle drag, vegetable oil, wind tunnel

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Authors: Kamilia Ounaissa, Sarra Fennira, Asma Ben Brahim, Marwa Omri, Abdelmajid Abid

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The palm oil is the vegetable oil the most used by the food-processing industry in the world. It is chosen for its economic and technologic advantages. However, this oil arouses the debate because of its high content in saturated fatty acids, which are fats promoting atherosclerosis. Purposes of the work: To study the frequency and the rate of consumption of industrial products containing some palm oil and specify the rate of this oil in certain consummated products. Methodology: We proceeded to a consumer survey using a questionnaire collecting a list of food containing the palm oil, sold on the Tunisian market. We then analyzed the most consumed food to specify their fat content by “Soxhelt’s” method. Finally, we studied the composition in various fatty acids of the extracted fat using the chromatography in the gas phase (CPG) Results: Our results show that investigated individuals having a normal weight have a more important and more frequent consumption of products rich in palm oil than overweight subjects. The most consumed foods are biscuits, cakes, wafers, chocolates, chips, cereal, creams to be spread and canned pilchard. The content in palm oil of these products varies from 10 % to 31 %. The analysis by CPG showed an important content in saturated fatty acid, in particular in palmitic acid, ranging from 40 % to 63 % of the fat of these products. Conclusion: Our study shows a high frequency of consumption of food products, the analysis of which proved a high content in palm oil. Theses facts justifies the necessity of a regulation of the use of palm oil in food products and the application of a label detailing the type and fat rates used.

Keywords: palm oil, palmitic acid, food industry, fatty acids, atherosclerosis

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Rachel Williams, Shiqi Yang

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Our research explores the influence nationalism has had on media coverage of the COVID-19 pandemic as it relates to China in the United States through an inclusive qualitative analysis of two US news networks, Fox News and CNN. In total, the transcripts of sixteen videos uploaded on YouTube, each with more than 100,000 views, were gathered for data processing. Co-occurrence networks generated by KH Coder illuminate the themes and narratives underpinning the reports from Fox News and CNN. The results of in-depth content analysis with keywords suggest that the pandemic has been framed in an ethnopopulist nationalist manner, although to varying degrees between networks. Specifically, the authors found that Fox News is more likely to report hypotheses or statements as a fact; on the contrary, CNN is more likely to quote data and statements from official institutions. Future research into how nationalist narratives have developed in China and in other US news coverage with a more systematic and quantitative method can be conducted to expand on these findings.

Keywords: nationalism, media studies, us and china, COVID-19, social media, communication studies

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Authors: Eda Gök

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Peridynamics is a new modeling concept of non-local interactions for solid structures. The formulations of Peridynamic (PD) theory are based on integral equations rather than differential equations. Through, undefined equations of associated problems are avoided. PD theory might be defined as continuum version of molecular dynamics. The medium is usually modeled with mass particles bonded together. Particles interact with each other directly across finite distances through central forces named as bonds. The main assumption of this theory is that the body is composed of material points which interact with other material points within a finite distance. Although, PD theory developed for discontinuities, it gives good results for structures which have no discontinuities. In this paper, displacement control of the isotropic plate under the effect of tensile and bending loading has been investigated by means of PD theory. A MATLAB code is generated to create PD bonds and corresponding surface correction factors. Using generated MATLAB code the geometry of the specimen is generated, and the code is implemented in Finite Element Software. The results obtained from non-local continuum theory are compared with the Finite Element Analysis results and analytical solution. The results show good agreement.

Keywords: non-local continuum mechanics, peridynamic theory, solid structures, tensile loading, flexural loading

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Authors: Elizabeth Howarth, Dawn Green, Sean Connolly, Geena Vabulas, Sara Smolley

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Through the EU Horizon 2020 Nuvoic Project, the project team recruited 70 individuals in the UK and Ireland to test the Voiceitt speech recognition app and provide user feedback to developers. The app is designed for people with dysarthric speech, to support communication with unfamiliar people and access to speech-driven technologies such as smart home equipment and smart assistants. Participants with atypical speech, due to a range of conditions such as cerebral palsy, acquired brain injury, Down syndrome, stroke and hearing impairment, were recruited, primarily through organisations supporting disabled people. Most had physical or learning disabilities in addition to dysarthric speech. The project team worked with individuals, their families and local support teams, to provide access to the app, including through additional assistive technologies where needed. Testing was user-led, with participants asked to identify and test use cases most relevant to their daily lives over a period of three months or more. Ongoing technical support and training were provided remotely and in-person throughout the testing period. Structured interviews were used to collect feedback on users' experiences, with delivery adapted to individuals' needs and preferences. Informal feedback was collected through ongoing contact between participants, their families and support teams and the project team. Focus groups were held to collect feedback on specific design proposals. User feedback shared with developers has led to improvements to the user interface and functionality, including faster voice training, simplified navigation, the introduction of gamification elements and of switch access as an alternative to touchscreen access, with other feature requests from users still in development. This work offers a case-study in successful and inclusive co-design with the disabled community.

Keywords: co-design, assistive technology, dysarthria, inclusive speech recognition

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Authors: Rachel Cherner

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Introduction: The current study investigates several user characteristics that may predict the adoption of digital mental health supports. The extent to which individual characteristics predict preferences for functional elements of computer-mediated social support (CMSS) platforms and mental health (MH) apps is relatively unstudied. Aims: The present study seeks to illuminate the relationship between broad user characteristics and perceived attraction to CMSS platforms and MH apps. Methods: Participants (n=353) were recruited using convenience sampling methods (i.e., digital flyers, email distribution, and online survey forums). The sample was 68% male, and 32% female, with a mean age of 29. Participant racial and ethnic breakdown was 75% White, 7%, 5% Asian, and 5% Black or African American. Participants were asked to complete a 25-minute self-report questionnaire that included empirically validated measures assessing a battery of characteristics (i.e., subjective levels of anxiety/depression via PHQ-9 (Patient Health Questionnaire 9-item) and GAD-7 (Generalized Anxiety Disorder 7-item); attachment style via MAQ (Measure of Attachment Qualities); personality types via TIPI (The 10-Item Personality Inventory); growth mindset and mental health-seeking attitudes via GM (Growth Mindset Scale) and MHSAS (Mental Help Seeking Attitudes Scale)) and subsequent attitudes toward CMSS platforms and MH apps. Results: A stepwise linear regression was used to test if user characteristics significantly predicted attitudes towards key features of CMSS platforms and MH apps. The overall regression was statistically significant (R² =.20, F(1,344)=14.49, p<.000). Conclusion: This original study examines the clinical and sociocultural factors influencing decisions to use CMSS platforms and MH apps. Findings provide valuable insight for increasing adoption and engagement with digital mental health support. Fostering a growth mindset may be a method of increasing participant/patient engagement. In addition, CMSS platforms and MH apps may empower under-resourced and minority groups to gain basic access to mental health support. We do not assume this final model contains the best predictors of use; this is merely a preliminary step toward understanding the psychology and attitudes of CMSS platform/MH app users.

Keywords: computer-mediated social support platforms, digital mental health, growth mindset, health-seeking attitudes, mental health apps, user characteristics

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Authors: Xuan (Iris) Li, Jenny Zhengye Hou, Greg Hearn

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Food waste is a global issue, with an estimated 30% to 50% of food created never being consumed. Therefore, it is vital to reduce food waste and convert wasted food into recyclable outputs. TikTok provides a simple way of creating and duetting videos in just a few steps by using templates with the same sound/vision/caption effects to produce personalized content – this is called a duet, which is revealing to study the impact of TikTok on wasting more food or saving food. The research focuses on examining food-related content on TikTok, with particular attention paid to two distinct themes, food waste pranks and food-saving practices, to understand the potential impacts of these themes on adolescents and their attitudes toward sustainable food consumption practices. Specifically, the analysis explores how TikTok content related to food waste and/or food saving may contribute to the normalization and promotion of either positive or negative food behaviours among young viewers. The research employed content analysis and semi-structured interviews to understand what factors contribute to the difference in popularity between food pranks and food-saving videos and insights from the former can be applied to the latter to increase their communication effectiveness. The first category of food content on TikTok under examination pertains to food waste, including videos featuring pranks and mukbang. These forms of content have the potential to normalize or even encourage food waste behaviours among adolescents, exacerbating the already significant food waste problem. The second category of TikTok food content under examination relates to food saving, for example, videos teaching viewers how to maximize the use of food to reduce waste. This type of content can potentially empower adolescents to act against food waste and foster positive and sustainable food practices in their communities. The initial findings of the study suggest that TikTok content related to pranks appears to be more popular among viewers than content focused on teaching people how to save food. Additionally, these types of videos are gaining fans at a faster rate than content promoting more sustainable food practices. However, we argue there is a great potential for social media platforms like TikTok to play an educative role in promoting positive behaviour change among young people by sharing engaging content suitable to target audiences. This research serves as the first to investigate the potential utility of TikTok in food waste reduction and underscores the important role social media platforms can play in promoting sustainable food practices. The findings will help governments, organizations, and communities promote tailored and effective interventions to reduce food waste and help achieve the United Nations’ sustainable development goal of halving food waste by 2030.

Keywords: food waste reduction, behaviour, social media, TikTok, adolescents

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Authors: Motonori Tamura

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The hydrogen barrier properties of the coatings of diamond-like carbon (DLC) were evaluated. Using plasma chemical vapor deposition and sputtering, DLC coatings were deposited on Type 316L stainless steels. The hydrogen permeation rate was reduced to 1/1000 or lower by the DLC coatings. The DLC coatings with high hydrogen content had high hydrogen barrier function. For hydrogen diffusion in coatings, the movement of atoms through hydrogen trap sites such as pores in coatings, and crystal defects such as dislocations, is important. The DLC coatings are amorphous, and there are both sp3 and sp2 bonds, and excess hydrogen could be found in the interstitial space and the hydrogen trap sites. In the DLC coatings with high hydrogen content, these hydrogen trap sites are likely already filled with hydrogen atoms, and the movement of new hydrogen atoms could be limited.

Keywords: hydrogen permeation, stainless steels, diamond-like carbon, hydrogen trap sites

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Authors: Lida Moghaddam-Banaem, Mahmood Tavoosi, Soheila Khalili

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Objective: The main objective of this study was designing a breast cancer health literacy questionnaire and assess its psychometric properties. Methods: A comprehensive literature review was performed to develop a primary questionnaire consisting of five domains. Qualitative and quantitative content validity were assessed by relevant experts, and after some modifications, the content validity index (CVI) and content validity ratio (CVR) were calculated. Qualitative and quantitative face validity were evaluated by a number of patients, and the impact score for each item was calculated. 225 women with breast cancer were asked to fill out the questionnaire and construct validity was determined by using exploratory factor analysis. The reliability was tested by Cronbach's alpha coefficient. Results: A 36-item questionnaire with five domains of reading, having access, understanding, assessing/judgment, and decision making/behavior was designed. 2 items were omitted in the qualitative content validity process. All items achieved optimum values in CVI, CVR and impact scores. Content and face validity of the questionnaire were confirmed too. According to the exploratory factor analysis, the five-factor solution accounted for 64.98 percent of the observed variance. Conclusion: Due to the obtained satisfactory validity and reliability, this tool can be used to assess health literacy in women with breast cancer. Health policy makers can use these findings for improving health-related behaviors in breast cancer patients.

Keywords: health literacy, breast cancer, questionnaire, psychometric properties

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Authors: Chelsea Peterson-Salahuddin

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Over the past decade, news outlets have increasingly used social media as a means to create and distribute news content to audiences. Ephemerality, the transitory nature of media, and mobility, media viewing on mobile technologies, are two increasingly salient attributes of social media content; yet little is known about how these features influence news selection practices of news outlets when distributing news via social media. To account for this gap, this study examines the influences of ephemerality and mobility on social media news content on the social media application Snapchat, in order to understand how these qualities of digital media influence and shape news content. Findings from this study suggest that understandings of ephemerality and mobility play a key role in influencing social media news. This paper suggests that as these factors become increasingly salient in our dominant news viewing environments, being able to understand how they manifest themselves in online news reporting practices is critical for both scholars and practitioners of news as they aim to understand what 'newsworthiness' means in the current, digital age. Findings from this study also enhance our current understandings of how the technological affordances of online and digital media platforms play a key role in shaping the kinds being produced and what information is being prioritized and highlighted in our contemporary news media environment. This is especially important in our current era where new mediums and technologies for news dissemination are continuously arising, and reorienting our understandings of what is considered ‘news'. As a key site of mass communication, discourse, and stories highlighted in the news do critical work in defining culture and ideology. Thus, better understanding the contours of news in our contemporary moment is critical in understanding cultural norms and meaning-making.

Keywords: content analysis, ephemerality, mobile communication, social media news

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Authors: Karen Guerrero

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Kindergarten-12th grade teachers engaged in teacher professional development (PD) on game-based learning techniques and strategies to support teaching STEMSS (STEM + Social Studies with an emphasis on geography across the curriculum) to language learners. Ten effective strategies have supported teaching content and language in tandem. To provide exiting teacher PD on summer and spring breaks, gamification has integrated these strategies to engage linguistically diverse student populations to provide informal language practice while students engage in the content. Teachers brought a STEMSS lesson to the PD, engaged in a wide variety of games (dice, cards, board, physical, digital, etc.), critiqued the games based on gaming elements, then developed, brainstormed, presented, piloted, and published their game-based STEMSS lessons to share with their colleagues. Pre and post-surveys and focus groups were conducted to demonstrate an increase in knowledge, skills, and self-efficacy in using gamification to teach content in the classroom. Provide an engaging strategy (gamification) to support teaching content and language to linguistically diverse students in the K-12 classroom. Game-based learning supports informal language practice while developing academic vocabulary utilized in the game elements/content focus, building both content knowledge through play and language development through practice. The study also investigated teacher's increase in knowledge, skills, and self-efficacy in using games to teach language learners. Mixed methods were used to investigate knowledge, skills, and self-efficacy prior to and after the gamification teacher training (pre/post) and to understand the content and application of developing and utilizing game-based learning to teach. This study will contribute to the body of knowledge in applying game-based learning theories to the K-12 classroom to support English learners in developing English skills and STEMSS content knowledge.

Keywords: gamification, teacher professional development, STEM, English learners, game-based learning

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Authors: Fouad Inel, Lakhdar Khochemane

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This article presents a comparative response specification performance between two controllers of three and four cable based robots for various applications. The main objective of this work is: the first is to use the direct and inverse geometric model to study and simulate the end effector position of the robot with three and four cables. A graphical user interface has been implemented in order to visualizing the position of the robot. Secondly, we present the determination of static and dynamic tensions and lengths of cables required to flow different trajectories. At the end, we study the response of our systems in closed loop with a Proportional-IntegratedDerivative (PID) and Proportional-Integrated (PD) controllers then this last are compared the results of the same examples using MATLAB/Simulink; we found that the PID method gives the better performance, such as rapidly speed response, settling time, compared to PD controller.

Keywords: dynamic modeling, geometric modeling, graphical user interface, open loop, parallel cable-based robots, PID/PD controllers

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Authors: Abdullah Al-Nassri, Ahmed Al-Alawi

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Seaweeds are classified into three groups: red, green, and brown. Each group of seaweeds consists of several types that have differences in composition. Even at the species level, there are differences in some ingredients, although in general composition, they are the same. Environmental conditions, availability of nutrients, and maturity stage are the main reasons for composition differences. In this study, two red seaweed species, Melanothamnus somalensis & Gelidium omanense, were collected in September 2021 from Sadh (Dhofar governorate, Oman). Five organic solvents were used sequentially to achieve extraction. The solvents were applied in the following order: hexane, dichloromethane, ethyl acetate, acetone, and methanol. Preparative HPLC (PrepLC) was performed to fraction the extracts. The chemical composition was measured; also, total phenols, flavonoids, and tannins were investigated. The structure of the extracts was analyzed by Fourier-transform infrared spectroscopy (FTIR). Seaweeds demonstrated high differences in terms of chemical composition, total phenolic content (TPC), total flavonoid content (TFC), and total tannin content (TTC). Gelidium omanense showed high moisture content, lipid content and carbohydrates (9.8 ± 0.15 %, 2.29 ± 0.09 % and 70.15 ± 0.42 %, respectively) compared to Melanothamnus somalensis (6.85 ± 0.01 %, 2.05 ± 0.12 % and 52.7 ± 0.36 % respectively). However, Melanothamnus somalensis showed high ash content and protein (27.68 ± 0.40 % and 52.7 ± 0.36 % respectively) compared to Gelidium omanense (8.07 ± 0.39 % and 9.70 ± 0.22 % respectively). Melanothamnus somalensis showed higher elements and minerals content, especially sodium and potassium. This is attributed to the jelly-like structure of Melanothamnus somalensis, which allows storage of more solutes compared to the leafy-like structure of Gelidium omanense. Furthermore, Melanothamnus somalensis had higher TPC in all fractions except the hexane fraction than Gelidium omanense. Except with hexane, TFC in the other solvents’ extracts was significantly different between Gelidium omanense and Melanothamnus somalensis. In all fractions, except dichloromethane and ethyl acetate fractions, there were no significant differences in TTC between Gelidium omanense and Melanothamnus somalensis. FTIR spectra showed variation between fractions, which is an indication of different functional groups.

Keywords: chemical composition, organic extract, Omani seaweeds, biological activity, FTIR

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Authors: Benalia Kouini, Aicha Serier

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This work aims to investigate the structure–property relationship in ternary nanocomposites consisting of polypropylene as the matrix, polyamide 66 as the minor phase and treated nanoclay DELLITE 67G as the reinforcement. All PP/PA66/Nanoclay systems with polypropylene grafted maleic anhydride PP-g-MAH as a compatibilizer were prepared via melt compounding and characterized in terms of nanoclay content. Morphological structure was investigated by scanning electron microscopy. The rheological behavior of the nanocomposites was determined by various methods, viz melt flow index (MFI) and parallel plate rheological measurements. The PP/PP-g-MAH/PA66 nanocomposites showed a homogeneous morphology supporting the compatibility improvement between PP, PA66 and nanoclay. SEM results revealed the formation of nanocomposites as the nanoclay was intercalated and exfoliated. In the ternary nanocomposites, the rheological behavior showed that, the complex viscosity is increased with increasing the nanoclay content; however, at low frequencies this increase is governed by the content of nanofiller while at high frequencies it is mainly determined by talc content. A similar trend was also observed for the variations of storage modulus (G′) and loss modulus (G″) with frequency. The results showed that the use of nanoclay considerably affects the melt elasticity.

Keywords: nanocomposites, polypropylene, polyamide66, modified nanoclay, rheology

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lorenço

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The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in a smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore relying on fixed operational models would be inappropriate. This paper presents a study on developing an Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose an Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

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Authors: Alper Tolga Kumtepe, Erdem Erdogdu, M. Recep Okur, Eda Kaypak, Ozlem Kaya, Serap Ugur, Deniz Dincer, Hakan Yildirim

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Interaction is one of the most important components of open and distance learning. According to Moore, who proposed one of the keystones on interaction types, there are three basic types of interaction: learner-teacher, learner-content, and learner-learner. From these interaction types, learner-content interaction, without doubt, can be identified as the most fundamental one on which all education is based. Efficacy, efficiency, and attraction of open and distance learning systems can be achieved by the practice of effective learner-content interaction. With the development of new technologies, interactive e-learning materials have been commonly used as a resource in open and distance learning, along with the printed books. The intellectual engagement of the learners with the content that is course materials may also affect their satisfaction for the open and distance learning practices in general. Learner satisfaction holds an important place in open and distance learning since it will eventually contribute to the achievement of learning outcomes. Using the learner-content interaction activities in course materials, Anadolu University, by its Open Education system, tries to involve learners in deep and meaningful learning practices. Especially, during the e-learning material design and production processes, identifying appropriate learner-content interaction activities within the context of learning outcomes holds a big importance. Considering the lack of studies adopting this approach, as well as its being a study on the use of e-learning materials in Open Education system, this research holds a big value in open and distance learning literature. In this respect, the present study aimed to investigate a) which learner-content interaction activities included in interactive courses are the most effective in learners’ achievement of verbal information learning outcomes and b) to what extent distance learners are satisfied with these learner-content interaction activities. For this study, the quasi-experimental research design was adopted. The 120 participants of the study were from Anadolu University Open Education Faculty students living in Eskişehir. The students were divided into 6 groups randomly. While 5 of these groups received different learner-content interaction activities as a part of the experiment, the other group served as the control group. The data were collected mainly through two instruments: pre-test and post-test. In addition to those tests, learners’ perceived learning was assessed with an item at the end of the program. The data collected from pre-test and post-test were analyzed by ANOVA, and in the light of the findings of this approximately 24-month study, suggestions for the further design of e-learning materials within the context of learner-content interaction activities will be provided at the conference. The current study is planned to be an antecedent for the following studies that will examine the effects of activities on other learning domains.

Keywords: interaction, distance education, interactivity, online courses

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Authors: Yozna Gurung

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This paper presents preliminary findings from an on-going study on the use of Internal State Terms (IST) in the production of narratives of Hindi-English bilinguals in an attempt to identify children at risk for Specific Language Impairment. Narratives were examined for macrostructure (story structure and story complexity) and internal state terms or mental state terms (IST/MST). 31 students generated stories based on six pictures that were matched for content and story structure in L1 (Hindi) and L2 (English) using a wordless picture narrative. From 30 sample population, 2 students are at risk of Specific Language Impairment, according to this study i.e 6.45%. They showed least development in story grammar as well as IST in both their languages.

Keywords: internal state terms, macrostructure, specific language impairment, wordless picture narrative

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Authors: Tahra Elobeid, Emmerich Berghofer

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The aim of this study is to find innovative approaches for the production of iron rich foods using natural iron sources. The vehicle used for fortification was sorghum whereas the iron fortificant was white bean. Fortified sorghum cookies were produced from five different mixtures; iron content, iron bioavailability, cookie texture and acceptability were measured. Cookies were prepared from the three fortified flours; 90% sorghum + 10% white bean (S9WB1), 75% sorghum + 25% white bean (S3WB1), 50% sorghum + 50% white bean (S1WB1) and 100% sorghum and 100% white bean. The functional properties gave good results in all the formulations. Statistical analysis of the iron content in the five different cookies showed that there was significant difference at the 95% confidence level (ANOVA). The iron content in all the recipes including the 100% sorghum improved, the increase ranging from 112% in 100% sorghum cookies to 476% in 100% white bean cookies. This shows that the increase in the amount of white bean used for fortification leads to the improvement of the iron content of cookies. The bioavailability of iron ranged from 21.3% in 100% sorghum to 28.6% in 100% white bean cookies. In the 100% sorghum cookies the iron bioavailability increased with reference to raw sorghum due to the addition of eggs. Bioavailability of iron in raw sorghum is 16.2%, therefore the percentage increase ranged from 5.1% to 28.6%. The cookies prepared from 10% white bean (S9WB1) scored the lowest 3.7 in terms of acceptability. They were the least preferred due to their somewhat soft texture. The 30% white bean cookies (S3WB1) gave results comparable to the 50% (S1WB1) and 100% white bean cookies. Cookies prepared with high percentage of white bean (50% and 100% white bean) gave the best results. Therefore cookie formulations from sorghum and white bean are successful in improving the iron status of anaemic individuals.

Keywords: sorghum, white bean, iron content, bioavailable iron, cookies

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Authors: Sebastião Pais, João Casal, Ricardo Ponciano, Sérgio Lourenço

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The adaptation paradigm is a basic defining feature for pervasive computing systems. Adaptation systems must work efficiently in smart environment while providing suitable information relevant to the user system interaction. The key objective is to deduce the information needed information changes. Therefore, relying on fixed operational models would be inappropriate. This paper presents a study on developing a Intelligent Personal Assistant to assist the user in interacting with their Smart Environment. We propose a Unsupervised and Language-Independent Adaptation through Intelligent Speech Interface and a set of methods of Acquiring Knowledge, namely Semantic Similarity and Unsupervised Learning.

Keywords: intelligent personal assistants, intelligent speech interface, unsupervised learning, language-independent, knowledge acquisition, association measures, symmetric word similarities, attributional word similarities

Procedia PDF Downloads 644

Authors: Benjamin Okike

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There is a need to hide information along the superhighway. Today, information relating to the survival of individuals, organizations, or government agencies is transmitted from one point to another. Adversaries are always on the watch along the superhighway to intercept any information that would enable them to inflict psychological ‘injuries’ to their victims. But with information encryption, this can be prevented completely or at worst reduced to the barest minimum. There is no doubt that so many encryption techniques have been proposed, and some of them are already being implemented. However, adversaries always discover loopholes on them to perpetuate their evil plans. In this work, we propose the enhanced data encryption standard (EDES) that would deploy randomly generated numbers as an encryption method. Each time encryption is to be carried out, a new set of random numbers would be generated, thereby making it almost impossible for cryptanalysts to decrypt any information encrypted with this newly proposed method.

Keywords: encryption, enhanced data encryption, encryption techniques, information security

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Authors: Ifeanyi Adigwe

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The influence of television on adolescents is prevalent and widespread because television is a powerful sex educator for adolescents. This study examined the relationship between viewing sexual content on television and sexual behaviour of adolescents in public senior secondary schools in Lagos, Nigeria. The study employed a survey research design with a structured questionnaire as instrument. The multi-stage sampling technique was adopted. Firstly, purposive sampling was adopted in selecting 3 educational districts namely: Agege, Maryland, and Agboju. These educational districts were chosen for convenience and its wide coverage area of public senior secondary schools in Lagos State. Secondly, the researcher adopted systematic sampling to select the schools. The schools were listed in alphabetical order in each district and every 10th school were selected, yielding 13 schools altogether. A total of 501 copies of questionnaire were administered to the students and a total 491 copies of the questionnaire were retrieved. Only 453 copies of the questionnaire met the inclusion criteria and were used for analysis. Data were analyzed using descriptive statistics, Pearson Correlation, Principal components analysis, and regression analysis. Results of correlation analysis showed a positive and significant relationship between adolescent sexual belief and their preference for sexual content in television (r =0.117, N =453, p=0.13), viewing sexual content on television and adolescent sexual behavior, (r =-0.112, N =453, p<0.05), adolescent television preference and their preference for sexual content in television (r =0.328, N =453, p<0.05), adolescent television preference and adolescent’s sexual behavior (r=0.093, N =453, p<0.05). However, a negative but significant relationship exists between adolescent’s sexual knowledge and their sexual behavior (r=-122, N=453, p=0.0009). Pearson’s correlation between adolescents’ sexual knowledge and sexual behavior shows that there is a positive significant but strong relationship between adolescent’s sexual knowledge and their sexual behavior (r=0.967, N=453, p<0.05). The results also show that adolescent’s preference for sexual content in television informs them about their sexuality, development and sexual health. The descriptive and inferential analysis of data revealed that the interaction among adolescent sexual belief, knowledge and adolescents’ preference of sexual in television and its resultant effect on adolescent sexual behavior is apparent because sexual belief and norms about sex of an adolescent can induce his television preference of sexual content on television. The study concludes that exposure to sexual content in television can impact on adolescent sexual behaviour. There is no doubt that the actual outcome of television viewing and adolescent sexual behavior remains controversial because adolescent sexual behavior is multifaceted and multi-dimensional. Since behavior is learned overtime, the frequency of exposure and nature of sexual content viewed overtime induces and hastens sexual activity.

Keywords: adolescent sexual behavior, Nigeria, sexual belief, sexual content, sexual knowledge, television preference

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Authors: Vivian Li

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With the rapid development of technology, virtual reality (VR) and augmented reality (AR) are becoming increasingly prominent in our lives. Museums have led the way in digitization, offering their collections to the wider public through the open internet, which is dramatically changing our experience of art. Technology is also being implemented into our physical art-viewing experience, enabling museums to capture historical sites while creating a more immersive experience for patrons. This study takes a qualitative approach, examining secondary sources and synthesizing information from interviews with field professionals to answer the question: to what extent is the contemporary perception of art transformed by the digitization of art museums? The findings establish that museums are becoming increasingly open with their collections, utilizing digitization to spread their intellectual content to people worldwide and to diversify their audiences. The use of VR and AR is also enabling museums to preserve and showcase historical artifacts and sites in a more interactive and user-focused way. Technology is also crafting new forms of art and art museums. Ultimately, the intersection of technology and museums is not changing the definition of art but rather offering new modes for the public to experience and learn about arts and history.

Keywords: art, augmented reality, digitization, museums, technology, virtual reality

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Authors: Maurizio Dapor, Isabel Abril, Pablo de Vera, Rafael Garcia-Molina

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The ionization yield of ion tracks in polymers and bio-molecular systems reaches a maximum, known as the Bragg peak, close to the end of the ion trajectories. Along the path of the ions through the materials, many electrons are generated, which produce a cascade of further ionizations and, consequently, a shower of secondary electrons. Among these, very low energy secondary electrons can produce damage in the biomolecules by dissociative electron attachment. This work deals with the calculation of the energy distribution of electrons produced by protons in a sample of polymethylmethacrylate (PMMA), a material that is used as a phantom for living tissues in hadron therapy. PMMA is also of relevance for microelectronics in CMOS technologies and as a photoresist mask in electron beam lithography. We present a Monte Carlo code that, starting from a realistic description of the energy distribution of the electrons ejected by protons moving through PMMA, simulates the entire cascade of generated secondary electrons. By following in detail the motion of all these electrons, we find the radial distribution of the energy that they deposit in PMMA for several initial proton energies characteristic of the Bragg peak.

Keywords: Monte Carlo method, secondary electrons, energetic ions, ion-beam cancer therapy, ionization cross section, polymethylmethacrylate, proton beams, secondary electrons, radial energy distribution

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

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Authors: Aleksandra Czubek

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As AI systems increasingly shape content creation, existing copyright frameworks face significant challenges in determining liability for AI-generated outputs. Current legal discussions largely focus on who bears responsibility for infringing works, be it developers, users, or entities benefiting from AI outputs. This paper introduces a novel concept of algorithmic obligations, proposing that AI developers be subject to proactive duties that ensure their models prevent copyright infringement before it occurs. Building on principles of obligations law traditionally applied to human actors, the paper suggests a shift from reactive enforcement to proactive legal requirements. AI developers would be legally mandated to incorporate copyright-aware mechanisms within their systems, turning optional safeguards into enforceable standards. These obligations could vary in implementation across international, EU, UK, and U.S. legal frameworks, creating a multi-jurisdictional approach to copyright compliance. This paper explores how the EU’s existing copyright framework, exemplified by the Copyright Directive (2019/790), could evolve to impose a duty of foresight on AI developers, compelling them to embed mechanisms that prevent infringing outputs. By drawing parallels to GDPR’s “data protection by design,” a similar principle could be applied to copyright law, where AI models are designed to minimize copyright risks. In the UK, post-Brexit text and data mining exemptions are seen as pro-innovation but pose risks to copyright protections. This paper proposes a balanced approach, introducing algorithmic obligations to complement these exemptions. AI systems benefiting from text and data mining provisions should integrate safeguards that flag potential copyright violations in real time, ensuring both innovation and protection. In the U.S., where copyright law focuses on human-centric works, this paper suggests an evolution toward algorithmic due diligence. AI developers would have a duty similar to product liability, ensuring that their systems do not produce infringing outputs, even if the outputs themselves cannot be copyrighted. This framework introduces a shift from post-infringement remedies to preventive legal structures, where developers actively mitigate risks. The paper also breaks new ground by addressing obligations surrounding the training data of large language models (LLMs). Currently, training data is often treated under exceptions such as the EU’s text and data mining provisions or U.S. fair use. However, this paper proposes a proactive framework where developers are obligated to verify and document the legal status of their training data, ensuring it is licensed or otherwise cleared for use. In conclusion, this paper advocates for an obligations-centered model that shifts AI-related copyright law from reactive litigation to proactive design. By holding AI developers to a heightened standard of care, this approach aims to prevent infringement at its source, addressing both the outputs of AI systems and the training processes that underlie them.

Keywords: ip, technology, copyright, data, infringement, comparative analysis

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Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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Authors: Abbas S. Al-Ameeri Rawaa H. Issa

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The internal sulfate attack is considered as a very important problem of concrete manufacture in Iraq and Middle East countries. Sulfate drastically influences the properties of concrete. This experimental study is aimed at investigating the effect of internal sulfates on fresh and some of the hardened properties of self compacting concrete (SCC) made from locally available materials. Tests were conducted on five mixes, with five SO3 levels (3.9, 5, 6, 7 and 8) (% by wt. of cement). The last four SO3 levels are outside the limits of the Iraqi specifications (IQS NO.45/1984). The results indicated that sulfate passively influenced the fresh properties such as decreased workability, and effect on hardened properties of the self compacting concrete. Also, the result indicated the optimum SO3 content which gives maximum strength and little tendency to expanding, which showed up at a content equal to 5% (by wt of cement), is more than acceptable limits of Iraqi specifications. Further increase in sulfates content in concrete after this optimum value showed a considerable reduction in mechanical properties of self-compacting concrete, and increment in expansion of concrete. The percentages of reduction in compressive strength, splitting tensile strength, flexural strength, static modulus of elasticity and ultrasonic pulse velocity at their later age were ranged between 10.89-36.14%, 12.90-33.33%, 7.98-36.35%, 16.36 -38.37% and 1.03-10.88% respectively.

Keywords: self-compacting concrete, sulfate attack, internal sulfate attack, fresh properties, harden properties, optimum SO3 content

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Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

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Authors: Dayane de Almeida

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This work aims at presenting a study that demonstrates the usability of categories of analysis from Discourse Semiotics – also known as Greimassian Semiotics in authorship cases in forensic contexts. It is necessary to know if the categories examined in semiotic analysis (the ‘grammar’ of the content plane) can distinguish authors. Thus, a study with 4 sets of texts from a corpus of ‘not on demand’ written samples (those texts differ in formality degree, purpose, addressees, themes, etc.) was performed. Each author contributed with 20 texts, separated into 2 groups of 10 (Author1A, Author1B, and so on). The hypothesis was that texts from a single author were semiotically more similar to each other than texts from different authors. The assumptions and issues that led to this idea are as follows: -The features analyzed in authorship studies mostly relate to the expression plane: they are manifested on the ‘surface’ of texts. If language is both expression and content, content would also have to be considered for more accurate results. Style is present in both planes. -Semiotics postulates the content plane is structured in a ‘grammar’ that underlies expression, and that presents different levels of abstraction. This ‘grammar’ would be a style marker. -Sociolinguistics demonstrates intra-speaker variation: an individual employs different linguistic uses in different situations. Then, how to determine if someone is the author of several texts, distinct in nature (as it is the case in most forensic sets), when it is known intra-speaker variation is dependent on so many factors?-The idea is that the more abstract the level in the content plane, the lower the intra-speaker variation, because there will be a greater chance for the author to choose the same thing. If two authors recurrently chose the same options, differently from one another, it means each one’s option has discriminatory power. -Size is another issue for various attribution methods. Since most texts in real forensic settings are short, methods relying only on the expression plane tend to fail. The analysis of the content plane as proposed by greimassian semiotics would be less size-dependable. -The semiotic analysis was performed using the software Corpus Tool, generating tags to allow the counting of data. Then, similarities and differences were quantitatively measured, through the application of the Jaccard coefficient (a statistical measure that compares the similarities and differences between samples). The results showed the hypothesis was confirmed and, hence, the grammatical categories of the content plane may successfully be used in questioned authorship scenarios.

Keywords: authorship attribution, content plane, forensic linguistics, greimassian semiotics, intraspeaker variation, style

Procedia PDF Downloads 242